• // Python tips and tutorials
• // Python and the web
• // Algorithms
• // Benchmarks
• // Other
• // Useful scripts and snippets
• // Links

###// 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]

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]

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]

• IPython magic function %watermark - for printing date- and time-stamps and various system info

• Shell script for prepending Python-shebangs to .py files.

• convert 'tab-delimited' to 'comma-separated' CSV files [IPython nb]

• A random string generator function

###// Links [back to top]

• PyPI - the Python Package Index - the official repository for all open source Python modules and packages

• PEP 8 - The official style guide for Python code

// 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

• Learn Python The Hard Way - one of the most popular and recommended resources for learning Python

• Dive Into Python / Dive Into Python 3 - a free Python book for experienced programmers

• The Hitchhiker’s Guide to Python - a free best-practice handbook for both novices and experts

• Think Python - How to Think Like a Computer Scientist - an introduction for beginners starting with basic concepts of programming

// 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.

• SciPy Stack - Python packages (NumPy, pandas, SciPy, IPython, Matplotlib) for scientific computing

• 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