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‎cheatsheet.md‎

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A dictionary can also contain many dictionaries, this is called nested dictionaries.
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### Dictionary unpacking
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A double asterisk `**` denotes dictionary unpacking. Its operand must be a mapping. Each mapping item is added to the new dictionary. Later values replace values already set by earlier dict items and earlier dictionary unpackings.
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Originally proposed by [PEP 448](https://peps.python.org/pep-0448/).
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#### Simple Dictionary Unpacking Example
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1. Define the Function
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```python
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def make_sandwich(protein, cheese, sauce, extras=None):
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"""Prints the ingredients of a customized sandwich."""
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sandwich = f"A {protein} sandwich"
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if cheese:
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sandwich += f" with {cheese}"
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if sauce:
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sandwich += f" and {sauce} on it"
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if extras:
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sandwich += f" (plus {extras})"
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print(sandwich)
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```
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2. Define the Configuration Dictionary
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We create a **dictionary** where the **keys** match the **keyword argument names** of the function (`protein`, `cheese`, `sauce`, etc.).
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```python
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# Our sandwich configuration stored in a dictionary
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sandwich_settings = {
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'protein': 'turkey',
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'cheese': 'provolone',
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'sauce': 'mayo',
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'extras': 'lettuce and tomato'
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}
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```
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3. Use the Unpacking Operator (`**`)
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We call the function and use `**` to unpack the dictionary. The `**` operator turns the dictionary's key-value pairs into individual keyword arguments.
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```python
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# Unpack the dictionary into keyword arguments
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make_sandwich(**sandwich_settings)
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```
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**Output:**
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```
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A turkey sandwich with provolone and mayo on it (plus lettuce and tomato)
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```
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**What the `**` Does**
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The line `make_sandwich(**sandwich_settings)` is functionally equivalent to writing:
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```python
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make_sandwich(
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protein='turkey',
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cheese='provolone',
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sauce='mayo',
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extras='lettuce and tomato'
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)
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```
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The `**` operator is a clean way to pass a dynamic or pre-configured set of arguments to a function.
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### Tuple
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A tuple is a collection which is ordered, indexed and unchangeable. In Python tuples are written with round brackets.

‎generatedfiles/books.md‎

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:::{grid-item-card}
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:link: https://jakevdp.github.io/WhirlwindTourOfPython/
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{octicon}`smiley;1em;caption-text` **A Whirlwind Tour of Python**
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{octicon}`megaphone;1em;caption-text` **A Whirlwind Tour of Python**
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^^^
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A Whirlwind Tour of Python is a fast-paced introduction to essential features of the Python language, aimed at researchers and developers who are already familiar with programming in another language.
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:::{grid-item-card}
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:link: https://github.com/dabeaz-course/python-mastery
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{octicon}`bookmark;1em;caption-text` **Advanced Python Mastery**
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{octicon}`checklist;1em;caption-text` **Advanced Python Mastery**
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^^^
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An exercise-driven course on Advanced Python Programming that was battle-tested several hundred times on the corporate-training circuit for more than a decade. Written by David Beazley.
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:::{grid-item-card}
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:link: https://www.thedigitalcatbooks.com/pycabook-introduction/
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{octicon}`zap;1em;caption-text` **Clean Architectures in Python**
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{octicon}`bookmark;1em;caption-text` **Clean Architectures in Python**
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^^^
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This book is about a software design methodology. With lots of Python examples and a strong emphasis on TDD.
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:::{grid-item-card}
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:link: https://runestone.academy/ns/books/published/fopp/index.html
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{octicon}`book;1em;caption-text` **Foundations of Python Programming**
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{octicon}`heart;1em;caption-text` **Foundations of Python Programming**
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^^^
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This book is to teach you to understand and create computer programs in Python. With hands-on activities!
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:link: https://www.labri.fr/perso/nrougier/from-python-to-numpy/
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{octicon}`telescope;1em;caption-text` **From Python to Numpy**
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{octicon}`heart;1em;caption-text` **From Python to Numpy**
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The goal of this book is to explain advanced techniques for using Numpy.
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:link: https://developers.google.com/edu/python
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{octicon}`checklist;1em;caption-text` **Google's Python Class**
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{octicon}`file;1em;caption-text` **Google's Python Class**
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^^^
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Free online course book for people with a little bit of programming experience who want to learn Python
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[Read more or use this reference »](https://developers.google.com/edu/python)
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:::
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:::{grid-item-card}
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:link: https://leanpub.com/insidethepythonvirtualmachine/read
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{octicon}`light-bulb;1em;caption-text` **Inside The Python Virtual Machine**
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^^^
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```{image} https://d2sofvawe08yqg.cloudfront.net/insidethepythonvirtualmachine/s_shelf?1721860161
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:height: 100px
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```
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Inside the Python Virtual Machine provides a guided tour under the covers of the Python interpreter for the curious pythonista. It attempts to show the user what happens from the moment the user executes a piece of Python code to the point when the interpreter returns the result of executing the piece of code.
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[Read more or use this reference »](https://leanpub.com/insidethepythonvirtualmachine/read)
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:::
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:::{grid-item-card}
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:link: https://book.pythontips.com/en/latest/index.html
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{octicon}`tools;1em;caption-text` **Intermediate Python**
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{octicon}`tag;1em;caption-text` **Intermediate Python**
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The topics which are discussed in this book open up your mind towards some nice corners of Python language.
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:link: https://learningds.org/intro.html
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{octicon}`hubot;1em;caption-text` **Learning Data Science**
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{octicon}`check-circle;1em;caption-text` **Learning Data Science**
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Principles and Techniques of Data Science: This open book is tailored for ML! (Python numpy, classification etc)
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:link: https://pythonbook.org/
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{octicon}`pencil;1em;caption-text` **Professional Python Programming**
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{octicon}`bookmark;1em;caption-text` **Professional Python Programming**
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Open access book that covers topics that are important for a professional programmer.
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:link: https://www.labri.fr/perso/nrougier/python-opengl/
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{octicon}`pencil;1em;caption-text` **Python & OpenGL for Scientific Visualization**
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{octicon}`checklist;1em;caption-text` **Python & OpenGL for Scientific Visualization**
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he goal of this book is to reconciliate Python programmers with OpenGL, providing both an introduction to modern OpenGL and a set of basic and advanced techniques in order to achieve both fast, scalable & beautiful scientific visualizations.
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:link: https://jakevdp.github.io/PythonDataScienceHandbook/
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{octicon}`checklist;1em;caption-text` **Python Data Science Handbook**
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{octicon}`project;1em;caption-text` **Python Data Science Handbook**
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A book about doing data science with Python.
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:link: https://py-pkgs.org/welcome
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{octicon}`thumbsup;1em;caption-text` **Python Packages**
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{octicon}`project;1em;caption-text` **Python Packages**
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Python Packages is an open source book that describes modern and efficient workflows for creating Python packages.
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:link: https://www.tomasbeuzen.com/python-programming-for-data-science/README.html
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{octicon}`file;1em;caption-text` **Python Programming for Data Science**
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{octicon}`briefcase;1em;caption-text` **Python Programming for Data Science**
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Covers everything you need to know to start using Python for data science.
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:link: https://python-programming.quantecon.org/intro.html
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{octicon}`briefcase;1em;caption-text` **Python Programming for Economics and Finance**
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{octicon}`file;1em;caption-text` **Python Programming for Economics and Finance**
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Python for scientific computing, with a focus on economics and finance.
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:link: https://wesmckinney.com/book/
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{octicon}`note;1em;caption-text` **Python for Data Analysis, 3E**
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{octicon}`stack;1em;caption-text` **Python for Data Analysis, 3E**
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This book is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python.
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:link: https://goodresearch.dev/
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{octicon}`telescope;1em;caption-text` **The Good Research Code Handbook**
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{octicon}`pencil;1em;caption-text` **The Good Research Code Handbook**
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Handbook is for all who do a lot of programming as part of their research. It will teach you, in a practical manner, how to organize your code so that it is easy to understand and works reliably.
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:link: https://docs.python-guide.org/
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{octicon}`tag;1em;caption-text` **The Hitchhiker’s Guide to Python**
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{octicon}`hubot;1em;caption-text` **The Hitchhiker’s Guide to Python**
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Python Best Practices Guidebook.
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:link: https://www.pyopensci.org/python-package-guide/index.html
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{octicon}`project;1em;caption-text` **pyOpenSci Python Package Guide**
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{octicon}`bookmark;1em;caption-text` **pyOpenSci Python Package Guide**
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Learn how to create a Python package from start to finish. Also great tutorials for writing test, documentation and more!
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‎generatedfiles/commercialcompanies.md‎

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:link: https://www.anaconda.com/
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{octicon}`bookmark;1em;caption-text` **Anaconda**
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{octicon}`stack;1em;caption-text` **Anaconda**
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Anaconda sits at the center of the AI revolution. We provide data science tools, MLOps, and data & model management to empower our customers and community with AI capabilities to propel their projects forward.
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:link: https://astral.sh/
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{octicon}`tag;1em;caption-text` **Astral**
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{octicon}`bookmark;1em;caption-text` **Astral**
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Next-gen Python tooling
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‎generatedfiles/communities.md‎

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:link: https://conda.org/
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{octicon}`package;1em;caption-text` **Conda Community**
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{octicon}`cross-reference;1em;caption-text` **Conda Community**
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A community supporting a language-agnostic, multi-platform package management ecosystem for projects of any size and complexity.
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:link: https://jazzband.co/
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{octicon}`megaphone;1em;caption-text` **Jazzband**
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{octicon}`thumbsup;1em;caption-text` **Jazzband**
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Jazzband is a collaborative community to share the responsibility of maintaining Python-based projects.
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:link: https://palletsprojects.com/
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{octicon}`light-bulb;1em;caption-text` **Pallets**
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{octicon}`hubot;1em;caption-text` **Pallets**
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Pallets is the open source community organization that develops and supports popular Python frameworks.
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:link: https://pydata.org/
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{octicon}`project;1em;caption-text` **PyData**
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{octicon}`file;1em;caption-text` **PyData**
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PyData is an educational program of NumFOCUS, a 501(c)(3) nonprofit charity.
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{octicon}`zap;1em;caption-text` **Python Documentation Community**
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{octicon}`eye;1em;caption-text` **Python Documentation Community**
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The Documentation Team will be contributors to documentation who participate regularly to CPython documentation and monthly meetings (synchronously or asynchronously). A goal of this team will be to build a global community around CPython documentation.
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{octicon}`zap;1em;caption-text` **The Scientific Python project**
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{octicon}`tag;1em;caption-text` **The Scientific Python project**
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The scientific Python ecosystem is a loose federation of community-developed and -owned Python projects widely used in scientific research, technical computing, and data science.
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‎generatedfiles/datascience.md‎

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{octicon}`stack;1em;caption-text` **Foundations of Data Science with Python**
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{octicon}`thumbsup;1em;caption-text` **Foundations of Data Science with Python**
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```{image} https://github.com/jmshea/Foundations-of-Data-Science-with-Python/raw/main/images/3d-book.png
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{octicon}`cross-reference;1em;caption-text` **Learning Data Science**
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Principles and Techniques of Data Science: This open book is tailored for ML! (Python numpy, classification etc)
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‎generatedfiles/foundations.md‎

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:link: https://numfocus.org/
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{octicon}`project;1em;caption-text` **NumFOCUS**
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{octicon}`tools;1em;caption-text` **NumFOCUS**
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NumFOCUS is to promote open practices in research, data, and scientific computing
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{octicon}`project;1em;caption-text` **WheelNext**
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WheelNext is an open-source initiative (https://github.com/wheelnext & https://wheelnext.dev/) aiming to improve the user experience in the Python packaging ecosystem, specifically around the scientific computing and machine/deep learning space. We also anticipate benefits in other domains that heavily rely on performance of compiled Python extension modules - the benefit of utilizing one's hardware more optimally is not exclusive to any single domain.
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{octicon}`tag;1em;caption-text` **pyOpenSci**
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Community that supports free and open Python tools for processing scientific data.
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