A collection of useful scripts, tutorials, and other Python-related things
###// Python tips and tutorials
- A collection of not so obvious Python stuff you should know! [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/not_so_obvious_python_stuff.ipynb?create=1)]
- Python's scope resolution for variable names and the LEGB rule [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/scope_resolution_legb_rule.ipynb?create=1)]
- Key differences between Python 2.x and Python 3.x [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/key_differences_between_python_2_and_3.ipynb?create=1)]
- A thorough guide to SQLite database operations in Python [[Markdown](./sqlite3_howto/README.md)]
- Unit testing in Python - Why we want to make it a habit [[Markdown](./tutorials/unit_testing.md)]
- Installing Scientific Packages for Python3 on MacOS 10.9 Mavericks [[Markdown](./tutorials/installing_scientific_packages.md)]
- Sorting CSV files using the Python csv module [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/sorting_csvs.ipynb)]
- Using Cython with and without IPython magic [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/running_cython.ipynb)]
- Parallel processing via the multiprocessing module [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/multiprocessing_intro.ipynb?create=1)]
- Entry point: Data - using sci-packages to prepare data for Machine Learning tasks and other data analyses [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/python_data_entry_point.ipynb?create=1)]
- Awesome things that you can do in IPython Notebooks (in progress) [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/awesome_things_ipynb.ipynb)]
###// Python and the web
- Creating internal links in IPython Notebooks and Markdown docs [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/table_of_contents_ipython.ipynb)]
- Converting Markdown to HTML and adding Python syntax highlighting [[Markdown](./tutorials/markdown_syntax_highlighting/README.md)]
###// Algorithms
*The algorithms category was moved to a separate GitHub repository [rasbt/algorithms_in_ipython_notebooks](https://github.com/rasbt/algorithms_in_ipython_notebooks)*
- Sorting Algorithms [[IPython nb](http://nbviewer.ipython.org/github/rasbt/algorithms_in_ipython_notebooks/blob/master/ipython_nbs/sorting/sorting_algorithms.ipynb?create=1)]
- Linear regression via the least squares fit method [[IPython nb](http://nbviewer.ipython.org/github/rasbt/algorithms_in_ipython_notebooks/blob/master/ipython_nbs/statistics/linregr_least_squares_fit.ipynb?create=1)]
- Dixon's Q test to identify outliers for small sample sizes [[IPython nb](http://nbviewer.ipython.org/github/rasbt/algorithms_in_ipython_notebooks/blob/master/ipython_nbs/statistics/dixon_q_test.ipynb?create=1)]
- Sequential Selection Algorithms [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/sorting_csvs.ipynb)]
###// Benchmarks
*For more recent benchmarks, please also see my separate
GitHub repository [One-Python-benchmark-per-day](https://github.com/rasbt/One-Python-benchmark-per-day)*
- Python benchmarks via `timeit` [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/benchmarks/timeit_tests.ipynb?create=1)]
- Least squares fit method for linear regression sped up via Cython [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/benchmarks/cython_least_squares.ipynb?create=1)]
- Benchmarks of different palindrome functions [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/benchmarks/palindrome_timeit.ipynb?create=1)]
###// Other
- Happy Mother's Day [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/other/happy_mothers_day.ipynb?create=1)]
- Numeric matrix manipulation - The cheat sheet for MATLAB, Python NumPy, R, and Julia [[Markdown](./tutorials/matrix_cheatsheet.md)]
###// Useful scripts and snippets
- [IPython magic function %date](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/ipython_magic/datemagic.ipynb) - for printing date stamps and/or the current Python/IPython version
- [Shell script](./useful_scripts/prepend_python_shebang.sh) for prepending Python-shebangs to .py files.
- convert 'tab-delimited' to 'comma-separated' CSV files [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/useful_scripts/fix_tab_csv.ipynb?create=1)]
- A random string generator [function](./useful_scripts/random_string_generator.py)
###// Links
- [PyPI - the Python Package Index](https://pypi.python.org/pypi) - the official repository for all open source Python modules and packages
- [PEP 8](http://legacy.python.org/dev/peps/pep-0008/) - The official style guide for Python code
**// News**
- [Python subreddit](http://www.reddit.com/r/Python/) - my favorite resource to catch up with Python news and great Python-related articles
- [Python community on Google+](https://plus.google.com/communities/103393744324769547228) - a nice and friendly community to share and discuss everything about Python
- [Python Weekly](http://www.pythonweekly.com) - A free weekly newsletter featuring curated news, articles, new releases, jobs etc. related to Python
**// Resources for learning Python**
- [Learn Python The Hard Way](http://learnpythonthehardway.org/book/) - one of the most popular and recommended resources for learning Python
- [Dive Into Python](http://www.diveintopython.net) / [Dive Into Python 3](http://getpython3.com/diveintopython3/) - a free Python book for experienced programmers
- [The Hitchhiker’s Guide to Python](http://docs.python-guide.org/en/latest/) - a free best-practice handbook for both novices and experts
- [Think Python - How to Think Like a Computer Scientist](http://www.greenteapress.com/thinkpython/) - an introduction for beginners starting with basic concepts of programming
**// My favorite Python projects and packages**
- [The IPython Notebook](http://ipython.org/notebook.html) - 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](http://www.scipy.org/index.html) - Python packages (NumPy, pandas, SciPy, IPython, Matplotlib) for scientific computing
- [Cython](http://cython.org) - C-extensions for Python, an optimizing static compiler to combine Python and C code
- [Numba](http://numba.pydata.org) - an just-in-time specializing compiler which compiles annotated Python and NumPy code to LLVM (through decorators)