Python Code
Samples
Medium snippets you can copy, study, and run in the browser editor.
Detect Circular Imports Across Python Projects Automatically
This script walks through all .py files in a directory, builds an import graph, and uses depth-first search to find cycles—printing each circular dependency chain.
import ast
import sys
from pathlib import Path
from collections import defaultdict, deque
def find_imports(filepath):
"""Return set of module names imported by a Python file."""
imports = set()
try:
with open(filepath) as f:
tree = ast.parse(f.read())
except (SyntaxError, UnicodeDe…Find Unused Python Packages Automatically
Scan a Python project's source files for imports and list installed packages not imported anywhere.
import pkg_resources
import ast
import os
import sys
from pathlib import Path
def find_imports_in_project(project_dir="."):
imports = set()
for py_file in Path(project_dir).rglob("*.py"):
try:
with open(py_file, "r") as f:
tree = ast.parse(f.read())
for node in …How to Generate a Dependency Graph for Python Projects
This script walks through a Python project directory, parses each .py file's imports, and prints a dependency graph showing which modules depend on which other modules.
import os
import ast
from pathlib import Path
from collections import defaultdict
def get_imports(filepath):
with open(filepath) as f:
try:
tree = ast.parse(f.read())
except SyntaxError:
return []
imports = []
for node in ast.walk(tree):
if isinstance(node, …How to Train a Gradient Boosting Regressor in Python
Build and evaluate a scikit-learn GradientBoostingRegressor on a synthetic dataset, printing test MSE and feature importances.
import numpy as np
from sklearn.ensemble import GradientBoostingRegressor
from sklearn.metrics import mean_squared_error
def train_gradient_boosting_mock():
# Toy regression dataset
np.random.seed(42)
X = np.random.rand(100, 3) * 10
y = 2 * X[:, 0] - 1.5 * X[:, 1] + 0.5 * X[:, 2] + np.random.normal(0,…Browse by section
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Guide: free Python code samples library
Copy-ready Python snippets for learners and developers
PythonSkillset code samples are short, focused examples organised by topic and difficulty. Every snippet is server-rendered HTML — readable by search engines and easy to copy. Open any sample, read the notes, copy the code, then press Try in editor to run it in the browser with Pyodide.
How to use this library
- Pick a topic section — strings, lists, files, functions, and more
- Open a sample, read How it works, and copy the code block
- Run it in the IDE, tweak values, then take a related quiz or tutorial lesson
Samples vs tutorials and challenges
Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.