code_snippets
Python code examples from Corey Schafer's YouTube tutorials, kept in one repository.
- Stars
- 10.6k
- Forks
- 17.1k
- Licence
- MIT
- Language
- Jupyter Notebook
- Last update
- 2.3 years ago
- Type
- Learning resource
No commits in over a year — check for forks or alternatives before adopting.
What it is
This repository collects code snippets from Corey Schafer's Python tutorial videos. The README provided is only a title, so its exact contents and organization cannot be confirmed here. Based on the name and primary language (Jupyter Notebook), it appears to hold example code that learners can read and run alongside the videos.
- Open a notebook to read a tutorial's code step by step
- Run example snippets to see how a Python concept behaves
- Use the examples as a reference while watching the related videos
Great for
- People following Corey Schafer's Python tutorial videos who want the matching code
- Beginners who learn Python by reading and running example code
- Learners who want to compare their own code against working examples
Not ideal for
- Developers looking for a library or tool to install into a project, since this appears to be a set of examples (the README does not describe a package)
- People who need documentation on the README alone, since the README provided contains only a title
How to get it
- 1
Clone and build from source
Clone the repository
git clone https://github.com/CoreyMSchafer/code_snippets - 2
Run it
- Clone the repository to your computer
- Open the repository folder and find the notebook for the tutorial you want
- Open the notebook in Jupyter and run the cells in order
- 3
Get the most out of it
- Watch the matching video alongside the notebook to connect code to explanation
- Modify and rerun cells to test how changes affect the output
- Check the repository's file list for topics that match your learning goals
Downloads
Strengths
- Comes from a well-known Python educator with a large audience (about 10.6k stars)
- Released under the MIT license, which permits reuse
- Uses Jupyter Notebooks, which let you run code cell by cell
Trade-offs
- The README provided is only a title, so the project's structure and scope are not documented here
- No description, topics, or releases are listed, and the last push was 2024-08-01
Stats synced from GitHub. The assessment above was drafted with AI from the project's README on 2026-10-29 and may miss recent changes — check the README before relying on a command. MIT licence: free to use, modify and distribute, including commercially, as long as you keep the copyright notice.