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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
How to Load a .env File Manually in Python
Parse a .env-style key-value file into a Python dictionary using only the standard library, with comment and quoted-value handling.
import re
from pathlib import Path
def load_dotenv_file(filepath: str) -> dict[str, str]:
"""Parse a .env-style file into a dictionary."""
env = {}
path = Path(filepath)
if not path.exists():
raise FileNotFoundError(f"Environment file not found: {filepath}")
for line in path.read_text()…How to Use singledispatch for Type-Based Overloading in Python
This code demonstrates Python's functools.singledispatch decorator to create functions that behave differently based on the type of their first argument.
from functools import singledispatch
@singledispatch
def process(value):
return f"Unknown type: {type(value).__name__}"
@process.register(int)
def _(value):
return f"Integer: {value * 2}"
@process.register(str)
def _(value):
return f"String: {value.upper()}"
@process.register(list)
def _(value):
re…How to Build an Error Code Enum in Python
Define an API error code enum with descriptions and build structured error payloads for HTTP responses.
from enum import Enum
class APIErrorCode(Enum):
SUCCESS = 0
BAD_REQUEST = 400
UNAUTHORIZED = 401
FORBIDDEN = 403
NOT_FOUND = 404
CONFLICT = 409
INTERNAL_ERROR = 500
def describe_error(code):
descriptions = {
APIErrorCode.SUCCESS: "Request completed successfully",
APIE…Automatically Highlight Data Validation Errors Inside Excel Files in Python
Load an Excel file with openpyxl, iterate over cells, and highlight invalid data (empty, negative) with a red fill and error message.
import openpyxl
from openpyxl.styles import PatternFill
from pathlib import Path
def highlight_validation_errors(filepath: str, output_path: str = None):
wb = openpyxl.load_workbook(filepath)
red_fill = PatternFill(start_color="FF0000", end_color="FF0000", fill_type="solid")
for sheet in wb.worksheet…Chunk Large File Upload Simulation by Blocks in Python
A Python script reads a large binary file in fixed-size chunks and simulates a block-by-block upload with per-chunk SHA256 hashing.
import os
import hashlib
from pathlib import Path
def read_file_in_chunks(file_path, chunk_size=8196):
"""Yield chunks of a file as bytes."""
with open(file_path, 'rb') as f:
while chunk := f.read(chunk_size):
yield chunk
def simulate_chunked_upload(file_path, chunk_size=8196):
"""S…Download Files from Internet with Progress Bar in Python
Download a file from the internet while displaying a text progress bar in the terminal.
import urllib.request
import sys
def download_with_progress(url, filename):
"""Download a file with a simple text progress bar."""
def report_hook(block_count, block_size, total_size):
downloaded = block_count * block_size
if total_size > 0:
percent = min(100, int(downloaded * 100 …How to Load Pickle Files Safely in Python
This code demonstrates how to load pickle files safely in Python by using a restricted unpickler that only allows specific, trusted classes, preventing arbitrary code execution from untrusted pickles.
import pickle
# Default pickle.load is unsafe: it executes arbitrary code when unpickling.
class Unsafe:
def __reduce__(self):
return (eval, ("open('/tmp/pickle_demo.txt', 'w').write('pwned')",))
# Create a malicious payload (simulating untrusted source)
malicious_data = pickle.dumps(Unsafe())
# Safe ap…How to Load a YAML Subset in Python Without PyYAML
Parse a flat, key-value YAML file with the Python standard library (re and pathlib), handling comments, quotes, and inline comments while skipping nested structures.
import re
from pathlib import Path
def load_yaml_subset(path):
"""Load a flat YAML file (key: value) without external dependencies."""
data = {}
with open(path, 'r', encoding='utf-8') as f:
for line in f:
# Skip empty lines and comments
line = line.strip()
if no…How to Load and Save JSON Files in Python
Load and save JSON files with pretty formatting using Python's standard library json module and pathlib.
import json
from pathlib import Path
def load_json(filepath: str) -> dict:
"""Load JSON data from a file."""
path = Path(filepath)
with path.open("r", encoding="utf-8") as f:
return json.load(f)
def save_json(filepath: str, data: dict) -> None:
"""Save data to a JSON file with pretty format…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 Environment-Specific Config JSON in Python
Loads a base JSON config and overlays environment-specific overrides, merging the two dictionaries into one final config.
import json
import pathlib
def load_config(base_path: pathlib.Path, env: str) -> dict:
base_config = json.loads(base_path.read_text())
env_path = base_path.with_name(f"config.{env}.json")
if env_path.exists():
env_config = json.loads(env_path.read_text())
return {**base_config, **env_conf…How to Parse INI Config Files in Python with configparser
Load and read settings from an INI file using Python's built-in configparser module, with type-safe value access.
import configparser
from pathlib import Path
# Create a sample INI file for demonstration
sample_content = """
[Database]
host = localhost
port = 5432
user = admin
password = secret123
[Logging]
level = INFO
file = app.log
max_size = 10MB
"""
config_file = Path("sample_config.ini")
config_file.write_text(sample_con…How to Read a JSON File into a Dictionary in Python
Load a JSON file into a Python dictionary using the json.load() function with proper file handling and UTF-8 encoding.
import json
from pathlib import Path
def read_json_file(filepath: str) -> dict:
"""Read a JSON file and return its contents as a dictionary."""
path = Path(filepath)
with path.open("r", encoding="utf-8") as f:
data = json.load(f)
return data
if __name__ == "__main__":
# Create a sample JS…How to Read and Write Text Files in Python
This code provides simple helper functions to save and load text files using Python's standard pathlib library.
from pathlib import Path
def save_text_data(filename: str, content: str) -> None:
file_path = Path(filename)
file_path.write_text(content, encoding="utf-8")
def load_text_data(filename: str) -> str:
file_path = Path(filename)
return file_path.read_text(encoding="utf-8")
if __name__ == "__main__":…How to Serialize a Python Object to Pickle Bytes in Memory
Serialize a Python object to pickle bytes in memory with pickle.dumps, then deserialize it back with pickle.loads and verify the roundtrip.
import pickle
class Person:
def __init__(self, name, age, skills):
self.name = name
self.age = age
self.skills = skills
def main():
person = Person("Alice", 30, ["Python", "SQL", "Docker"])
# Serialize to bytes in memory
pickle_bytes = pickle.dumps(person)
print(…How to Stream Large CSV Files in Python
Process a large CSV file in memory-efficient chunks using Python's csv module, yielding batches of rows instead of loading everything at once.
import csv
from pathlib import Path
def process_csv_in_chunks(file_path, chunk_size=1000):
"""Yield rows from a large CSV file in chunks without loading all into memory."""
with open(file_path, 'r', newline='') as f:
reader = csv.DictReader(f)
chunk = []
for row in reader:
…How to Pickle a Python Dict and Load It Back
Save a dictionary to a binary file with pickle.dump() and reload it with pickle.load(), showing the round trip and type preservation.
import pickle
data = {"name": "Alice", "scores": [87, 92, 95], "active": True}
print("Original dict:", data)
with open("safe_demo.pkl", "wb") as f:
pickle.dump(data, f)
with open("safe_demo.pkl", "rb") as f:
loaded = pickle.load(f)
print("Loaded dict:", loaded)
print("Type:", type(loaded).__name__)
print(…How to Validate JSON Types per Key in Python
Load a JSON object and validate the type of each key against an expected schema, reporting missing or mismatched fields.
import json
from typing import Any, Dict, Type
def validate_json_types(data: Dict[str, Any], schema: Dict[str, Type]) -> Dict[str, str]:
"""Validate that each key in data matches the expected type in schema."""
errors = {}
for key, expected_type in schema.items():
if key not in data:
e…Composable Predicates with the &, |, ~ Operators in Python
Define a reusable Predicate class that combines boolean checks with & (AND), | (OR), and ~ (NOT) operators.
class Predicate:
def __init__(self, func, name=None):
self.func = func
self.name = name or getattr(func, "__name__", "predicate")
def __call__(self, value):
return self.func(value)
def __and__(self, other):
return Predicate(lambda v: self(v) and other(v), f"({self.name} AN…How to Build a Data Helper Class in Python with OOP
Create a beginner-friendly Python class that loads CSV data, filters records by field, and counts entries using object-oriented programming.
class DataHelper:
"""A beginner-friendly OOP helper for handling simple datasets."""
def __init__(self, filename):
self.filename = filename
self.data = self._load_data()
def _load_data(self):
"""Load data from a CSV file into a list of dictionaries."""
import csv
…How to Lazy Load an Expensive Attribute with a Proxy in Python
This code shows a Proxy class that lazily loads an ExpensiveResource only when first accessed, caching it for subsequent uses.
class ExpensiveResource:
def __init__(self, name):
self.name = name
print(f"Expensive resource '{name}' created (e.g., DB connection)")
def use(self):
return f"Using {self.name}"
class Proxy:
def __init__(self, name):
self._name = name
self._resource = None
@p…Parse CSV Data with a Python Class
Encapsulate CSV file loading and column/row access methods in a reusable DataParser class for beginners.
class DataParser:
def __init__(self, file_path):
self.file_path = file_path
self.data = []
def load_data(self):
with open(self.file_path, 'r') as file:
for line in file:
row = line.strip().split(',')
self.data.append(row)
return self.…Build a lazy generator to read file lines in Python
Create a generator function that yields file lines one at a time, avoiding loading the entire file into memory, and demonstrate its lazy processing.
def lazy_lines(filepath):
"""Yield lines from a file one at a time without loading the whole file into memory."""
with open(filepath, 'r', encoding='utf-8') as file:
for line in file:
yield line.rstrip('\n')
if __name__ == "__main__":
# Create a sample file to demonstrate
sample_c…Memory efficient map over large file in Python
A generator-based streaming map that processes a large file line by line without loading the whole file into memory.
import sys
def process_lines(file_path):
"""Memory-efficient map over a large file: yields processed lines."""
with open(file_path, 'r') as f:
for line in f:
# Example mapping: strip whitespace and uppercase
yield line.strip().upper()
if __name__ == "__main__":
# Use a sma…Browse by section
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