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A collection of useful scripts, tutorials, and other Python-related things
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README.md

A collection of useful scripts, tutorials, and other Python-related things


###// Python tips and tutorials [back to top]

  • A collection of not so obvious Python stuff you should know! [IPython nb]

  • Python's scope resolution for variable names and the LEGB rule [IPython nb]

  • Key differences between Python 2.x and Python 3.x [IPython nb]

  • A thorough guide to SQLite database operations in Python [Markdown]

  • Unit testing in Python - Why we want to make it a habit [Markdown]

  • Installing Scientific Packages for Python3 on MacOS 10.9 Mavericks [Markdown]

  • Sorting CSV files using the Python csv module [IPython nb]

  • Using Cython with and without IPython magic [IPython nb]

  • Parallel processing via the multiprocessing module [IPython nb]

  • Entry point: Data - using sci-packages to prepare data for Machine Learning tasks and other data analyses [IPython nb]

  • Awesome things that you can do in IPython Notebooks (in progress) [IPython nb]

  • A collection of useful regular expressions [IPython nb]


###// Python and the web [back to top]

  • Creating internal links in IPython Notebooks and Markdown docs [IPython nb]

  • Converting Markdown to HTML and adding Python syntax highlighting [Markdown]


###// Algorithms [[back to top](#a-collection-of-useful-scripts-tutorials-and-other-python-related-things)]

The algorithms category was moved to a separate GitHub repository rasbt/algorithms_in_ipython_notebooks

  • Sorting Algorithms [IPython nb]

  • Linear regression via the least squares fit method [IPython nb]

  • Dixon's Q test to identify outliers for small sample sizes [IPython nb]

  • Sequential Selection Algorithms [IPython nb]

  • Counting points inside a hypercube [IPython nb]


###// Plotting and Visualization [[back to top](#a-collection-of-useful-scripts-tutorials-and-other-python-related-things)]
  • a matplotlib gallery in IPython notebooks [GitHub repo]

###// Benchmarks [[back to top](#a-collection-of-useful-scripts-tutorials-and-other-python-related-things)]

The benchmark category was moved to a separate GitHub repository One-Python-benchmark-per-day

  • 1 - Reversing strings [IPython nb]
  • 2 - Calculating sample means [IPython nb]
  • 3 - 6 different ways to count elements using a dict [IPython nb]
  • 4 - Python vs. Cython vs. Numba [IPython nb]
  • 4.2 - (C)Python compilers - Cython vs. Numba vs. Parakeet [IPython nb]
  • 5 - Comparing 9 ways for flattening lists of sublists [IPython nb]
  • 6 - Determining if a string is a number [IPython nb]
  • 7 - Speeding up NumPy array expressions with Numexpr [IPython nb]
  • 7.2 - Just-in-time compilers for NumPy array expressions [IPython nb]
  • 8 - Calculating square roots and exponents [IPython nb]
  • 9 - The most Pythonic way to check if a string ends with a particular substring [IPython nb]
  • 10 - Cython - Bridging the gap between Python and Fortran [IPython nb]
  • 11 - The deque container data type [IPython nb]
  • 12 - Lightning fast insertion into sorted lists via the bisect module [IPython nb]
  • 13 - Parallel processing via the multiprocessing module [IPython nb]
  • 14 - Python's and NumPy's in-place operator functions [IPython nb]
  • 15 - Array indexing in NumPy: Extracting rows and columns [IPython nb]
  • 16 - Vectorizing a classic for-loop in NumPy [IPython nb]
  • 17 - Stacking NumPy arrays [IPython nb]

###// Other [back to top]

  • Happy Mother's [IPython nb]

  • Numeric matrix manipulation - The cheat sheet for MATLAB, Python NumPy, R, and Julia [Markdown]

  • Python Book Reviews [Markdown]


###// Useful scripts and snippets [back to top]


###// Links [back to top]

// News

  • Python subreddit - my favorite resource to catch up with Python news and great Python-related articles

  • Python community on Google+ - a nice and friendly community to share and discuss everything about Python

  • Python Weekly - A free weekly newsletter featuring curated news, articles, new releases, jobs etc. related to Python

// Resources for learning Python

// My favorite Python projects and packages

  • The IPython Notebook - an interactive computational environment for combining code execution, documentation (with Markdown and LateX support), inline plots, and rich media all in one document.

  • matplotlib - Python's favorite plotting library

  • NumPy - a library for multi-dimensional arrays and matrices, along with a large library of high-level mathematical functions to operate on these arrays

  • SciPy - a library that provides various useful functions for numerical computing, such as modules for optimization, linear algebra, integration, interpolation, ...

  • pandas - high-performance, easy-to-use data structures and data analysis tools build on top of Numpy

  • Cython - C-extensions for Python, an optimizing static compiler to combine Python and C code

  • Numba - an just-in-time specializing compiler which compiles annotated Python and NumPy code to LLVM (through decorators)

  • scikit-learn - a powerful machine learning library for Python and tools for efficient data mining and analysis