أفضل 10 أكواد Python يبحث عنها المطوّرون

مجموعة أكواد Python عملية لأشهر المهام. كل كود جاهز للنسخ مع شرح، ويحلّ مشكلة حقيقية.

1) قراءة وكتابة JSON

import json
from pathlib import Path

def read_json(file_path: str) -> dict:
    """Read a JSON file and return dict."""
    return json.loads(Path(file_path).read_text(encoding="utf-8"))

def write_json(data: dict, file_path: str, indent: int = 2) -> None:
    """Write dict to JSON file with UTF-8."""
    Path(file_path).write_text(
        json.dumps(data, ensure_ascii=False, indent=indent),
        encoding="utf-8"
    )

# استخدام
config = read_json("config.json")
config["updated_at"] = "2026-09-03"
write_json(config, "config.json")

2) استدعاء REST API

import requests
from typing import Optional

def fetch_data(url: str, headers: Optional[dict] = None, timeout: int = 30) -> dict:
    """Fetch JSON from URL with error handling."""
    response = requests.get(url, headers=headers or {}, timeout=timeout)
    response.raise_for_status() # يرفع HTTPError إذا فشل
    return response.json()

# استخدام
data = fetch_data(
    "https://api.example.com/users/123",
    headers={"Authorization": "Bearer YOUR_TOKEN"}
)
print(data["name"])

مع Retry Logic:

from time import sleep

def fetch_with_retry(url: str, retries: int = 3) -> dict:
    for i in range(retries):
        try:
            return fetch_data(url)
        except requests.HTTPError as e:
            if i == retries - 1:
                raise
            sleep(2 ** i) # Exponential backoff

3) Web Scraping (BeautifulSoup)

import requests
from bs4 import BeautifulSoup

def scrape_article_titles(url: str) -> list[str]:
    """Extract article titles from a page."""
    response = requests.get(url, headers={"User-Agent": "Mozilla/5.0"})
    response.raise_for_status()
    
    soup = BeautifulSoup(response.text, "html.parser")
    return [h2.get_text(strip=True) for h2 in soup.find_all("h2")]

# استخدام
titles = scrape_article_titles("https://example.com/blog")
for title in titles:
    print(title)

تحذير: راجع robots.txt وسياسات الموقع قبل السحب.

4) قراءة Excel وكتابته (pandas)

import pandas as pd

# قراءة
df = pd.read_excel("sales.xlsx", sheet_name="Q3")
print(df.head())
print(df.describe())

# فلترة
top_customers = df[df["total"] > 10000].sort_values("total", ascending=False)

# تجميع
by_region = df.groupby("region")["total"].sum().reset_index()

# كتابة
top_customers.to_excel("top_customers.xlsx", index=False)
by_region.to_csv("by_region.csv", index=False)

5) إرسال إيميلات (SMTP)

import smtplib
from email.message import EmailMessage
from email.utils import make_msgid

def send_email(
    from_addr: str,
    to_addr: str,
    subject: str,
    body: str,
    smtp_host: str,
    smtp_port: int,
    password: str
) -> None:
    """Send plain text email via SMTP."""
    msg = EmailMessage()
    msg["From"] = from_addr
    msg["To"] = to_addr
    msg["Subject"] = subject
    msg["Message-ID"] = make_msgid()
    msg.set_content(body)
    
    with smtplib.SMTP_SSL(smtp_host, smtp_port) as server:
        server.login(from_addr, password)
        server.send_message(msg)

# استخدام (Gmail مع App Password)
send_email(
    from_addr="you@gmail.com",
    to_addr="client@example.com",
    subject="اجتماع الأسبوع القادم",
    body="مرحباً،\n\nأودّ...",
    smtp_host="smtp.gmail.com",
    smtp_port=465,
    password="your-app-password" # ليست كلمة السرّ العادية
)

6) العمل مع قواعد البيانات (SQLite)

import sqlite3
from contextlib import contextmanager

@contextmanager
def db_connection(db_path: str):
    """Context manager for SQLite connections."""
    conn = sqlite3.connect(db_path)
    conn.row_factory = sqlite3.Row # الوصول كـdict
    try:
        yield conn
        conn.commit()
    except:
        conn.rollback()
        raise
    finally:
        conn.close()

# إنشاء جدول
with db_connection("app.db") as conn:
    conn.execute("""
        CREATE TABLE IF NOT EXISTS users (
            id INTEGER PRIMARY KEY,
            name TEXT NOT NULL,
            email TEXT UNIQUE
        )
    """)

# إدراج
with db_connection("app.db") as conn:
    conn.execute(
        "INSERT INTO users (name, email) VALUES (?, ?)",
        ("أحمد", "ahmed@example.com")
    )

# استعلام
with db_connection("app.db") as conn:
    for row in conn.execute("SELECT * FROM users"):
        print(row["name"], row["email"])

7) استدعاء ChatGPT API

from openai import OpenAI
import os

client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))

def ask_gpt(question: str, system: str = "You are a helpful assistant.") -> str:
    """Ask ChatGPT a question."""
    response = client.chat.completions.create(
        model="gpt-5-mini",
        messages=[
            {"role": "system", "content": system},
            {"role": "user", "content": question}
        ]
    )
    return response.choices[0].message.content

# استخدام
answer = ask_gpt("ما عاصمة السعودية؟")
print(answer)

8) معالجة الصور (Pillow)

from PIL import Image
from pathlib import Path

def resize_and_watermark(input_path: str, output_path: str, size: tuple = (800, 800)) -> None:
    """Resize image and add watermark."""
    img = Image.open(input_path)
    img.thumbnail(size) # يحافظ على النسبة
    
    # حفظ
    img.save(output_path, quality=85, optimize=True)

def convert_to_webp(input_path: str) -> str:
    """Convert image to WebP format."""
    output = str(Path(input_path).with_suffix(".webp"))
    Image.open(input_path).save(output, "WEBP", quality=80)
    return output

# استخدام
resize_and_watermark("large.jpg", "medium.jpg")
webp_path = convert_to_webp("photo.jpg")

9) أتمتة الملفّات

from pathlib import Path
import shutil
from datetime import datetime, timedelta

def organize_downloads(downloads_dir: str) -> None:
    """Organize downloads folder by file type."""
    dir_path = Path(downloads_dir)
    
    categories = {
        "images": [".jpg", ".jpeg", ".png", ".gif", ".webp"],
        "documents": [".pdf", ".docx", ".txt", ".xlsx"],
        "videos": [".mp4", ".avi", ".mkv"],
        "archives": [".zip", ".rar", ".7z"]
    }
    
    for file in dir_path.iterdir():
        if file.is_file():
            for category, extensions in categories.items():
                if file.suffix.lower() in extensions:
                    target_dir = dir_path / category
                    target_dir.mkdir(exist_ok=True)
                    shutil.move(str(file), target_dir / file.name)
                    break

def delete_old_files(directory: str, days_old: int = 30) -> None:
    """Delete files older than X days."""
    cutoff = datetime.now() - timedelta(days=days_old)
    for file in Path(directory).iterdir():
        if file.is_file() and datetime.fromtimestamp(file.stat().st_mtime) < cutoff:
            file.unlink()
            print(f"Deleted: {file.name}")

# استخدام
organize_downloads("/Users/you/Downloads")
delete_old_files("/tmp", days_old=7)

10) FastAPI Endpoint

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel, EmailStr

app = FastAPI()

class UserCreate(BaseModel):
    name: str
    email: EmailStr
    age: int

users_db = {}

@app.post("/users")
async def create_user(user: UserCreate):
    if user.email in users_db:
        raise HTTPException(400, "Email already exists")
    user_id = len(users_db) + 1
    users_db[user.email] = {**user.dict(), "id": user_id}
    return users_db[user.email]

@app.get("/users/{email}")
async def get_user(email: EmailStr):
    if email not in users_db:
        raise HTTPException(404, "User not found")
    return users_db[email]

# تشغيل: uvicorn main:app --reload

نصائح ذهبية

1. استخدم Type hints دائماً، يساعد IDE و AI
2. Handle errors، لا تفترض النجاح
3. Use logging بدل print للإنتاج
4. Write tests، pytest معياري
5. Environment variables لـSecrets، لا في الكود

المصادر الرسمية

• Python Docs
• Requests
• BeautifulSoup
• Pandas
• FastAPI

اقرأ أيضاً: أكواد أتمتة يومية · Web Scraping، دليل عملي · OpenAI API، دليل البدء · Claude Code، دليل المطوّر