File Handling

# ── WRITING a file ───────────────────────────
with open("notes.txt", "w", encoding="utf-8") as f:
    f.write("Line 1: Python is awesome!\n")
    f.write("Line 2: File handling is easy.\n")
    f.write("Line 3: Always use 'with'.\n")
# File is automatically closed here

# ── READING the whole file at once ───────────
with open("notes.txt", "r", encoding="utf-8") as f:
    content = f.read()
    print(content)

# ── READING line by line (memory-efficient) ──
with open("notes.txt", "r", encoding="utf-8") as f:
    for line in f:
        print(line.strip())   # strip removes the trailing \n

# ── READING into a list ───────────────────────
with open("notes.txt") as f:
    lines = f.readlines()     # list of strings, each with \n
    print(f"{len(lines)} lines read")

# ── APPENDING to existing file ───────────────
with open("notes.txt", "a", encoding="utf-8") as f:
    f.write("Line 4: Appended without overwriting!\n")

# ── WRITING multiple lines at once ───────────
data = ["Ali\n", "Sara\n", "Zara\n"]
with open("names.txt", "w") as f:
    f.writelines(data)

import csv

# ── WRITING a CSV ─────────────────────────────
students = [
    ["Name",    "Age", "GPA",  "City"],       # header row
    ["Ali",     20,   3.85, "Lahore"],
    ["Sara",    22,   3.92, "Karachi"],
    ["Fatima",  21,   3.75, "Islamabad"],
]

with open("students.csv", "w", newline="", encoding="utf-8") as f:
    writer = csv.writer(f)
    writer.writerows(students)

# ── READING a CSV ─────────────────────────────
with open("students.csv", "r", encoding="utf-8") as f:
    reader = csv.reader(f)
    for row in reader:
        print(row)

# ── DictReader — rows as dicts (headers as keys) ─
with open("students.csv", "r", encoding="utf-8") as f:
    reader = csv.DictReader(f)
    for row in reader:
        print(f"{row['Name']}: GPA {row['GPA']}")
# Ali: GPA 3.85
# Sara: GPA 3.92

# ── DictWriter — write dicts to CSV ──────────
records = [
    {"product": "Book",      "price": 1500},
    {"product": "Keyboard",  "price": 3200},
]
with open("products.csv", "w", newline="") as f:
    writer = csv.DictWriter(f, fieldnames=["product", "price"])
    writer.writeheader()
    writer.writerows(records)

import json

data = {
    "app"    : "BitWithBite",
    "version": "2.0",
    "students": [
        {"name": "Ali",  "gpa": 3.85},
        {"name": "Sara", "gpa": 3.92},
    ],
    "active": True
}

# ── Write to JSON file ────────────────────────
with open("data.json", "w", encoding="utf-8") as f:
    json.dump(data, f, indent=2, ensure_ascii=False)
# indent=2 makes it human-readable
# ensure_ascii=False preserves Urdu/Arabic characters

# ── Read from JSON file ───────────────────────
with open("data.json", "r", encoding="utf-8") as f:
    loaded = json.load(f)

print(loaded["app"])                   # BitWithBite
print(loaded["students"][0]["name"])  # Ali

# ── JSON string conversion ────────────────────
json_str = json.dumps(data, indent=2)   # dict → string
back     = json.loads(json_str)          # string → dict

# ── Useful pattern: update a JSON config ─────
def update_config(path, key, value):
    with open(path) as f: config = json.load(f)
    config[key] = value
    with open(path, "w") as f: json.dump(config, f, indent=2)

update_config("data.json", "version", "2.1")

from pathlib import Path

# Current directory
cwd = Path.cwd()
print(cwd)

# Build paths with / operator (works on all OS!)
data_dir = cwd / "data"
file_path= data_dir / "students.csv"

# Create directories
data_dir.mkdir(exist_ok=True)   # no error if already exists

# Path properties
p = Path("data/students.csv")
print(p.name)        # students.csv
print(p.stem)        # students
print(p.suffix)      # .csv
print(p.parent)      # data
print(p.exists())     # True/False
print(p.is_file())    # True if it's a file

# Read/write directly from Path objects
config = Path("config.txt")
config.write_text("debug=True\nport=8000\n", encoding="utf-8")
print(config.read_text(encoding="utf-8"))

# List all files matching a pattern
for csv_file in Path(".").glob("*.csv"):
    print(f"Found: {csv_file.name} ({csv_file.stat().st_size} bytes)")

# Recursive glob — find all Python files in any subdirectory
for py_file in Path(".").rglob("*.py"):
    print(py_file)