File, JSON, CSV ও HTTP

from pathlib import Path

BASE_DIR = Path(__file__).parent          # এই file যে folder এ আছে
DATA_DIR = BASE_DIR / "data"              # / দিয়ে path জোড়া
DATA_DIR.mkdir(exist_ok=True)             # folder না থাকলে বানাও

file = DATA_DIR / "expenses.json"
print(file.name)        # expenses.json
print(file.suffix)      # .json
print(file.exists())

for p in DATA_DIR.glob("*.json"):         # সব json file
    print(p)

from pathlib import Path

note = Path("note.txt")

# লেখা (পুরনোটা মুছে)
note.write_text("প্রথম লাইন\n", encoding="utf-8")

# শেষে যোগ করা
with note.open("a", encoding="utf-8") as f:
    f.write("দ্বিতীয় লাইন\n")

# পুরোটা পড়া
print(note.read_text(encoding="utf-8"))

# লাইন ধরে পড়া (বড় file এর জন্য)
with note.open(encoding="utf-8") as f:
    for line in f:
        print(line.rstrip())

import json
from pathlib import Path

expenses = [
    {"id": 1, "title": "দুপুরের খাবার", "amount": 18000, "category": "food"},
    {"id": 2, "title": "রিকশা", "amount": 6000, "category": "transport"},
]

path = Path("expenses.json")

# Python → JSON file
path.write_text(json.dumps(expenses, ensure_ascii=False, indent=2), encoding="utf-8")

# JSON file → Python
loaded = json.loads(path.read_text(encoding="utf-8"))
print(loaded[0]["title"])

from datetime import datetime
from pydantic import BaseModel, TypeAdapter

class Expense(BaseModel):
    id: int
    title: str
    amount: int
    spent_at: datetime

items = [Expense(id=1, title="চা", amount=2000, spent_at=datetime.now())]

adapter = TypeAdapter(list[Expense])
raw = adapter.dump_json(items, indent=2)                # bytes, datetime সহ
back = adapter.validate_json(raw)                       # আবার Expense list, যাচাইসহ

import json
import os
from pathlib import Path

def save_json_atomic(path: Path, data) -> None:
    tmp = path.with_suffix(".tmp")
    tmp.write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")
    os.replace(tmp, path)      # এক ধাপে বদল: হয় পুরনো file, নয় পুরো নতুন file

import csv
from pathlib import Path

rows = [
    {"date": "2026-10-01", "title": "বাজার", "amount": 1250.00},
    {"date": "2026-10-02", "title": "বিদ্যুৎ বিল", "amount": 980.50},
]

path = Path("report.csv")
with path.open("w", newline="", encoding="utf-8-sig") as f:    # -sig: Excel এ বাংলা ঠিক দেখাবে
    writer = csv.DictWriter(f, fieldnames=["date", "title", "amount"])
    writer.writeheader()
    writer.writerows(rows)

with path.open(encoding="utf-8-sig") as f:
    for row in csv.DictReader(f):
        print(row["title"], float(row["amount"]))

import httpx

with httpx.Client(base_url="https://jsonplaceholder.typicode.com", timeout=10.0) as client:
    # GET, query parameter সহ
    r = client.get("/posts", params={"userId": 1})
    r.raise_for_status()                 # 4xx/5xx হলে exception
    posts = r.json()
    print(len(posts), posts[0]["title"])

    # POST, JSON body সহ
    r = client.post("/posts", json={"title": "নতুন", "body": "লেখা", "userId": 1})
    print(r.status_code, r.json())

    # Header (যেমন token)
    r = client.get("/users/1", headers={"Authorization": "Bearer abc123"})

import httpx
import logging

logger = logging.getLogger(__name__)

class WeatherError(Exception):
    pass

def get_temperature(client: httpx.Client, lat: float, lng: float) -> float:
    try:
        r = client.get(
            "https://api.open-meteo.com/v1/forecast",
            params={"latitude": lat, "longitude": lng, "current": "temperature_2m"},
        )
        r.raise_for_status()
    except httpx.TimeoutException as e:
        raise WeatherError("Weather service সময়মতো সাড়া দেয়নি") from e
    except httpx.HTTPStatusError as e:
        logger.warning("Weather API %s: %s", e.response.status_code, e.response.text[:200])
        raise WeatherError("Weather service error") from e

    data = r.json()
    return data["current"]["temperature_2m"]

from datetime import datetime, timedelta, timezone
from zoneinfo import ZoneInfo

now_utc = datetime.now(timezone.utc)
dhaka = now_utc.astimezone(ZoneInfo("Asia/Dhaka"))
print(dhaka.strftime("%d %B %Y, %I:%M %p"))      # 29 October 2026, 10:15 AM

tomorrow = now_utc + timedelta(days=1)
iso = now_utc.isoformat()                         # API তে পাঠানোর জন্য: '2026-10-29T04:15:00+00:00'
parsed = datetime.fromisoformat(iso)