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# ─── analytics.py ──────────────────────────────────────────────────────────────
import os
import json
from datetime import datetime, timedelta, timezone
from filelock import FileLock # pip install filelock
import pandas as pd # already available in HF images
COUNTS_FILE = "/data/request_counts.json"
LOCK_FILE = COUNTS_FILE + ".lock"
def _load() -> dict:
if not os.path.exists(COUNTS_FILE):
return {}
with open(COUNTS_FILE) as f:
return json.load(f)
def _save(data: dict):
with open(COUNTS_FILE, "w") as f:
json.dump(data, f)
async def record_request() -> None:
"""Increment today's counter (UTC) atomically."""
today = datetime.now(timezone.utc).strftime("%Y-%m-%d")
with FileLock(LOCK_FILE):
data = _load()
data[today] = data.get(today, 0) + 1
_save(data)
def last_n_days_df(n: int = 30) -> pd.DataFrame:
"""Return a DataFrame with a row for each of the past *n* days."""
now = datetime.now(timezone.utc)
with FileLock(LOCK_FILE):
data = _load()
records = []
for i in range(n):
day = (now - timedelta(days=n - 1 - i))
day_str = day.strftime("%Y-%m-%d")
# Format date for display (MMM DD)
display_date = day.strftime("%b %d")
records.append({
"date": display_date,
"count": data.get(day_str, 0),
"full_date": day_str # Keep full date for tooltip
})
return pd.DataFrame(records) |