Reference library

Files & data

Read and write files safely; parse JSON, CSV, and common text formats.

4 matches
Files & data medium

Build a Secure Local Password Vault with Encrypted Storage in Python

A Python class that stores and retrieves passwords in an encrypted JSON file using Fernet symmetric encryption from the cryptography library.

encryption security passwords
Python
import json
import os
import base64
import hashlib
from cryptography.fernet import Fernet
from getpass import getpass

class PasswordVault:
    def __init__(self, vault_file="vault.json", key_file="vault.key"):
        self.vault_file = vault_file
        self.key_file = key_file
        self.key = self._load_or_creat…
50 0 Open
Files & data easy

Build a Simple ETL Pipeline in Python

A simple ETL pipeline that reads JSON Lines, transforms records with filtering and normalization, and writes the result to JSON.

etl json jsonl
Python
import json
from pathlib import Path


def read_input(file_path: Path) -> list[dict]:
    """Read JSON lines file into list of dicts."""
    with file_path.open("r", encoding="utf-8") as f:
        return [json.loads(line) for line in f if line.strip()]


def transform(records: list[dict]) -> list[dict]:
    """Transf…
13 0 Open
Files & data medium

Create a Python Tool That Generates Professional Excel Dashboards

Generate a professional sales dashboard in an Excel workbook with styled headers, a bar chart, and formatted number cells using the openpyxl library.

openpyxl excel dashboard
Python
import openpyxl
from openpyxl.chart import BarChart, Reference
from openpyxl.styles import Font, PatternFill, Alignment, Border, Side
from openpyxl.utils import get_column_letter

def create_sales_dashboard(workbook_path: str) -> None:
    """Generate a professional sales dashboard in an Excel workbook."""
    wb = op…
49 0 Open
Files & data medium

Join two CSV files on shared key column in Python

Merge rows from two CSV files by a common key column, outputting combined records to a new file.

csv join dictreader
Python
import csv

def join_csv(file1, file2, key, output="joined.csv"):
    # Read first CSV into dict keyed by the join column
    with open(file1, newline="") as f1:
        reader1 = csv.DictReader(f1)
        data1 = {row[key]: row for row in reader1}

    # Read second CSV and merge matching rows
    with open(file2, n…
15 0 Open

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