init

Co-authored-by: Cursor <cursoragent@cursor.com>

.env

@@ -0,0 +1 @@
+GIT_USER_TOKEN=c42edf3a584adbcac211c8c4ac13988efe56b0a5

.gitignore

@@ -82,9 +82,6 @@ celerybeat-schedule
 # SageMath parsed files
 *.sage.py
 
-# dotenv
-.env
-
 # virtualenv
 .venv
 venv/
@@ -99,3 +96,6 @@ ENV/
 # macOS metadata
 .DS_Store
 
+# 로컬 추천 번호 산출물 (Git 추적 제외)
+resources/recommend_ball.biz_25.json
+

DataCrawler.py

@@ -4,6 +4,9 @@ import time
 import requests
 # JSON 포맷을 다루기 위한 라이브러리를 호출합니다.
 import json
+from datetime import datetime, timedelta
+import random
+import socket
 
 import urllib3
 
@@ -19,8 +22,15 @@ except ModuleNotFoundError:
         def sendMsg(self, msg):
             pass
 
-_LOTTO_URL = "https://www.dhlottery.co.kr/common.do?method=getLottoNumber&drwNo={}"
-_REQUEST_TIMEOUT = 15
+_LOTTO_URLS = (
+    "https://www.dhlottery.co.kr/common.do?method=getLottoNumber&drwNo={}",
+    "https://dhlottery.co.kr/common.do?method=getLottoNumber&drwNo={}",
+)
+_REQUEST_TIMEOUT = float(os.environ.get("LOTTO_REQUEST_TIMEOUT", "12"))
+_FETCH_RETRIES_PER_DRAW = int(os.environ.get("LOTTO_FETCH_RETRIES", "3"))
+_BACKOFF_BASE_SECONDS = float(os.environ.get("LOTTO_BACKOFF_BASE", "0.7"))
+_MAX_CONSECUTIVE_FETCH_FAILURES = int(os.environ.get("LOTTO_MAX_CONSEC_FAIL", "8"))
+_CONNECTION_PROBE_TIMEOUT = float(os.environ.get("LOTTO_PROBE_TIMEOUT", "3"))
 _BROWSER_HEADERS = {
     "User-Agent": (
         "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 "
@@ -51,33 +61,62 @@ class DataCrawler:
         self.bot = TelegramBot()
         self._session = requests.Session()
         self._session.headers.update(_BROWSER_HEADERS)
+        self._last_fetch_error = ""
+
+    def _can_reach_lottery_host(self):
+        """
+        API 호스트 TCP 연결 가능 여부를 빠르게 확인합니다.
+        완전한 보장은 아니지만, 완전 차단 상태를 조기 감지해 불필요한 대기 시간을 줄입니다.
+        """
+        for host in ("www.dhlottery.co.kr", "dhlottery.co.kr"):
+            try:
+                with socket.create_connection((host, 443), timeout=_CONNECTION_PROBE_TIMEOUT):
+                    return True
+            except OSError:
+                continue
+        return False
 
     def _fetch_draw(self, drw_no):
         """동행복권 API에서 단일 회차 결과를 가져옵니다. 실패 시 None."""
-        url = _LOTTO_URL.format(int(drw_no))
-        for verify in (_ssl_verify_arg(), False):
-            for method in ("POST", "GET"):
-                try:
-                    res = self._session.request(
-                        method,
-                        url,
-                        timeout=_REQUEST_TIMEOUT,
-                        verify=verify,
-                    )
-                    if res.status_code != 200:
-                        continue
-                    text = res.text.strip()
-                    if not text.startswith("{"):
-                        continue
-                    result = json.loads(text)
-                except (
-                    requests.RequestException,
-                    ValueError,
-                    json.JSONDecodeError,
-                ):
-                    continue
-                if isinstance(result, dict) and result.get("returnValue") == "success":
-                    return result
+        self._last_fetch_error = ""
+        verify_options = (_ssl_verify_arg(), False)
+        last_error = "unknown"
+        for attempt in range(1, _FETCH_RETRIES_PER_DRAW + 1):
+            for raw_url in _LOTTO_URLS:
+                url = raw_url.format(int(drw_no))
+                for verify in verify_options:
+                    for method in ("POST", "GET"):
+                        try:
+                            res = self._session.request(
+                                method,
+                                url,
+                                timeout=_REQUEST_TIMEOUT,
+                                verify=verify,
+                            )
+                            if res.status_code != 200:
+                                last_error = "http {}".format(res.status_code)
+                                continue
+                            text = res.text.strip()
+                            if not text.startswith("{"):
+                                last_error = "non-json response"
+                                continue
+                            result = json.loads(text)
+                        except (
+                            requests.RequestException,
+                            ValueError,
+                            json.JSONDecodeError,
+                        ) as ex:
+                            last_error = str(ex)
+                            continue
+                        if isinstance(result, dict) and result.get("returnValue") == "success":
+                            return result
+                        rv = result.get("returnValue") if isinstance(result, dict) else "unknown"
+                        last_error = "api returnValue={}".format(rv)
+            if attempt < _FETCH_RETRIES_PER_DRAW:
+                # 지수 백오프 + 지터로 일시적 네트워크 혼잡 완화
+                delay = _BACKOFF_BASE_SECONDS * (2 ** (attempt - 1)) + random.uniform(0, 0.25)
+                time.sleep(delay)
+        self._last_fetch_error = last_error
         return None
 
     def _append_draw_files(self, lottoHistoryFile, result):
@@ -120,6 +159,99 @@ class DataCrawler:
             return None
         return last_json.get("drwNo")
 
+    def _read_draw_map_from_json(self, json_path):
+        """
+        JSONL 전체를 읽어 drwNo -> record 맵으로 반환합니다.
+        잘못된 라인/중복 라인은 정리 대상이며, 마지막 유효값을 유지합니다.
+        """
+        draw_map = {}
+        if not os.path.isfile(json_path) or os.path.getsize(json_path) == 0:
+            return draw_map
+
+        with open(json_path, "r", encoding="utf-8") as fp:
+            for line in fp:
+                line = line.strip()
+                if not line:
+                    continue
+                try:
+                    data = json.loads(line)
+                except json.JSONDecodeError:
+                    continue
+                if (
+                    isinstance(data, dict)
+                    and data.get("returnValue") == "success"
+                    and isinstance(data.get("drwNo"), int)
+                ):
+                    draw_map[data["drwNo"]] = data
+
+        return draw_map
+
+    def _write_draw_map_files(self, lottoHistoryFile, draw_map):
+        """
+        drwNo 오름차순으로 json/txt를 재생성합니다.
+        누락 회차 보강/중복 제거 후 일관된 파일 상태를 보장합니다.
+        """
+        json_path = lottoHistoryFile + ".json"
+        txt_path = lottoHistoryFile + ".txt"
+        with open(json_path, "w", encoding="utf-8") as json_fp, open(
+            txt_path, "w", encoding="utf-8"
+        ) as text_fp:
+            for drw_no in sorted(draw_map.keys()):
+                result = draw_map[drw_no]
+                json_fp.write(json.dumps(result, ensure_ascii=False) + "\n")
+                text_fp.write(
+                    "%d,%d,%d,%d,%d,%d,%d,%d\n"
+                    % (
+                        drw_no,
+                        result["drwtNo1"],
+                        result["drwtNo2"],
+                        result["drwtNo3"],
+                        result["drwtNo4"],
+                        result["drwtNo5"],
+                        result["drwtNo6"],
+                        result["bnusNo"],
+                    )
+                )
+
+    def _get_last_week_draw_date(self):
+        """
+        '지난 주' 기준 토요일 날짜를 반환합니다.
+        예: 금요일(2026-05-08) 실행 시 직전 토요일(2026-05-02)
+        """
+        now = datetime.now()
+        days_since_saturday = (now.weekday() - 5) % 7
+        latest_saturday = now.date() - timedelta(days=days_since_saturday)
+        # 토요일이면서 추첨 전(20시 이전)이라면 지난 주 토요일을 목표로 사용
+        if now.weekday() == 5 and now.hour < 20:
+            latest_saturday = latest_saturday - timedelta(days=7)
+        return latest_saturday
+
+    def _estimate_target_draw_no(self, draw_map):
+        """
+        기존 데이터의 마지막 drwNoDate와 지난 주 토요일을 비교해
+        이번 실행에서 확보해야 할 목표 회차를 계산합니다.
+        """
+        if not draw_map:
+            return None
+
+        last_no = max(draw_map.keys())
+        last_data = draw_map[last_no]
+        last_date_str = last_data.get("drwNoDate", "")
+        try:
+            last_date = datetime.strptime(last_date_str, "%Y-%m-%d").date()
+        except ValueError:
+            return last_no
+
+        target_date = self._get_last_week_draw_date()
+        if target_date <= last_date:
+            return last_no
+
+        week_gap = (target_date - last_date).days // 7
+        if week_gap <= 0:
+            return last_no
+
+        return last_no + week_gap
+
     # 로또 당첨 데이터를 수집해서 파일로 저장합니다.
     # lottoHistoryFile: 로또 당첨 데이터를 저장할 파일 (확장자 제외)
     def craw(self, lottoHistoryFile, drwNo=None):
@@ -161,44 +293,97 @@ class DataCrawler:
 
     def excute(self, resource_path):
         """
-        resources/lotto_history.* 를 마지막 회차 이후까지 연속으로 갱신합니다.
-        (기존: 날짜 비교 + 1회차만 수집 → 누락·정지가 잦음)
+        resources/lotto_history.* 를 지난 주 기준으로 누락 없이 동기화합니다.
+        - 마지막 회차+1만 확인하지 않고, 1~목표회차 범위에서 누락 회차를 탐지/보강
+        - 중복/깨진 라인을 정리해 json/txt를 일관 상태로 재생성
         """
         lottoHistoryFile = os.path.join(resource_path, "lotto_history")
         json_path = lottoHistoryFile + ".json"
 
-        last_no = self._read_last_draw_from_json(json_path)
-        if last_no is None:
-            self.craw(lottoHistoryFile)
+        draw_map = self._read_draw_map_from_json(json_path)
+
+        # 기존 이력이 비었거나 깨졌으면 전체 재수집(기존 동작 유지)
+        if not draw_map:
             try:
+                self.craw(lottoHistoryFile)
                 self.bot.sendMsg("[Lottery Crawler] full history rebuilt (no valid json).")
             except Exception:
                 pass
             return True
 
-        added = 0
-        next_no = last_no + 1
-        while True:
-            result = self._fetch_draw(next_no)
-            if result is None:
-                break
-            self._append_draw_files(lottoHistoryFile, result)
-            added += 1
-            next_no += 1
-            time.sleep(0.35)
+        target_no = self._estimate_target_draw_no(draw_map)
+        if target_no is None:
+            target_no = max(draw_map.keys())
 
-        if added == 0:
+        if not self._can_reach_lottery_host():
+            msg = "[Lottery Crawler] network blocked: cannot reach dhlottery host."
+            print(msg)
+            try:
+                self.bot.sendMsg(msg)
+            except Exception:
+                pass
+            return False
+
+        missing_nos = [no for no in range(1, target_no + 1) if no not in draw_map]
+        added = 0
+        failed = []
+        aborted_missing_nos = []
+        consecutive_failure = 0
+        fail_reasons = {}
+        for no in missing_nos:
+            result = self._fetch_draw(no)
+            if result is None:
+                failed.append(no)
+                reason = self._last_fetch_error or "unknown"
+                fail_reasons[reason] = fail_reasons.get(reason, 0) + 1
+                consecutive_failure += 1
+                if consecutive_failure >= _MAX_CONSECUTIVE_FETCH_FAILURES:
+                    aborted_missing_nos = [x for x in missing_nos if x > no]
+                    break
+                continue
+            draw_map[no] = result
+            added += 1
+            consecutive_failure = 0
+            time.sleep(0.2)
+
+        # 누락 보강 또는 중복 정리 여지가 있으면 파일을 재생성
+        self._write_draw_map_files(lottoHistoryFile, draw_map)
+
+        last_no = max(draw_map.keys())
+        if added == 0 and not failed:
             try:
                 self.bot.sendMsg(
-                    "[Lottery Crawler] up to date (last drwNo={}).".format(last_no)
+                    "[Lottery Crawler] up to date (last drwNo={}, target={}).".format(
+                        last_no, target_no
+                    )
+                )
+            except Exception:
+                pass
+        elif failed:
+            sample = ",".join(str(x) for x in failed[:10])
+            reason_items = sorted(fail_reasons.items(), key=lambda x: x[1], reverse=True)
+            reason_str = "; ".join("{} x{}".format(reason, count) for reason, count in reason_items[:3])
+            if aborted_missing_nos:
+                reason_str += " | aborted {} pending draws due to consecutive failures".format(
+                    len(aborted_missing_nos)
+                )
+            try:
+                self.bot.sendMsg(
+                    "[Lottery Crawler] appended {}, failed {} draw(s): {}{} | {}".format(
+                        added,
+                        len(failed),
+                        sample,
+                        "..." if len(failed) > 10 else "",
+                        reason_str or "no reason",
+                    )
                 )
             except Exception:
                 pass
         else:
             try:
                 self.bot.sendMsg(
-                    "[Lottery Crawler] appended {} draw(s), last drwNo={}.".format(
-                        added, last_no + added
+                    "[Lottery Crawler] appended {} draw(s), last drwNo={}, target={}.".format(
+                        added, last_no, target_no
                     )
                 )
             except Exception:

PROMPT.txt

@@ -1,11 +1,12 @@
 데이터는 다음과 같습니다.
 (학습 데이터)
-- train.json, train.txt
-- 1회차부터 800회차
+- lotto_history.txt에서 회차부터 800회차
 
 (검증 데이터)
-- valid.json, valid.txt
-- 801회차부터 1000회차
+- lotto_history.txt에서 801회차부터 1000회차
+
+(테스트 데이터)
+- lotto_history.txt에서 1001회차부터 이후 모두
 
 파일 구조를 먼저 이해하세요.
 
@@ -110,3 +111,6 @@
 그리고 요구사항에 대해서 시도 방법을 설계하세요.
 그리고 반복적으로 실행해서 최적화된 방법을 찾아서 적용해주세요.
 (최적화는 언제든 학습 데이터로 최적화를 해야 합니다. 그리고 검증 데이터로 테스트만 수행하세요.)
+
+당첨번호에 대한 추천 개수가 100개 미만이어야 합니다.
+1_FilterTest_25.py, BallFilter_25.py를 참고해서 최적의 final_filterTest.py, final_BallFilter.py를 작성해 주세요.

README.md

@@ -1,343 +1,112 @@
-# 실행 순서
+# deeplottery
 
-## final_BallFilter · `final_filterTest.py` (miniconda **ncue**)
+`deeplottery`는 로또 번호를 예측하는 프로젝트가 아니라, **전체 조합(45C6)을 규칙 기반으로 필터링해 후보를 줄이는 시스템**입니다.  
+핵심은 `BallFilter` 엔진이며, 운영 실행(`final_practice.py`)과 검증(`final_FilterTest.py`)이 분리되어 있습니다.
 
-임계값은 `tools/compute_final_filter_params.py`가 학습 구간(1~800회) 분포에서 생성하며, 결과는 `final_filter_params.py`에 기록됩니다.
+## 목표와 설계 의도
+
+- 목표: 통계/패턴 기반 규칙으로 비효율 조합을 제거하고 후보군을 관리 가능한 크기로 축소
+- 설계 의도:
+  - 필터 규칙은 `final_BallFilter.py` 한 곳에서 관리
+  - 운영 추천 생성과 과거 회차 검증을 분리하여 반복 개선
+  - 같은 엔진을 운영/검증에서 공통 사용해 일관성 유지
+
+## 전체 아키텍처
+
+1. 데이터 수집/갱신
+   - `DataCrawler.py`가 로또 API를 호출해 `resources/lotto_history.json`, `resources/lotto_history.txt` 갱신
+2. 필터 엔진 로딩
+   - `final_BallFilter.py`의 `BallFilter`가 과거 당첨 이력을 메모리로 적재
+3. 운영 후보 생성
+   - `final_practice.py`가 다음 회차 기준 전체 조합을 순회하며 `BallFilter.filter()`로 통과 조합만 저장
+4. 필터 성능 검증
+   - `final_FilterTest.py`가 과거 당첨번호를 기준으로 어떤 필터가 당첨을 걸렀는지/통과시켰는지 분석
+
+## 핵심 파일 설명
+
+- `final_BallFilter.py`
+  - 프로젝트 핵심 엔진
+  - `extract_final_candidates()`에서 규칙 기반 탈락 사유(`set`)를 생성
+  - `filter()`는 실사용 진입점이며, 반환 `set`이 비어 있으면 통과
+- `final_practice.py`
+  - 운영 실행 스크립트
+  - `predict1()` 고정 11조합을 유지
+  - `predict2()`는 1차 필터 통과 조합을 만든 뒤, 2차 포트폴리오 선별로 최종 추천 수를 제한
+  - 총 추천 개수는 고정수 포함 최대 70게임(70,000원) 상한을 적용
+  - 결과를 `resources/recommend_ball.biz_25.json`에 저장하고 Telegram 전송
+- `final_FilterTest.py`
+  - 검증/분석 스크립트
+  - `find_filter_method()`로 회차별 필터 적중 통계 확인
+  - `find_final_candidates()`로 특정 회차 후보군 재생성
+- `DataCrawler.py`
+  - 과거 이력 파일 수집/보강
+  - 네트워크 실패 재시도/백오프 및 누락 회차 보완 처리
+- `TelegramBot.py`
+  - 추천 결과 메시지 전송
+- `resources/`
+  - `lotto_history.json`: 회차별 원본 JSON 라인 데이터
+  - `lotto_history.txt`: 회차별 CSV 형태 요약 데이터
+  - `recommend_ball.biz_25.json`: 회차별 추천 결과 저장 파일
+
+## 실행 방법
+
+Python 실행은 Miniconda `ncue` 환경을 사용합니다.
 
 ```bash
 conda activate ncue
-python tools/compute_final_filter_params.py
-python final_filterTest.py
+python DataCrawler.py
+python final_FilterTest.py
+python final_practice.py
 ```
 
-conda 경로를 쓰기 어려우면 프로젝트의 `scripts/run_with_ncue.sh`로 동일하게 실행할 수 있습니다.
+## 동작 방식 상세
 
-```bash
-./scripts/run_with_ncue.sh tools/compute_final_filter_params.py
-./scripts/run_with_ncue.sh final_filterTest.py
-```
+- 입력: 1~45에서 6개 조합 전체
+- 처리:
+  - 1차: `BallFilter` 규칙 필터 적용
+  - 2차: 고정 11조합을 유지한 채, 겹침도 기반 포트폴리오 선별로 후보 축소
+- 출력:
+  - 탈락 조합: 탈락 사유 집합 반환
+  - 최종 추천 조합: 예산 상한(최대 70,000원) 내에서 저장/전송
 
-* FilterFeature.py를 실행한다.
-  * lotto_history.json을 읽어서 all_filter_[1-100].[cluster,csv,feature] 파일을 생성한다.
+주요 규칙 범주 예시:
 
+- 합/평균 및 전주 대비 차이
+- 앞 3개/뒤 3개 합 패턴
+- 고저 비율, 끝자리 패턴, AC 값
+- 배수 개수(3/4/5/6 등)
+- 최근 N주 출현 빈도/중복 관련 규칙
+- 비선호 2개/3개 조합 제거 규칙
 
-* FilterFeatureCluster.py를 실행한다.
-  * 첫수는 1~10까지만 허용한다.
-  * random_state 전체 내 각 cluster에 대해서 당첨 회수를 파악하여 ./resources/cluster_win_info.csv 파일을 생성한다.
-  * 생성 파일
-    * filtertest_1.csv: random_state 내 cluster 개수를 파악한다.
-    * filtertest_2.csv: random_state 내 cluster 개수 별 전체 당첨 회수를 파악한다.
-    * filtertest_3.csv: random_state 내 cluster 개수 별 최초 당첨 번호만 파악한다.
+## 디렉터리 현재 상태 (2026-05-08)
 
+### 최상위 파일/디렉터리 현황
 
-* 실행할 random_state와 cluster 번호 파악
-  * filtertest_2.csv과 answer_pattern_analsys.xlsx을 이용하여 선별한다.
+- 실행/핵심
+  - `DataCrawler.py`
+  - `final_BallFilter.py`
+  - `final_FilterTest.py`
+  - `final_practice.py`
+  - `final_Practice.py` (구버전 스크립트)
+  - `TelegramBot.py`
+- 레거시 참조 파일
+  - `BallFilter_22.py`, `BallFilter_25.py`
+  - `1_FilterTest_22.py`, `1_FilterTest_25.py`
+  - `2_FilterTestReview_22.py`, `2_FilterTestReview_25.py`
+  - `3_Practice_22.py`, `3_Practice_25.py`
+  - `fixed10.py`
+- 데이터/설정
+  - `resources/`
+  - `requirements.txt`
+  - `scripts/`
 
+### Git 작업 트리 상태(요약)
 
-* cluster_info.json 파일 업데이트
-  * 실행할 random_state와 cluster 번호를 json 형태로 등록한다.
+- 수정됨: `DataCrawler.py`, `README.md`, `final_BallFilter.py`, `final_practice.py`, `resources/lotto_history.json`, `resources/lotto_history.txt`
+- 삭제됨: `filter_model.py`, `final_filter_params.py`, `train.py`, `valid.py`
+- 신규(미추적): `resources/recommend_ball.biz_25.json`
 
+## 주의 사항
 
-* Util_filegen.py 실행
-  * m1, amd, intel 컴퓨터에서 실행할 sh, bat 파일을 생성한다.
-  * 파이썬 내에서 아래 두 부분만 수정하면 된다. 
-    * m1_file_max, amd_file_max, intel_file_max = 8,12,7
-    * m1_proc_limit, amd_proc_limit, intel_proc_limit = 124,125,110
-
-
-* 각 장비에서 sh와 bat 파일 실행
-
-
-## Ruleset(임계값 설정) 기반으로 운영하기
-
-`filter_model.BallFilter`의 주요 임계값(합/평균/앞3합/뒤3합/간격 등)을 **JSON ruleset**으로 외부화했습니다.
-이제 “코드 수정 없이” ruleset 파일만 바꿔서 실험/튜닝을 자동화할 수 있습니다.
-
-- **기본 ruleset 경로**: `resources/rulesets/default.json`
-- **주의/한계**: 로또는 본질적으로 랜덤(독립/균등 가설)이며, ruleset은 “구매 조합 수를 줄이기 위한 필터”입니다. **당첨 보장/예측을 주장하지 않습니다.**
-
-### valid 성능 확인 예시
-
-```bash
-python scripts/eval_filters.py \
-  --data valid \
-  --resources resources \
-  --ruleset resources/rulesets/default.json \
-  --start-no 801 --end-no 1000 \
-  --survivors-samples 0
-```
-
-### survivors(생존 조합 수) 근사 포함 예시
-
-```bash
-python scripts/eval_filters.py \
-  --data valid \
-  --resources resources \
-  --ruleset resources/rulesets/default.json \
-  --start-no 801 --end-no 1000 \
-  --survivors-samples 3000
-```
-
-## 자동 튜닝 → ruleset 생성 → 일괄 평가 파이프라인
-
-### 1) train 기반 자동 튜닝(후보 ruleset 생성)
-
-아래 스크립트는 **train 구간에서만** 임계값을 랜덤 탐색으로 튜닝한 뒤,
-`resources/rulesets/`에 `Balanced.json`, `Coverage-First.json`을 저장합니다.
-
-```bash
-python scripts/tune_ruleset.py \
-  --resources resources \
-  --base-ruleset resources/rulesets/default.json \
-  --out-dir resources/rulesets \
-  --train-start 21 --train-end 800 \
-  --hit-rate-min 0.01 \
-  --iters 200 \
-  --mc-samples 40000
-```
-
-- **Coverage-First**: survivors(생존 조합 수) 최소화를 우선
-- **Balanced**: survivors를 줄이되 hit-rate도 함께 고려
-
-> 주의: survivors는 전수(8,145,060조합) 대신 **풀링 Monte Carlo**로 근사하므로 오차가 있습니다.
-
-### 2) valid/train 구간에서 ruleset 일괄 평가
-
-```bash
-python scripts/eval_rulesets.py \
-  --resources resources \
-  --rulesets-dir resources/rulesets \
-  --data valid \
-  --start-no 801 --end-no 1000 \
-  --survivors-samples 0
-```
-
-# Query
-```SQL
-##### 전체 진행 확인 #####
-
-with source_count as (
-    select source, count(*) as source_count
-      from cluster_info
-     where priority not in (99)
-       and source in (1,3)
-     group by 1
-),
-ball_count as (
-    # 1) random_state, cluster 별 추천볼 개수
-    select source, random_state, cluster, ball_cnt
-    from (
-        SELECT source, random_state, cluster, count(*)
-        as ball_cnt
-          from recommend_ball
-         where no=1136
-           and b1 > 0
-         group by 1,2,3
-        union all
-        SELECT source, random_state, cluster, 0 as ball_cnt
-          from recommend_ball
-         where no=1136
-           and b1 = 0
-         group by 1,2,3
-    ) lj
-),
-source_rc_cluster_list as (
-    select ci.source, ci.random_state, ci.cluster, ci.cluster_count, ci.win_count, ci.priority, rc.source_count, bc.ball_cnt
-      from cluster_info ci
-            left join source_count rc on ci.source = rc.source
-            left join ball_count bc on ci.source = bc.source and ci.random_state = bc.random_state and ci.cluster = bc.cluster
-     where ci.priority not in (99)
-       and ci.source in (1,3)
-),
-source_process as (
-    select source, "done" as type, count(*) as cnt from source_rc_cluster_list
-      where ball_cnt is not NULL
-     group by 1,2
-    union all
-    select source, "yet" as type, count(*) as cnt from source_rc_cluster_list
-     where ball_cnt is NULL
-     group by 1,2
-)
-select source, type, cnt, 
-    case when source=1 then concat(round(100.0 * cnt / (select source_count from source_count where source=1),2), '%')
-         when source=3 then concat(round(100.0 * cnt / (select source_count from source_count where source=3),2), '%')
-    end as rate from source_process order by 1,2
-;
-
-### 미진행 클러스터 확인 ###
-SELECT ci.source, ci.random_state, ci.cluster, lj.cnt 
-  from cluster_info ci 
-  	left join (select source, random_state, cluster, count(*) as cnt from recommend_ball rb where no=1136 group by 1,2,3) lj on ci.source=lj.source and ci.random_state=lj.random_state and ci.cluster=lj.cluster
- where priority not in (99)
-   and lj.cnt is null
- order by 1,2,3
- ;
-
-
-
-
-##### 전체 cluster 확인 #####
-
-with raw_data as (
-    select rb.source, ci.priority, rb.random_state, rb.cluster, ci.cluster_count, ci.win_count, b1, count(*) as ball_cnt
-      from recommend_ball rb left join cluster_info ci on rb.source=ci.source and rb.random_state = ci.random_state and rb.cluster = ci.cluster 
-     where no=1136
-     group by 1,2,3,4,5,6,7
-),
-all_cluster as (
-    select source, priority, random_state, cluster, ball_cnt
-      from raw_data
-     where (
-            (source = 1 and priority in (1,2)) or 
-            (source = 3 and priority in (1,2))
-     )
-     group by 1,2,3,4
-),
-valid_total_cluster as (
-    select source, priority, random_state, cluster, ball_cnt
-      from raw_data
-     where (
-        (source = 1 and priority = 1 and
-                ball_cnt BETWEEN 50 and 80
-        ) or 
-        (source = 1 and priority = 2 and (
-                win_count = 12 and ball_cnt BETWEEN 50 and 80)
-        ) or
-        (source = 3 and priority = 1 and 
-                (ball_cnt BETWEEN 1 and 30 or ball_cnt BETWEEN 50 and 100)
-        ) or
-        (source = 3 and priority = 2 and (
-                win_count=13 and (ball_cnt BETWEEN 1 and 30 or ball_cnt BETWEEN 50 and 100))
-        ) or
-        (source = 1 and 
-        	((win_count between 5 and 10) and ball_cnt BETWEEN 1 and 20)
-        )
-     )
-     group by 1,2,3,4
-),
-valid_none_0_cluster as (
-    select source, priority, random_state, cluster, ball_cnt
-      from raw_data
-     where b1 <> 0 AND 
-     (
-        (source = 1 and priority = 1 and
-                ball_cnt BETWEEN 50 and 80
-        ) or 
-        (source = 1 and priority = 2 and (
-                win_count = 12 and ball_cnt BETWEEN 50 and 80)
-        ) or
-        (source = 3 and priority = 1 and 
-                (ball_cnt BETWEEN 1 and 30 or ball_cnt BETWEEN 50 and 100)
-        ) or
-        (source = 3 and priority = 2 and (
-                win_count=13 and (ball_cnt BETWEEN 1 and 30 or ball_cnt BETWEEN 50 and 100))
-        ) or
-        (source = 1 and 
-        	((win_count between 5 and 10) and ball_cnt BETWEEN 1 and 20)
-        )
-     )
-     group by 1,2,3,4
-)
-# 전체 클러스터 개수
-select 1 as col, count(*) from all_cluster
-union all
-# 조건에 해당하는 클러스터 개수
-select 2 as col, count(*) from valid_total_cluster
-union all
-# 조건에 해당하는 클러스터 중 추천이 0이 아닌 유효한 클러스터 개수
-select 3 as col, count(*) from valid_none_0_cluster
-;
-
-
-
-
-
-
-
-##### 가장 많은 추천볼 ##### 
-select b1,b2,b3,b4,b5,b6,count(*) as ball_cnt
-  from recommend_ball
- where no=1136
-   and b1>0
- group by 1,2,3,4,5,6
-order by 7 desc;
-
-
-
-
-
-
-##### 추천볼 분석 #####
-
-with priority as (
-    select source, random_state, cluster, cluster_count, win_count, priority
-      from cluster_info
-    where priority not in (99)
-),
-recommend as (
-    select source, random_state, cluster, b1,b2,b3,b4,b5,b6
-      from recommend_ball
-    where b1 > 0
-      and no=1136
-),
-recommend_count as (
-    select source, random_state, cluster, count(*) as ball_cnt
-      from recommend_ball
-    where b1 > 0
-      and no=1136
-    group by 1,2,3
-),
-raw_data as (
-    select r.source, r.random_state, r.cluster, p.cluster_count, p.win_count, p.priority, r.b1,r.b2,r.b3,r.b4,r.b5,r.b6, rc.ball_cnt
-      from recommend r 
-        left join priority p on r.source=p.source and r.random_state=p.random_state and r.cluster=p.cluster
-        left join recommend_count rc on r.source=rc.source and r.random_state=rc.random_state and r.cluster=rc.cluster        
-),
-candidate as (
-    select source, random_state, cluster, cluster_count, win_count, priority, b1,b2,b3,b4,b5,b6, ball_cnt
-      from raw_data
-     where (
-        (source = 0 and b1=7)
-        or (source = 1 and priority=-1 and ball_cnt<=140 and (
-      			b1 not in (13, 19, 28)
-      			and b2 not in (13, 19, 28)
-      			and b3 not in (13, 19, 28)
-      			and b4 not in (13, 19, 28)
-      			and b5 not in (13, 19, 28)
-      			and b6 not in (13, 19, 28)
-      		)
-      	)
-        or (source = 3 and priority=-1 and ball_cnt<=150 and (
-      			b1 not in (13, 19, 28)
-      			and b2 not in (13, 19, 28)
-      			and b3 not in (13, 19, 28)
-      			and b4 not in (13, 19, 28)
-      			and b5 not in (13, 19, 28)
-      			and b6 not in (13, 19, 28)
-      		)
-        )
-     )
-)
-#select source, random_state,cluster,b1,b2,b3,b4,b5,b6 from candidate order by 4,5,6,7,8,9;
-, duplication as (
-    # 히스트업한 추천볼에서 중복을 제거함34
-    select source, random_state, cluster, cluster_count, win_count, priority, b1,b2,b3,b4,b5,b6, ball_cnt
-     from (
-        select source, random_state, cluster, cluster_count, win_count, priority, b1,b2,b3,b4,b5,b6, ball_cnt,
-                ROW_NUMBER() OVER(PARTITION BY b1,b2,b3,b4,b5,b6 ORDER BY b1,b2,b3,b4,b5,b6) AS rnk
-          from candidate
-    ) a
-    where rnk=1
-     order by source,random_state,cluster,b1,b2,b3,b4,b5,b6
-)
-select count(*) as cnt from duplication;
-#select source, priority, random_state, cluster, win_count, count(*) as cnt from duplication group by 1,2,3;
-#select b1, count(*) as ball_cnt from duplication group by 1
-#select b6, count(*) as ball_cnt from duplication group by 1
-#select source,random_state,cluster,b1,b2,b3,b4,b5,b6 from duplication order by 4,5,6,7,8,9;
-
-
-
-
-
-```
+- 이 프로젝트는 통계적 휴리스틱 기반의 후보 축소 도구이며 당첨을 보장하지 않습니다.
+- 필터가 강해질수록 후보 수는 줄지만, 실제 당첨 조합을 배제할 위험도 함께 증가합니다.

filter_model_3.py

@@ -1,94 +0,0 @@
-"""
-filter_model_3.py
-
-OR-composed BallFilter:
-- A candidate ball is ACCEPTED if it passes EITHER filter_model_1 OR filter_model_2.
-- A candidate ball is REJECTED only if it fails BOTH.
-
-This keeps the same public interface used across the project:
-    BallFilter(lottoHistoryFileName, ruleset_path=..., ruleset=...)
-    .filter(ball, no, until_end=False, df=None, filter_ball=None) -> set[str]
-    .extract_final_candidates(ball, no=None, until_end=False, df=None) -> set[str]
-
-Notes:
-- The underlying filters return a non-empty set of failure reasons when rejected.
-- Callers treat "len(result) == 0" as PASS.
-"""
-
-from __future__ import annotations
-
-from typing import Any, Dict, Optional
-
-import filter_model_1 as fm1
-import filter_model_2 as fm2
-
-
-class BallFilter:
-    """
-    OR composition of filter_model_1.BallFilter and filter_model_2.BallFilter.
-
-    - If model1 PASSES OR model2 PASSES -> return empty set()
-    - If both FAIL -> return union of reasons (prefixed for debugging)
-    """
-
-    def __init__(
-        self,
-        lottoHistoryFileName: Optional[str] = None,
-        # Backward compatible single ruleset knobs (applied to both if specific ones not provided)
-        ruleset_path: Optional[str] = None,
-        ruleset: Optional[Dict[str, Any]] = None,
-        # Optional per-model overrides
-        ruleset_path_1: Optional[str] = None,
-        ruleset_path_2: Optional[str] = None,
-        ruleset_1: Optional[Dict[str, Any]] = None,
-        ruleset_2: Optional[Dict[str, Any]] = None,
-    ):
-        rp1 = ruleset_path_1 if ruleset_path_1 is not None else ruleset_path
-        rp2 = ruleset_path_2 if ruleset_path_2 is not None else ruleset_path
-        r1 = ruleset_1 if ruleset_1 is not None else ruleset
-        r2 = ruleset_2 if ruleset_2 is not None else ruleset
-
-        self.m1 = fm1.BallFilter(lottoHistoryFileName, ruleset_path=rp1, ruleset=r1)
-        self.m2 = fm2.BallFilter(lottoHistoryFileName, ruleset_path=rp2, ruleset=r2)
-
-    #
-    # Delegate common helper methods (both models expose the same API)
-    #
-    def getBall(self, no):
-        return self.m1.getBall(no)
-
-    def getLastNo(self, YMD):
-        return self.m1.getLastNo(YMD)
-
-    def getNextNo(self, YMD):
-        return self.m1.getNextNo(YMD)
-
-    def getYMD(self, no):
-        return self.m1.getYMD(no)
-
-    def _prefixed(self, prefix: str, reasons: set) -> set:
-        # keep stable, readable debug strings
-        return {f"{prefix}{r}" for r in reasons}
-
-    def extract_final_candidates(self, ball, no=None, until_end: bool = False, df=None):
-        """
-        OR-pass semantics:
-        - If either model returns empty set -> PASS (return empty set)
-        - Else -> FAIL (return union of reasons)
-        """
-        r1 = self.m1.extract_final_candidates(ball=ball, no=no, until_end=until_end, df=df)
-        if len(r1) == 0:
-            return set()
-        r2 = self.m2.extract_final_candidates(ball=ball, no=no, until_end=until_end, df=df)
-        if len(r2) == 0:
-            return set()
-        # both failed
-        return self._prefixed("m1:", set(r1)) | self._prefixed("m2:", set(r2))
-
-    def filter(self, ball, no, until_end: bool = False, df=None, filter_ball=None):
-        """
-        Keep signature compatible with existing callers.
-        - filter_ball is ignored here (callers typically pre-filter before calling .filter()).
-        """
-        return self.extract_final_candidates(ball=ball, no=no, until_end=until_end, df=df)
-

final_filterTest.py

@@ -1,50 +1,33 @@
-# -*- coding: utf-8 -*-
-"""
-학습(1~800) / 검증(801~1000) / 테스트(1001~) 구간별 필터 통과(당첨번호가 필터를 통과하는지) 분석.
-1_FilterTest_25.py 와 동일한 흐름이며 BallFilter 대신 final_BallFilter.BallFilter 를 사용합니다.
-
-실행: miniconda 환경 ncue 에서 `python final_filterTest.py` (README 참고).
-"""
-from __future__ import annotations
-
-import datetime
 import os
-import time
-
 import pandas as pd
-
+import itertools
 from final_BallFilter import BallFilter
-
-# PROMPT.txt 기준 구간
-TRAIN_NO = (1, 800)
-VALID_NO = (801, 1000)
-TEST_NO = (1001, 10**9)
-
+import time
+import datetime
 
 class FilterTest:
-    def __init__(self, resources_path: str):
-        lotto_json = os.path.join(resources_path, "lotto_history.json")
-        self.ballFilter = BallFilter(lotto_json)
 
-    def find_filter_method(self, df_ball, filter_ball=None, no_min=None, no_max=None):
-        """no_min~no_max 회차만 역순으로 검사 (None 이면 전체)."""
+    def __init__(self, resources_path):
+        lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.json')
+        self.ballFilter = BallFilter(lottoHistoryFileName)
+
+        return
+
+    def find_filter_method(self, df_ball, filter_ball=None):
         win_count = 0
+
         no_filter_ball = {}
+
+        printLog = True
         filter_dic = {}
         filter_dic_len = {}
         filter_dic_1 = {}
         filter_dic_2 = {}
+        for i in range(len(df_ball)-1, 19, -1):
 
-        idx_list = list(range(len(df_ball) - 1, 19, -1))
-        for i in idx_list:
-            no = int(df_ball["no"].iloc[i])
-            if no_min is not None and no < no_min:
-                continue
-            if no_max is not None and no > no_max:
-                continue
-
-            answer = df_ball[df_ball["no"] == no].values.tolist()[0]
-            answer = answer[1:7]
+            no = df_ball['no'].iloc[i]
+            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
+            answer = sorted(answer[1:7])
 
             filter_type = self.ballFilter.filter(ball=answer, no=no, until_end=True, df=df_ball)
             filter_type = list(filter_type)
@@ -53,60 +36,180 @@ class FilterTest:
             if size == 0:
                 win_count += 1
                 no_filter_ball[no] = answer
+                print("\t", no)
             elif size == 1:
                 key = filter_type[0]
-                filter_dic_1[key] = filter_dic_1.get(key, 0) + 1
+                if key not in filter_dic_1:
+                    filter_dic_1[key] = 1
+                else:
+                    filter_dic_1[key] += 1
+
+                if printLog:
+                    print("\t", no, filter_type)
             elif size == 2:
-                key = ",".join(filter_type)
-                filter_dic_2[key] = filter_dic_2.get(key, 0) + 1
+                key = ','.join(filter_type)
+                if key not in filter_dic_2:
+                    filter_dic_2[key] = 1
+                else:
+                    filter_dic_2[key] += 1
+
+                if printLog:
+                    print("\t", no, filter_type)
             else:
+                if printLog:
+                    print("\t", no, filter_type)
+
+                # 회차별 필터개수가 적은 것을 정렬하기 위함
                 if size not in filter_dic_len:
                     filter_dic_len[size] = []
                 filter_dic_len[size].append(filter_type)
 
             for f_t in filter_type:
-                filter_dic[f_t] = filter_dic.get(f_t, 0) + 1
+                if f_t not in filter_dic:
+                    filter_dic[f_t] = 1
+                else:
+                    filter_dic[f_t] += 1
 
-        print("\n\t[구간 {}~{}] 필터에 걸리지 않은 회차 (당첨 조합 통과)]".format(no_min, no_max))
-        print("\tcount: {:,} (통과)".format(len(no_filter_ball)))
-        for no in sorted(no_filter_ball.keys()):
+        print("\n\t[필터 개수가 적은 것부터 최적화를 위함]")
+        sorted_filter_dic_len = sorted(filter_dic_len.keys())
+        for filter_count in sorted_filter_dic_len:
+            for filter_type in filter_dic_len[filter_count]:
+                print("\t\t>{} > {}".format(filter_count, filter_type))
+
+        print("\n\t[걸러진 유일 필터]")
+        sorted_filter_dic_1 = sorted(filter_dic_1.items(), key=lambda x: x[1], reverse=True)
+        for i in range(len(sorted_filter_dic_1)):
+            print("\t\t>", sorted_filter_dic_1[i][0], "->", sorted_filter_dic_1[i][1])
+
+        print("\n\t[2개 필터에 걸린 경우]")
+        sorted_filter_dic_2 = sorted(filter_dic_2.items(), key=lambda x: x[1], reverse=True)
+        for i in range(len(sorted_filter_dic_2)):
+            print("\t\t>", sorted_filter_dic_2[i][0], "->", sorted_filter_dic_2[i][1])
+
+        print("\n\t[Filter 유형 별 걸린 개수]")
+        sorted_filter_dic = sorted(filter_dic.items(), key=lambda x: x[1], reverse=True)
+        for i in range(len(sorted_filter_dic)):
+            print("\t\t>", sorted_filter_dic[i][0], "->", sorted_filter_dic[i][1])
+
+        print("\n\t# 필터에 걸리지 않고 당첨된 회차")
+        print("\tcount: {:,} / total: {:,}".format(len(no_filter_ball), len(df_ball)))
+        for no in no_filter_ball:
             print("\t\t>", no, no_filter_ball[no])
+        print("\tcount: {:,} / total: {:,}".format(len(no_filter_ball), len(df_ball)))
 
-        return win_count, no_filter_ball
+        return win_count
 
-    def report_split(self, df_ball, name: str, lo: int, hi: int):
-        print("\n" + "=" * 60)
-        print(" {} | 회차 {} ~ {}".format(name, lo, hi))
-        print("=" * 60)
-        t0 = time.time()
-        wc, _ = self.find_filter_method(df_ball, no_min=lo, no_max=hi)
-        elapsed = datetime.timedelta(seconds=time.time() - t0)
-        span = hi - lo + 1
-        rate = (wc / span * 100) if span else 0
-        print("\t처리 시간: {}".format(elapsed))
-        print("\t통과 회차 수: {} / {} ({:.2f}%)".format(wc, span, rate))
-        if lo >= TRAIN_NO[0] and hi <= TRAIN_NO[1]:
-            need = max(1, span // 100)
-            print("\t(참고) 100회당 최소 1회 기준 대략 {}회 이상이면 충족".format(need))
-        if lo >= VALID_NO[0] and hi <= VALID_NO[1]:
-            print("\t(참고) 검증 200회 구간에서 최소 3회 이상이면 요구사항 예시 충족")
-        return wc
+    def find_final_candidates(self, no, df_ball, filter_ball=None):
+        final_candidates = []
+
+        generation_balls = list(range(1, 46))
+
+        nCr = list(itertools.combinations(generation_balls, 6))
+        for idx, ball in enumerate(nCr):
+
+            if idx % 1000000 == 0:
+                print("   - {} processed...".format(idx))
+
+            if filter_ball is not None and 0 < len(set(ball) & set(filter_ball)):
+                continue
+
+            ball = sorted(list(ball))
+            filter_type = self.ballFilter.filter(ball=ball, no=no, until_end=False, df=df_ball)
+            filter_size = len(filter_type)
+
+            if filter_size:
+                continue
+
+            final_candidates.append(ball)
+
+        return final_candidates
+
+    def check_filter_method(self, df_ball, p_win_count, filter_ball=None):
+
+        win_count = 0
+        for i in range(len(df_ball)-1, 0, -1):
+
+            no = df_ball['no'].iloc[i]
+            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
+            answer = sorted(answer[1:7])
+
+            if filter_ball is not None and len(set(answer) & set(filter_ball)):
+                continue
+
+            filter_type = self.ballFilter.extract_final_candidates(answer, no=no, until_end=True, df=df_ball)
+
+            if len(filter_type) == 0:
+                win_count += 1
+                print("\t\t>{}. {}".format(no, answer))
+
+        print("\n\t> {} / {} p_win_count, {} total".format( win_count, p_win_count, len(df_ball)-1) )
+
+        return
+
+    def validate(self, df_ball, nos=None):
+        win_history = {}
+
+        for no in nos:
+            print(no, "processing...")
+            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
+            answer = sorted(answer[1:7])
+
+            generation_balls = list(range(1, 46))
+            nCr = list(itertools.combinations(generation_balls, 6))
+            for idx, ball in enumerate(nCr):
+                if idx % 1000000 == 0:
+                    print("   - {} processed...".format(idx))
+                ball = sorted(list(ball))
+                filter_type = self.ballFilter.extract_final_candidates(ball, no=no, until_end=True, df=df_ball)
+                if 0 == len(filter_type) and len(set(answer)&set(ball))==6:
+                    win_history[no] = answer
+                    print("win.. no: {}, answer: {}".format(no, str(answer)))
+                    break
+
+        return win_history
 
 
-if __name__ == "__main__":
-    resources_path = os.path.join(os.path.dirname(__file__), "resources")
-    csv_path = os.path.join(resources_path, "lotto_history.txt")
-    df_ball = pd.read_csv(csv_path, header=None)
-    df_ball.columns = ["no", "b1", "b2", "b3", "b4", "b5", "b6", "bn"]
+if __name__ == '__main__':
 
-    ft = FilterTest(resources_path)
+    resources_path = 'resources'
 
-    ft.report_split(df_ball, "학습 TRAIN", TRAIN_NO[0], TRAIN_NO[1])
-    ft.report_split(df_ball, "검증 VALID", VALID_NO[0], min(VALID_NO[1], int(df_ball["no"].max())))
-    if int(df_ball["no"].max()) >= TEST_NO[0]:
-        ft.report_split(
-            df_ball,
-            "테스트 TEST",
-            TEST_NO[0],
-            int(df_ball["no"].max()),
-        )
+    lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.txt')
+    df_ball = pd.read_csv(lottoHistoryFileName, header=None)
+    df_ball.columns = ['no', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'bn']
+
+    filter_ball=[]
+    filterTest = FilterTest(resources_path)
+
+    print("STEP #1. 필터 방법 추출")
+    start = time.time()
+    win_count = filterTest.find_filter_method(df_ball, filter_ball)
+    process_time = datetime.timedelta(seconds=time.time() - start)
+    print("process_time: ", process_time)
+
+    """
+    print("\n\n")
+    no = df_ball['no'].values[-1]
+    ball = df_ball[df_ball['no'] == no].values.tolist()[0]
+    answer = ball[1:7]
+
+    print("STEP #0. 최종 후보 선정")
+    start = time.time()
+    final_candidates = filterTest.find_final_candidates(no, df_ball, filter_ball=None)
+    process_time = datetime.timedelta(seconds=time.time() - start)
+    print("process_time: ", process_time)
+
+    print("   > size: {}".format(len(final_candidates)))
+    file_name = os.path.join(resources_path, 'final_candidates.biz_a1.txt')
+    with open(file_name, 'w+') as outFp:
+        for ball in final_candidates:
+            ball_str = [str(b) for b in answer]
+            outFp.write("{}\n".format(','.join(ball_str)))
+
+    print('{}회, 정답: {}\n'.format(no, str(answer)))
+    """
+
+    #print("\n\n")
+    #print("STEP #2. 당첨 회수 확인")
+    #filterTest.check_filter_method(df_ball, win_count)
+
+    # 오리지널 버전 (자질 파일에 고정): 당첨 22개

final_practice.py

@@ -0,0 +1,409 @@
+# 웹 호출 라이브러리를 호출합니다.
+import time
+import requests
+from DataCrawler import DataCrawler
+
+import json
+import os
+import random
+import pandas as pd
+import itertools
+from collections import Counter
+from datetime import datetime, timedelta
+from TelegramBot import TelegramBot
+
+from final_BallFilter import BallFilter
+
+COST_PER_GAME = 1000
+MAX_BUDGET_KRW = 70000
+MAX_GAMES_PER_DRAW = MAX_BUDGET_KRW // COST_PER_GAME
+
+class Practice:
+
+    bot = None
+    preprocessor = None
+    predictor = None
+
+    extract_count = None
+
+    def __init__(self, resources_path):
+        self.bot = TelegramBot()
+
+        return
+
+    # 로또 당첨 데이터를 수집해서 파일로 저장합니다.
+    # lottoHistoryFile: 로또 당첨 데이터를 저장할 파일
+    def craw(self, lottoHistoryFile, drwNo=None):
+
+        ball = None
+        if drwNo != None:
+            # 로또 데이터를 저장할 파일을 선언합니다.
+            jsonFp = open(lottoHistoryFile + ".json", 'a', encoding="utf-8")
+            textFp = open(lottoHistoryFile + ".txt", 'a', encoding="utf-8")
+
+            url = 'https://dhlottery.co.kr/common.do?method=getLottoNumber&drwNo=' + str(drwNo)
+            # URL을 호출합니다.
+            res = requests.post(url)
+            # 호출한 결과에 대해서 Json 포맷을 가져옵니다.
+            result = res.json()
+
+            if result['returnValue'] != 'success':
+                return None
+
+            # 가져온 Json 포맷을 파일로 저장합니다.
+            jsonFp.write(json.dumps(result, ensure_ascii=False) + "\n")
+            textFp.write("%d,%d,%d,%d,%d,%d,%d,%d\n" % (drwNo, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
+            print("%d,%d,%d,%d,%d,%d,%d,%d" % (drwNo, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
+
+            ball = [result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']]
+        else:
+            # 로또 데이터를 저장할 파일을 선언합니다.
+            jsonFp = open(lottoHistoryFile + ".json", 'w', encoding="utf-8")
+            textFp = open(lottoHistoryFile + ".txt", 'w', encoding="utf-8")
+
+            # 1회차부터 지정된 회차까지 로또 당첨 번호를 수집합니다.
+            idx = 1
+            while True:
+                # 1회차부터 지정된 회차까지의 URL을 생성합니다.
+                url = 'https://dhlottery.co.kr/common.do?method=getLottoNumber&drwNo=' + str(idx)
+                # URL을 호출합니다.
+                res = requests.post(url)
+                # 호출한 결과에 대해서 Json 포맷을 가져옵니다.
+                result = res.json()
+                if result['returnValue'] != 'success':
+                    break
+                # 가져온 Json 포맷을 파일로 저장합니다.
+                jsonFp.write(json.dumps(result, ensure_ascii=False) + "\n")
+                textFp.write("%d,%d,%d,%d,%d,%d,%d,%d\n" % (idx, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
+                print("%d,%d,%d,%d,%d,%d,%d,%d" % (idx, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
+                ball = [result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']]
+                idx += 1
+                time.sleep(0.5)
+        # 저장한 파일을 종료합니다.
+        jsonFp.close()
+        textFp.close()
+
+        return ball
+
+    def predict1(self, result_json):
+        result_json.append([6, 7, 10, 11, 20, 45])
+        result_json.append([5, 12, 16, 27, 39, 45])
+        result_json.append([5, 15, 18, 29, 36, 41])
+        result_json.append([1, 17, 20, 25, 36, 45])
+        result_json.append([6, 15, 20, 23, 37, 43])
+        result_json.append([8, 15, 19, 23, 38, 41])
+        result_json.append([3, 14, 20, 27, 35, 45])
+        result_json.append([5, 11, 19, 24, 40, 45])
+        result_json.append([5, 9, 20, 25, 32, 37])
+        result_json.append([2, 13, 19, 27, 40, 43])
+        result_json.append([4, 13, 17, 28, 39, 43])
+
+        return
+
+    def validate_fixed_balls(self, resources_path, ymd, fixed_balls):
+        """
+        고정수 BallFilter 통과 여부를 검증한다.
+
+        Returns:
+            dict: total, passed_count, failed_count, draw_no, details
+        """
+        lotto_history_json = os.path.join(resources_path, 'lotto_history.json')
+        ball_filter = BallFilter(lotto_history_json)
+        draw_no = ball_filter.getNextNo(ymd)
+
+        lotto_history_txt = os.path.join(resources_path, 'lotto_history.txt')
+        df_ball = pd.read_csv(lotto_history_txt, header=None)
+        df_ball.columns = ['no', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'bn']
+        prev_row = df_ball[df_ball['no'] == draw_no - 1].values.tolist()[0]
+        p_ball = prev_row[1:7]
+
+        details = []
+        passed_count = 0
+        for index, ball in enumerate(fixed_balls):
+            filter_type = ball_filter.filter(
+                ball=ball, no=draw_no, until_end=False, df=df_ball, p_ball=p_ball
+            )
+            passed = len(filter_type) == 0
+            if passed:
+                passed_count += 1
+            details.append({
+                'index': index + 1,
+                'ball': ball,
+                'passed': passed,
+                'filter_reasons': sorted(filter_type),
+            })
+
+        return {
+            'draw_no': draw_no,
+            'total': len(fixed_balls),
+            'passed_count': passed_count,
+            'failed_count': len(fixed_balls) - passed_count,
+            'details': details,
+        }
+
+    @staticmethod
+    def format_fixed_validation_summary(validation):
+        """고정수 검증 결과를 Telegram/로그용 문자열로 변환한다."""
+        lines = [
+            "   - 고정수 필터 검증: {}/{} 통과".format(
+                validation['passed_count'], validation['total']
+            )
+        ]
+        if validation['failed_count'] > 0:
+            lines.append(
+                "   - 필터 예외 포함: {}개 (고정수 유지)".format(
+                    validation['failed_count']
+                )
+            )
+            for item in validation['details']:
+                if item['passed']:
+                    continue
+                reason = item['filter_reasons'][0] if item['filter_reasons'] else 'unknown'
+                lines.append(
+                    "     * #{} {} -> {}".format(item['index'], item['ball'], reason)
+                )
+        return "\n".join(lines)
+
+    def _can_add_ball(self, ball, fixed_balls, selected_balls, max_overlap):
+        ball_set = set(ball)
+
+        for fixed_ball in fixed_balls:
+            if len(ball_set & set(fixed_ball)) > max_overlap:
+                return False
+
+        for selected_ball in selected_balls:
+            if len(ball_set & set(selected_ball)) > max_overlap:
+                return False
+
+        return True
+
+    @staticmethod
+    def _portfolio_number_counts(fixed_balls, selected_balls):
+        """포트폴리오 내 번호 등장 횟수를 집계한다."""
+        counts = Counter()
+        for ball in fixed_balls + selected_balls:
+            counts.update(ball)
+        return counts
+
+    @staticmethod
+    def _coverage_priority(ball, number_counts):
+        """낮을수록 포트폴리오에 덜 등장한 번호 위주 조합이다."""
+        return sum(number_counts.get(number, 0) for number in ball)
+
+    def _pick_best_candidate(self, unique_candidates, selected_keys, fixed_balls, selected, max_overlap):
+        """겹침 제약을 만족하는 후보 중 번호 커버리지가 가장 넓은 조합을 고른다."""
+        number_counts = self._portfolio_number_counts(fixed_balls, selected)
+        best_candidate = None
+        best_score = None
+        best_key = None
+
+        for candidate in unique_candidates:
+            key = tuple(candidate)
+            if key in selected_keys:
+                continue
+            if not self._can_add_ball(candidate, fixed_balls, selected, max_overlap):
+                continue
+
+            score = self._coverage_priority(candidate, number_counts)
+            if best_candidate is None or score < best_score or (score == best_score and key < best_key):
+                best_candidate = candidate
+                best_score = score
+                best_key = key
+
+        return best_candidate, best_key
+
+    def select_portfolio(self, fixed_balls, candidates, target_count, shuffle_seed=None):
+        """
+        2차 포트폴리오 선정:
+        - 중복 제거
+        - shuffle_seed 기반 셔플로 순서 편향 완화
+        - 고정수/선정수 간 중복도(겹치는 번호 수) 제약을 단계적으로 완화하며 선택
+        - 동률 후보는 번호 커버리지가 넓은 조합 우선
+        """
+        unique_candidates = []
+        seen = set()
+        fixed_keys = {tuple(sorted(fixed_ball)) for fixed_ball in fixed_balls}
+
+        for candidate in candidates:
+            key = tuple(sorted(candidate))
+            if key in seen or key in fixed_keys:
+                continue
+            seen.add(key)
+            unique_candidates.append(list(key))
+
+        if shuffle_seed is not None:
+            rng = random.Random(int(shuffle_seed))
+            rng.shuffle(unique_candidates)
+
+        if target_count <= 0:
+            return []
+
+        if len(unique_candidates) <= target_count:
+            return unique_candidates
+
+        selected = []
+        selected_keys = set()
+        overlap_stages = [2, 3, 4, 5]
+
+        for max_overlap in overlap_stages:
+            while len(selected) < target_count:
+                best_candidate, best_key = self._pick_best_candidate(
+                    unique_candidates, selected_keys, fixed_balls, selected, max_overlap
+                )
+                if best_candidate is None:
+                    break
+
+                selected.append(best_candidate)
+                selected_keys.add(best_key)
+
+            if len(selected) >= target_count:
+                return selected
+
+        while len(selected) < target_count:
+            best_candidate, best_key = self._pick_best_candidate(
+                unique_candidates, selected_keys, fixed_balls, selected, max_overlap=6
+            )
+            if best_candidate is None:
+                break
+            selected.append(best_candidate)
+            selected_keys.add(best_key)
+
+        return selected
+
+    def predict2(self, resources_path, ymd, fixed_balls, max_games_per_draw=MAX_GAMES_PER_DRAW):
+
+        candidates = [i for i in range(1, 46)]
+
+        lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.json')
+        ballFilter = BallFilter(lottoHistoryFileName)
+        no = ballFilter.getNextNo(ymd)
+        print("회차: {}".format(no))
+
+        lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.txt')
+        df_ball = pd.read_csv(lottoHistoryFileName, header=None)
+        df_ball.columns = ['no', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'bn']
+
+        prev_row = df_ball[df_ball['no'] == no - 1].values.tolist()[0]
+        p_ball = prev_row[1:7]
+
+        passed_candidates = []
+        for idx, ball in enumerate(itertools.combinations(candidates, 6)):
+
+            if idx % 1000000 == 0:
+                print("   - {} processed, pass: {}".format(idx, len(passed_candidates)))
+            ball = list(ball)
+
+            filter_type = ballFilter.filter(
+                ball=ball, no=no, until_end=False, df=df_ball, p_ball=p_ball
+            )
+            filter_size = len(filter_type)
+
+            if 0 < filter_size:
+                continue
+
+            passed_candidates.append(ball)
+
+        variable_target_count = max(0, max_games_per_draw - len(fixed_balls))
+        selected_candidates = self.select_portfolio(
+            fixed_balls=fixed_balls,
+            candidates=passed_candidates,
+            target_count=variable_target_count,
+            shuffle_seed=ymd,
+        )
+
+        p_no = prev_row[0]
+
+        return p_no, p_ball, selected_candidates, len(passed_candidates), variable_target_count
+
+if __name__ == '__main__':
+
+    PROJECT_HOME = '.'
+    resources_path = os.path.join(PROJECT_HOME, 'resources')
+
+    # 데이터 수집
+    #dataCrawler = DataCrawler()
+    #dataCrawler.excute(resources_path)
+
+    today = datetime.today()
+    if today.weekday() == 5:
+        if today.hour > 20:
+            this_weekend = today + timedelta(days=(12 - today.weekday()))
+        else:
+            this_weekend = today + timedelta(days=(5 - today.weekday()))
+    elif today.weekday() == 6:
+        this_weekend = today + timedelta(days=(12 - today.weekday()))
+    else:
+        this_weekend = today + timedelta(days=(5 - today.weekday()))
+
+    last_weekend = (this_weekend - timedelta(days=7)).strftime('%Y%m%d')
+    ymd = this_weekend.strftime('%Y%m%d')
+
+    print("ymd: {}".format(ymd))
+
+    # 로또 예측
+    practice = Practice(resources_path)
+
+    recommend_result_file = os.path.join(resources_path, "recommend_ball.biz_25.json")
+    if os.path.isfile(recommend_result_file):
+        with open(recommend_result_file, "r", encoding="utf-8") as result_fp:
+            result_json = json.load(result_fp)
+        result_json[ymd] = []
+    else:
+        result_json = {ymd: []}
+
+    # 매주 고정
+    fixed_balls = []
+    practice.predict1(fixed_balls)
+    fixed_validation = practice.validate_fixed_balls(
+        resources_path=resources_path,
+        ymd=ymd,
+        fixed_balls=fixed_balls,
+    )
+    print(Practice.format_fixed_validation_summary(fixed_validation))
+    result_json[ymd].extend(fixed_balls)
+
+    # 필터 기반 예측
+    p_no, p_ball, selected_candidates, passed_count, variable_target_count = practice.predict2(
+        resources_path=resources_path,
+        ymd=ymd,
+        fixed_balls=fixed_balls,
+        max_games_per_draw=MAX_GAMES_PER_DRAW
+    )
+    result_json[ymd].extend(selected_candidates)
+
+    if '_meta' not in result_json:
+        result_json['_meta'] = {}
+    result_json['_meta'][ymd] = {
+        'fixed_validation': fixed_validation,
+        'passed_count': passed_count,
+        'selected_count': len(selected_candidates),
+        'portfolio_shuffle_seed': ymd,
+    }
+
+    with open(recommend_result_file, 'w', encoding='utf-8') as outFp:
+        json.dump(result_json, outFp, ensure_ascii=False)
+
+    total_games = len(result_json[ymd])
+    total_cost = total_games * COST_PER_GAME
+    p_str = "[지난주] {}\n   - {} 회차, {}\n[금주] {}\n   - {} 회차\n[모델#25]\n".format(last_weekend, p_no, str(p_ball), ymd, (p_no + 1))
+    p_str += "   - 고정수: {}개\n".format(len(fixed_balls))
+    p_str += Practice.format_fixed_validation_summary(fixed_validation) + "\n"
+    p_str += "   - 필터 통과 후보: {}개\n".format(passed_count)
+    p_str += "   - 추가 선정: {}개 (목표 {}개)\n".format(len(selected_candidates), variable_target_count)
+    p_str += "   - 총 추천: {}개, 총 금액: {:,}원 (한도 {:,}원)\n".format(total_games, total_cost, MAX_BUDGET_KRW)
+    for i, ball in enumerate(result_json[ymd]):
+        p_str += "   {}. {}\n".format((i+1), str(ball))
+        if (i+1) % 100 == 0:
+            practice.bot.sendMsg("{}".format(p_str))
+            p_str = ''
+
+    if len(result_json[ymd]) % 100 != 0:
+        practice.bot.sendMsg("{}".format(p_str))
+
+    print("size: {}".format(total_games))
+    print("cost: {:,} KRW / limit: {:,} KRW".format(total_cost, MAX_BUDGET_KRW))
+
+    # https://youtu.be/QjBsui8Ob14?si=4dC3q8p0Yu5ZWK1K
+    # https://www.youtube.com/watch?v=YwiHaa1KNwA
+
+    print("done...")

practice_1.py

@@ -1,179 +0,0 @@
-# 웹 호출 라이브러리를 호출합니다.
-import time
-import requests
-from DataCrawler import DataCrawler
-
-import json
-import os
-import pandas as pd
-import itertools
-from datetime import datetime, timedelta
-from TelegramBot import TelegramBot
-
-from filter_model_1 import BallFilter
-
-class Practice:
-
-    bot = None
-    preprocessor = None
-    predictor = None
-
-    extract_count = None
-
-    def __init__(self, resources_path):
-        self.bot = TelegramBot()
-
-        return
-
-    # 로또 당첨 데이터를 수집해서 파일로 저장합니다.
-    # lottoHistoryFile: 로또 당첨 데이터를 저장할 파일
-    def craw(self, lottoHistoryFile, drwNo=None):
-
-        ball = None
-        if drwNo != None:
-            # 로또 데이터를 저장할 파일을 선언합니다.
-            jsonFp = open(lottoHistoryFile + ".json", 'a', encoding="utf-8")
-            textFp = open(lottoHistoryFile + ".txt", 'a', encoding="utf-8")
-
-            url = 'https://dhlottery.co.kr/common.do?method=getLottoNumber&drwNo=' + str(drwNo)
-            # URL을 호출합니다.
-            res = requests.post(url)
-            # 호출한 결과에 대해서 Json 포맷을 가져옵니다.
-            result = res.json()
-
-            if result['returnValue'] != 'success':
-                return None
-
-            # 가져온 Json 포맷을 파일로 저장합니다.
-            jsonFp.write(json.dumps(result, ensure_ascii=False) + "\n")
-            textFp.write("%d,%d,%d,%d,%d,%d,%d,%d\n" % (drwNo, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
-            print("%d,%d,%d,%d,%d,%d,%d,%d" % (drwNo, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
-
-            ball = [result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']]
-        else:
-            # 로또 데이터를 저장할 파일을 선언합니다.
-            jsonFp = open(lottoHistoryFile + ".json", 'w', encoding="utf-8")
-            textFp = open(lottoHistoryFile + ".txt", 'w', encoding="utf-8")
-
-            # 1회차부터 지정된 회차까지 로또 당첨 번호를 수집합니다.
-            idx = 1
-            while True:
-                # 1회차부터 지정된 회차까지의 URL을 생성합니다.
-                url = 'https://dhlottery.co.kr/common.do?method=getLottoNumber&drwNo=' + str(idx)
-                # URL을 호출합니다.
-                res = requests.post(url)
-                # 호출한 결과에 대해서 Json 포맷을 가져옵니다.
-                result = res.json()
-                if result['returnValue'] != 'success':
-                    break
-                # 가져온 Json 포맷을 파일로 저장합니다.
-                jsonFp.write(json.dumps(result, ensure_ascii=False) + "\n")
-                textFp.write("%d,%d,%d,%d,%d,%d,%d,%d\n" % (idx, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
-                print("%d,%d,%d,%d,%d,%d,%d,%d" % (idx, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
-                ball = [result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']]
-                idx += 1
-                time.sleep(0.5)
-        # 저장한 파일을 종료합니다.
-        jsonFp.close()
-        textFp.close()
-
-        return ball
-
-    def predict1(self, result_json):
-        result_json.append([6,7,10,11,20,45])
-        return
-
-    def predict2(self, resources_path, ymd, result_json):
-
-        candidates = [i for i in range(1, 46)]
-
-        lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.json')
-        ballFilter = BallFilter(lottoHistoryFileName)
-        no = ballFilter.getNextNo(ymd)
-        print("회차: {}".format(no))
-
-        lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.txt')
-        df_ball = pd.read_csv(lottoHistoryFileName, header=None)
-        df_ball.columns = ['no', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'bn']
-
-        #filter_ball=[1,2,4,6,10,11,11,17,18,20,21,22,23,24,26,27,28,30,31,32,33,34,37,38,39,40,42,44]
-        nCr = list(itertools.combinations(candidates, 6))
-        for idx, ball in enumerate(nCr):
-
-            if idx % 1000000 == 0:
-                print("   - {} processed...".format(idx))
-
-            ball = list(ball)
-
-            filter_type = ballFilter.filter(ball=ball, no=no, until_end=False, df=df_ball)
-            filter_size = len(filter_type)
-
-            if 0 < filter_size:
-                continue
-
-            result_json.append(ball)
-
-        p_ball = df_ball[df_ball['no'] == no - 1].values.tolist()[0]
-        p_no = p_ball[0]
-        p_ball = p_ball[1:7]
-
-        return p_no, p_ball
-
-if __name__ == '__main__':
-
-    PROJECT_HOME = '.'
-    resources_path = os.path.join(PROJECT_HOME, 'resources')
-
-    today = datetime.today()
-    if today.weekday() == 5:
-        if today.hour > 20:
-            this_weekend = today + timedelta(days=(12 - today.weekday()))
-        else:
-            this_weekend = today + timedelta(days=(5 - today.weekday()))
-    elif today.weekday() == 6:
-        this_weekend = today + timedelta(days=(12 - today.weekday()))
-    else:
-        this_weekend = today + timedelta(days=(5 - today.weekday()))
-
-    last_weekend = (this_weekend - timedelta(days=7)).strftime('%Y%m%d')
-    ymd = this_weekend.strftime('%Y%m%d')
-
-    print("ymd: {}".format(ymd))
-
-    # 로또 예측
-    practice = Practice(resources_path)
-
-    # 데이터 수집
-    lottoHistoryFile = PROJECT_HOME + '/resources/lotto_history'
-    lottoHistoryFileName = lottoHistoryFile + '.json'
-    with open(lottoHistoryFileName, "r", encoding='utf-8') as f:
-        for line in f:
-            if line != '\n':
-                last_json = json.loads(line)
-
-    #ball = practice.craw(lottoHistoryFile, drwNo=last_json['drwNo'] + 1)
-
-    result_json = {ymd: []}
-
-    # 매주 고정
-    practice.predict1(result_json[ymd])
-    # 필터 기반 예측
-    p_no, p_ball = practice.predict2(resources_path, ymd, result_json[ymd])
-
-    p_str = "[지난주] {}\n   - {} 회차, {}\n[금주] {}\n   - {} 회차\n[모델#25]\n".format(last_weekend, p_no, str(p_ball), ymd, (p_no + 1))
-    for i, ball in enumerate(result_json[ymd]):
-        p_str += "   {}. {}\n".format((i+1), str(ball))
-        if (i+1) % 100 == 0:
-            practice.bot.sendMsg("{}".format(p_str))
-            p_str = ''
-
-    if len(result_json[ymd]) % 100 != 0:
-        practice.bot.sendMsg("{}".format(p_str))
-
-    size = len(result_json[ymd])
-    print("size: {}".format(size))
-
-    # https://youtu.be/QjBsui8Ob14?si=4dC3q8p0Yu5ZWK1K
-    # https://www.youtube.com/watch?v=YwiHaa1KNwA
-
-    print("done...")

practice_2.py

@@ -1,179 +0,0 @@
-# 웹 호출 라이브러리를 호출합니다.
-import time
-import requests
-from DataCrawler import DataCrawler
-
-import json
-import os
-import pandas as pd
-import itertools
-from datetime import datetime, timedelta
-from TelegramBot import TelegramBot
-
-from filter_model_2 import BallFilter
-
-class Practice:
-
-    bot = None
-    preprocessor = None
-    predictor = None
-
-    extract_count = None
-
-    def __init__(self, resources_path):
-        self.bot = TelegramBot()
-
-        return
-
-    # 로또 당첨 데이터를 수집해서 파일로 저장합니다.
-    # lottoHistoryFile: 로또 당첨 데이터를 저장할 파일
-    def craw(self, lottoHistoryFile, drwNo=None):
-
-        ball = None
-        if drwNo != None:
-            # 로또 데이터를 저장할 파일을 선언합니다.
-            jsonFp = open(lottoHistoryFile + ".json", 'a', encoding="utf-8")
-            textFp = open(lottoHistoryFile + ".txt", 'a', encoding="utf-8")
-
-            url = 'https://dhlottery.co.kr/common.do?method=getLottoNumber&drwNo=' + str(drwNo)
-            # URL을 호출합니다.
-            res = requests.post(url)
-            # 호출한 결과에 대해서 Json 포맷을 가져옵니다.
-            result = res.json()
-
-            if result['returnValue'] != 'success':
-                return None
-
-            # 가져온 Json 포맷을 파일로 저장합니다.
-            jsonFp.write(json.dumps(result, ensure_ascii=False) + "\n")
-            textFp.write("%d,%d,%d,%d,%d,%d,%d,%d\n" % (drwNo, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
-            print("%d,%d,%d,%d,%d,%d,%d,%d" % (drwNo, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
-
-            ball = [result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']]
-        else:
-            # 로또 데이터를 저장할 파일을 선언합니다.
-            jsonFp = open(lottoHistoryFile + ".json", 'w', encoding="utf-8")
-            textFp = open(lottoHistoryFile + ".txt", 'w', encoding="utf-8")
-
-            # 1회차부터 지정된 회차까지 로또 당첨 번호를 수집합니다.
-            idx = 1
-            while True:
-                # 1회차부터 지정된 회차까지의 URL을 생성합니다.
-                url = 'https://dhlottery.co.kr/common.do?method=getLottoNumber&drwNo=' + str(idx)
-                # URL을 호출합니다.
-                res = requests.post(url)
-                # 호출한 결과에 대해서 Json 포맷을 가져옵니다.
-                result = res.json()
-                if result['returnValue'] != 'success':
-                    break
-                # 가져온 Json 포맷을 파일로 저장합니다.
-                jsonFp.write(json.dumps(result, ensure_ascii=False) + "\n")
-                textFp.write("%d,%d,%d,%d,%d,%d,%d,%d\n" % (idx, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
-                print("%d,%d,%d,%d,%d,%d,%d,%d" % (idx, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
-                ball = [result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']]
-                idx += 1
-                time.sleep(0.5)
-        # 저장한 파일을 종료합니다.
-        jsonFp.close()
-        textFp.close()
-
-        return ball
-
-    def predict1(self, result_json):
-        result_json.append([6,7,10,11,20,45])
-        return
-
-    def predict2(self, resources_path, ymd, result_json):
-
-        candidates = [i for i in range(1, 46)]
-
-        lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.json')
-        ballFilter = BallFilter(lottoHistoryFileName)
-        no = ballFilter.getNextNo(ymd)
-        print("회차: {}".format(no))
-
-        lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.txt')
-        df_ball = pd.read_csv(lottoHistoryFileName, header=None)
-        df_ball.columns = ['no', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'bn']
-
-        #filter_ball=[1,2,4,6,10,11,11,17,18,20,21,22,23,24,26,27,28,30,31,32,33,34,37,38,39,40,42,44]
-        nCr = list(itertools.combinations(candidates, 6))
-        for idx, ball in enumerate(nCr):
-
-            if idx % 1000000 == 0:
-                print("   - {} processed...".format(idx))
-
-            ball = list(ball)
-
-            filter_type = ballFilter.filter(ball=ball, no=no, until_end=False, df=df_ball)
-            filter_size = len(filter_type)
-
-            if 0 < filter_size:
-                continue
-
-            result_json.append(ball)
-
-        p_ball = df_ball[df_ball['no'] == no - 1].values.tolist()[0]
-        p_no = p_ball[0]
-        p_ball = p_ball[1:7]
-
-        return p_no, p_ball
-
-if __name__ == '__main__':
-
-    PROJECT_HOME = '.'
-    resources_path = os.path.join(PROJECT_HOME, 'resources')
-
-    today = datetime.today()
-    if today.weekday() == 5:
-        if today.hour > 20:
-            this_weekend = today + timedelta(days=(12 - today.weekday()))
-        else:
-            this_weekend = today + timedelta(days=(5 - today.weekday()))
-    elif today.weekday() == 6:
-        this_weekend = today + timedelta(days=(12 - today.weekday()))
-    else:
-        this_weekend = today + timedelta(days=(5 - today.weekday()))
-
-    last_weekend = (this_weekend - timedelta(days=7)).strftime('%Y%m%d')
-    ymd = this_weekend.strftime('%Y%m%d')
-
-    print("ymd: {}".format(ymd))
-
-    # 로또 예측
-    practice = Practice(resources_path)
-
-    # 데이터 수집
-    lottoHistoryFile = PROJECT_HOME + '/resources/lotto_history'
-    lottoHistoryFileName = lottoHistoryFile + '.json'
-    with open(lottoHistoryFileName, "r", encoding='utf-8') as f:
-        for line in f:
-            if line != '\n':
-                last_json = json.loads(line)
-
-    #ball = practice.craw(lottoHistoryFile, drwNo=last_json['drwNo'] + 1)
-
-    result_json = {ymd: []}
-
-    # 매주 고정
-    practice.predict1(result_json[ymd])
-    # 필터 기반 예측
-    p_no, p_ball = practice.predict2(resources_path, ymd, result_json[ymd])
-
-    p_str = "[지난주] {}\n   - {} 회차, {}\n[금주] {}\n   - {} 회차\n[모델#25]\n".format(last_weekend, p_no, str(p_ball), ymd, (p_no + 1))
-    for i, ball in enumerate(result_json[ymd]):
-        p_str += "   {}. {}\n".format((i+1), str(ball))
-        if (i+1) % 100 == 0:
-            practice.bot.sendMsg("{}".format(p_str))
-            p_str = ''
-
-    if len(result_json[ymd]) % 100 != 0:
-        practice.bot.sendMsg("{}".format(p_str))
-
-    size = len(result_json[ymd])
-    print("size: {}".format(size))
-
-    # https://youtu.be/QjBsui8Ob14?si=4dC3q8p0Yu5ZWK1K
-    # https://www.youtube.com/watch?v=YwiHaa1KNwA
-
-    print("done...")

practice_3.py

@@ -1,546 +0,0 @@
-# 웹 호출 라이브러리를 호출합니다.
-import time
-import requests
-from DataCrawler import DataCrawler
-
-import json
-import os
-import copy
-import pandas as pd
-import itertools
-from datetime import datetime, timedelta
-from TelegramBot import TelegramBot
-
-from filter_model_3 import BallFilter
-
-class Practice:
-
-    bot = None
-    preprocessor = None
-    predictor = None
-
-    extract_count = None
-    TARGET_MIN_SURVIVORS = 30
-    TARGET_MAX_SURVIVORS = 150
-    PREDICT_TIMEOUT_SECONDS = 180
-
-    def __init__(self, resources_path):
-        self.bot = TelegramBot()
-        self.resources_path = resources_path
-
-        return
-
-    # 로또 당첨 데이터를 수집해서 파일로 저장합니다.
-    # lottoHistoryFile: 로또 당첨 데이터를 저장할 파일
-    def craw(self, lottoHistoryFile, drwNo=None):
-
-        ball = None
-        if drwNo != None:
-            # 로또 데이터를 저장할 파일을 선언합니다.
-            jsonFp = open(lottoHistoryFile + ".json", 'a', encoding="utf-8")
-            textFp = open(lottoHistoryFile + ".txt", 'a', encoding="utf-8")
-
-            url = 'https://dhlottery.co.kr/common.do?method=getLottoNumber&drwNo=' + str(drwNo)
-            # URL을 호출합니다.
-            res = requests.post(url)
-            # 호출한 결과에 대해서 Json 포맷을 가져옵니다.
-            result = res.json()
-
-            if result['returnValue'] != 'success':
-                return None
-
-            # 가져온 Json 포맷을 파일로 저장합니다.
-            jsonFp.write(json.dumps(result, ensure_ascii=False) + "\n")
-            textFp.write("%d,%d,%d,%d,%d,%d,%d,%d\n" % (drwNo, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
-            print("%d,%d,%d,%d,%d,%d,%d,%d" % (drwNo, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
-
-            ball = [result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']]
-        else:
-            # 로또 데이터를 저장할 파일을 선언합니다.
-            jsonFp = open(lottoHistoryFile + ".json", 'w', encoding="utf-8")
-            textFp = open(lottoHistoryFile + ".txt", 'w', encoding="utf-8")
-
-            # 1회차부터 지정된 회차까지 로또 당첨 번호를 수집합니다.
-            idx = 1
-            while True:
-                # 1회차부터 지정된 회차까지의 URL을 생성합니다.
-                url = 'https://dhlottery.co.kr/common.do?method=getLottoNumber&drwNo=' + str(idx)
-                # URL을 호출합니다.
-                res = requests.post(url)
-                # 호출한 결과에 대해서 Json 포맷을 가져옵니다.
-                result = res.json()
-                if result['returnValue'] != 'success':
-                    break
-                # 가져온 Json 포맷을 파일로 저장합니다.
-                jsonFp.write(json.dumps(result, ensure_ascii=False) + "\n")
-                textFp.write("%d,%d,%d,%d,%d,%d,%d,%d\n" % (idx, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
-                print("%d,%d,%d,%d,%d,%d,%d,%d" % (idx, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
-                ball = [result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']]
-                idx += 1
-                time.sleep(0.5)
-        # 저장한 파일을 종료합니다.
-        jsonFp.close()
-        textFp.close()
-
-        return ball
-
-    def predict1(self, result_json):
-        result_json.append([6, 7, 10, 11, 20, 45])
-        result_json.append([2, 7, 17, 28, 35, 39])
-        result_json.append([6, 10, 19, 25, 33, 35])
-        result_json.append([3, 17, 20, 24, 35, 45])
-        result_json.append([5, 15, 18, 29, 36, 41])
-        result_json.append([6, 15, 20, 23, 37, 43])
-        result_json.append([8, 15, 19, 23, 38, 41])
-        result_json.append([5, 11, 19, 24, 40, 45])
-        result_json.append([9, 16, 18, 23, 35, 43])
-        result_json.append([7, 13, 19, 28, 33, 44])
-        result_json.append([7, 11, 18, 29, 37, 42])
-        print("회차(predict1)")
-        return
-
-    def predict2(self, resources_path, ymd, result_json):
-
-        candidates = [i for i in range(1, 46)]
-
-        lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.json')
-        ballFilter = BallFilter(lottoHistoryFileName)
-        no = ballFilter.getNextNo(ymd)
-        print("회차(predict2): {}".format(no))
-
-        lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.txt')
-        df_ball = pd.read_csv(lottoHistoryFileName, header=None)
-        df_ball.columns = ['no', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'bn']
-
-        #filter_ball=[1,2,4,6,10,11,11,17,18,20,21,22,23,24,26,27,28,30,31,32,33,34,37,38,39,40,42,44]
-        nCr = list(itertools.combinations(candidates, 6))
-        for idx, ball in enumerate(nCr):
-
-            if idx % 1000000 == 0:
-                print("   - {} processed...".format(idx))
-
-            ball = list(ball)
-
-            filter_type = ballFilter.filter(ball=ball, no=no, until_end=False, df=df_ball)
-            filter_size = len(filter_type)
-
-            if 0 < filter_size:
-                continue
-
-            result_json.append(ball)
-
-        p_ball = df_ball[df_ball['no'] == no - 1].values.tolist()[0]
-        p_no = p_ball[0]
-        p_ball = p_ball[1:7]
-
-        return p_no, p_ball
-
-    def predict3(self, resources_path, ymd, result_json):
-        candidates = [i for i in range(1, 46)]
-        lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.json')
-        no = BallFilter(lottoHistoryFileName).getNextNo(ymd)
-        print("회차(predict3): {}".format(no))
-        predict_start_ts = time.time()
-        deadline_ts = predict_start_ts + self.PREDICT_TIMEOUT_SECONDS
-
-        lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.txt')
-        df_ball = pd.read_csv(lottoHistoryFileName, header=None)
-        df_ball.columns = ['no', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'bn']
-
-        p_ball = df_ball[df_ball['no'] == no - 1].values.tolist()[0]
-        p_no = p_ball[0]
-        p_ball = sorted(p_ball[1:7])
-
-        base_ruleset = self._get_base_ruleset()
-        tighten_rulesets = [
-            self._build_ruleset(
-                base_ruleset=base_ruleset,
-                enabled_overrides={
-                    "paper_patterns": True,
-                    "ban_triples_legacy": True,
-                    "all_in_previous7": True,
-                    "previous_neighbors": True,
-                },
-                allowed_overrides={
-                    "ac_value": [8, 9],
-                    "uniq_last_digit_count": [4, 5],
-                    "even_count": [2, 3, 4],
-                },
-            ),
-            self._build_ruleset(
-                base_ruleset=base_ruleset,
-                enabled_overrides={
-                    "paper_patterns": True,
-                    "ban_triples_legacy": True,
-                    "all_in_previous7": True,
-                    "previous_neighbors": True,
-                },
-                allowed_overrides={
-                    "ac_value": [8, 9],
-                    "uniq_last_digit_count": [4, 5],
-                    "even_count": [2, 3, 4],
-                    "sum": [112, 114, 121, 123, 126, 127, 131, 132, 138, 146, 148],
-                    "sum_prev_diff": [13, 14, 17, 18, 26, 28, 29, 30, 32, 39, 40],
-                },
-            ),
-        ]
-        relax_rulesets = [
-            self._build_ruleset(
-                base_ruleset=base_ruleset,
-                enabled_overrides={
-                    "paper_patterns": False,
-                    "ban_triples_legacy": False,
-                },
-            ),
-            self._build_ruleset(
-                base_ruleset=base_ruleset,
-                enabled_overrides={
-                    "paper_patterns": False,
-                    "ban_triples_legacy": False,
-                    "previous_neighbors": False,
-                    "all_in_previous7": False,
-                },
-            ),
-            self._build_ruleset(
-                base_ruleset=base_ruleset,
-                enabled_overrides={
-                    "paper_patterns": False,
-                    "ban_triples_legacy": False,
-                    "previous_neighbors": False,
-                    "all_in_previous7": False,
-                    "weeks_8_count": False,
-                    "weeks_12_count": False,
-                    "weeks_16_count": False,
-                    "weeks_20_count": False,
-                },
-            ),
-        ]
-
-        min_survivors = self.TARGET_MIN_SURVIVORS
-        max_survivors = self.TARGET_MAX_SURVIVORS
-        chosen = []
-        stage_name = "base"
-
-        current_info = self._collect_candidates(
-            candidates=candidates,
-            no=no,
-            df_ball=df_ball,
-            ruleset=base_ruleset,
-            stop_when_gt=max_survivors,
-            stage_name="base",
-            predict_start_ts=predict_start_ts,
-            deadline_ts=deadline_ts,
-        )
-        current = current_info["candidates"]
-        if current_info["timed_out"]:
-            chosen = self._finalize_on_timeout(current, p_ball, min_survivors, max_survivors)
-            stage_name = "base_timeout_fallback"
-            print("predict3 stage: {}, survivors: {}".format(stage_name, len(chosen)))
-            for ball in chosen:
-                result_json.append(ball)
-            return p_no, p_ball
-
-        if min_survivors <= len(current) <= max_survivors:
-            chosen = current
-        elif len(current) > max_survivors:
-            chosen = current
-            stage_name = "base_overflow"
-            for idx, rs in enumerate(tighten_rulesets, start=1):
-                t_info = self._collect_candidates(
-                    candidates=candidates,
-                    no=no,
-                    df_ball=df_ball,
-                    ruleset=rs,
-                    stop_when_gt=max_survivors,
-                    stage_name="tighten_{}".format(idx),
-                    predict_start_ts=predict_start_ts,
-                    deadline_ts=deadline_ts,
-                )
-                t = t_info["candidates"]
-                if t_info["timed_out"]:
-                    chosen = self._finalize_on_timeout(t, p_ball, min_survivors, max_survivors)
-                    stage_name = "tighten_{}_timeout_fallback".format(idx)
-                    break
-                if min_survivors <= len(t) <= max_survivors:
-                    chosen = t
-                    stage_name = "tighten_{}".format(idx)
-                    break
-                if len(t) <= max_survivors:
-                    chosen = t
-                    stage_name = "tighten_{}".format(idx)
-
-            if len(chosen) > max_survivors:
-                full_info = self._collect_candidates(
-                    candidates=candidates,
-                    no=no,
-                    df_ball=df_ball,
-                    ruleset=tighten_rulesets[-1],
-                    stop_when_gt=None,
-                    stage_name="tighten_full_rank",
-                    predict_start_ts=predict_start_ts,
-                    deadline_ts=deadline_ts,
-                )
-                full_for_ranking = full_info["candidates"]
-                if full_info["timed_out"]:
-                    chosen = self._finalize_on_timeout(full_for_ranking, p_ball, min_survivors, max_survivors)
-                    stage_name = "tighten_rank_timeout_fallback"
-                else:
-                    chosen = self._rank_and_trim(full_for_ranking, p_ball, max_survivors)
-                    stage_name = "tighten_rank_trim"
-        else:
-            chosen = current
-            stage_name = "base_underflow"
-            for idx, rs in enumerate(relax_rulesets, start=1):
-                r_info = self._collect_candidates(
-                    candidates=candidates,
-                    no=no,
-                    df_ball=df_ball,
-                    ruleset=rs,
-                    stop_when_gt=None,
-                    stop_when_gte=min_survivors,
-                    stage_name="relax_{}".format(idx),
-                    predict_start_ts=predict_start_ts,
-                    deadline_ts=deadline_ts,
-                )
-                r = r_info["candidates"]
-                chosen = r
-                stage_name = "relax_{}".format(idx)
-                if r_info["timed_out"]:
-                    chosen = self._finalize_on_timeout(r, p_ball, min_survivors, max_survivors)
-                    stage_name = "relax_{}_timeout_fallback".format(idx)
-                    break
-                if len(r) >= min_survivors:
-                    break
-
-            if len(chosen) == 0:
-                stage_name = "relax_zero_fallback"
-                chosen = self._fallback_candidates_from_prev(p_ball, min_survivors)
-            elif len(chosen) < min_survivors:
-                stage_name = "{}_fill".format(stage_name)
-                fill = self._fallback_candidates_from_prev(
-                    p_ball,
-                    min_survivors - len(chosen),
-                    exclude=set(tuple(x) for x in chosen),
-                )
-                chosen.extend(fill)
-
-        print("predict3 stage: {}, survivors: {}".format(stage_name, len(chosen)))
-        for ball in chosen:
-            result_json.append(ball)
-        return p_no, p_ball
-
-    def _get_base_ruleset(self):
-        history_json = os.path.join(self.resources_path, "lotto_history.json")
-        base_filter = BallFilter(history_json)
-        return copy.deepcopy(base_filter.m1.ruleset)
-
-    def _build_ruleset(self, base_ruleset, enabled_overrides=None, allowed_overrides=None):
-        ruleset = copy.deepcopy(base_ruleset)
-        ruleset.setdefault("filters", {})
-        enabled_overrides = enabled_overrides or {}
-        allowed_overrides = allowed_overrides or {}
-        for key, value in enabled_overrides.items():
-            ruleset["filters"].setdefault(key, {})
-            ruleset["filters"][key]["enabled"] = bool(value)
-        for key, values in allowed_overrides.items():
-            ruleset["filters"].setdefault(key, {})
-            ruleset["filters"][key]["enabled"] = True
-            ruleset["filters"][key]["allowed"] = list(values)
-        return ruleset
-
-    def _collect_candidates(
-        self,
-        candidates,
-        no,
-        df_ball,
-        ruleset,
-        stop_when_gt=None,
-        stop_when_gte=None,
-        stage_name="base",
-        predict_start_ts=None,
-        deadline_ts=None,
-    ):
-        lottoHistoryFileName = os.path.join(self.resources_path, "lotto_history.json")
-        ballFilter = BallFilter(lottoHistoryFileName, ruleset=ruleset)
-        result = []
-        last_idx = 0
-        for idx, ball in enumerate(itertools.combinations(candidates, 6), start=1):
-            last_idx = idx
-            if deadline_ts is not None and deadline_ts <= time.time():
-                elapsed = (time.time() - predict_start_ts) if predict_start_ts is not None else 0.0
-                print("   - [{}] timeout after {:,} processed (elapsed: {:.1f}s, survivors: {:,})".format(stage_name, idx, elapsed, len(result)))
-                return {"candidates": result, "timed_out": True, "processed": idx}
-            if idx % 1000000 == 0:
-                elapsed = (time.time() - predict_start_ts) if predict_start_ts is not None else 0.0
-                print("   - [{}] {:,} processed... (elapsed: {:.1f}s, survivors: {:,})".format(stage_name, idx, elapsed, len(result)))
-            b = list(ball)
-            if len(ballFilter.filter(ball=b, no=no, until_end=False, df=df_ball)) == 0:
-                result.append(b)
-                if stop_when_gt is not None and len(result) > stop_when_gt:
-                    return {"candidates": result, "timed_out": False, "processed": idx}
-                if stop_when_gte is not None and len(result) >= stop_when_gte:
-                    return {"candidates": result, "timed_out": False, "processed": idx}
-        return {"candidates": result, "timed_out": False, "processed": last_idx}
-
-    def _finalize_on_timeout(self, partial_candidates, prev_ball, min_survivors, max_survivors):
-        chosen = list(partial_candidates)
-        if len(chosen) > max_survivors:
-            chosen = self._rank_and_trim(chosen, prev_ball, max_survivors)
-        elif len(chosen) < min_survivors:
-            fill = self._fallback_candidates_from_prev(
-                prev_ball,
-                min_survivors - len(chosen),
-                exclude=set(tuple(x) for x in chosen),
-            )
-            chosen.extend(fill)
-        return chosen
-
-    def _rank_and_trim(self, candidates, prev_ball, limit):
-        scored = [(self._score_candidate(ball, prev_ball), ball) for ball in candidates]
-        scored.sort(key=lambda x: x[0])
-        return [ball for _, ball in scored[:limit]]
-
-    def _score_candidate(self, ball, prev_ball):
-        sum_diff = abs(sum(ball) - sum(prev_ball))
-        even_cnt = len([x for x in ball if x % 2 == 0])
-        uniq_last = len(set([x % 10 for x in ball]))
-        contiguous_penalty = 0
-        s = sorted(ball)
-        for i in range(1, len(s)):
-            if s[i] - s[i - 1] == 1:
-                contiguous_penalty += 1
-        score = 0
-        score += sum_diff
-        score += abs(even_cnt - 3) * 2
-        score += abs(uniq_last - 5) * 2
-        score += contiguous_penalty
-        return score
-
-    def _fallback_candidates_from_prev(self, prev_ball, need_count, exclude=None):
-        exclude = exclude or set()
-        seed = sorted(prev_ball)
-        out = []
-        delta_patterns = [
-            (0, 0, 0, 0, 0, 0),
-            (-1, 0, 0, 0, 0, 1),
-            (0, -1, 0, 0, 1, 0),
-            (0, 0, -1, 1, 0, 0),
-            (-2, 0, 0, 0, 0, 2),
-            (0, -2, 0, 0, 2, 0),
-            (0, 0, -2, 2, 0, 0),
-            (-1, -1, 0, 0, 1, 1),
-            (1, 0, -1, 0, 0, 0),
-            (0, 1, 0, -1, 0, 0),
-            (1, -1, 1, -1, 1, -1),
-            (-1, 1, -1, 1, -1, 1),
-        ]
-        shift = 0
-        while len(out) < need_count and shift <= 8:
-            for delta in delta_patterns:
-                cand = [seed[i] + delta[i] for i in range(6)]
-                cand = [min(45, max(1, v + shift)) for v in cand]
-                cand = sorted(cand)
-                if len(set(cand)) != 6:
-                    continue
-                t = tuple(cand)
-                if t in exclude:
-                    continue
-                exclude.add(t)
-                out.append(cand)
-                if len(out) >= need_count:
-                    break
-            shift += 1
-        return out
-
-    def _merge_unique_balls(self, base_balls, extra_balls):
-        seen = set(tuple(sorted(x)) for x in base_balls)
-        for ball in extra_balls:
-            key = tuple(sorted(ball))
-            if key not in seen:
-                base_balls.append(list(ball))
-                seen.add(key)
-        return base_balls
-
-    def _sorted_unique_balls(self, balls):
-        """
-        Normalize (sort within ball), de-duplicate, then sort lexicographically.
-        Returns List[List[int]].
-        """
-        uniq = {}
-        for b in balls:
-            key = tuple(sorted(b))
-            uniq[key] = list(key)
-        return [list(t) for t in sorted(uniq.keys())]
-
-if __name__ == '__main__':
-
-    PROJECT_HOME = '.'
-    resources_path = os.path.join(PROJECT_HOME, 'resources')
-
-    today = datetime.today()
-    if today.weekday() == 5:
-        if today.hour > 20:
-            this_weekend = today + timedelta(days=(12 - today.weekday()))
-        else:
-            this_weekend = today + timedelta(days=(5 - today.weekday()))
-    elif today.weekday() == 6:
-        this_weekend = today + timedelta(days=(12 - today.weekday()))
-    else:
-        this_weekend = today + timedelta(days=(5 - today.weekday()))
-
-    last_weekend = (this_weekend - timedelta(days=7)).strftime('%Y%m%d')
-    ymd = this_weekend.strftime('%Y%m%d')
-
-    print("ymd: {}".format(ymd))
-
-    # 로또 예측
-    practice = Practice(resources_path)
-
-    # 데이터 수집
-    lottoHistoryFile = PROJECT_HOME + '/resources/lotto_history'
-    lottoHistoryFileName = lottoHistoryFile + '.json'
-    with open(lottoHistoryFileName, "r", encoding='utf-8') as f:
-        for line in f:
-            if line != '\n':
-                last_json = json.loads(line)
-
-    #ball = practice.craw(lottoHistoryFile, drwNo=last_json['drwNo'] + 1)
-
-    result_json = {ymd: []}
-
-    # 매주 고정
-    practice.predict1(result_json[ymd])
-    # 필터 기반 예측(기존/신규): 결과는 합친 후 정렬해서 predict1 결과 뒤에 붙인다.
-    predict2_json = []
-    p_no, p_ball = practice.predict2(resources_path, ymd, predict2_json)
-
-    predict3_json = []
-    p_no3, p_ball3 = practice.predict3(resources_path, ymd, predict3_json)
-
-    merged_predict = []
-    practice._merge_unique_balls(merged_predict, predict2_json)
-    practice._merge_unique_balls(merged_predict, predict3_json)
-    merged_predict = practice._sorted_unique_balls(merged_predict)
-
-    # predict1 결과에 merged_predict를 정렬된 순서로 append(중복 제거)
-    practice._merge_unique_balls(result_json[ymd], merged_predict)
-    if p_no3 == p_no:
-        p_ball = p_ball3
-
-    p_str = "[지난주] {}\n   - {} 회차, {}\n[금주] {}\n   - {} 회차\n[모델#25]\n".format(last_weekend, p_no, str(p_ball), ymd, (p_no + 1))
-    for i, ball in enumerate(result_json[ymd]):
-        p_str += "   {}. {}\n".format((i+1), str(ball))
-        if (i+1) % 100 == 0:
-            practice.bot.sendMsg("{}".format(p_str))
-            p_str = ''
-
-    if len(result_json[ymd]) % 100 != 0:
-        practice.bot.sendMsg("{}".format(p_str))
-
-    size = len(result_json[ymd])
-    print("size: {}".format(size))
-
-    # https://youtu.be/QjBsui8Ob14?si=4dC3q8p0Yu5ZWK1K
-    # https://www.youtube.com/watch?v=YwiHaa1KNwA
-
-    print("done...")

practice_3_FilterTest.py

@@ -1,216 +0,0 @@
-import os
-import pandas as pd
-import itertools
-from filter_model_3 import BallFilter
-import time
-import datetime
-
-class FilterTest:
-
-    ballFilter = None
-
-    def __init__(self, resources_path):
-        lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.json')
-        self.ballFilter = BallFilter(lottoHistoryFileName)
-
-        return
-
-    def find_filter_method(self, df_ball, filter_ball=None):
-        win_count = 0
-
-        no_filter_ball = {}
-
-        printLog = True
-        filter_dic = {}
-        filter_dic_len = {}
-        filter_dic_1 = {}
-        filter_dic_2 = {}
-        for i in range(len(df_ball)-1, 19, -1):
-
-            no = df_ball['no'].iloc[i]
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            filter_type = self.ballFilter.filter(ball=answer, no=no, until_end=True, df=df_ball)
-            filter_type = list(filter_type)
-            size = len(filter_type)
-
-            if size == 0:
-                win_count += 1
-                no_filter_ball[no] = answer
-                print("\t", no)
-            elif size == 1:
-                key = filter_type[0]
-                if key not in filter_dic_1:
-                    filter_dic_1[key] = 1
-                else:
-                    filter_dic_1[key] += 1
-
-                if printLog:
-                    print("\t", no, filter_type)
-            elif size == 2:
-                key = ','.join(filter_type)
-                if key not in filter_dic_2:
-                    filter_dic_2[key] = 1
-                else:
-                    filter_dic_2[key] += 1
-
-                if printLog:
-                    print("\t", no, filter_type)
-            else:
-                if printLog:
-                    print("\t", no, filter_type)
-
-                # 회차별 필터개수가 적은 것을 정렬하기 위함
-                if size not in filter_dic_len:
-                    filter_dic_len[size] = []
-                filter_dic_len[size].append(filter_type)
-
-            for f_t in filter_type:
-                if f_t not in filter_dic:
-                    filter_dic[f_t] = 1
-                else:
-                    filter_dic[f_t] += 1
-
-        print("\n\t[필터 개수가 적은 것부터 최적화를 위함]")
-        sorted_filter_dic_len = sorted(filter_dic_len.keys())
-        for filter_count in sorted_filter_dic_len:
-            for filter_type in filter_dic_len[filter_count]:
-                print("\t\t>{} > {}".format(filter_count, filter_type))
-
-        print("\n\t[걸러진 유일 필터]")
-        sorted_filter_dic_1 = sorted(filter_dic_1.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic_1)):
-            print("\t\t>", sorted_filter_dic_1[i][0], "->", sorted_filter_dic_1[i][1])
-
-        print("\n\t[2개 필터에 걸린 경우]")
-        sorted_filter_dic_2 = sorted(filter_dic_2.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic_2)):
-            print("\t\t>", sorted_filter_dic_2[i][0], "->", sorted_filter_dic_2[i][1])
-
-        print("\n\t[Filter 유형 별 걸린 개수]")
-        sorted_filter_dic = sorted(filter_dic.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic)):
-            print("\t\t>", sorted_filter_dic[i][0], "->", sorted_filter_dic[i][1])
-
-        print("\n\t# 필터에 걸리지 않고 당첨된 회차")
-        print("\tcount: {:,} / total: {:,}".format(len(no_filter_ball), len(df_ball)))
-        for no in no_filter_ball:
-            print("\t\t>", no, no_filter_ball[no])
-        print("\tcount: {:,} / total: {:,}".format(len(no_filter_ball), len(df_ball)))
-
-        return win_count
-
-    def find_final_candidates(self, no, df_ball, filter_ball=None):
-        final_candidates = []
-
-        generation_balls = list(range(1, 46))
-
-        nCr = list(itertools.combinations(generation_balls, 6))
-        for idx, ball in enumerate(nCr):
-
-            if idx % 1000000 == 0:
-                print("   - {} processed...".format(idx))
-
-            if filter_ball is not None and 0 < len(set(ball) & set(filter_ball)):
-                continue
-
-            filter_type = self.ballFilter.filter(ball=ball, no=no, until_end=False, df=df_ball)
-            filter_size = len(filter_type)
-
-            if filter_size:
-                continue
-
-            final_candidates.append(ball)
-
-        return final_candidates
-
-    def check_filter_method(self, df_ball, p_win_count, filter_ball=None):
-
-        win_count = 0
-        for i in range(len(df_ball)-1, 0, -1):
-
-            no = df_ball['no'].iloc[i]
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            if filter_ball is not None and len(set(answer) & set(filter_ball)):
-                continue
-
-            filter_type = self.ballFilter.extract_final_candidates(answer, no=no, until_end=True, df=df_ball)
-
-            if len(filter_type) == 0:
-                win_count += 1
-                print("\t\t>{}. {}".format(no, answer))
-
-        print("\n\t> {} / {} p_win_count, {} total".format( win_count, p_win_count, len(df_ball)-1) )
-
-        return
-
-    def validate(self, df_ball, nos=None):
-        win_history = {}
-
-        for no in nos:
-            print(no, "processing...")
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            generation_balls = list(range(1, 46))
-            nCr = list(itertools.combinations(generation_balls, 6))
-            for idx, ball in enumerate(nCr):
-                if idx % 1000000 == 0:
-                    print("   - {} processed...".format(idx))
-                ball = list(ball)
-                filter_type = self.ballFilter.extract_final_candidates(ball, no=no, until_end=True, df=df_ball)
-                if 0 == len(filter_type) and len(set(answer)&set(ball))==6:
-                    win_history[no] = answer
-                    print("win.. no: {}, answer: {}".format(no, str(answer)))
-                    break
-
-        return win_history
-
-
-if __name__ == '__main__':
-
-    resources_path = 'resources'
-
-    lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.txt')
-    df_ball = pd.read_csv(lottoHistoryFileName, header=None)
-    df_ball.columns = ['no', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'bn']
-
-    filter_ball=[]
-    filterTest = FilterTest(resources_path)
-
-    print("STEP #1. 필터 방법 추출")
-    start = time.time()
-    win_count = filterTest.find_filter_method(df_ball, filter_ball)
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    """
-    print("\n\n")
-    no = df_ball['no'].values[-1]
-    ball = df_ball[df_ball['no'] == no].values.tolist()[0]
-    answer = ball[1:7]
-
-    print("STEP #0. 최종 후보 선정")
-    start = time.time()
-    final_candidates = filterTest.find_final_candidates(no, df_ball, filter_ball=None)
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    print("   > size: {}".format(len(final_candidates)))
-    file_name = os.path.join(resources_path, 'final_candidates.biz_a1.txt')
-    with open(file_name, 'w+') as outFp:
-        for ball in final_candidates:
-            ball_str = [str(b) for b in answer]
-            outFp.write("{}\n".format(','.join(ball_str)))
-
-    print('{}회, 정답: {}\n'.format(no, str(answer)))
-    """
-
-    #print("\n\n")
-    #print("STEP #2. 당첨 회수 확인")
-    #filterTest.check_filter_method(df_ball, win_count)
-
-    # 오리지널 버전 (자질 파일에 고정): 당첨 22개

practice_3_new.py

@@ -1,490 +0,0 @@
-# 웹 호출 라이브러리를 호출합니다.
-import time
-import requests
-
-import json
-import os
-import copy
-import pandas as pd
-import itertools
-from datetime import datetime, timedelta
-from TelegramBot import TelegramBot
-
-from filter_model_3 import BallFilter
-
-class Practice:
-
-    bot = None
-    preprocessor = None
-    predictor = None
-
-    extract_count = None
-    TARGET_MIN_SURVIVORS = 30
-    TARGET_MAX_SURVIVORS = 150
-    PREDICT_TIMEOUT_SECONDS = 180
-
-    def __init__(self, resources_path):
-        self.bot = TelegramBot()
-        self.resources_path = resources_path
-
-        return
-
-    # 로또 당첨 데이터를 수집해서 파일로 저장합니다.
-    # lottoHistoryFile: 로또 당첨 데이터를 저장할 파일
-    def craw(self, lottoHistoryFile, drwNo=None):
-
-        ball = None
-        if drwNo != None:
-            # 로또 데이터를 저장할 파일을 선언합니다.
-            jsonFp = open(lottoHistoryFile + ".json", 'a', encoding="utf-8")
-            textFp = open(lottoHistoryFile + ".txt", 'a', encoding="utf-8")
-
-            url = 'https://dhlottery.co.kr/common.do?method=getLottoNumber&drwNo=' + str(drwNo)
-            # URL을 호출합니다.
-            res = requests.post(url)
-            # 호출한 결과에 대해서 Json 포맷을 가져옵니다.
-            result = res.json()
-
-            if result['returnValue'] != 'success':
-                return None
-
-            # 가져온 Json 포맷을 파일로 저장합니다.
-            jsonFp.write(json.dumps(result, ensure_ascii=False) + "\n")
-            textFp.write("%d,%d,%d,%d,%d,%d,%d,%d\n" % (drwNo, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
-            print("%d,%d,%d,%d,%d,%d,%d,%d" % (drwNo, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
-
-            ball = [result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']]
-        else:
-            # 로또 데이터를 저장할 파일을 선언합니다.
-            jsonFp = open(lottoHistoryFile + ".json", 'w', encoding="utf-8")
-            textFp = open(lottoHistoryFile + ".txt", 'w', encoding="utf-8")
-
-            # 1회차부터 지정된 회차까지 로또 당첨 번호를 수집합니다.
-            idx = 1
-            while True:
-                # 1회차부터 지정된 회차까지의 URL을 생성합니다.
-                url = 'https://dhlottery.co.kr/common.do?method=getLottoNumber&drwNo=' + str(idx)
-                # URL을 호출합니다.
-                res = requests.post(url)
-                # 호출한 결과에 대해서 Json 포맷을 가져옵니다.
-                result = res.json()
-                if result['returnValue'] != 'success':
-                    break
-                # 가져온 Json 포맷을 파일로 저장합니다.
-                jsonFp.write(json.dumps(result, ensure_ascii=False) + "\n")
-                textFp.write("%d,%d,%d,%d,%d,%d,%d,%d\n" % (idx, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
-                print("%d,%d,%d,%d,%d,%d,%d,%d" % (idx, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
-                ball = [result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']]
-                idx += 1
-                time.sleep(0.5)
-        # 저장한 파일을 종료합니다.
-        jsonFp.close()
-        textFp.close()
-
-        return ball
-
-    def predict1(self, result_json):
-        result_json.append([6, 7, 10, 11, 20, 45])
-        result_json.append([2, 7, 17, 28, 35, 39])
-        result_json.append([6, 10, 19, 25, 33, 35])
-        result_json.append([3, 17, 20, 24, 35, 45])
-        result_json.append([5, 15, 18, 29, 36, 41])
-        result_json.append([6, 15, 20, 23, 37, 43])
-        result_json.append([8, 15, 19, 23, 38, 41])
-        result_json.append([5, 11, 19, 24, 40, 45])
-        result_json.append([9, 16, 18, 23, 35, 43])
-        result_json.append([7, 13, 19, 28, 33, 44])
-        result_json.append([7, 11, 18, 29, 37, 42])
-        return
-
-    def predict2(self, resources_path, ymd, result_json):
-        candidates = [i for i in range(1, 46)]
-        lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.json')
-        no = BallFilter(lottoHistoryFileName).getNextNo(ymd)
-        print("회차: {}".format(no))
-        predict_start_ts = time.time()
-        deadline_ts = predict_start_ts + self.PREDICT_TIMEOUT_SECONDS
-
-        lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.txt')
-        df_ball = pd.read_csv(lottoHistoryFileName, header=None)
-        df_ball.columns = ['no', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'bn']
-
-        p_ball = df_ball[df_ball['no'] == no - 1].values.tolist()[0]
-        p_no = p_ball[0]
-        p_ball = sorted(p_ball[1:7])
-
-        # 기본/강화/완화 단계별 ruleset
-        base_ruleset = self._get_base_ruleset()
-        tighten_rulesets = [
-            self._build_ruleset(
-                base_ruleset=base_ruleset,
-                enabled_overrides={
-                    "paper_patterns": True,
-                    "ban_triples_legacy": True,
-                    "all_in_previous7": True,
-                    "previous_neighbors": True,
-                },
-                allowed_overrides={
-                    "ac_value": [8, 9],
-                    "uniq_last_digit_count": [4, 5],
-                    "even_count": [2, 3, 4],
-                },
-            ),
-            self._build_ruleset(
-                base_ruleset=base_ruleset,
-                enabled_overrides={
-                    "paper_patterns": True,
-                    "ban_triples_legacy": True,
-                    "all_in_previous7": True,
-                    "previous_neighbors": True,
-                },
-                allowed_overrides={
-                    "ac_value": [8, 9],
-                    "uniq_last_digit_count": [4, 5],
-                    "even_count": [2, 3, 4],
-                    "sum": [112, 114, 121, 123, 126, 127, 131, 132, 138, 146, 148],
-                    "sum_prev_diff": [13, 14, 17, 18, 26, 28, 29, 30, 32, 39, 40],
-                },
-            ),
-        ]
-        relax_rulesets = [
-            self._build_ruleset(
-                base_ruleset=base_ruleset,
-                enabled_overrides={
-                    "paper_patterns": False,
-                    "ban_triples_legacy": False,
-                },
-            ),
-            self._build_ruleset(
-                base_ruleset=base_ruleset,
-                enabled_overrides={
-                    "paper_patterns": False,
-                    "ban_triples_legacy": False,
-                    "previous_neighbors": False,
-                    "all_in_previous7": False,
-                },
-            ),
-            self._build_ruleset(
-                base_ruleset=base_ruleset,
-                enabled_overrides={
-                    "paper_patterns": False,
-                    "ban_triples_legacy": False,
-                    "previous_neighbors": False,
-                    "all_in_previous7": False,
-                    "weeks_8_count": False,
-                    "weeks_12_count": False,
-                    "weeks_16_count": False,
-                    "weeks_20_count": False,
-                },
-            ),
-        ]
-
-        min_survivors = self.TARGET_MIN_SURVIVORS
-        max_survivors = self.TARGET_MAX_SURVIVORS
-        chosen = []
-        stage_name = "base"
-
-        current_info = self._collect_candidates(
-            candidates=candidates,
-            no=no,
-            df_ball=df_ball,
-            ruleset=base_ruleset,
-            stop_when_gt=max_survivors,
-            stage_name="base",
-            predict_start_ts=predict_start_ts,
-            deadline_ts=deadline_ts,
-        )
-        current = current_info["candidates"]
-        if current_info["timed_out"]:
-            chosen = self._finalize_on_timeout(current, p_ball, min_survivors, max_survivors)
-            stage_name = "base_timeout_fallback"
-            print("candidate_stage: {}, survivors: {}".format(stage_name, len(chosen)))
-            for ball in chosen:
-                result_json.append(ball)
-            return p_no, p_ball
-
-        if min_survivors <= len(current) <= max_survivors:
-            chosen = current
-        elif len(current) > max_survivors:
-            chosen = current
-            stage_name = "base_overflow"
-            for idx, rs in enumerate(tighten_rulesets, start=1):
-                t_info = self._collect_candidates(
-                    candidates=candidates,
-                    no=no,
-                    df_ball=df_ball,
-                    ruleset=rs,
-                    stop_when_gt=max_survivors,
-                    stage_name="tighten_{}".format(idx),
-                    predict_start_ts=predict_start_ts,
-                    deadline_ts=deadline_ts,
-                )
-                t = t_info["candidates"]
-                if t_info["timed_out"]:
-                    chosen = self._finalize_on_timeout(t, p_ball, min_survivors, max_survivors)
-                    stage_name = "tighten_{}_timeout_fallback".format(idx)
-                    break
-                if min_survivors <= len(t) <= max_survivors:
-                    chosen = t
-                    stage_name = "tighten_{}".format(idx)
-                    break
-                if len(t) <= max_survivors:
-                    chosen = t
-                    stage_name = "tighten_{}".format(idx)
-            if len(chosen) > max_survivors:
-                # 상한 가드 강제 적용: 품질 점수 상위 N개만 사용
-                full_info = self._collect_candidates(
-                    candidates=candidates,
-                    no=no,
-                    df_ball=df_ball,
-                    ruleset=tighten_rulesets[-1],
-                    stop_when_gt=None,
-                    stage_name="tighten_full_rank",
-                    predict_start_ts=predict_start_ts,
-                    deadline_ts=deadline_ts,
-                )
-                full_for_ranking = full_info["candidates"]
-                if full_info["timed_out"]:
-                    chosen = self._finalize_on_timeout(full_for_ranking, p_ball, min_survivors, max_survivors)
-                    stage_name = "tighten_rank_timeout_fallback"
-                else:
-                    chosen = self._rank_and_trim(full_for_ranking, p_ball, max_survivors)
-                    stage_name = "tighten_rank_trim"
-        else:
-            chosen = current
-            stage_name = "base_underflow"
-            for idx, rs in enumerate(relax_rulesets, start=1):
-                # relax는 하한(min_survivors)만 채우면 충분하므로 조기 종료
-                r_info = self._collect_candidates(
-                    candidates=candidates,
-                    no=no,
-                    df_ball=df_ball,
-                    ruleset=rs,
-                    stop_when_gt=None,
-                    stop_when_gte=min_survivors,
-                    stage_name="relax_{}".format(idx),
-                    predict_start_ts=predict_start_ts,
-                    deadline_ts=deadline_ts,
-                )
-                r = r_info["candidates"]
-                chosen = r
-                stage_name = "relax_{}".format(idx)
-                if r_info["timed_out"]:
-                    chosen = self._finalize_on_timeout(r, p_ball, min_survivors, max_survivors)
-                    stage_name = "relax_{}_timeout_fallback".format(idx)
-                    break
-                if len(r) >= min_survivors:
-                    break
-
-            if len(chosen) == 0:
-                # 0개 생존 방지: 가장 완화된 규칙에서도 0개면 직전 결과와 유사한 조합으로 최소 개수 확보
-                stage_name = "relax_zero_fallback"
-                chosen = self._fallback_candidates_from_prev(p_ball, min_survivors)
-            elif len(chosen) < min_survivors:
-                # 하한 가드: 부족분은 완화 후보/고정 후보 기반으로 보강
-                stage_name = "{}_fill".format(stage_name)
-                fill = self._fallback_candidates_from_prev(p_ball, min_survivors - len(chosen), exclude=set(tuple(x) for x in chosen))
-                chosen.extend(fill)
-
-        print("candidate_stage: {}, survivors: {}".format(stage_name, len(chosen)))
-        for ball in chosen:
-            result_json.append(ball)
-        return p_no, p_ball
-
-    def _get_base_ruleset(self):
-        history_json = os.path.join(self.resources_path, "lotto_history.json")
-        base_filter = BallFilter(history_json)
-        return copy.deepcopy(base_filter.m1.ruleset)
-
-    def _build_ruleset(self, base_ruleset, enabled_overrides=None, allowed_overrides=None):
-        ruleset = copy.deepcopy(base_ruleset)
-        ruleset.setdefault("filters", {})
-        enabled_overrides = enabled_overrides or {}
-        allowed_overrides = allowed_overrides or {}
-        for key, value in enabled_overrides.items():
-            ruleset["filters"].setdefault(key, {})
-            ruleset["filters"][key]["enabled"] = bool(value)
-        for key, values in allowed_overrides.items():
-            ruleset["filters"].setdefault(key, {})
-            ruleset["filters"][key]["enabled"] = True
-            ruleset["filters"][key]["allowed"] = list(values)
-        return ruleset
-
-    def _collect_candidates(
-        self,
-        candidates,
-        no,
-        df_ball,
-        ruleset,
-        stop_when_gt=None,
-        stop_when_gte=None,
-        stage_name="base",
-        predict_start_ts=None,
-        deadline_ts=None,
-    ):
-        lottoHistoryFileName = os.path.join(self.resources_path, "lotto_history.json")
-        ballFilter = BallFilter(lottoHistoryFileName, ruleset=ruleset)
-        result = []
-        last_idx = 0
-        for idx, ball in enumerate(itertools.combinations(candidates, 6), start=1):
-            last_idx = idx
-            if deadline_ts is not None and deadline_ts <= time.time():
-                elapsed = (time.time() - predict_start_ts) if predict_start_ts is not None else 0.0
-                print("   - [{}] timeout after {:,} processed (elapsed: {:.1f}s, survivors: {:,})".format(stage_name, idx, elapsed, len(result)))
-                return {
-                    "candidates": result,
-                    "timed_out": True,
-                    "processed": idx,
-                }
-            if idx % 1000000 == 0:
-                elapsed = (time.time() - predict_start_ts) if predict_start_ts is not None else 0.0
-                print("   - [{}] {:,} processed... (elapsed: {:.1f}s, survivors: {:,})".format(stage_name, idx, elapsed, len(result)))
-            b = list(ball)
-            if len(ballFilter.filter(ball=b, no=no, until_end=False, df=df_ball)) == 0:
-                result.append(b)
-                if stop_when_gt is not None and len(result) > stop_when_gt:
-                    return {
-                        "candidates": result,
-                        "timed_out": False,
-                        "processed": idx,
-                    }
-                if stop_when_gte is not None and len(result) >= stop_when_gte:
-                    return {
-                        "candidates": result,
-                        "timed_out": False,
-                        "processed": idx,
-                    }
-        return {
-            "candidates": result,
-            "timed_out": False,
-            "processed": last_idx,
-        }
-
-    def _finalize_on_timeout(self, partial_candidates, prev_ball, min_survivors, max_survivors):
-        chosen = list(partial_candidates)
-        if len(chosen) > max_survivors:
-            chosen = self._rank_and_trim(chosen, prev_ball, max_survivors)
-        elif len(chosen) < min_survivors:
-            fill = self._fallback_candidates_from_prev(
-                prev_ball,
-                min_survivors - len(chosen),
-                exclude=set(tuple(x) for x in chosen),
-            )
-            chosen.extend(fill)
-        return chosen
-
-    def _rank_and_trim(self, candidates, prev_ball, limit):
-        scored = [(self._score_candidate(ball, prev_ball), ball) for ball in candidates]
-        scored.sort(key=lambda x: x[0])
-        return [ball for _, ball in scored[:limit]]
-
-    def _score_candidate(self, ball, prev_ball):
-        sum_diff = abs(sum(ball) - sum(prev_ball))
-        even_cnt = len([x for x in ball if x % 2 == 0])
-        uniq_last = len(set([x % 10 for x in ball]))
-        contiguous_penalty = 0
-        s = sorted(ball)
-        for i in range(1, len(s)):
-            if s[i] - s[i - 1] == 1:
-                contiguous_penalty += 1
-        score = 0
-        score += sum_diff
-        score += abs(even_cnt - 3) * 2
-        score += abs(uniq_last - 5) * 2
-        score += contiguous_penalty
-        return score
-
-    def _fallback_candidates_from_prev(self, prev_ball, need_count, exclude=None):
-        exclude = exclude or set()
-        seed = sorted(prev_ball)
-        out = []
-        delta_patterns = [
-            (0, 0, 0, 0, 0, 0),
-            (-1, 0, 0, 0, 0, 1),
-            (0, -1, 0, 0, 1, 0),
-            (0, 0, -1, 1, 0, 0),
-            (-2, 0, 0, 0, 0, 2),
-            (0, -2, 0, 0, 2, 0),
-            (0, 0, -2, 2, 0, 0),
-            (-1, -1, 0, 0, 1, 1),
-            (1, 0, -1, 0, 0, 0),
-            (0, 1, 0, -1, 0, 0),
-            (1, -1, 1, -1, 1, -1),
-            (-1, 1, -1, 1, -1, 1),
-        ]
-        shift = 0
-        while len(out) < need_count and shift <= 8:
-            for delta in delta_patterns:
-                cand = [seed[i] + delta[i] for i in range(6)]
-                cand = [min(45, max(1, v + shift)) for v in cand]
-                cand = sorted(cand)
-                if len(set(cand)) != 6:
-                    continue
-                t = tuple(cand)
-                if t in exclude:
-                    continue
-                exclude.add(t)
-                out.append(cand)
-                if len(out) >= need_count:
-                    break
-            shift += 1
-        return out
-
-if __name__ == '__main__':
-
-    PROJECT_HOME = '.'
-    resources_path = os.path.join(PROJECT_HOME, 'resources')
-
-    today = datetime.today()
-    if today.weekday() == 5:
-        if today.hour > 20:
-            this_weekend = today + timedelta(days=(12 - today.weekday()))
-        else:
-            this_weekend = today + timedelta(days=(5 - today.weekday()))
-    elif today.weekday() == 6:
-        this_weekend = today + timedelta(days=(12 - today.weekday()))
-    else:
-        this_weekend = today + timedelta(days=(5 - today.weekday()))
-
-    last_weekend = (this_weekend - timedelta(days=7)).strftime('%Y%m%d')
-    ymd = this_weekend.strftime('%Y%m%d')
-
-    print("ymd: {}".format(ymd))
-
-    # 로또 예측
-    practice = Practice(resources_path)
-
-    # 데이터 수집
-    lottoHistoryFile = PROJECT_HOME + '/resources/lotto_history'
-    lottoHistoryFileName = lottoHistoryFile + '.json'
-    with open(lottoHistoryFileName, "r", encoding='utf-8') as f:
-        for line in f:
-            if line != '\n':
-                last_json = json.loads(line)
-
-    #ball = practice.craw(lottoHistoryFile, drwNo=last_json['drwNo'] + 1)
-
-    result_json = {ymd: []}
-
-    # 매주 고정
-    practice.predict1(result_json[ymd])
-    # 필터 기반 예측
-    p_no, p_ball = practice.predict2(resources_path, ymd, result_json[ymd])
-
-    p_str = "[지난주] {}\n   - {} 회차, {}\n[금주] {}\n   - {} 회차\n[모델#25]\n".format(last_weekend, p_no, str(p_ball), ymd, (p_no + 1))
-    for i, ball in enumerate(result_json[ymd]):
-        p_str += "   {}. {}\n".format((i+1), str(ball))
-        if (i+1) % 100 == 0:
-            practice.bot.sendMsg("{}".format(p_str))
-            p_str = ''
-
-    if len(result_json[ymd]) % 100 != 0:
-        practice.bot.sendMsg("{}".format(p_str))
-
-    size = len(result_json[ymd])
-    print("size: {}".format(size))
-
-    # https://youtu.be/QjBsui8Ob14?si=4dC3q8p0Yu5ZWK1K
-    # https://www.youtube.com/watch?v=YwiHaa1KNwA
-
-    print("done...")

practice_3_old.py

@@ -1,189 +0,0 @@
-# 웹 호출 라이브러리를 호출합니다.
-import time
-import requests
-from DataCrawler import DataCrawler
-
-import json
-import os
-import pandas as pd
-import itertools
-from datetime import datetime, timedelta
-from TelegramBot import TelegramBot
-
-from filter_model_3 import BallFilter
-
-class Practice:
-
-    bot = None
-    preprocessor = None
-    predictor = None
-
-    extract_count = None
-
-    def __init__(self, resources_path):
-        self.bot = TelegramBot()
-
-        return
-
-    # 로또 당첨 데이터를 수집해서 파일로 저장합니다.
-    # lottoHistoryFile: 로또 당첨 데이터를 저장할 파일
-    def craw(self, lottoHistoryFile, drwNo=None):
-
-        ball = None
-        if drwNo != None:
-            # 로또 데이터를 저장할 파일을 선언합니다.
-            jsonFp = open(lottoHistoryFile + ".json", 'a', encoding="utf-8")
-            textFp = open(lottoHistoryFile + ".txt", 'a', encoding="utf-8")
-
-            url = 'https://dhlottery.co.kr/common.do?method=getLottoNumber&drwNo=' + str(drwNo)
-            # URL을 호출합니다.
-            res = requests.post(url)
-            # 호출한 결과에 대해서 Json 포맷을 가져옵니다.
-            result = res.json()
-
-            if result['returnValue'] != 'success':
-                return None
-
-            # 가져온 Json 포맷을 파일로 저장합니다.
-            jsonFp.write(json.dumps(result, ensure_ascii=False) + "\n")
-            textFp.write("%d,%d,%d,%d,%d,%d,%d,%d\n" % (drwNo, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
-            print("%d,%d,%d,%d,%d,%d,%d,%d" % (drwNo, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
-
-            ball = [result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']]
-        else:
-            # 로또 데이터를 저장할 파일을 선언합니다.
-            jsonFp = open(lottoHistoryFile + ".json", 'w', encoding="utf-8")
-            textFp = open(lottoHistoryFile + ".txt", 'w', encoding="utf-8")
-
-            # 1회차부터 지정된 회차까지 로또 당첨 번호를 수집합니다.
-            idx = 1
-            while True:
-                # 1회차부터 지정된 회차까지의 URL을 생성합니다.
-                url = 'https://dhlottery.co.kr/common.do?method=getLottoNumber&drwNo=' + str(idx)
-                # URL을 호출합니다.
-                res = requests.post(url)
-                # 호출한 결과에 대해서 Json 포맷을 가져옵니다.
-                result = res.json()
-                if result['returnValue'] != 'success':
-                    break
-                # 가져온 Json 포맷을 파일로 저장합니다.
-                jsonFp.write(json.dumps(result, ensure_ascii=False) + "\n")
-                textFp.write("%d,%d,%d,%d,%d,%d,%d,%d\n" % (idx, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
-                print("%d,%d,%d,%d,%d,%d,%d,%d" % (idx, result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']))
-                ball = [result['drwtNo1'], result['drwtNo2'], result['drwtNo3'], result['drwtNo4'], result['drwtNo5'], result['drwtNo6'], result['bnusNo']]
-                idx += 1
-                time.sleep(0.5)
-        # 저장한 파일을 종료합니다.
-        jsonFp.close()
-        textFp.close()
-
-        return ball
-
-    def predict1(self, result_json):
-        result_json.append([6, 7, 10, 11, 20, 45])
-        result_json.append([2, 7, 17, 28, 35, 39])
-        result_json.append([6, 10, 19, 25, 33, 35])
-        result_json.append([3, 17, 20, 24, 35, 45])
-        result_json.append([5, 15, 18, 29, 36, 41])
-        result_json.append([6, 15, 20, 23, 37, 43])
-        result_json.append([8, 15, 19, 23, 38, 41])
-        result_json.append([5, 11, 19, 24, 40, 45])
-        result_json.append([9, 16, 18, 23, 35, 43])
-        result_json.append([7, 13, 19, 28, 33, 44])
-        result_json.append([7, 11, 18, 29, 37, 42])
-        return
-
-    def predict2(self, resources_path, ymd, result_json):
-
-        candidates = [i for i in range(1, 46)]
-
-        lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.json')
-        ballFilter = BallFilter(lottoHistoryFileName)
-        no = ballFilter.getNextNo(ymd)
-        print("회차: {}".format(no))
-
-        lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.txt')
-        df_ball = pd.read_csv(lottoHistoryFileName, header=None)
-        df_ball.columns = ['no', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'bn']
-
-        #filter_ball=[1,2,4,6,10,11,11,17,18,20,21,22,23,24,26,27,28,30,31,32,33,34,37,38,39,40,42,44]
-        nCr = list(itertools.combinations(candidates, 6))
-        for idx, ball in enumerate(nCr):
-
-            if idx % 1000000 == 0:
-                print("   - {} processed...".format(idx))
-
-            ball = list(ball)
-
-            filter_type = ballFilter.filter(ball=ball, no=no, until_end=False, df=df_ball)
-            filter_size = len(filter_type)
-
-            if 0 < filter_size:
-                continue
-
-            result_json.append(ball)
-
-        p_ball = df_ball[df_ball['no'] == no - 1].values.tolist()[0]
-        p_no = p_ball[0]
-        p_ball = p_ball[1:7]
-
-        return p_no, p_ball
-
-if __name__ == '__main__':
-
-    PROJECT_HOME = '.'
-    resources_path = os.path.join(PROJECT_HOME, 'resources')
-
-    today = datetime.today()
-    if today.weekday() == 5:
-        if today.hour > 20:
-            this_weekend = today + timedelta(days=(12 - today.weekday()))
-        else:
-            this_weekend = today + timedelta(days=(5 - today.weekday()))
-    elif today.weekday() == 6:
-        this_weekend = today + timedelta(days=(12 - today.weekday()))
-    else:
-        this_weekend = today + timedelta(days=(5 - today.weekday()))
-
-    last_weekend = (this_weekend - timedelta(days=7)).strftime('%Y%m%d')
-    ymd = this_weekend.strftime('%Y%m%d')
-
-    print("ymd: {}".format(ymd))
-
-    # 로또 예측
-    practice = Practice(resources_path)
-
-    # 데이터 수집
-    lottoHistoryFile = PROJECT_HOME + '/resources/lotto_history'
-    lottoHistoryFileName = lottoHistoryFile + '.json'
-    with open(lottoHistoryFileName, "r", encoding='utf-8') as f:
-        for line in f:
-            if line != '\n':
-                last_json = json.loads(line)
-
-    #ball = practice.craw(lottoHistoryFile, drwNo=last_json['drwNo'] + 1)
-
-    result_json = {ymd: []}
-
-    # 매주 고정
-    practice.predict1(result_json[ymd])
-    # 필터 기반 예측
-    p_no, p_ball = practice.predict2(resources_path, ymd, result_json[ymd])
-
-    p_str = "[지난주] {}\n   - {} 회차, {}\n[금주] {}\n   - {} 회차\n[모델#25]\n".format(last_weekend, p_no, str(p_ball), ymd, (p_no + 1))
-    for i, ball in enumerate(result_json[ymd]):
-        p_str += "   {}. {}\n".format((i+1), str(ball))
-        if (i+1) % 100 == 0:
-            practice.bot.sendMsg("{}".format(p_str))
-            p_str = ''
-
-    if len(result_json[ymd]) % 100 != 0:
-        practice.bot.sendMsg("{}".format(p_str))
-
-    size = len(result_json[ymd])
-    print("size: {}".format(size))
-
-    # https://youtu.be/QjBsui8Ob14?si=4dC3q8p0Yu5ZWK1K
-    # https://www.youtube.com/watch?v=YwiHaa1KNwA
-
-    print("done...")

resources/lotto_history.json

@@ -1216,3 +1216,14 @@
 {"returnValue": "success", "drwNoDate": "2026-03-21", "drwNo": 1216, "drwtNo1": 3, "drwtNo2": 10, "drwtNo3": 14, "drwtNo4": 15, "drwtNo5": 23, "drwtNo6": 24, "bnusNo": 25}
 {"returnValue": "success", "drwNoDate": "2026-03-28", "drwNo": 1217, "drwtNo1": 8, "drwtNo2": 10, "drwtNo3": 15, "drwtNo4": 20, "drwtNo5": 29, "drwtNo6": 31, "bnusNo": 41}
 {"returnValue": "success", "drwNoDate": "2026-04-04", "drwNo": 1218, "drwtNo1": 3, "drwtNo2": 28, "drwtNo3": 31, "drwtNo4": 32, "drwtNo5": 42, "drwtNo6": 45, "bnusNo": 25}
+{"returnValue": "success", "drwNoDate": "2026-04-11", "drwNo": 1219, "drwtNo1": 1, "drwtNo2": 2, "drwtNo3": 15, "drwtNo4": 28, "drwtNo5": 39, "drwtNo6": 45, "bnusNo": 31}
+{"returnValue": "success", "drwNoDate": "2026-04-18", "drwNo": 1220, "drwtNo1": 2, "drwtNo2": 22, "drwtNo3": 25, "drwtNo4": 28, "drwtNo5": 34, "drwtNo6": 43, "bnusNo": 16}
+{"returnValue": "success", "drwNoDate": "2026-04-25", "drwNo": 1221, "drwtNo1": 6, "drwtNo2": 13, "drwtNo3": 18, "drwtNo4": 28, "drwtNo5": 30, "drwtNo6": 36, "bnusNo": 9}
+{"returnValue": "success", "drwNoDate": "2026-05-02", "drwNo": 1222, "drwtNo1": 4, "drwtNo2": 11, "drwtNo3": 17, "drwtNo4": 22, "drwtNo5": 32, "drwtNo6": 41, "bnusNo": 34}
+{"returnValue": "success", "drwNoDate": "2026-05-09", "drwNo": 1223, "drwtNo1": 16, "drwtNo2": 18, "drwtNo3": 20, "drwtNo4": 32, "drwtNo5": 33, "drwtNo6": 39, "bnusNo": 26}
+{"returnValue": "success", "drwNoDate": "2026-05-16", "drwNo": 1224, "drwtNo1": 9, "drwtNo2": 18, "drwtNo3": 21, "drwtNo4": 27, "drwtNo5": 44, "drwtNo6": 45, "bnusNo": 28}
+{"returnValue": "success", "drwNoDate": "2026-05-23", "drwNo": 1225, "drwtNo1": 8, "drwtNo2": 9, "drwtNo3": 19, "drwtNo4": 25, "drwtNo5": 41, "drwtNo6": 42, "bnusNo": 33}
+{"returnValue": "success", "drwNoDate": "2026-05-30", "drwNo": 1226, "drwtNo1": 4, "drwtNo2": 6, "drwtNo3": 13, "drwtNo4": 17, "drwtNo5": 26, "drwtNo6": 28, "bnusNo": 41}
+{"returnValue": "success", "drwNoDate": "2026-06-06", "drwNo": 1227, "drwtNo1": 1, "drwtNo2": 14, "drwtNo3": 16, "drwtNo4": 34, "drwtNo5": 41, "drwtNo6": 44, "bnusNo": 13}
+{"returnValue": "success", "drwNoDate": "2026-06-13", "drwNo": 1228, "drwtNo1": 24, "drwtNo2": 29, "drwtNo3": 30, "drwtNo4": 31, "drwtNo5": 35, "drwtNo6": 44, "bnusNo": 1}
+{"returnValue": "success", "drwNoDate": "2026-06-20", "drwNo": 1229, "drwtNo1": 12, "drwtNo2": 13, "drwtNo3": 29, "drwtNo4": 34, "drwtNo5": 37, "drwtNo6": 42, "bnusNo": 16}

resources/lotto_history.txt

@@ -1204,7 +1204,7 @@
 1204,8,16,28,30,31,44,27
 1205,1,4,16,23,31,41,2
 1206,1,3,17,26,27,42,23
-1207,10,22,24,27,38,45,11
+1207,10,22,24,27,38,45,21
 1208,6,27,30,36,38,42,25
 1209,2,17,20,35,37,39,24
 1210,1,7,9,17,27,38,31
@@ -1216,3 +1216,14 @@
 1216,3,10,14,15,23,24,25
 1217,8,10,15,20,29,31,41
 1218,3,28,31,32,42,45,25
+1219,1,2,15,28,39,45,31
+1220,2,22,25,28,34,43,16
+1221,6,13,18,28,30,36,9
+1222,4,11,17,22,32,41,34
+1223,16,18,20,32,33,39,26
+1224,9,18,21,27,44,45,28
+1225,8,9,19,25,41,42,33
+1226,4,6,13,17,26,28,41
+1227,1,14,16,34,41,44,13
+1228,24,29,30,31,35,44,1
+1229,12,13,29,34,37,42,16

review_1.py

@@ -1,99 +0,0 @@
-import os
-import time
-import datetime
-import pandas as pd
-import itertools
-from filter_model_1 import BallFilter
-
-class FilterTestReview:
-
-    ballFilter = None
-
-    def __init__(self, resources_path):
-        lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.json')
-        self.ballFilter = BallFilter(lottoHistoryFileName)
-
-        return
-
-    def validate(self, df_ball, nos=None):
-
-        win_history = {}
-        win_history_size = {}
-
-        for no in nos:
-
-            print("[{} 회차]".format(no))
-            balls = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = balls[1:7].copy()  # copy()로 복사
-            bonus = balls[7]
-
-            final_candidates = []
-            win_dic = {1: [], 2: [], 3: [], 4: [], 5: []}
-            generation_balls = list(range(1, 46))
-            nCr = list(itertools.combinations(generation_balls, 6))
-            for idx, ball in enumerate(nCr):
-
-                if idx % 1000000 == 0:
-                    print("   - {} processed...".format(idx))
-
-                ball = list(ball)
-
-                filter_type = self.ballFilter.filter(ball=ball, no=no, until_end=False, df=df_ball)
-                filter_size = len(filter_type)
-
-                if 0 < filter_size:
-                    continue
-
-                final_candidates.append(ball)
-
-                match = len(set(ball) & set(answer))
-                if match == 6:
-                    if no not in win_history:  # 중복 방지
-                        win_history[no] = answer.copy()  # copy()로 복사
-                    if ball not in win_dic[1]:  # 같은 조합 중복 방지
-                        win_dic[1].append(ball.copy())  # copy()로 복사
-
-                else:
-                    if match == 3:
-                        win_dic[5].append(ball)
-                    elif match == 4:
-                        win_dic[4].append(ball)
-                    elif match == 5:
-                        # 2등 판별: 5개 맞고 보너스 번호 포함
-                        if bonus in ball:
-                            win_dic[2].append(ball)
-                        else:
-                            win_dic[3].append(ball)
-
-                win_history_size[no] = len(final_candidates)
-
-            print("no: {}, answer: {}, size: {}".format(no, answer, len(final_candidates)))
-            print("   > 1등: {}, 2등: {}, 3등: {}, 4등: {}, 5등: {}".format(len(win_dic[1]), len(win_dic[2]), len(win_dic[3]), len(win_dic[4]), len(win_dic[5])))
-
-        return win_history, win_history_size
-
-
-if __name__ == '__main__':
-
-    PROJECT_HOME = '.'
-    resources_path = os.path.join(PROJECT_HOME, 'resources')
-
-    lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.txt')
-    df_ball = pd.read_csv(lottoHistoryFileName, header=None)
-    df_ball.columns = ['no', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'bn']
-
-    filterTestReview = FilterTestReview(resources_path)
-
-    start = time.time()
-    #win_history = filterTest.validate(df_ball, nos =[1046,1022,1004,900,869,816,797,696,574,524,523,461,356,324,303,289,147,71], filter_ball = [1,2,4,6,10,11,11,17,18,20,21,22,23,24,26,27,28,30,31,32,33,34,37,38,39,40,42,44])
-    win_history, win_history_size = filterTestReview.validate(
-        df_ball,
-        #nos=range(1126, 21, -1),
-        nos=[1057,1046,1022,900,841,816,696,593,574,426,356,324,303,245,147,139,71])
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    print("{} 회 당첨".format(len(win_history)))
-    sorted_win_history = sorted(win_history.keys())
-    for i in range(len(sorted_win_history)):
-        print("\t>{} > {} ({})".format(sorted_win_history[i], win_history[sorted_win_history[i]], win_history_size[sorted_win_history[i]]))

review_2.py

@@ -1,99 +0,0 @@
-import os
-import time
-import datetime
-import pandas as pd
-import itertools
-from filter_model_2 import BallFilter
-
-class FilterTestReview:
-
-    ballFilter = None
-
-    def __init__(self, resources_path):
-        lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.json')
-        self.ballFilter = BallFilter(lottoHistoryFileName)
-
-        return
-
-    def validate(self, df_ball, nos=None):
-
-        win_history = {}
-        win_history_size = {}
-
-        for no in nos:
-
-            print("[{} 회차]".format(no))
-            balls = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = balls[1:7].copy()  # copy()로 복사
-            bonus = balls[7]
-
-            final_candidates = []
-            win_dic = {1: [], 2: [], 3: [], 4: [], 5: []}
-            generation_balls = list(range(1, 46))
-            nCr = list(itertools.combinations(generation_balls, 6))
-            for idx, ball in enumerate(nCr):
-
-                if idx % 1000000 == 0:
-                    print("   - {} processed...".format(idx))
-
-                ball = list(ball)
-
-                filter_type = self.ballFilter.filter(ball=ball, no=no, until_end=False, df=df_ball)
-                filter_size = len(filter_type)
-
-                if 0 < filter_size:
-                    continue
-
-                final_candidates.append(ball)
-
-                match = len(set(ball) & set(answer))
-                if match == 6:
-                    if no not in win_history:  # 중복 방지
-                        win_history[no] = answer.copy()  # copy()로 복사
-                    if ball not in win_dic[1]:  # 같은 조합 중복 방지
-                        win_dic[1].append(ball.copy())  # copy()로 복사
-
-                else:
-                    if match == 3:
-                        win_dic[5].append(ball)
-                    elif match == 4:
-                        win_dic[4].append(ball)
-                    elif match == 5:
-                        # 2등 판별: 5개 맞고 보너스 번호 포함
-                        if bonus in ball:
-                            win_dic[2].append(ball)
-                        else:
-                            win_dic[3].append(ball)
-
-                win_history_size[no] = len(final_candidates)
-
-            print("no: {}, answer: {}, size: {}".format(no, answer, len(final_candidates)))
-            print("   > 1등: {}, 2등: {}, 3등: {}, 4등: {}, 5등: {}".format(len(win_dic[1]), len(win_dic[2]), len(win_dic[3]), len(win_dic[4]), len(win_dic[5])))
-
-        return win_history, win_history_size
-
-
-if __name__ == '__main__':
-
-    PROJECT_HOME = '.'
-    resources_path = os.path.join(PROJECT_HOME, 'resources')
-
-    lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.txt')
-    df_ball = pd.read_csv(lottoHistoryFileName, header=None)
-    df_ball.columns = ['no', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'bn']
-
-    filterTestReview = FilterTestReview(resources_path)
-
-    start = time.time()
-    #win_history = filterTest.validate(df_ball, nos =[1046,1022,1004,900,869,816,797,696,574,524,523,461,356,324,303,289,147,71], filter_ball = [1,2,4,6,10,11,11,17,18,20,21,22,23,24,26,27,28,30,31,32,33,34,37,38,39,40,42,44])
-    win_history, win_history_size = filterTestReview.validate(
-        df_ball,
-        #nos=range(1126, 21, -1),
-        nos=[1057,1046,1022,900,841,816,696,593,574,426,356,324,303,245,147,139,71])
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    print("{} 회 당첨".format(len(win_history)))
-    sorted_win_history = sorted(win_history.keys())
-    for i in range(len(sorted_win_history)):
-        print("\t>{} > {} ({})".format(sorted_win_history[i], win_history[sorted_win_history[i]], win_history_size[sorted_win_history[i]]))

review_3.py

@@ -1,99 +0,0 @@
-import os
-import time
-import datetime
-import pandas as pd
-import itertools
-from filter_model_3 import BallFilter
-
-class FilterTestReview:
-
-    ballFilter = None
-
-    def __init__(self, resources_path):
-        lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.json')
-        self.ballFilter = BallFilter(lottoHistoryFileName)
-
-        return
-
-    def validate(self, df_ball, nos=None):
-
-        win_history = {}
-        win_history_size = {}
-
-        for no in nos:
-
-            print("[{} 회차]".format(no))
-            balls = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = balls[1:7].copy()  # copy()로 복사
-            bonus = balls[7]
-
-            final_candidates = []
-            win_dic = {1: [], 2: [], 3: [], 4: [], 5: []}
-            generation_balls = list(range(1, 46))
-            nCr = list(itertools.combinations(generation_balls, 6))
-            for idx, ball in enumerate(nCr):
-
-                if idx % 1000000 == 0:
-                    print("   - {} processed...".format(idx))
-
-                ball = list(ball)
-
-                filter_type = self.ballFilter.filter(ball=ball, no=no, until_end=False, df=df_ball)
-                filter_size = len(filter_type)
-
-                if 0 < filter_size:
-                    continue
-
-                final_candidates.append(ball)
-
-                match = len(set(ball) & set(answer))
-                if match == 6:
-                    if no not in win_history:  # 중복 방지
-                        win_history[no] = answer.copy()  # copy()로 복사
-                    if ball not in win_dic[1]:  # 같은 조합 중복 방지
-                        win_dic[1].append(ball.copy())  # copy()로 복사
-
-                else:
-                    if match == 3:
-                        win_dic[5].append(ball)
-                    elif match == 4:
-                        win_dic[4].append(ball)
-                    elif match == 5:
-                        # 2등 판별: 5개 맞고 보너스 번호 포함
-                        if bonus in ball:
-                            win_dic[2].append(ball)
-                        else:
-                            win_dic[3].append(ball)
-
-                win_history_size[no] = len(final_candidates)
-
-            print("no: {}, answer: {}, size: {}".format(no, answer, len(final_candidates)))
-            print("   > 1등: {}, 2등: {}, 3등: {}, 4등: {}, 5등: {}".format(len(win_dic[1]), len(win_dic[2]), len(win_dic[3]), len(win_dic[4]), len(win_dic[5])))
-
-        return win_history, win_history_size
-
-
-if __name__ == '__main__':
-
-    PROJECT_HOME = '.'
-    resources_path = os.path.join(PROJECT_HOME, 'resources')
-
-    lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.txt')
-    df_ball = pd.read_csv(lottoHistoryFileName, header=None)
-    df_ball.columns = ['no', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'bn']
-
-    filterTestReview = FilterTestReview(resources_path)
-
-    start = time.time()
-    #win_history = filterTest.validate(df_ball, nos =[1046,1022,1004,900,869,816,797,696,574,524,523,461,356,324,303,289,147,71], filter_ball = [1,2,4,6,10,11,11,17,18,20,21,22,23,24,26,27,28,30,31,32,33,34,37,38,39,40,42,44])
-    win_history, win_history_size = filterTestReview.validate(
-        df_ball,
-        #nos=range(1126, 21, -1),
-        nos=[1057,1046,1022,900,841,816,696,593,574,426,356,324,303,245,147,139,71])
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    print("{} 회 당첨".format(len(win_history)))
-    sorted_win_history = sorted(win_history.keys())
-    for i in range(len(sorted_win_history)):
-        print("\t>{} > {} ({})".format(sorted_win_history[i], win_history[sorted_win_history[i]], win_history_size[sorted_win_history[i]]))

scripts/run_with_ncue.sh

@@ -1,17 +1,9 @@
 #!/usr/bin/env bash
-# miniconda 환경 ncue에서 Python으로 인자 실행: ./scripts/run_with_ncue.sh final_filterTest.py
 set -euo pipefail
-ROOT="$(cd "$(dirname "$0")/.." && pwd)"
-cd "$ROOT"
-for base in "${MINICONDA_HOME:-}" "$HOME/miniconda3" "$HOME/miniforge3" "$HOME/anaconda3" "$HOME/mambaforge"; do
-  [ -n "$base" ] || continue
-  c="$base/bin/conda"
-  if [ -x "$c" ]; then
-    exec "$c" run -n ncue -- python "$@"
-  fi
-done
-if [ -n "${CONDA_EXE:-}" ] && [ -x "$CONDA_EXE" ]; then
-  exec "$CONDA_EXE" run -n ncue -- python "$@"
-fi
-echo "conda ncue 환경을 찾지 못했습니다. 터미널에서: conda activate ncue && python \"\$@\"" >&2
-exit 1
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+REPO_ROOT="$(cd "${SCRIPT_DIR}/.." && pwd)"
+export PATH="${HOME}/miniconda3/bin:${HOME}/anaconda3/bin:/opt/anaconda3/bin:${PATH}"
+source "$(conda info --base)/etc/profile.d/conda.sh"
+conda activate ncue
+cd "${REPO_ROOT}"
+exec python "$@"

test_1.py

@@ -1,236 +0,0 @@
-import os
-import argparse
-import pandas as pd
-import itertools
-from filter_model_1 import BallFilter
-import time
-import datetime
-
-class FilterTest:
-
-    ballFilter = None
-
-    def __init__(self, resources_path, ruleset_path=None, history_json="lotto_history.json"):
-        # test는 이전회차/최근 N주 윈도우 feature가 필수이므로 전체 히스토리(json)를 사용해야 한다.
-        lottoHistoryFileName = os.path.join(resources_path, history_json)
-        self.ballFilter = BallFilter(lottoHistoryFileName, ruleset_path=ruleset_path)
-
-        return
-
-    def find_filter_method(self, df_ball, start_no, end_no, filter_ball=None):
-        win_count = 0
-
-        no_filter_ball = {}
-
-        printLog = True
-        filter_dic = {}
-        filter_dic_len = {}
-        filter_dic_1 = {}
-        filter_dic_2 = {}
-        # df_ball 은 전체 히스토리일 수 있으며, 채점은 [start_no, end_no] 범위만 수행한다.
-        for i in range(len(df_ball) - 1, -1, -1):
-
-            no = df_ball['no'].iloc[i]
-            no = int(no)
-            if no < start_no or end_no < no:
-                continue
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            filter_type = self.ballFilter.filter(ball=answer, no=no, until_end=True, df=df_ball)
-            filter_type = list(filter_type)
-            size = len(filter_type)
-
-            if size == 0:
-                win_count += 1
-                no_filter_ball[no] = answer
-                print("\t", no)
-            elif size == 1:
-                key = filter_type[0]
-                if key not in filter_dic_1:
-                    filter_dic_1[key] = 1
-                else:
-                    filter_dic_1[key] += 1
-
-                if printLog:
-                    print("\t", no, filter_type)
-            elif size == 2:
-                key = ','.join(filter_type)
-                if key not in filter_dic_2:
-                    filter_dic_2[key] = 1
-                else:
-                    filter_dic_2[key] += 1
-
-                if printLog:
-                    print("\t", no, filter_type)
-            else:
-                if printLog:
-                    print("\t", no, filter_type)
-
-                # 회차별 필터개수가 적은 것을 정렬하기 위함
-                if size not in filter_dic_len:
-                    filter_dic_len[size] = []
-                filter_dic_len[size].append(filter_type)
-
-            for f_t in filter_type:
-                if f_t not in filter_dic:
-                    filter_dic[f_t] = 1
-                else:
-                    filter_dic[f_t] += 1
-
-        print("\n\t[필터 개수가 적은 것부터 최적화를 위함]")
-        sorted_filter_dic_len = sorted(filter_dic_len.keys())
-        for filter_count in sorted_filter_dic_len:
-            for filter_type in filter_dic_len[filter_count]:
-                print("\t\t>{} > {}".format(filter_count, filter_type))
-
-        print("\n\t[걸러진 유일 필터]")
-        sorted_filter_dic_1 = sorted(filter_dic_1.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic_1)):
-            print("\t\t>", sorted_filter_dic_1[i][0], "->", sorted_filter_dic_1[i][1])
-
-        print("\n\t[2개 필터에 걸린 경우]")
-        sorted_filter_dic_2 = sorted(filter_dic_2.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic_2)):
-            print("\t\t>", sorted_filter_dic_2[i][0], "->", sorted_filter_dic_2[i][1])
-
-        print("\n\t[Filter 유형 별 걸린 개수]")
-        sorted_filter_dic = sorted(filter_dic.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic)):
-            print("\t\t>", sorted_filter_dic[i][0], "->", sorted_filter_dic[i][1])
-
-        print("\n\t# 필터에 걸리지 않고 당첨된 회차")
-        total = max(0, end_no - start_no + 1)
-        rate = (100 * len(no_filter_ball) / total) if total else 0.0
-        print("\tcount: {:,} / total: {:,} ({:.2})%".format(len(no_filter_ball), total, rate))
-        for no in no_filter_ball:
-            print("\t\t>", no, no_filter_ball[no])
-        print("\tcount: {:,} / total: {:,} ({:.2})%".format(len(no_filter_ball), total, rate))
-
-        return win_count
-
-    def find_final_candidates(self, no, df_ball, filter_ball=None):
-        final_candidates = []
-
-        generation_balls = list(range(1, 46))
-
-        nCr = list(itertools.combinations(generation_balls, 6))
-        for idx, ball in enumerate(nCr):
-
-            if idx % 1000000 == 0:
-                print("   - {} processed...".format(idx))
-
-            if filter_ball is not None and 0 < len(set(ball) & set(filter_ball)):
-                continue
-
-            filter_type = self.ballFilter.filter(ball=ball, no=no, until_end=False, df=df_ball)
-            filter_size = len(filter_type)
-
-            if filter_size:
-                continue
-
-            final_candidates.append(ball)
-
-        return final_candidates
-
-    def check_filter_method(self, df_ball, p_win_count, filter_ball=None):
-
-        win_count = 0
-        for i in range(len(df_ball)-1, 0, -1):
-
-            no = df_ball['no'].iloc[i]
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            if filter_ball is not None and len(set(answer) & set(filter_ball)):
-                continue
-
-            filter_type = self.ballFilter.extract_final_candidates(answer, no=no, until_end=True, df=df_ball)
-
-            if len(filter_type) == 0:
-                win_count += 1
-                print("\t\t>{}. {}".format(no, answer))
-
-        print("\n\t> {} / {} p_win_count, {} total".format( win_count, p_win_count, len(df_ball)-1) )
-
-        return
-
-    def validate(self, df_ball, nos=None):
-        win_history = {}
-
-        for no in nos:
-            print(no, "processing...")
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            generation_balls = list(range(1, 46))
-            nCr = list(itertools.combinations(generation_balls, 6))
-            for idx, ball in enumerate(nCr):
-                if idx % 1000000 == 0:
-                    print("   - {} processed...".format(idx))
-                ball = list(ball)
-                filter_type = self.ballFilter.extract_final_candidates(ball, no=no, until_end=True, df=df_ball)
-                if 0 == len(filter_type) and len(set(answer)&set(ball))==6:
-                    win_history[no] = answer
-                    print("win.. no: {}, answer: {}".format(no, str(answer)))
-                    break
-
-        return win_history
-
-
-if __name__ == '__main__':
-
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--resources", default="resources")
-    parser.add_argument(
-        "--ruleset",
-        default=None,
-        help="Ruleset JSON path (optional). Default: filter_model_1.py 내장 ruleset 사용",
-    )
-    parser.add_argument("--start-no", type=int, default=1001)
-    parser.add_argument("--end-no", type=int, default=1204)
-    args = parser.parse_args()
-
-    resources_path = args.resources
-
-    # 전체 히스토리 txt를 사용해 previous/window feature를 정상 계산하되, 채점은 test 범위만 수행한다.
-    lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.txt')
-    df_ball = pd.read_csv(lottoHistoryFileName, header=None)
-    df_ball.columns = ['no', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'bn']
-
-    filter_ball=[]
-    filterTest = FilterTest(resources_path, ruleset_path=args.ruleset, history_json='lotto_history.json')
-
-    print("STEP #1. 필터 방법 추출")
-    start = time.time()
-    win_count = filterTest.find_filter_method(df_ball, start_no=args.start_no, end_no=args.end_no, filter_ball=filter_ball)
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    """
-    print("\n\n")
-    no = df_ball['no'].values[-1]
-    ball = df_ball[df_ball['no'] == no].values.tolist()[0]
-    answer = ball[1:7]
-
-    print("STEP #0. 최종 후보 선정")
-    start = time.time()
-    final_candidates = filterTest.find_final_candidates(no, df_ball, filter_ball=None)
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    print("   > size: {}".format(len(final_candidates)))
-    file_name = os.path.join(resources_path, 'final_candidates.biz_a1.txt')
-    with open(file_name, 'w+') as outFp:
-        for ball in final_candidates:
-            ball_str = [str(b) for b in answer]
-            outFp.write("{}\n".format(','.join(ball_str)))
-
-    print('{}회, 정답: {}\n'.format(no, str(answer)))
-    """
-
-    #print("\n\n")
-    #print("STEP #2. 당첨 회수 확인")
-    #filterTest.check_filter_method(df_ball, win_count)
-
-    # 오리지널 버전 (자질 파일에 고정): 당첨 22개

test_2.py

@@ -1,236 +0,0 @@
-import os
-import argparse
-import pandas as pd
-import itertools
-from filter_model_2 import BallFilter
-import time
-import datetime
-
-class FilterTest:
-
-    ballFilter = None
-
-    def __init__(self, resources_path, ruleset_path=None, history_json="lotto_history.json"):
-        # test는 이전회차/최근 N주 윈도우 feature가 필수이므로 전체 히스토리(json)를 사용해야 한다.
-        lottoHistoryFileName = os.path.join(resources_path, history_json)
-        self.ballFilter = BallFilter(lottoHistoryFileName, ruleset_path=ruleset_path)
-
-        return
-
-    def find_filter_method(self, df_ball, start_no, end_no, filter_ball=None):
-        win_count = 0
-
-        no_filter_ball = {}
-
-        printLog = True
-        filter_dic = {}
-        filter_dic_len = {}
-        filter_dic_1 = {}
-        filter_dic_2 = {}
-        # df_ball 은 전체 히스토리일 수 있으며, 채점은 [start_no, end_no] 범위만 수행한다.
-        for i in range(len(df_ball) - 1, -1, -1):
-
-            no = df_ball['no'].iloc[i]
-            no = int(no)
-            if no < start_no or end_no < no:
-                continue
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            filter_type = self.ballFilter.filter(ball=answer, no=no, until_end=True, df=df_ball)
-            filter_type = list(filter_type)
-            size = len(filter_type)
-
-            if size == 0:
-                win_count += 1
-                no_filter_ball[no] = answer
-                print("\t", no)
-            elif size == 1:
-                key = filter_type[0]
-                if key not in filter_dic_1:
-                    filter_dic_1[key] = 1
-                else:
-                    filter_dic_1[key] += 1
-
-                if printLog:
-                    print("\t", no, filter_type)
-            elif size == 2:
-                key = ','.join(filter_type)
-                if key not in filter_dic_2:
-                    filter_dic_2[key] = 1
-                else:
-                    filter_dic_2[key] += 1
-
-                if printLog:
-                    print("\t", no, filter_type)
-            else:
-                if printLog:
-                    print("\t", no, filter_type)
-
-                # 회차별 필터개수가 적은 것을 정렬하기 위함
-                if size not in filter_dic_len:
-                    filter_dic_len[size] = []
-                filter_dic_len[size].append(filter_type)
-
-            for f_t in filter_type:
-                if f_t not in filter_dic:
-                    filter_dic[f_t] = 1
-                else:
-                    filter_dic[f_t] += 1
-
-        print("\n\t[필터 개수가 적은 것부터 최적화를 위함]")
-        sorted_filter_dic_len = sorted(filter_dic_len.keys())
-        for filter_count in sorted_filter_dic_len:
-            for filter_type in filter_dic_len[filter_count]:
-                print("\t\t>{} > {}".format(filter_count, filter_type))
-
-        print("\n\t[걸러진 유일 필터]")
-        sorted_filter_dic_1 = sorted(filter_dic_1.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic_1)):
-            print("\t\t>", sorted_filter_dic_1[i][0], "->", sorted_filter_dic_1[i][1])
-
-        print("\n\t[2개 필터에 걸린 경우]")
-        sorted_filter_dic_2 = sorted(filter_dic_2.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic_2)):
-            print("\t\t>", sorted_filter_dic_2[i][0], "->", sorted_filter_dic_2[i][1])
-
-        print("\n\t[Filter 유형 별 걸린 개수]")
-        sorted_filter_dic = sorted(filter_dic.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic)):
-            print("\t\t>", sorted_filter_dic[i][0], "->", sorted_filter_dic[i][1])
-
-        print("\n\t# 필터에 걸리지 않고 당첨된 회차")
-        total = max(0, end_no - start_no + 1)
-        rate = (100 * len(no_filter_ball) / total) if total else 0.0
-        print("\tcount: {:,} / total: {:,} ({:.2})%".format(len(no_filter_ball), total, rate))
-        for no in no_filter_ball:
-            print("\t\t>", no, no_filter_ball[no])
-        print("\tcount: {:,} / total: {:,} ({:.2})%".format(len(no_filter_ball), total, rate))
-
-        return win_count
-
-    def find_final_candidates(self, no, df_ball, filter_ball=None):
-        final_candidates = []
-
-        generation_balls = list(range(1, 46))
-
-        nCr = list(itertools.combinations(generation_balls, 6))
-        for idx, ball in enumerate(nCr):
-
-            if idx % 1000000 == 0:
-                print("   - {} processed...".format(idx))
-
-            if filter_ball is not None and 0 < len(set(ball) & set(filter_ball)):
-                continue
-
-            filter_type = self.ballFilter.filter(ball=ball, no=no, until_end=False, df=df_ball)
-            filter_size = len(filter_type)
-
-            if filter_size:
-                continue
-
-            final_candidates.append(ball)
-
-        return final_candidates
-
-    def check_filter_method(self, df_ball, p_win_count, filter_ball=None):
-
-        win_count = 0
-        for i in range(len(df_ball)-1, 0, -1):
-
-            no = df_ball['no'].iloc[i]
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            if filter_ball is not None and len(set(answer) & set(filter_ball)):
-                continue
-
-            filter_type = self.ballFilter.extract_final_candidates(answer, no=no, until_end=True, df=df_ball)
-
-            if len(filter_type) == 0:
-                win_count += 1
-                print("\t\t>{}. {}".format(no, answer))
-
-        print("\n\t> {} / {} p_win_count, {} total".format( win_count, p_win_count, len(df_ball)-1) )
-
-        return
-
-    def validate(self, df_ball, nos=None):
-        win_history = {}
-
-        for no in nos:
-            print(no, "processing...")
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            generation_balls = list(range(1, 46))
-            nCr = list(itertools.combinations(generation_balls, 6))
-            for idx, ball in enumerate(nCr):
-                if idx % 1000000 == 0:
-                    print("   - {} processed...".format(idx))
-                ball = list(ball)
-                filter_type = self.ballFilter.extract_final_candidates(ball, no=no, until_end=True, df=df_ball)
-                if 0 == len(filter_type) and len(set(answer)&set(ball))==6:
-                    win_history[no] = answer
-                    print("win.. no: {}, answer: {}".format(no, str(answer)))
-                    break
-
-        return win_history
-
-
-if __name__ == '__main__':
-
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--resources", default="resources")
-    parser.add_argument(
-        "--ruleset",
-        default=None,
-        help="Ruleset JSON path (optional). Default: filter_model_1.py 내장 ruleset 사용",
-    )
-    parser.add_argument("--start-no", type=int, default=1001)
-    parser.add_argument("--end-no", type=int, default=1204)
-    args = parser.parse_args()
-
-    resources_path = args.resources
-
-    # 전체 히스토리 txt를 사용해 previous/window feature를 정상 계산하되, 채점은 test 범위만 수행한다.
-    lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.txt')
-    df_ball = pd.read_csv(lottoHistoryFileName, header=None)
-    df_ball.columns = ['no', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'bn']
-
-    filter_ball=[]
-    filterTest = FilterTest(resources_path, ruleset_path=args.ruleset, history_json='lotto_history.json')
-
-    print("STEP #1. 필터 방법 추출")
-    start = time.time()
-    win_count = filterTest.find_filter_method(df_ball, start_no=args.start_no, end_no=args.end_no, filter_ball=filter_ball)
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    """
-    print("\n\n")
-    no = df_ball['no'].values[-1]
-    ball = df_ball[df_ball['no'] == no].values.tolist()[0]
-    answer = ball[1:7]
-
-    print("STEP #0. 최종 후보 선정")
-    start = time.time()
-    final_candidates = filterTest.find_final_candidates(no, df_ball, filter_ball=None)
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    print("   > size: {}".format(len(final_candidates)))
-    file_name = os.path.join(resources_path, 'final_candidates.biz_a1.txt')
-    with open(file_name, 'w+') as outFp:
-        for ball in final_candidates:
-            ball_str = [str(b) for b in answer]
-            outFp.write("{}\n".format(','.join(ball_str)))
-
-    print('{}회, 정답: {}\n'.format(no, str(answer)))
-    """
-
-    #print("\n\n")
-    #print("STEP #2. 당첨 회수 확인")
-    #filterTest.check_filter_method(df_ball, win_count)
-
-    # 오리지널 버전 (자질 파일에 고정): 당첨 22개

test_3.py

@@ -1,236 +0,0 @@
-import os
-import argparse
-import pandas as pd
-import itertools
-from filter_model_3 import BallFilter
-import time
-import datetime
-
-class FilterTest:
-
-    ballFilter = None
-
-    def __init__(self, resources_path, ruleset_path=None, history_json="lotto_history.json"):
-        # test는 이전회차/최근 N주 윈도우 feature가 필수이므로 전체 히스토리(json)를 사용해야 한다.
-        lottoHistoryFileName = os.path.join(resources_path, history_json)
-        self.ballFilter = BallFilter(lottoHistoryFileName, ruleset_path=ruleset_path)
-
-        return
-
-    def find_filter_method(self, df_ball, start_no, end_no, filter_ball=None):
-        win_count = 0
-
-        no_filter_ball = {}
-
-        printLog = True
-        filter_dic = {}
-        filter_dic_len = {}
-        filter_dic_1 = {}
-        filter_dic_2 = {}
-        # df_ball 은 전체 히스토리일 수 있으며, 채점은 [start_no, end_no] 범위만 수행한다.
-        for i in range(len(df_ball) - 1, -1, -1):
-
-            no = df_ball['no'].iloc[i]
-            no = int(no)
-            if no < start_no or end_no < no:
-                continue
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            filter_type = self.ballFilter.filter(ball=answer, no=no, until_end=True, df=df_ball)
-            filter_type = list(filter_type)
-            size = len(filter_type)
-
-            if size == 0:
-                win_count += 1
-                no_filter_ball[no] = answer
-                print("\t", no)
-            elif size == 1:
-                key = filter_type[0]
-                if key not in filter_dic_1:
-                    filter_dic_1[key] = 1
-                else:
-                    filter_dic_1[key] += 1
-
-                if printLog:
-                    print("\t", no, filter_type)
-            elif size == 2:
-                key = ','.join(filter_type)
-                if key not in filter_dic_2:
-                    filter_dic_2[key] = 1
-                else:
-                    filter_dic_2[key] += 1
-
-                if printLog:
-                    print("\t", no, filter_type)
-            else:
-                if printLog:
-                    print("\t", no, filter_type)
-
-                # 회차별 필터개수가 적은 것을 정렬하기 위함
-                if size not in filter_dic_len:
-                    filter_dic_len[size] = []
-                filter_dic_len[size].append(filter_type)
-
-            for f_t in filter_type:
-                if f_t not in filter_dic:
-                    filter_dic[f_t] = 1
-                else:
-                    filter_dic[f_t] += 1
-
-        print("\n\t[필터 개수가 적은 것부터 최적화를 위함]")
-        sorted_filter_dic_len = sorted(filter_dic_len.keys())
-        for filter_count in sorted_filter_dic_len:
-            for filter_type in filter_dic_len[filter_count]:
-                print("\t\t>{} > {}".format(filter_count, filter_type))
-
-        print("\n\t[걸러진 유일 필터]")
-        sorted_filter_dic_1 = sorted(filter_dic_1.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic_1)):
-            print("\t\t>", sorted_filter_dic_1[i][0], "->", sorted_filter_dic_1[i][1])
-
-        print("\n\t[2개 필터에 걸린 경우]")
-        sorted_filter_dic_2 = sorted(filter_dic_2.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic_2)):
-            print("\t\t>", sorted_filter_dic_2[i][0], "->", sorted_filter_dic_2[i][1])
-
-        print("\n\t[Filter 유형 별 걸린 개수]")
-        sorted_filter_dic = sorted(filter_dic.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic)):
-            print("\t\t>", sorted_filter_dic[i][0], "->", sorted_filter_dic[i][1])
-
-        print("\n\t# 필터에 걸리지 않고 당첨된 회차")
-        total = max(0, end_no - start_no + 1)
-        rate = (100 * len(no_filter_ball) / total) if total else 0.0
-        print("\tcount: {:,} / total: {:,} ({:.2})%".format(len(no_filter_ball), total, rate))
-        for no in no_filter_ball:
-            print("\t\t>", no, no_filter_ball[no])
-        print("\tcount: {:,} / total: {:,} ({:.2})%".format(len(no_filter_ball), total, rate))
-
-        return win_count
-
-    def find_final_candidates(self, no, df_ball, filter_ball=None):
-        final_candidates = []
-
-        generation_balls = list(range(1, 46))
-
-        nCr = list(itertools.combinations(generation_balls, 6))
-        for idx, ball in enumerate(nCr):
-
-            if idx % 1000000 == 0:
-                print("   - {} processed...".format(idx))
-
-            if filter_ball is not None and 0 < len(set(ball) & set(filter_ball)):
-                continue
-
-            filter_type = self.ballFilter.filter(ball=ball, no=no, until_end=False, df=df_ball)
-            filter_size = len(filter_type)
-
-            if filter_size:
-                continue
-
-            final_candidates.append(ball)
-
-        return final_candidates
-
-    def check_filter_method(self, df_ball, p_win_count, filter_ball=None):
-
-        win_count = 0
-        for i in range(len(df_ball)-1, 0, -1):
-
-            no = df_ball['no'].iloc[i]
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            if filter_ball is not None and len(set(answer) & set(filter_ball)):
-                continue
-
-            filter_type = self.ballFilter.extract_final_candidates(answer, no=no, until_end=True, df=df_ball)
-
-            if len(filter_type) == 0:
-                win_count += 1
-                print("\t\t>{}. {}".format(no, answer))
-
-        print("\n\t> {} / {} p_win_count, {} total".format( win_count, p_win_count, len(df_ball)-1) )
-
-        return
-
-    def validate(self, df_ball, nos=None):
-        win_history = {}
-
-        for no in nos:
-            print(no, "processing...")
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            generation_balls = list(range(1, 46))
-            nCr = list(itertools.combinations(generation_balls, 6))
-            for idx, ball in enumerate(nCr):
-                if idx % 1000000 == 0:
-                    print("   - {} processed...".format(idx))
-                ball = list(ball)
-                filter_type = self.ballFilter.extract_final_candidates(ball, no=no, until_end=True, df=df_ball)
-                if 0 == len(filter_type) and len(set(answer)&set(ball))==6:
-                    win_history[no] = answer
-                    print("win.. no: {}, answer: {}".format(no, str(answer)))
-                    break
-
-        return win_history
-
-
-if __name__ == '__main__':
-
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--resources", default="resources")
-    parser.add_argument(
-        "--ruleset",
-        default=None,
-        help="Ruleset JSON path (optional). Default: filter_model_1.py 내장 ruleset 사용",
-    )
-    parser.add_argument("--start-no", type=int, default=1001)
-    parser.add_argument("--end-no", type=int, default=1204)
-    args = parser.parse_args()
-
-    resources_path = args.resources
-
-    # 전체 히스토리 txt를 사용해 previous/window feature를 정상 계산하되, 채점은 test 범위만 수행한다.
-    lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.txt')
-    df_ball = pd.read_csv(lottoHistoryFileName, header=None)
-    df_ball.columns = ['no', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'bn']
-
-    filter_ball=[]
-    filterTest = FilterTest(resources_path, ruleset_path=args.ruleset, history_json='lotto_history.json')
-
-    print("STEP #1. 필터 방법 추출")
-    start = time.time()
-    win_count = filterTest.find_filter_method(df_ball, start_no=args.start_no, end_no=args.end_no, filter_ball=filter_ball)
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    """
-    print("\n\n")
-    no = df_ball['no'].values[-1]
-    ball = df_ball[df_ball['no'] == no].values.tolist()[0]
-    answer = ball[1:7]
-
-    print("STEP #0. 최종 후보 선정")
-    start = time.time()
-    final_candidates = filterTest.find_final_candidates(no, df_ball, filter_ball=None)
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    print("   > size: {}".format(len(final_candidates)))
-    file_name = os.path.join(resources_path, 'final_candidates.biz_a1.txt')
-    with open(file_name, 'w+') as outFp:
-        for ball in final_candidates:
-            ball_str = [str(b) for b in answer]
-            outFp.write("{}\n".format(','.join(ball_str)))
-
-    print('{}회, 정답: {}\n'.format(no, str(answer)))
-    """
-
-    #print("\n\n")
-    #print("STEP #2. 당첨 회수 확인")
-    #filterTest.check_filter_method(df_ball, win_count)
-
-    # 오리지널 버전 (자질 파일에 고정): 당첨 22개

tools/compute_final_filter_params.py

@@ -1,405 +0,0 @@
-#!/usr/bin/env python3
-"""
-학습 구간(1~800회) 당첨번호로 final_BallFilter.extract_final_candidates 에 쓸 허용 집합을 계산합니다.
-표준 라이브러리 + pandas(df 호환)만 사용합니다.
-"""
-from __future__ import annotations
-
-import csv
-import re
-from collections import defaultdict
-from pathlib import Path
-
-ROOT = Path(__file__).resolve().parents[1]
-HISTORY = ROOT / "resources" / "lotto_history.txt"
-BALLFILTER_SRC = ROOT / "BallFilter_25.py"
-OUT = ROOT / "final_filter_params.py"
-
-TRAIN_LO = 1
-TRAIN_HI = 800
-
-# 학습 분포에서 너무 넓은 합집합(union)을 피하기 위해 고유값 기준 백분위 밴드 후,
-# 각 회차 특성값이 밴드 밖이면 해당 값을 다시 포함(학습 당첨 100% 커버).
-# 좁을수록 필터가 강해짐. 학습·검증 균형은 이 값과 final_filterTest.py 결과로 조정.
-PCT_LO = 8
-PCT_HI = 92
-
-PRIME = {2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43}
-COMPOSITE = {4, 6, 8, 9, 10, 12, 14, 15, 16, 18, 20, 21, 22, 24, 25, 26, 27, 28, 30, 32, 33, 34, 35, 36, 38, 39, 40, 42, 44, 45}
-
-
-def load_draws():
-    rows = []
-    with open(HISTORY, newline="", encoding="utf-8") as f:
-        for p in csv.reader(f):
-            if not p:
-                continue
-            no = int(p[0])
-            balls = sorted(int(x) for x in p[1:7])
-            rows.append((no, balls))
-    rows.sort(key=lambda x: x[0])
-    return {no: b for no, b in rows}
-
-
-def get_ac(ball):
-    ac = set()
-    for i in range(5, -1, -1):
-        for j in range(i - 1, -1, -1):
-            ac.add(ball[i] - ball[j])
-    return len(ac) - (6 - 1)
-
-
-def interval_sum(ball):
-    return sum(ball[i] - ball[i - 1] for i in range(1, 6))
-
-
-def first_letter_sum(ball):
-    acc = [str(b)[0] for b in ball if len(str(b)) == 2]
-    return sum(int(x) for x in acc)
-
-
-def last_letter_sum(ball):
-    acc = [str(b)[1] for b in ball if len(str(b)) == 2] + [str(b) for b in ball if len(str(b)) == 1]
-    return sum(int(x) for x in acc)
-
-
-def uniq_end_digits(ball):
-    return len({b % 10 for b in ball})
-
-
-def high_low(ball):
-    low = sum(1 for b in ball if b < 23)
-    high = sum(1 for b in ball if 23 < b)
-    return low, high
-
-
-def section10_count(ball):
-    section = set()
-    for b in ball:
-        section.add(int(b / 10))
-    return len(section)
-
-
-def count_mult(ball, m):
-    return sum(1 for b in ball if b % m == 0)
-
-
-def continus_max(ball):
-    w = ball
-    best = 1
-    run = 1
-    for i in range(1, 6):
-        if w[i] == w[i - 1] + 1:
-            run += 1
-            best = max(best, run)
-        else:
-            run = 1
-    return best
-
-
-def weeks_freq(draws_map, answer, no, week):
-    s = set()
-    for w in range(1, week + 1):
-        prev_no = no - w
-        if prev_no not in draws_map:
-            continue
-        for b in draws_map[prev_no]:
-            s.add(b)
-    return sum(1 for b in answer if b in s)
-
-
-def pct_band_unique(values, lo=PCT_LO, hi=PCT_HI):
-    """고유값 정렬 후 백분위 구간에 들어가는 값만 유지. 고유 개수가 적으면 전부 유지."""
-    if not values:
-        return set()
-    u = sorted(set(values))
-    if len(u) <= 6:
-        return set(u)
-    n = len(u)
-    il = int((lo / 100.0) * (n - 1))
-    ih = int((hi / 100.0) * (n - 1))
-    low_b, high_b = u[il], u[ih]
-    return {x for x in u if low_b <= x <= high_b}
-
-
-def parse_pair_triple_rules():
-    """BallFilter_25.filterPairBall / filterTriplePairBall 에서 규칙 추출."""
-    text = BALLFILTER_SRC.read_text(encoding="utf-8")
-    pairs = []
-    for m in re.finditer(r"len\(set_ball & \{([^}]+)\}\) == 2", text):
-        parts = [int(x.strip()) for x in m.group(1).split(",")]
-        if len(parts) == 2:
-            pairs.append(frozenset(parts))
-    triples = []
-    for m in re.finditer(r"len\(set_ball & \{([^}]+)\}\) == 3", text):
-        parts = [int(x.strip()) for x in m.group(1).split(",")]
-        if len(parts) == 3:
-            triples.append(frozenset(parts))
-    return pairs, triples
-
-
-def main():
-    draws = load_draws()
-    pair_rules, triple_rules = parse_pair_triple_rules()
-
-    train_draws = {n: draws[n] for n in range(TRAIN_LO, TRAIN_HI + 1) if n in draws}
-
-    # 블랙리스트: 학습 당첨 6개에 함께 등장한 쌍/삼은 제외(당첨을 막지 않음)
-    train_pairs_seen = set()
-    train_triples_seen = set()
-    for b in train_draws.values():
-        for i in range(6):
-            for j in range(i + 1, 6):
-                train_pairs_seen.add(frozenset((b[i], b[j])))
-        for i in range(6):
-            for j in range(i + 1, 6):
-                for k in range(j + 1, 6):
-                    train_triples_seen.add(frozenset((b[i], b[j], b[k])))
-
-    pair_block = [p for p in pair_rules if p not in train_pairs_seen]
-    triple_block = [t for t in triple_rules if t not in train_triples_seen]
-
-    sets = defaultdict(set)
-    flags_prev = {"need_relax_previous": False, "need_relax_prev7": False}
-
-    for no in range(2, TRAIN_HI + 1):
-        if no not in draws or (no - 1) not in draws:
-            continue
-        ball = draws[no]
-        p_ball = draws[no - 1]
-
-        s = sum(ball)
-        sets["sum6"].add(s)
-        sets["sum6_diff"].add(abs(s - sum(p_ball)))
-
-        avg = s // 6
-        pavg = sum(p_ball) // 6
-        sets["avg6"].add(avg)
-        sets["avg6_diff"].add(abs(avg - pavg))
-
-        s3f = ball[0] + ball[1] + ball[2]
-        ps3f = p_ball[0] + p_ball[1] + p_ball[2]
-        sets["sum3f"].add(s3f)
-        sets["sum3f_diff"].add(abs(s3f - ps3f))
-
-        s3b = ball[3] + ball[4] + ball[5]
-        ps3b = p_ball[3] + p_ball[4] + p_ball[5]
-        sets["sum3b"].add(s3b)
-        sets["sum3b_diff"].add(abs(s3b - ps3b))
-
-        l, h = high_low(ball)
-        sets["hl_allowed"].add((l, h))
-
-        gh = ball[0] + ball[5]
-        pgh = p_ball[0] + p_ball[5]
-        sets["go_sum"].add(gh)
-        sets["go_sum_diff"].add(abs(gh - pgh))
-
-        iv = interval_sum(ball)
-        piv = interval_sum(p_ball)
-        sets["interval"].add(iv)
-        sets["interval_diff"].add(abs(iv - piv))
-
-        fl = first_letter_sum(ball)
-        pfl = first_letter_sum(p_ball)
-        sets["first_letter"].add(fl)
-        sets["first_letter_diff"].add(abs(fl - pfl))
-
-        ll = last_letter_sum(ball)
-        pll = last_letter_sum(p_ball)
-        sets["last_letter"].add(ll)
-        sets["last_letter_diff"].add(abs(ll - pll))
-
-        sets["b0"].add(ball[0])
-        sets["b0_diff"].add(abs(ball[0] - p_ball[0]))
-        sets["b5"].add(ball[5])
-        sets["b5_diff"].add(abs(ball[5] - p_ball[5]))
-
-        sets["uniq_end"].add(uniq_end_digits(ball))
-        sets["uniq_end_diff"].add(abs(uniq_end_digits(ball) - uniq_end_digits(p_ball)))
-
-        ac = get_ac(ball)
-        pac = get_ac(p_ball)
-        sets["ac"].add(ac)
-        sets["ac_diff"].add(abs(ac - pac))
-
-        for m in (3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 17, 19, 23):
-            sets[f"mul{m}"].add(count_mult(ball, m))
-            sets[f"mul{m}_diff"].add(abs(count_mult(ball, m) - count_mult(p_ball, m)))
-
-        pn = len(set(ball) & PRIME)
-        sets["prime_n"].add(pn)
-
-        cn = len(set(ball) & COMPOSITE)
-        sets["composite_n"].add(cn)
-        sets["composite_diff"].add(abs(cn - len(set(p_ball) & COMPOSITE)))
-
-        ev = sum(1 for b in ball if b % 2 == 0)
-        pev = sum(1 for b in p_ball if b % 2 == 0)
-        sets["even_n"].add(ev)
-        sets["even_diff"].add(abs(ev - pev))
-
-        sc = section10_count(ball)
-        psc = section10_count(p_ball)
-        sets["sec10"].add(sc)
-        sets["sec10_diff"].add(abs(sc - psc))
-
-        for wk in (8, 12, 16, 20):
-            ex = weeks_freq(draws, ball, no, wk)
-            pex = weeks_freq(draws, p_ball, no, wk)
-            sets[f"w{wk}"].add(ex)
-            sets[f"w{wk}_diff"].add(abs(ex - pex))
-
-        sets["continus_max"].add(continus_max(ball))
-
-        # filterPreviousNumber (원본과 동일)
-        pb_set = set(p_ball)
-        bad_prev = True
-        for i in range(6):
-            bi = ball[i]
-            if bi in pb_set or bi - 1 in pb_set or bi + 1 in pb_set:
-                bad_prev = False
-                break
-        if bad_prev:
-            flags_prev["need_relax_previous"] = True
-
-        # filterAllPreivous7
-        pb7 = set()
-        for i in range(no - 1, no - 8, -1):
-            if i in draws:
-                for x in draws[i]:
-                    pb7.add(x)
-        if len(set(ball) & pb7) == 6:
-            flags_prev["need_relax_prev7"] = True
-
-    # 백분위로 타이트닝 후 학습 각 회차 특성 보강
-    keys_numeric = [
-        "sum6",
-        "sum6_diff",
-        "avg6",
-        "avg6_diff",
-        "sum3f",
-        "sum3f_diff",
-        "sum3b",
-        "sum3b_diff",
-        "go_sum",
-        "go_sum_diff",
-        "interval",
-        "interval_diff",
-        "first_letter",
-        "first_letter_diff",
-        "last_letter",
-        "last_letter_diff",
-        "b0",
-        "b0_diff",
-        "b5",
-        "b5_diff",
-        "uniq_end",
-        "uniq_end_diff",
-        "ac",
-        "ac_diff",
-        "prime_n",
-        "composite_n",
-        "composite_diff",
-        "even_n",
-        "even_diff",
-        "sec10",
-        "sec10_diff",
-    ]
-    for m in (3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 17, 19, 23):
-        keys_numeric.extend([f"mul{m}", f"mul{m}_diff"])
-    for wk in (8, 12, 16, 20):
-        keys_numeric.extend([f"w{wk}", f"w{wk}_diff"])
-    keys_numeric.append("continus_max")
-
-    for k in keys_numeric:
-        sets[k] = pct_band_unique(sets[k])
-
-    # 고저: (0,1)/(1,0) 만 제외하는 기존 로직 유지 + 학습에 나온 (l,h) 항상 허용
-    hl_skip = {(l, h) for l in (0, 1) for h in (0, 1)}
-
-    def emit():
-        lines = [
-            "# -*- coding: utf-8 -*-",
-            '"""학습 구간 {}~{}회 기준 자동 생성 — tools/compute_final_filter_params.py"""'.format(
-                TRAIN_LO, TRAIN_HI
-            ),
-            "",
-            "TRAIN_RANGE = ({}, {})".format(TRAIN_LO, TRAIN_HI),
-            "DISABLE_FILTER_PREVIOUS_NUMBER = {}".format(
-                str(flags_prev["need_relax_previous"])
-            ),
-            "DISABLE_FILTER_ALL_PREVIOUS_7 = {}".format(str(flags_prev["need_relax_prev7"])),
-            "",
-        ]
-
-        def sset(name, key):
-            v = sets[key]
-            lines.append("{} = {}".format(name, repr(sorted(v))))
-
-        sset("ALLOW_SUM6", "sum6")
-        sset("ALLOW_SUM6_DIFF", "sum6_diff")
-        sset("ALLOW_AVG6", "avg6")
-        sset("ALLOW_AVG6_DIFF", "avg6_diff")
-        sset("ALLOW_SUM3F", "sum3f")
-        sset("ALLOW_SUM3F_DIFF", "sum3f_diff")
-        sset("ALLOW_SUM3B", "sum3b")
-        sset("ALLOW_SUM3B_DIFF", "sum3b_diff")
-        lines.append("HL_SKIP = {}".format(repr(sorted(hl_skip))))
-        lines.append("HL_SEEN = {}".format(repr(sorted(sets['hl_allowed']))))
-        sset("ALLOW_GO_SUM", "go_sum")
-        sset("ALLOW_GO_SUM_DIFF", "go_sum_diff")
-        sset("ALLOW_INTERVAL", "interval")
-        sset("ALLOW_INTERVAL_DIFF", "interval_diff")
-        sset("ALLOW_FIRST_LETTER", "first_letter")
-        sset("ALLOW_FIRST_LETTER_DIFF", "first_letter_diff")
-        sset("ALLOW_LAST_LETTER", "last_letter")
-        sset("ALLOW_LAST_LETTER_DIFF", "last_letter_diff")
-        sset("ALLOW_B0", "b0")
-        sset("ALLOW_B0_DIFF", "b0_diff")
-        sset("ALLOW_B5", "b5")
-        sset("ALLOW_B5_DIFF", "b5_diff")
-        sset("ALLOW_UNIQ_END", "uniq_end")
-        sset("ALLOW_UNIQ_END_DIFF", "uniq_end_diff")
-        sset("ALLOW_AC", "ac")
-        sset("ALLOW_AC_DIFF", "ac_diff")
-        for m in (3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 17, 19, 23):
-            sset("ALLOW_MUL{}".format(m), "mul{}".format(m))
-            sset("ALLOW_MUL{}_DIFF".format(m), "mul{}_diff".format(m))
-        sset("ALLOW_PRIME_N", "prime_n")
-        sset("ALLOW_COMPOSITE_N", "composite_n")
-        sset("ALLOW_COMPOSITE_DIFF", "composite_diff")
-        sset("ALLOW_EVEN_N", "even_n")
-        sset("ALLOW_EVEN_DIFF", "even_diff")
-        sset("ALLOW_SEC10", "sec10")
-        sset("ALLOW_SEC10_DIFF", "sec10_diff")
-        for wk in (8, 12, 16, 20):
-            sset("ALLOW_W{}".format(wk), "w{}".format(wk))
-            sset("ALLOW_W{}_DIFF".format(wk), "w{}_diff".format(wk))
-        sset("ALLOW_CONTINUS_MAX", "continus_max")
-
-        lines.append("PAIR_BLOCKLIST = {}".format(repr([sorted(list(x)) for x in pair_block])))
-        lines.append("TRIPLE_BLOCKLIST = {}".format(repr([sorted(list(x)) for x in triple_block])))
-        lines.extend(["", "# frozenset 캐시", ""])
-        allow_names = []
-        for line in list(lines):
-            if line.startswith("ALLOW_") and " = " in line:
-                name = line.split(" = ")[0]
-                allow_names.append(name)
-        for name in allow_names:
-            short = name.replace("ALLOW_", "", 1)
-            lines.append("_F_{} = frozenset({})".format(short, name))
-        lines.append("_F_HL_SEEN = frozenset(HL_SEEN)")
-        lines.append("")
-        return "\n".join(lines) + "\n"
-
-    OUT.write_text(emit(), encoding="utf-8")
-    print("Wrote", OUT)
-    print("pair rules:", len(pair_rules), "-> block", len(pair_block))
-    print("triple rules:", len(triple_rules), "-> block", len(triple_block))
-    print("DISABLE_FILTER_PREVIOUS_NUMBER", flags_prev["need_relax_previous"])
-    print("DISABLE_FILTER_ALL_PREVIOUS_7", flags_prev["need_relax_prev7"])
-
-
-if __name__ == "__main__":
-    main()

train_1.py

@@ -1,231 +0,0 @@
-import os
-import argparse
-import pandas as pd
-import itertools
-from filter_model_1 import BallFilter
-import time
-import datetime
-
-class FilterTest:
-
-    ballFilter = None
-
-    def __init__(self, resources_path, ruleset_path=None):
-        lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.json')
-        self.ballFilter = BallFilter(lottoHistoryFileName, ruleset_path=ruleset_path)
-
-        return
-
-    def find_filter_method(self, df_ball, start_no, end_no):
-        win_count = 0
-
-        no_filter_ball = {}
-
-        printLog = True
-        filter_dic = {}
-        filter_dic_len = {}
-        filter_dic_1 = {}
-        filter_dic_2 = {}
-        for i in range(len(df_ball)-1, 19, -1):
-            no = df_ball['no'].iloc[i]
-            if no < start_no or end_no < no:
-                continue
-
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            filter_type = self.ballFilter.filter(ball=answer, no=no, until_end=True, df=df_ball)
-            filter_type = list(filter_type)
-            size = len(filter_type)
-
-            if size == 0:
-                win_count += 1
-                no_filter_ball[no] = answer
-                print("\t", no)
-            elif size == 1:
-                key = filter_type[0]
-                if key not in filter_dic_1:
-                    filter_dic_1[key] = 1
-                else:
-                    filter_dic_1[key] += 1
-
-                if printLog:
-                    print("\t", no, filter_type)
-            elif size == 2:
-                key = ','.join(filter_type)
-                if key not in filter_dic_2:
-                    filter_dic_2[key] = 1
-                else:
-                    filter_dic_2[key] += 1
-
-                if printLog:
-                    print("\t", no, filter_type)
-            else:
-                if printLog:
-                    print("\t", no, filter_type)
-
-                # 회차별 필터개수가 적은 것을 정렬하기 위함
-                if size not in filter_dic_len:
-                    filter_dic_len[size] = []
-                filter_dic_len[size].append(filter_type)
-
-            for f_t in filter_type:
-                if f_t not in filter_dic:
-                    filter_dic[f_t] = 1
-                else:
-                    filter_dic[f_t] += 1
-
-        print("\n\t[필터 개수가 적은 것부터 최적화를 위함]")
-        sorted_filter_dic_len = sorted(filter_dic_len.keys())
-        for filter_count in sorted_filter_dic_len:
-            for filter_type in filter_dic_len[filter_count]:
-                print("\t\t>{} > {}".format(filter_count, filter_type))
-
-        print("\n\t[걸러진 유일 필터]")
-        sorted_filter_dic_1 = sorted(filter_dic_1.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic_1)):
-            print("\t\t>", sorted_filter_dic_1[i][0], "->", sorted_filter_dic_1[i][1])
-
-        print("\n\t[2개 필터에 걸린 경우]")
-        sorted_filter_dic_2 = sorted(filter_dic_2.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic_2)):
-            print("\t\t>", sorted_filter_dic_2[i][0], "->", sorted_filter_dic_2[i][1])
-
-        print("\n\t[Filter 유형 별 걸린 개수]")
-        sorted_filter_dic = sorted(filter_dic.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic)):
-            print("\t\t>", sorted_filter_dic[i][0], "->", sorted_filter_dic[i][1])
-
-        print("\n\t# 필터에 걸리지 않고 당첨된 회차")
-        print("\tcount: {:,} / total: {:,} ({:.2})%".format(len(no_filter_ball), len(df_ball), 100 * len(no_filter_ball) / len(df_ball)))
-        for no in no_filter_ball:
-            print("\t\t>", no, no_filter_ball[no])
-        print("\tcount: {:,} / total: {:,} ({:.2})%".format(len(no_filter_ball), len(df_ball), 100 * len(no_filter_ball) / len(df_ball)))
-
-        return win_count
-
-    def find_final_candidates(self, no, df_ball, filter_ball=None):
-        final_candidates = []
-
-        generation_balls = list(range(1, 46))
-
-        nCr = list(itertools.combinations(generation_balls, 6))
-        for idx, ball in enumerate(nCr):
-
-            if idx % 1000000 == 0:
-                print("   - {} processed...".format(idx))
-
-            if filter_ball is not None and 0 < len(set(ball) & set(filter_ball)):
-                continue
-
-            filter_type = self.ballFilter.filter(ball=ball, no=no, until_end=False, df=df_ball)
-            filter_size = len(filter_type)
-
-            if filter_size:
-                continue
-
-            final_candidates.append(ball)
-
-        return final_candidates
-
-    def check_filter_method(self, df_ball, p_win_count, filter_ball=None):
-
-        win_count = 0
-        for i in range(len(df_ball)-1, 0, -1):
-
-            no = df_ball['no'].iloc[i]
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            if filter_ball is not None and len(set(answer) & set(filter_ball)):
-                continue
-
-            filter_type = self.ballFilter.extract_final_candidates(answer, no=no, until_end=True, df=df_ball)
-
-            if len(filter_type) == 0:
-                win_count += 1
-                print("\t\t>{}. {}".format(no, answer))
-
-        print("\n\t> {} / {} p_win_count, {} total".format( win_count, p_win_count, len(df_ball)-1) )
-
-        return
-
-    def validate(self, df_ball, nos=None):
-        win_history = {}
-
-        for no in nos:
-            print(no, "processing...")
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            generation_balls = list(range(1, 46))
-            nCr = list(itertools.combinations(generation_balls, 6))
-            for idx, ball in enumerate(nCr):
-                if idx % 1000000 == 0:
-                    print("   - {} processed...".format(idx))
-                ball = list(ball)
-                filter_type = self.ballFilter.extract_final_candidates(ball, no=no, until_end=True, df=df_ball)
-                if 0 == len(filter_type) and len(set(answer)&set(ball))==6:
-                    win_history[no] = answer
-                    print("win.. no: {}, answer: {}".format(no, str(answer)))
-                    break
-
-        return win_history
-
-
-if __name__ == '__main__':
-
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--resources", default="resources")
-    parser.add_argument(
-        "--ruleset",
-        default=None,
-        help="Ruleset JSON path (e.g. resources/rulesets/Coverage-First-S230a.json). Default: resources/rulesets/default.json if present.",
-    )
-    parser.add_argument("--start-no", type=int, default=1)
-    parser.add_argument("--end-no", type=int, default=800)
-    args = parser.parse_args()
-
-    resources_path = args.resources
-
-    # Use full history txt to support previous-draw/window features, but only score [start_no, end_no]
-    lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.txt')
-    df_ball = pd.read_csv(lottoHistoryFileName, header=None)
-    df_ball.columns = ['no', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'bn']
-
-    filter_ball=[]
-    filterTest = FilterTest(resources_path, ruleset_path=args.ruleset)
-
-    print("STEP #1. 필터 방법 추출")
-    start = time.time()
-    win_count = filterTest.find_filter_method(df_ball, start_no=args.start_no, end_no=args.end_no)
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    """
-    print("\n\n")
-    no = df_ball['no'].values[-1]
-    ball = df_ball[df_ball['no'] == no].values.tolist()[0]
-    answer = ball[1:7]
-
-    print("STEP #0. 최종 후보 선정")
-    start = time.time()
-    final_candidates = filterTest.find_final_candidates(no, df_ball, filter_ball=None)
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    print("   > size: {}".format(len(final_candidates)))
-    file_name = os.path.join(resources_path, 'final_candidates.biz_a1.txt')
-    with open(file_name, 'w+') as outFp:
-        for ball in final_candidates:
-            ball_str = [str(b) for b in answer]
-            outFp.write("{}\n".format(','.join(ball_str)))
-
-    print('{}회, 정답: {}\n'.format(no, str(answer)))
-    """
-
-    #print("\n\n")
-    #print("STEP #2. 당첨 회수 확인")
-    #filterTest.check_filter_method(df_ball, win_count)
-
-    # 오리지널 버전 (자질 파일에 고정): 당첨 22개

train_2.py

@@ -1,231 +0,0 @@
-import os
-import argparse
-import pandas as pd
-import itertools
-from filter_model_2 import BallFilter
-import time
-import datetime
-
-class FilterTest:
-
-    ballFilter = None
-
-    def __init__(self, resources_path, ruleset_path=None):
-        lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.json')
-        self.ballFilter = BallFilter(lottoHistoryFileName, ruleset_path=ruleset_path)
-
-        return
-
-    def find_filter_method(self, df_ball, start_no, end_no):
-        win_count = 0
-
-        no_filter_ball = {}
-
-        printLog = True
-        filter_dic = {}
-        filter_dic_len = {}
-        filter_dic_1 = {}
-        filter_dic_2 = {}
-        for i in range(len(df_ball)-1, 19, -1):
-            no = df_ball['no'].iloc[i]
-            if no < start_no or end_no < no:
-                continue
-
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            filter_type = self.ballFilter.filter(ball=answer, no=no, until_end=True, df=df_ball)
-            filter_type = list(filter_type)
-            size = len(filter_type)
-
-            if size == 0:
-                win_count += 1
-                no_filter_ball[no] = answer
-                print("\t", no)
-            elif size == 1:
-                key = filter_type[0]
-                if key not in filter_dic_1:
-                    filter_dic_1[key] = 1
-                else:
-                    filter_dic_1[key] += 1
-
-                if printLog:
-                    print("\t", no, filter_type)
-            elif size == 2:
-                key = ','.join(filter_type)
-                if key not in filter_dic_2:
-                    filter_dic_2[key] = 1
-                else:
-                    filter_dic_2[key] += 1
-
-                if printLog:
-                    print("\t", no, filter_type)
-            else:
-                if printLog:
-                    print("\t", no, filter_type)
-
-                # 회차별 필터개수가 적은 것을 정렬하기 위함
-                if size not in filter_dic_len:
-                    filter_dic_len[size] = []
-                filter_dic_len[size].append(filter_type)
-
-            for f_t in filter_type:
-                if f_t not in filter_dic:
-                    filter_dic[f_t] = 1
-                else:
-                    filter_dic[f_t] += 1
-
-        print("\n\t[필터 개수가 적은 것부터 최적화를 위함]")
-        sorted_filter_dic_len = sorted(filter_dic_len.keys())
-        for filter_count in sorted_filter_dic_len:
-            for filter_type in filter_dic_len[filter_count]:
-                print("\t\t>{} > {}".format(filter_count, filter_type))
-
-        print("\n\t[걸러진 유일 필터]")
-        sorted_filter_dic_1 = sorted(filter_dic_1.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic_1)):
-            print("\t\t>", sorted_filter_dic_1[i][0], "->", sorted_filter_dic_1[i][1])
-
-        print("\n\t[2개 필터에 걸린 경우]")
-        sorted_filter_dic_2 = sorted(filter_dic_2.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic_2)):
-            print("\t\t>", sorted_filter_dic_2[i][0], "->", sorted_filter_dic_2[i][1])
-
-        print("\n\t[Filter 유형 별 걸린 개수]")
-        sorted_filter_dic = sorted(filter_dic.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic)):
-            print("\t\t>", sorted_filter_dic[i][0], "->", sorted_filter_dic[i][1])
-
-        print("\n\t# 필터에 걸리지 않고 당첨된 회차")
-        print("\tcount: {:,} / total: {:,} ({:.2})%".format(len(no_filter_ball), len(df_ball), 100 * len(no_filter_ball) / len(df_ball)))
-        for no in no_filter_ball:
-            print("\t\t>", no, no_filter_ball[no])
-        print("\tcount: {:,} / total: {:,} ({:.2})%".format(len(no_filter_ball), len(df_ball), 100 * len(no_filter_ball) / len(df_ball)))
-
-        return win_count
-
-    def find_final_candidates(self, no, df_ball, filter_ball=None):
-        final_candidates = []
-
-        generation_balls = list(range(1, 46))
-
-        nCr = list(itertools.combinations(generation_balls, 6))
-        for idx, ball in enumerate(nCr):
-
-            if idx % 1000000 == 0:
-                print("   - {} processed...".format(idx))
-
-            if filter_ball is not None and 0 < len(set(ball) & set(filter_ball)):
-                continue
-
-            filter_type = self.ballFilter.filter(ball=ball, no=no, until_end=False, df=df_ball)
-            filter_size = len(filter_type)
-
-            if filter_size:
-                continue
-
-            final_candidates.append(ball)
-
-        return final_candidates
-
-    def check_filter_method(self, df_ball, p_win_count, filter_ball=None):
-
-        win_count = 0
-        for i in range(len(df_ball)-1, 0, -1):
-
-            no = df_ball['no'].iloc[i]
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            if filter_ball is not None and len(set(answer) & set(filter_ball)):
-                continue
-
-            filter_type = self.ballFilter.extract_final_candidates(answer, no=no, until_end=True, df=df_ball)
-
-            if len(filter_type) == 0:
-                win_count += 1
-                print("\t\t>{}. {}".format(no, answer))
-
-        print("\n\t> {} / {} p_win_count, {} total".format( win_count, p_win_count, len(df_ball)-1) )
-
-        return
-
-    def validate(self, df_ball, nos=None):
-        win_history = {}
-
-        for no in nos:
-            print(no, "processing...")
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            generation_balls = list(range(1, 46))
-            nCr = list(itertools.combinations(generation_balls, 6))
-            for idx, ball in enumerate(nCr):
-                if idx % 1000000 == 0:
-                    print("   - {} processed...".format(idx))
-                ball = list(ball)
-                filter_type = self.ballFilter.extract_final_candidates(ball, no=no, until_end=True, df=df_ball)
-                if 0 == len(filter_type) and len(set(answer)&set(ball))==6:
-                    win_history[no] = answer
-                    print("win.. no: {}, answer: {}".format(no, str(answer)))
-                    break
-
-        return win_history
-
-
-if __name__ == '__main__':
-
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--resources", default="resources")
-    parser.add_argument(
-        "--ruleset",
-        default=None,
-        help="Ruleset JSON path (e.g. resources/rulesets/Coverage-First-S230a.json). Default: resources/rulesets/default.json if present.",
-    )
-    parser.add_argument("--start-no", type=int, default=1)
-    parser.add_argument("--end-no", type=int, default=800)
-    args = parser.parse_args()
-
-    resources_path = args.resources
-
-    # Use full history txt to support previous-draw/window features, but only score [start_no, end_no]
-    lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.txt')
-    df_ball = pd.read_csv(lottoHistoryFileName, header=None)
-    df_ball.columns = ['no', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'bn']
-
-    filter_ball=[]
-    filterTest = FilterTest(resources_path, ruleset_path=args.ruleset)
-
-    print("STEP #1. 필터 방법 추출")
-    start = time.time()
-    win_count = filterTest.find_filter_method(df_ball, start_no=args.start_no, end_no=args.end_no)
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    """
-    print("\n\n")
-    no = df_ball['no'].values[-1]
-    ball = df_ball[df_ball['no'] == no].values.tolist()[0]
-    answer = ball[1:7]
-
-    print("STEP #0. 최종 후보 선정")
-    start = time.time()
-    final_candidates = filterTest.find_final_candidates(no, df_ball, filter_ball=None)
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    print("   > size: {}".format(len(final_candidates)))
-    file_name = os.path.join(resources_path, 'final_candidates.biz_a1.txt')
-    with open(file_name, 'w+') as outFp:
-        for ball in final_candidates:
-            ball_str = [str(b) for b in answer]
-            outFp.write("{}\n".format(','.join(ball_str)))
-
-    print('{}회, 정답: {}\n'.format(no, str(answer)))
-    """
-
-    #print("\n\n")
-    #print("STEP #2. 당첨 회수 확인")
-    #filterTest.check_filter_method(df_ball, win_count)
-
-    # 오리지널 버전 (자질 파일에 고정): 당첨 22개

train_3.py

@@ -1,231 +0,0 @@
-import os
-import argparse
-import pandas as pd
-import itertools
-from filter_model_3 import BallFilter
-import time
-import datetime
-
-class FilterTest:
-
-    ballFilter = None
-
-    def __init__(self, resources_path, ruleset_path=None):
-        lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.json')
-        self.ballFilter = BallFilter(lottoHistoryFileName, ruleset_path=ruleset_path)
-
-        return
-
-    def find_filter_method(self, df_ball, start_no, end_no):
-        win_count = 0
-
-        no_filter_ball = {}
-
-        printLog = True
-        filter_dic = {}
-        filter_dic_len = {}
-        filter_dic_1 = {}
-        filter_dic_2 = {}
-        for i in range(len(df_ball)-1, 19, -1):
-            no = df_ball['no'].iloc[i]
-            if no < start_no or end_no < no:
-                continue
-
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            filter_type = self.ballFilter.filter(ball=answer, no=no, until_end=True, df=df_ball)
-            filter_type = list(filter_type)
-            size = len(filter_type)
-
-            if size == 0:
-                win_count += 1
-                no_filter_ball[no] = answer
-                print("\t", no)
-            elif size == 1:
-                key = filter_type[0]
-                if key not in filter_dic_1:
-                    filter_dic_1[key] = 1
-                else:
-                    filter_dic_1[key] += 1
-
-                if printLog:
-                    print("\t", no, filter_type)
-            elif size == 2:
-                key = ','.join(filter_type)
-                if key not in filter_dic_2:
-                    filter_dic_2[key] = 1
-                else:
-                    filter_dic_2[key] += 1
-
-                if printLog:
-                    print("\t", no, filter_type)
-            else:
-                if printLog:
-                    print("\t", no, filter_type)
-
-                # 회차별 필터개수가 적은 것을 정렬하기 위함
-                if size not in filter_dic_len:
-                    filter_dic_len[size] = []
-                filter_dic_len[size].append(filter_type)
-
-            for f_t in filter_type:
-                if f_t not in filter_dic:
-                    filter_dic[f_t] = 1
-                else:
-                    filter_dic[f_t] += 1
-
-        print("\n\t[필터 개수가 적은 것부터 최적화를 위함]")
-        sorted_filter_dic_len = sorted(filter_dic_len.keys())
-        for filter_count in sorted_filter_dic_len:
-            for filter_type in filter_dic_len[filter_count]:
-                print("\t\t>{} > {}".format(filter_count, filter_type))
-
-        print("\n\t[걸러진 유일 필터]")
-        sorted_filter_dic_1 = sorted(filter_dic_1.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic_1)):
-            print("\t\t>", sorted_filter_dic_1[i][0], "->", sorted_filter_dic_1[i][1])
-
-        print("\n\t[2개 필터에 걸린 경우]")
-        sorted_filter_dic_2 = sorted(filter_dic_2.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic_2)):
-            print("\t\t>", sorted_filter_dic_2[i][0], "->", sorted_filter_dic_2[i][1])
-
-        print("\n\t[Filter 유형 별 걸린 개수]")
-        sorted_filter_dic = sorted(filter_dic.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic)):
-            print("\t\t>", sorted_filter_dic[i][0], "->", sorted_filter_dic[i][1])
-
-        print("\n\t# 필터에 걸리지 않고 당첨된 회차")
-        print("\tcount: {:,} / total: {:,} ({:.2})%".format(len(no_filter_ball), len(df_ball), 100 * len(no_filter_ball) / len(df_ball)))
-        for no in no_filter_ball:
-            print("\t\t>", no, no_filter_ball[no])
-        print("\tcount: {:,} / total: {:,} ({:.2})%".format(len(no_filter_ball), len(df_ball), 100 * len(no_filter_ball) / len(df_ball)))
-
-        return win_count
-
-    def find_final_candidates(self, no, df_ball, filter_ball=None):
-        final_candidates = []
-
-        generation_balls = list(range(1, 46))
-
-        nCr = list(itertools.combinations(generation_balls, 6))
-        for idx, ball in enumerate(nCr):
-
-            if idx % 1000000 == 0:
-                print("   - {} processed...".format(idx))
-
-            if filter_ball is not None and 0 < len(set(ball) & set(filter_ball)):
-                continue
-
-            filter_type = self.ballFilter.filter(ball=ball, no=no, until_end=False, df=df_ball)
-            filter_size = len(filter_type)
-
-            if filter_size:
-                continue
-
-            final_candidates.append(ball)
-
-        return final_candidates
-
-    def check_filter_method(self, df_ball, p_win_count, filter_ball=None):
-
-        win_count = 0
-        for i in range(len(df_ball)-1, 0, -1):
-
-            no = df_ball['no'].iloc[i]
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            if filter_ball is not None and len(set(answer) & set(filter_ball)):
-                continue
-
-            filter_type = self.ballFilter.extract_final_candidates(answer, no=no, until_end=True, df=df_ball)
-
-            if len(filter_type) == 0:
-                win_count += 1
-                print("\t\t>{}. {}".format(no, answer))
-
-        print("\n\t> {} / {} p_win_count, {} total".format( win_count, p_win_count, len(df_ball)-1) )
-
-        return
-
-    def validate(self, df_ball, nos=None):
-        win_history = {}
-
-        for no in nos:
-            print(no, "processing...")
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            generation_balls = list(range(1, 46))
-            nCr = list(itertools.combinations(generation_balls, 6))
-            for idx, ball in enumerate(nCr):
-                if idx % 1000000 == 0:
-                    print("   - {} processed...".format(idx))
-                ball = list(ball)
-                filter_type = self.ballFilter.extract_final_candidates(ball, no=no, until_end=True, df=df_ball)
-                if 0 == len(filter_type) and len(set(answer)&set(ball))==6:
-                    win_history[no] = answer
-                    print("win.. no: {}, answer: {}".format(no, str(answer)))
-                    break
-
-        return win_history
-
-
-if __name__ == '__main__':
-
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--resources", default="resources")
-    parser.add_argument(
-        "--ruleset",
-        default=None,
-        help="Ruleset JSON path (e.g. resources/rulesets/Coverage-First-S230a.json). Default: resources/rulesets/default.json if present.",
-    )
-    parser.add_argument("--start-no", type=int, default=1)
-    parser.add_argument("--end-no", type=int, default=800)
-    args = parser.parse_args()
-
-    resources_path = args.resources
-
-    # Use full history txt to support previous-draw/window features, but only score [start_no, end_no]
-    lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.txt')
-    df_ball = pd.read_csv(lottoHistoryFileName, header=None)
-    df_ball.columns = ['no', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'bn']
-
-    filter_ball=[]
-    filterTest = FilterTest(resources_path, ruleset_path=args.ruleset)
-
-    print("STEP #1. 필터 방법 추출")
-    start = time.time()
-    win_count = filterTest.find_filter_method(df_ball, start_no=args.start_no, end_no=args.end_no)
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    """
-    print("\n\n")
-    no = df_ball['no'].values[-1]
-    ball = df_ball[df_ball['no'] == no].values.tolist()[0]
-    answer = ball[1:7]
-
-    print("STEP #0. 최종 후보 선정")
-    start = time.time()
-    final_candidates = filterTest.find_final_candidates(no, df_ball, filter_ball=None)
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    print("   > size: {}".format(len(final_candidates)))
-    file_name = os.path.join(resources_path, 'final_candidates.biz_a1.txt')
-    with open(file_name, 'w+') as outFp:
-        for ball in final_candidates:
-            ball_str = [str(b) for b in answer]
-            outFp.write("{}\n".format(','.join(ball_str)))
-
-    print('{}회, 정답: {}\n'.format(no, str(answer)))
-    """
-
-    #print("\n\n")
-    #print("STEP #2. 당첨 회수 확인")
-    #filterTest.check_filter_method(df_ball, win_count)
-
-    # 오리지널 버전 (자질 파일에 고정): 당첨 22개

valid_1.py

@@ -1,234 +0,0 @@
-import os
-import argparse
-import pandas as pd
-import itertools
-from filter_model_1 import BallFilter
-import time
-import datetime
-
-class FilterTest:
-
-    ballFilter = None
-
-    def __init__(self, resources_path, ruleset_path=None, history_json="lotto_history.json"):
-        # validation should use full history for previous-draw/window features
-        lottoHistoryFileName = os.path.join(resources_path, history_json)
-        self.ballFilter = BallFilter(lottoHistoryFileName, ruleset_path=ruleset_path)
-
-        return
-
-    def find_filter_method(self, df_ball, start_no, end_no):
-        win_count = 0
-
-        no_filter_ball = {}
-
-        printLog = True
-        filter_dic = {}
-        filter_dic_len = {}
-        filter_dic_1 = {}
-        filter_dic_2 = {}
-        # evaluate only requested range, but allow df_ball to contain full history
-        for i in range(len(df_ball) - 1, -1, -1):
-            no = int(df_ball['no'].iloc[i])
-            if no < start_no or end_no < no:
-                continue
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            filter_type = self.ballFilter.filter(ball=answer, no=no, until_end=True, df=df_ball)
-            filter_type = list(filter_type)
-            size = len(filter_type)
-
-            if size == 0:
-                win_count += 1
-                no_filter_ball[no] = answer
-                print("\t", no)
-            elif size == 1:
-                key = filter_type[0]
-                if key not in filter_dic_1:
-                    filter_dic_1[key] = 1
-                else:
-                    filter_dic_1[key] += 1
-
-                if printLog:
-                    print("\t", no, filter_type)
-            elif size == 2:
-                key = ','.join(filter_type)
-                if key not in filter_dic_2:
-                    filter_dic_2[key] = 1
-                else:
-                    filter_dic_2[key] += 1
-
-                if printLog:
-                    print("\t", no, filter_type)
-            else:
-                if printLog:
-                    print("\t", no, filter_type)
-
-                # 회차별 필터개수가 적은 것을 정렬하기 위함
-                if size not in filter_dic_len:
-                    filter_dic_len[size] = []
-                filter_dic_len[size].append(filter_type)
-
-            for f_t in filter_type:
-                if f_t not in filter_dic:
-                    filter_dic[f_t] = 1
-                else:
-                    filter_dic[f_t] += 1
-
-        print("\n\t[필터 개수가 적은 것부터 최적화를 위함]")
-        sorted_filter_dic_len = sorted(filter_dic_len.keys())
-        for filter_count in sorted_filter_dic_len:
-            for filter_type in filter_dic_len[filter_count]:
-                print("\t\t>{} > {}".format(filter_count, filter_type))
-
-        print("\n\t[걸러진 유일 필터]")
-        sorted_filter_dic_1 = sorted(filter_dic_1.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic_1)):
-            print("\t\t>", sorted_filter_dic_1[i][0], "->", sorted_filter_dic_1[i][1])
-
-        print("\n\t[2개 필터에 걸린 경우]")
-        sorted_filter_dic_2 = sorted(filter_dic_2.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic_2)):
-            print("\t\t>", sorted_filter_dic_2[i][0], "->", sorted_filter_dic_2[i][1])
-
-        print("\n\t[Filter 유형 별 걸린 개수]")
-        sorted_filter_dic = sorted(filter_dic.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic)):
-            print("\t\t>", sorted_filter_dic[i][0], "->", sorted_filter_dic[i][1])
-
-        print("\n\t# 필터에 걸리지 않고 당첨된 회차")
-        total = max(0, end_no - start_no + 1)
-        rate = (100 * len(no_filter_ball) / total) if total else 0.0
-        print("\tcount: {:,} / total: {:,} ({:.2})%".format(len(no_filter_ball), total, rate))
-        for no in no_filter_ball:
-            print("\t\t>", no, no_filter_ball[no])
-        print("\tcount: {:,} / total: {:,} ({:.2})%".format(len(no_filter_ball), total, rate))
-
-        return win_count
-
-    def find_final_candidates(self, no, df_ball, filter_ball=None):
-        final_candidates = []
-
-        generation_balls = list(range(1, 46))
-
-        nCr = list(itertools.combinations(generation_balls, 6))
-        for idx, ball in enumerate(nCr):
-
-            if idx % 1000000 == 0:
-                print("   - {} processed...".format(idx))
-
-            if filter_ball is not None and 0 < len(set(ball) & set(filter_ball)):
-                continue
-
-            filter_type = self.ballFilter.filter(ball=ball, no=no, until_end=False, df=df_ball)
-            filter_size = len(filter_type)
-
-            if filter_size:
-                continue
-
-            final_candidates.append(ball)
-
-        return final_candidates
-
-    def check_filter_method(self, df_ball, p_win_count, filter_ball=None):
-
-        win_count = 0
-        for i in range(len(df_ball)-1, 0, -1):
-
-            no = df_ball['no'].iloc[i]
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            if filter_ball is not None and len(set(answer) & set(filter_ball)):
-                continue
-
-            filter_type = self.ballFilter.extract_final_candidates(answer, no=no, until_end=True, df=df_ball)
-
-            if len(filter_type) == 0:
-                win_count += 1
-                print("\t\t>{}. {}".format(no, answer))
-
-        print("\n\t> {} / {} p_win_count, {} total".format( win_count, p_win_count, len(df_ball)-1) )
-
-        return
-
-    def validate(self, df_ball, nos=None):
-        win_history = {}
-
-        for no in nos:
-            print(no, "processing...")
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            generation_balls = list(range(1, 46))
-            nCr = list(itertools.combinations(generation_balls, 6))
-            for idx, ball in enumerate(nCr):
-                if idx % 1000000 == 0:
-                    print("   - {} processed...".format(idx))
-                ball = list(ball)
-                filter_type = self.ballFilter.extract_final_candidates(ball, no=no, until_end=True, df=df_ball)
-                if 0 == len(filter_type) and len(set(answer)&set(ball))==6:
-                    win_history[no] = answer
-                    print("win.. no: {}, answer: {}".format(no, str(answer)))
-                    break
-
-        return win_history
-
-
-if __name__ == '__main__':
-
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--resources", default="resources")
-    parser.add_argument(
-        "--ruleset",
-        default=None,
-        help="Ruleset JSON path (e.g. resources/rulesets/Coverage-First-S230a.json). Default: resources/rulesets/default.json if present.",
-    )
-    parser.add_argument("--start-no", type=int, default=801)
-    parser.add_argument("--end-no", type=int, default=1000)
-    args = parser.parse_args()
-
-    resources_path = args.resources
-
-    # Use full history txt to support previous-draw/window features, but only score [start_no, end_no]
-    lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.txt')
-    df_ball = pd.read_csv(lottoHistoryFileName, header=None)
-    df_ball.columns = ['no', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'bn']
-
-    filter_ball=[]
-    filterTest = FilterTest(resources_path, ruleset_path=args.ruleset, history_json='lotto_history.json')
-
-    print("STEP #1. 필터 방법 추출")
-    start = time.time()
-    win_count = filterTest.find_filter_method(df_ball, start_no=args.start_no, end_no=args.end_no)
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    """
-    print("\n\n")
-    no = df_ball['no'].values[-1]
-    ball = df_ball[df_ball['no'] == no].values.tolist()[0]
-    answer = ball[1:7]
-
-    print("STEP #0. 최종 후보 선정")
-    start = time.time()
-    final_candidates = filterTest.find_final_candidates(no, df_ball, filter_ball=None)
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    print("   > size: {}".format(len(final_candidates)))
-    file_name = os.path.join(resources_path, 'final_candidates.biz_a1.txt')
-    with open(file_name, 'w+') as outFp:
-        for ball in final_candidates:
-            ball_str = [str(b) for b in answer]
-            outFp.write("{}\n".format(','.join(ball_str)))
-
-    print('{}회, 정답: {}\n'.format(no, str(answer)))
-    """
-
-    #print("\n\n")
-    #print("STEP #2. 당첨 회수 확인")
-    #filterTest.check_filter_method(df_ball, win_count)
-
-    # 오리지널 버전 (자질 파일에 고정): 당첨 22개

valid_2.py

@@ -1,234 +0,0 @@
-import os
-import argparse
-import pandas as pd
-import itertools
-from filter_model_2 import BallFilter
-import time
-import datetime
-
-class FilterTest:
-
-    ballFilter = None
-
-    def __init__(self, resources_path, ruleset_path=None, history_json="lotto_history.json"):
-        # validation should use full history for previous-draw/window features
-        lottoHistoryFileName = os.path.join(resources_path, history_json)
-        self.ballFilter = BallFilter(lottoHistoryFileName, ruleset_path=ruleset_path)
-
-        return
-
-    def find_filter_method(self, df_ball, start_no, end_no):
-        win_count = 0
-
-        no_filter_ball = {}
-
-        printLog = True
-        filter_dic = {}
-        filter_dic_len = {}
-        filter_dic_1 = {}
-        filter_dic_2 = {}
-        # evaluate only requested range, but allow df_ball to contain full history
-        for i in range(len(df_ball) - 1, -1, -1):
-            no = int(df_ball['no'].iloc[i])
-            if no < start_no or end_no < no:
-                continue
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            filter_type = self.ballFilter.filter(ball=answer, no=no, until_end=True, df=df_ball)
-            filter_type = list(filter_type)
-            size = len(filter_type)
-
-            if size == 0:
-                win_count += 1
-                no_filter_ball[no] = answer
-                print("\t", no)
-            elif size == 1:
-                key = filter_type[0]
-                if key not in filter_dic_1:
-                    filter_dic_1[key] = 1
-                else:
-                    filter_dic_1[key] += 1
-
-                if printLog:
-                    print("\t", no, filter_type)
-            elif size == 2:
-                key = ','.join(filter_type)
-                if key not in filter_dic_2:
-                    filter_dic_2[key] = 1
-                else:
-                    filter_dic_2[key] += 1
-
-                if printLog:
-                    print("\t", no, filter_type)
-            else:
-                if printLog:
-                    print("\t", no, filter_type)
-
-                # 회차별 필터개수가 적은 것을 정렬하기 위함
-                if size not in filter_dic_len:
-                    filter_dic_len[size] = []
-                filter_dic_len[size].append(filter_type)
-
-            for f_t in filter_type:
-                if f_t not in filter_dic:
-                    filter_dic[f_t] = 1
-                else:
-                    filter_dic[f_t] += 1
-
-        print("\n\t[필터 개수가 적은 것부터 최적화를 위함]")
-        sorted_filter_dic_len = sorted(filter_dic_len.keys())
-        for filter_count in sorted_filter_dic_len:
-            for filter_type in filter_dic_len[filter_count]:
-                print("\t\t>{} > {}".format(filter_count, filter_type))
-
-        print("\n\t[걸러진 유일 필터]")
-        sorted_filter_dic_1 = sorted(filter_dic_1.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic_1)):
-            print("\t\t>", sorted_filter_dic_1[i][0], "->", sorted_filter_dic_1[i][1])
-
-        print("\n\t[2개 필터에 걸린 경우]")
-        sorted_filter_dic_2 = sorted(filter_dic_2.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic_2)):
-            print("\t\t>", sorted_filter_dic_2[i][0], "->", sorted_filter_dic_2[i][1])
-
-        print("\n\t[Filter 유형 별 걸린 개수]")
-        sorted_filter_dic = sorted(filter_dic.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic)):
-            print("\t\t>", sorted_filter_dic[i][0], "->", sorted_filter_dic[i][1])
-
-        print("\n\t# 필터에 걸리지 않고 당첨된 회차")
-        total = max(0, end_no - start_no + 1)
-        rate = (100 * len(no_filter_ball) / total) if total else 0.0
-        print("\tcount: {:,} / total: {:,} ({:.2})%".format(len(no_filter_ball), total, rate))
-        for no in no_filter_ball:
-            print("\t\t>", no, no_filter_ball[no])
-        print("\tcount: {:,} / total: {:,} ({:.2})%".format(len(no_filter_ball), total, rate))
-
-        return win_count
-
-    def find_final_candidates(self, no, df_ball, filter_ball=None):
-        final_candidates = []
-
-        generation_balls = list(range(1, 46))
-
-        nCr = list(itertools.combinations(generation_balls, 6))
-        for idx, ball in enumerate(nCr):
-
-            if idx % 1000000 == 0:
-                print("   - {} processed...".format(idx))
-
-            if filter_ball is not None and 0 < len(set(ball) & set(filter_ball)):
-                continue
-
-            filter_type = self.ballFilter.filter(ball=ball, no=no, until_end=False, df=df_ball)
-            filter_size = len(filter_type)
-
-            if filter_size:
-                continue
-
-            final_candidates.append(ball)
-
-        return final_candidates
-
-    def check_filter_method(self, df_ball, p_win_count, filter_ball=None):
-
-        win_count = 0
-        for i in range(len(df_ball)-1, 0, -1):
-
-            no = df_ball['no'].iloc[i]
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            if filter_ball is not None and len(set(answer) & set(filter_ball)):
-                continue
-
-            filter_type = self.ballFilter.extract_final_candidates(answer, no=no, until_end=True, df=df_ball)
-
-            if len(filter_type) == 0:
-                win_count += 1
-                print("\t\t>{}. {}".format(no, answer))
-
-        print("\n\t> {} / {} p_win_count, {} total".format( win_count, p_win_count, len(df_ball)-1) )
-
-        return
-
-    def validate(self, df_ball, nos=None):
-        win_history = {}
-
-        for no in nos:
-            print(no, "processing...")
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            generation_balls = list(range(1, 46))
-            nCr = list(itertools.combinations(generation_balls, 6))
-            for idx, ball in enumerate(nCr):
-                if idx % 1000000 == 0:
-                    print("   - {} processed...".format(idx))
-                ball = list(ball)
-                filter_type = self.ballFilter.extract_final_candidates(ball, no=no, until_end=True, df=df_ball)
-                if 0 == len(filter_type) and len(set(answer)&set(ball))==6:
-                    win_history[no] = answer
-                    print("win.. no: {}, answer: {}".format(no, str(answer)))
-                    break
-
-        return win_history
-
-
-if __name__ == '__main__':
-
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--resources", default="resources")
-    parser.add_argument(
-        "--ruleset",
-        default=None,
-        help="Ruleset JSON path (e.g. resources/rulesets/Coverage-First-S230a.json). Default: resources/rulesets/default.json if present.",
-    )
-    parser.add_argument("--start-no", type=int, default=801)
-    parser.add_argument("--end-no", type=int, default=1000)
-    args = parser.parse_args()
-
-    resources_path = args.resources
-
-    # Use full history txt to support previous-draw/window features, but only score [start_no, end_no]
-    lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.txt')
-    df_ball = pd.read_csv(lottoHistoryFileName, header=None)
-    df_ball.columns = ['no', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'bn']
-
-    filter_ball=[]
-    filterTest = FilterTest(resources_path, ruleset_path=args.ruleset, history_json='lotto_history.json')
-
-    print("STEP #1. 필터 방법 추출")
-    start = time.time()
-    win_count = filterTest.find_filter_method(df_ball, start_no=args.start_no, end_no=args.end_no)
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    """
-    print("\n\n")
-    no = df_ball['no'].values[-1]
-    ball = df_ball[df_ball['no'] == no].values.tolist()[0]
-    answer = ball[1:7]
-
-    print("STEP #0. 최종 후보 선정")
-    start = time.time()
-    final_candidates = filterTest.find_final_candidates(no, df_ball, filter_ball=None)
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    print("   > size: {}".format(len(final_candidates)))
-    file_name = os.path.join(resources_path, 'final_candidates.biz_a1.txt')
-    with open(file_name, 'w+') as outFp:
-        for ball in final_candidates:
-            ball_str = [str(b) for b in answer]
-            outFp.write("{}\n".format(','.join(ball_str)))
-
-    print('{}회, 정답: {}\n'.format(no, str(answer)))
-    """
-
-    #print("\n\n")
-    #print("STEP #2. 당첨 회수 확인")
-    #filterTest.check_filter_method(df_ball, win_count)
-
-    # 오리지널 버전 (자질 파일에 고정): 당첨 22개

valid_3.py

@@ -1,234 +0,0 @@
-import os
-import argparse
-import pandas as pd
-import itertools
-from filter_model_3 import BallFilter
-import time
-import datetime
-
-class FilterTest:
-
-    ballFilter = None
-
-    def __init__(self, resources_path, ruleset_path=None, history_json="lotto_history.json"):
-        # validation should use full history for previous-draw/window features
-        lottoHistoryFileName = os.path.join(resources_path, history_json)
-        self.ballFilter = BallFilter(lottoHistoryFileName, ruleset_path=ruleset_path)
-
-        return
-
-    def find_filter_method(self, df_ball, start_no, end_no):
-        win_count = 0
-
-        no_filter_ball = {}
-
-        printLog = True
-        filter_dic = {}
-        filter_dic_len = {}
-        filter_dic_1 = {}
-        filter_dic_2 = {}
-        # evaluate only requested range, but allow df_ball to contain full history
-        for i in range(len(df_ball) - 1, -1, -1):
-            no = int(df_ball['no'].iloc[i])
-            if no < start_no or end_no < no:
-                continue
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            filter_type = self.ballFilter.filter(ball=answer, no=no, until_end=True, df=df_ball)
-            filter_type = list(filter_type)
-            size = len(filter_type)
-
-            if size == 0:
-                win_count += 1
-                no_filter_ball[no] = answer
-                print("\t", no)
-            elif size == 1:
-                key = filter_type[0]
-                if key not in filter_dic_1:
-                    filter_dic_1[key] = 1
-                else:
-                    filter_dic_1[key] += 1
-
-                if printLog:
-                    print("\t", no, filter_type)
-            elif size == 2:
-                key = ','.join(filter_type)
-                if key not in filter_dic_2:
-                    filter_dic_2[key] = 1
-                else:
-                    filter_dic_2[key] += 1
-
-                if printLog:
-                    print("\t", no, filter_type)
-            else:
-                if printLog:
-                    print("\t", no, filter_type)
-
-                # 회차별 필터개수가 적은 것을 정렬하기 위함
-                if size not in filter_dic_len:
-                    filter_dic_len[size] = []
-                filter_dic_len[size].append(filter_type)
-
-            for f_t in filter_type:
-                if f_t not in filter_dic:
-                    filter_dic[f_t] = 1
-                else:
-                    filter_dic[f_t] += 1
-
-        print("\n\t[필터 개수가 적은 것부터 최적화를 위함]")
-        sorted_filter_dic_len = sorted(filter_dic_len.keys())
-        for filter_count in sorted_filter_dic_len:
-            for filter_type in filter_dic_len[filter_count]:
-                print("\t\t>{} > {}".format(filter_count, filter_type))
-
-        print("\n\t[걸러진 유일 필터]")
-        sorted_filter_dic_1 = sorted(filter_dic_1.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic_1)):
-            print("\t\t>", sorted_filter_dic_1[i][0], "->", sorted_filter_dic_1[i][1])
-
-        print("\n\t[2개 필터에 걸린 경우]")
-        sorted_filter_dic_2 = sorted(filter_dic_2.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic_2)):
-            print("\t\t>", sorted_filter_dic_2[i][0], "->", sorted_filter_dic_2[i][1])
-
-        print("\n\t[Filter 유형 별 걸린 개수]")
-        sorted_filter_dic = sorted(filter_dic.items(), key=lambda x: x[1], reverse=True)
-        for i in range(len(sorted_filter_dic)):
-            print("\t\t>", sorted_filter_dic[i][0], "->", sorted_filter_dic[i][1])
-
-        print("\n\t# 필터에 걸리지 않고 당첨된 회차")
-        total = max(0, end_no - start_no + 1)
-        rate = (100 * len(no_filter_ball) / total) if total else 0.0
-        print("\tcount: {:,} / total: {:,} ({:.2})%".format(len(no_filter_ball), total, rate))
-        for no in no_filter_ball:
-            print("\t\t>", no, no_filter_ball[no])
-        print("\tcount: {:,} / total: {:,} ({:.2})%".format(len(no_filter_ball), total, rate))
-
-        return win_count
-
-    def find_final_candidates(self, no, df_ball, filter_ball=None):
-        final_candidates = []
-
-        generation_balls = list(range(1, 46))
-
-        nCr = list(itertools.combinations(generation_balls, 6))
-        for idx, ball in enumerate(nCr):
-
-            if idx % 1000000 == 0:
-                print("   - {} processed...".format(idx))
-
-            if filter_ball is not None and 0 < len(set(ball) & set(filter_ball)):
-                continue
-
-            filter_type = self.ballFilter.filter(ball=ball, no=no, until_end=False, df=df_ball)
-            filter_size = len(filter_type)
-
-            if filter_size:
-                continue
-
-            final_candidates.append(ball)
-
-        return final_candidates
-
-    def check_filter_method(self, df_ball, p_win_count, filter_ball=None):
-
-        win_count = 0
-        for i in range(len(df_ball)-1, 0, -1):
-
-            no = df_ball['no'].iloc[i]
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            if filter_ball is not None and len(set(answer) & set(filter_ball)):
-                continue
-
-            filter_type = self.ballFilter.extract_final_candidates(answer, no=no, until_end=True, df=df_ball)
-
-            if len(filter_type) == 0:
-                win_count += 1
-                print("\t\t>{}. {}".format(no, answer))
-
-        print("\n\t> {} / {} p_win_count, {} total".format( win_count, p_win_count, len(df_ball)-1) )
-
-        return
-
-    def validate(self, df_ball, nos=None):
-        win_history = {}
-
-        for no in nos:
-            print(no, "processing...")
-            answer = df_ball[df_ball['no'] == no].values.tolist()[0]
-            answer = answer[1:7]
-
-            generation_balls = list(range(1, 46))
-            nCr = list(itertools.combinations(generation_balls, 6))
-            for idx, ball in enumerate(nCr):
-                if idx % 1000000 == 0:
-                    print("   - {} processed...".format(idx))
-                ball = list(ball)
-                filter_type = self.ballFilter.extract_final_candidates(ball, no=no, until_end=True, df=df_ball)
-                if 0 == len(filter_type) and len(set(answer)&set(ball))==6:
-                    win_history[no] = answer
-                    print("win.. no: {}, answer: {}".format(no, str(answer)))
-                    break
-
-        return win_history
-
-
-if __name__ == '__main__':
-
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--resources", default="resources")
-    parser.add_argument(
-        "--ruleset",
-        default=None,
-        help="Ruleset JSON path (e.g. resources/rulesets/Coverage-First-S230a.json). Default: resources/rulesets/default.json if present.",
-    )
-    parser.add_argument("--start-no", type=int, default=801)
-    parser.add_argument("--end-no", type=int, default=1000)
-    args = parser.parse_args()
-
-    resources_path = args.resources
-
-    # Use full history txt to support previous-draw/window features, but only score [start_no, end_no]
-    lottoHistoryFileName = os.path.join(resources_path, 'lotto_history.txt')
-    df_ball = pd.read_csv(lottoHistoryFileName, header=None)
-    df_ball.columns = ['no', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'bn']
-
-    filter_ball=[]
-    filterTest = FilterTest(resources_path, ruleset_path=args.ruleset, history_json='lotto_history.json')
-
-    print("STEP #1. 필터 방법 추출")
-    start = time.time()
-    win_count = filterTest.find_filter_method(df_ball, start_no=args.start_no, end_no=args.end_no)
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    """
-    print("\n\n")
-    no = df_ball['no'].values[-1]
-    ball = df_ball[df_ball['no'] == no].values.tolist()[0]
-    answer = ball[1:7]
-
-    print("STEP #0. 최종 후보 선정")
-    start = time.time()
-    final_candidates = filterTest.find_final_candidates(no, df_ball, filter_ball=None)
-    process_time = datetime.timedelta(seconds=time.time() - start)
-    print("process_time: ", process_time)
-
-    print("   > size: {}".format(len(final_candidates)))
-    file_name = os.path.join(resources_path, 'final_candidates.biz_a1.txt')
-    with open(file_name, 'w+') as outFp:
-        for ball in final_candidates:
-            ball_str = [str(b) for b in answer]
-            outFp.write("{}\n".format(','.join(ball_str)))
-
-    print('{}회, 정답: {}\n'.format(no, str(answer)))
-    """
-
-    #print("\n\n")
-    #print("STEP #2. 당첨 회수 확인")
-    #filterTest.check_filter_method(df_ball, win_count)
-
-    # 오리지널 버전 (자질 파일에 고정): 당첨 22개