| |
| import os |
| import json |
| import asyncio |
| from datetime import datetime, timedelta, timezone |
| from filelock import FileLock |
| import pandas as pd |
|
|
| |
| |
| |
| |
| DATA_DIR = os.getenv("ANALYTICS_DATA_DIR") |
| if not DATA_DIR: |
| if os.path.exists("/data") and os.access("/data", os.W_OK): |
| DATA_DIR = "/data" |
| print("[Analytics] Using persistent storage at /data") |
| else: |
| DATA_DIR = "./data" |
| print("[Analytics] Using local storage at ./data") |
|
|
| os.makedirs(DATA_DIR, exist_ok=True) |
|
|
| COUNTS_FILE = os.path.join(DATA_DIR, "request_counts.json") |
| LOCK_FILE = os.path.join(DATA_DIR, "analytics.lock") |
|
|
|
|
| |
| |
| |
| def _load_counts() -> dict: |
| if not os.path.exists(COUNTS_FILE): |
| return {} |
| with open(COUNTS_FILE) as f: |
| try: |
| return json.load(f) |
| except json.JSONDecodeError: |
| return {} |
|
|
|
|
| def _save_counts(data: dict): |
| with open(COUNTS_FILE, "w") as f: |
| json.dump(data, f) |
|
|
|
|
| def _normalize_counts_schema(data: dict) -> dict: |
| """ |
| Ensure data is {date: {"search": int, "fetch": int}}. |
| Backward compatible with old schema {date: int}. |
| """ |
| normalized = {} |
| for day, value in data.items(): |
| if isinstance(value, dict): |
| normalized[day] = { |
| "search": int(value.get("search", 0)), |
| "fetch": int(value.get("fetch", 0)), |
| } |
| else: |
| |
| normalized[day] = {"search": int(value or 0), "fetch": 0} |
| return normalized |
|
|
|
|
| |
| |
| |
| def _record_request_sync(tool: str) -> None: |
| tool = (tool or "").strip().lower() |
| if tool not in {"search", "fetch"}: |
| |
| tool = "search" |
|
|
| today = datetime.now(timezone.utc).strftime("%Y-%m-%d") |
| with FileLock(LOCK_FILE): |
| data = _normalize_counts_schema(_load_counts()) |
| if today not in data: |
| data[today] = {"search": 0, "fetch": 0} |
| data[today][tool] = int(data[today].get(tool, 0)) + 1 |
| _save_counts(data) |
|
|
|
|
| async def record_request(tool: str) -> None: |
| """Increment today's counter (UTC) for the given tool: 'search' or 'fetch'.""" |
| await asyncio.to_thread(_record_request_sync, tool) |
|
|
|
|
| def last_n_days_count_df(tool: str, n: int = 30) -> pd.DataFrame: |
| """Return DataFrame with a row for each of the past n days for the given tool.""" |
| tool = (tool or "").strip().lower() |
| if tool not in {"search", "fetch"}: |
| tool = "search" |
|
|
| now = datetime.now(timezone.utc) |
| with FileLock(LOCK_FILE): |
| data = _normalize_counts_schema(_load_counts()) |
|
|
| records = [] |
| for i in range(n): |
| day = now - timedelta(days=n - 1 - i) |
| day_key = day.strftime("%Y-%m-%d") |
| display_date = day.strftime("%b %d") |
| counts = data.get(day_key, {"search": 0, "fetch": 0}) |
| records.append( |
| { |
| "date": display_date, |
| "count": int(counts.get(tool, 0)), |
| "full_date": day_key, |
| } |
| ) |
| return pd.DataFrame(records) |
|
|
