Streamlit • A faster way to build and share data apps
Streamlit turns data scripts into shareable web apps in minutes. All in pure Python. No front‑end experience required.
GitHub - sissbruecker/linkding: Self-hosted bookmark manager that is designed be to be minimal, fast, and easy to set up using Docker.
Self-hosted bookmark manager that is designed be to be minimal, fast, and easy to set up using Docker.
Pythonista 3 on the App Store
Pythonista is a complete scripting environment for Python, running directly on your iPad or iPhone. It includes support for both Python 3.6 and 2.7, so you can use all the language improvements in Python 3, while still having 2.7 available for backwards compatibility.
Learn Python by creating a video game | Opensource.com
Get to know Python the fun way using the step-by-step instructions in our new eBook.
Don’t be afraid to commit — Don't be afraid to commit 0.3 documentation
A workshop/tutorial for Python/Django developers who would like to contribute more to the projects they use, but need more grounding in some of the tools required. Don’t be afraid to commit will help put you in a position to commit successfully to collaborative projects. You’ll find it particularly useful if you think you have some good coding ideas, but find that managing the development process sometimes gets in the way of your actual development. The workshop will take participants through the complete cycle of identifying a simple issue in a Django or Python project, writing a patch with documentation, and submitting it.
Project Jupyter | Home
Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages.
Pelican Static Site Generator, Powered by Python
"Pelican is a static site generator, written in Python, that requires no database or server-side logic."
How to Think Like a Computer Scientist — How to Think Like a Computer Scientist: Learning with Python 3
Learning with Python 3 (RLE) Version date: February 2012 by Peter Wentworth, Jeffrey Elkner, Allen B. Downey, and Chris Meyers (based on 2nd edition by Jeffrey Elkner, Allen B. Downey, and Chris Meyers)
Reading and Writing Electronic Text: ITP Spring 2012
This course introduces the Python programming language as a tool for reading and writing digital text. This course is specifically geared to serve as a general-purpose introduction to programming in Python, but will be of special interest to students interested in poetics, language, creative writing and text analysis. Weekly programming exercises work toward a midterm project and culminate in a final project. Poetics topics covered include: character encodings (and other technical issues); cut-up and re-mixed texts; the algorithmic nature of poetic form (proposing poetic forms, generating text that conforms to poetic forms); transcoding/transcription (from/to text); generative algorithms: n-gram analysis, context-free grammars; performing digital writing. Programming topics covered include: object-oriented programming; functional programming (list comprehensions, recursion); getting data from the web; displaying data on the web; parsing data formats (e.g., markup languages); and text
Teaching Creative Writing with Python: OSCON 2011 - O'Reilly Conferences, July 25 - 29, 2011, Portland, OR
For the past three years, I have taught a graduate-level course in creative writing that masquerades as a course about Python. (NYU’s Interactive Telecommunications Program offers the course; you can see the syllabus here: http://rwet.decontextualize.com/) The course concerns the classic tension in poetry between decontextualization and juxtaposition: deciding what a text’s constituent elements are, breaking the text into those elements, and then bringing them back together in surprising and interesting ways. Students are taught not just about string processing and text analysis, but also about the poetic possibilities of using those techniques to algorithmically build new texts. Each semester, the course culminates in a live performance, in which each student must read aloud for an audience a text that one of their programs has generated.
Overview — NetworkX 1.6 documentation
NetworkX is a Python language software package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.