Files & data
Read and write files safely; parse JSON, CSV, and common text formats.
Build a Personal Work Hours Tracker in Python
A Python class that logs daily work hours to a CSV file and produces a weekly summary of total hours worked.
import csv
from pathlib import Path
from datetime import datetime, date
class WorkHoursTracker:
def __init__(self, file_path="work_hours.csv"):
self.file_path = Path(file_path)
if not self.file_path.exists():
with open(self.file_path, "w", newline="") as f:
writer = csv…Generate Timesheet Reports from Daily Logs in Python
Aggregate daily log entries by project and produce a formatted timesheet report using Python's standard library.
import json
from pathlib import Path
from collections import defaultdict
def generate_timesheet_report(daily_logs: list[dict]) -> str:
"""
Generate a timesheet report from daily log entries.
Args:
daily_logs: List of dicts with 'date', 'project', 'hours', 'task' keys
Returns:
…Generate a Monthly Calendar PDF in Python
Create a Python utility that generates a monthly calendar PDF using ReportLab, with weekday headers and day numbers laid out in a grid.
from calendar import TextCalendar
from datetime import datetime
from reportlab.lib.pagesizes import letter
from reportlab.pdfgen import canvas
import os
def generate_monthly_calendar_pdf(year, month, filename="calendar.pdf"):
cal = TextCalendar()
days = cal.monthdays2calendar(year, month)
month_name …How to Filter Files by Extension and Size in Python
Use pathlib to list files in a directory, filter by extension or minimum size, and return matching names or (name, size) pairs.
from pathlib import Path
def filter_files_by_extension(directory: str, extension: str) -> list:
"""Return a list of file names in directory with the given extension."""
path = Path(directory)
return [f.name for f in path.iterdir() if f.is_file() and f.suffix == extension]
def filter_files_by_size(directo…How to Memory Map Large Files Read-Only in Python
This code demonstrates reading only the tail of a large file using a read-only memory map (mmap) to avoid loading the entire file into memory.
import mmap
import os
def read_tail_with_mmap(filepath, bytes_from_end=64):
"""Read the last bytes of a large file using a read-only mmap."""
file_size = os.path.getsize(filepath)
start = max(0, file_size - bytes_from_end)
with open(filepath, "rb") as f:
with mmap.mmap(f.fileno(), length=0, a…How to Merge Dicts from Two JSON Files Like a Pro
This helper reads two JSON files that contain dicts, merges them with the second file overriding duplicate keys, and saves the result to a new file.
import json
from pathlib import Path
def merge_json_files(file1: str, file2: str, output: str = "merged.json") -> dict:
"""Merge two JSON files containing dicts, with file2 overriding file1."""
data1 = json.loads(Path(file1).read_text())
data2 = json.loads(Path(file2).read_text())
merged = {**data1,…How to Read a File with Retry on Temporary IOError in Python
Read a file with automatic retries on temporary IOError/OSError failures, using the pathlib module with configurable attempts and delay.
import time
from pathlib import Path
def read_file_with_retry(filepath: str | Path, max_attempts: int = 3, delay: float = 0.5) -> str:
"""Read a file with retries on temporary IO errors."""
path = Path(filepath)
last_error = None
for attempt in range(max_attempts):
try:
return pat…How to Validate JSON Schema Shape in Python
Validate JSON data against a schema using manual checks for required fields, types, and constraints.
import json
from typing import Any, Dict
def validate_person_schema(data: Dict[str, Any]) -> bool:
"""Validate a person object against expected schema shape."""
if not isinstance(data, dict):
return False
# Required fields check
required_fields = {"name", "age", "email"}
if not requir…Tail last N lines of growing log file in Python
Prints the last n lines of a log file and follows new content appended to it, polling for size changes.
import time
from pathlib import Path
def tail_log(file_path, n=10, poll_interval=1.0, timeout=10):
"""
Print the last n lines and follow new lines appended to a growing log file.
"""
path = Path(file_path)
# Read the last n lines from the current file
with path.open("r", encoding="utf-8") as f…Browse by section
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