Reference library

Python Code Samples

Easy snippets you can copy, study, and run in the browser editor.

2 matches
Git + Python easy

Upload Assets to GitHub Release with Python Mock

Simulates uploading binary and text assets to a GitHub release using a mock server, returning structured metadata for each upload.

git github releases
Python
import json
import os
import tempfile
from datetime import datetime

class ReleaseUploader:
    """Simulates uploading assets to a release with a mock server."""
    
    def __init__(self, owner: str, repo: str, tag: str):
        self.owner = owner
        self.repo = repo
        self.tag = tag
        self.uploade…
12 0 Open
ML engineering pipelines easy

How to Define Dagster ML Assets in Python

Define a chain of Dagster software-defined assets that compute raw features, normalized features, and predictions for an ML pipeline.

dagster ml-pipeline asset
Python
from dagster import asset


@asset
def raw_features():
    return {"sepal_length": [5.1, 4.9, 6.2], "sepal_width": [3.5, 3.0, 3.4]}


@asset
def normalized_features(raw_features):
    values = raw_features["sepal_length"]
    mean = sum(values) / len(values)
    std = (sum((x - mean) ** 2 for x in values) / len(values…
13 0 Open

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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

  1. Pick a topic section — strings, lists, files, functions, and more
  2. Open a sample, read How it works, and copy the code block
  3. 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.