mirror of
https://github.com/rasbt/python_reference.git
synced 2025-02-17 13:58:13 +00:00
147 lines
6.5 KiB
Markdown
Executable File
147 lines
6.5 KiB
Markdown
Executable File
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<div align="center">
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<h3>A collection of useful scripts, tutorials, and other Python-related things</h3>
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<img src="./Images/python-logo-master-v3-TM-flattened.png" alt=""> </div>
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<br>
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<br>
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<br>
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<br>
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###// Python tips and tutorials
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- 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)]
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- 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)]
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- 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)]
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- A thorough guide to SQLite database operations in Python [[Markdown](./sqlite3_howto/README.md)]
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- Unit testing in Python - Why we want to make it a habit [[Markdown](./tutorials/unit_testing.md)]
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- Installing Scientific Packages for Python3 on MacOS 10.9 Mavericks [[Markdown](./tutorials/installing_scientific_packages.md)]
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- Sorting CSV files using the Python csv module [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/sorting_csvs.ipynb)]
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- Using Cython with and without IPython magic [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/running_cython.ipynb)]
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- Parallel processing via the multiprocessing module [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/multiprocessing_intro.ipynb?create=1)]
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<br>
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###// Python and the web
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- 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)]
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- Converting Markdown to HTML and adding Python syntax highlighting [[Markdown](./tutorials/markdown_syntax_highlighting/README.md)]
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<br>
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###// Algorithms
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*The algorithms category was moved to a separate GitHub repository [rasbt/algorithms_in_ipython_notebooks](https://github.com/rasbt/algorithms_in_ipython_notebooks)*
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- Sorting Algorithms [[IPython nb](http://nbviewer.ipython.org/github/rasbt/algorithms_in_ipython_notebooks/blob/master/ipython_nbs/sorting/sorting_algorithms.ipynb?create=1)]
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- 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)]
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- 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)]
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- Sequential Selection Algorithms [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/sorting_csvs.ipynb)]
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<br>
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###// Benchmarks
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*For more recent benchmarks, please also see my separate
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GitHub repository [One-Python-benchmark-per-day](https://github.com/rasbt/One-Python-benchmark-per-day)*
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- Python benchmarks via `timeit` [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/benchmarks/timeit_tests.ipynb?create=1)]
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- 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)]
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- Benchmarks of different palindrome functions [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/benchmarks/palindrome_timeit.ipynb?create=1)]
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<br>
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###// Other
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- Happy Mother's Day [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/other/happy_mothers_day.ipynb?create=1)]
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- Numeric matrix manipulation - The cheat sheet for MATLAB, Python NumPy, R, and Julia [[Markdown](./tutorials/matrix_cheatsheet.md)]
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<br>
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###// Useful scripts and snippets
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- [Shell script](./useful_scripts/prepend_python_shebang.sh) for prepending Python-shebangs to .py files.
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- 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)]
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- A random string generator [function](./useful_scripts/random_string_generator.py)
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<br>
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<a id='links'></a>
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###// Links
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- [PyPI - the Python Package Index](https://pypi.python.org/pypi) - the official repository for all open source Python modules and packages
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- [PEP 8](http://legacy.python.org/dev/peps/pep-0008/) - The official style guide for Python code
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**// News**
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- [Python subreddit](http://www.reddit.com/r/Python/) - my favorite resource to catch up with Python news and great Python-related articles
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- [Python community on Google+](https://plus.google.com/communities/103393744324769547228) - a nice and friendly community to share and discuss everything about Python
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- [Python Weekly](http://www.pythonweekly.com) - A free weekly newsletter featuring curated news, articles, new releases, jobs etc. related to Python
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**// Resources for learning Python**
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- [Learn Python The Hard Way](http://learnpythonthehardway.org/book/) - one of the most popular and recommended resources for learning Python
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- [Dive Into Python](http://www.diveintopython.net) / [Dive Into Python 3](http://getpython3.com/diveintopython3/) - a free Python book for experienced programmers
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- [The Hitchhiker’s Guide to Python](http://docs.python-guide.org/en/latest/) - a free best-practice handbook for both novices and experts
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- [Think Python - How to Think Like a Computer Scientist](http://www.greenteapress.com/thinkpython/) - an introduction for beginners starting with basic concepts of programming
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**// My favorite Python projects and packages**
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- [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.
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- [SciPy Stack](http://www.scipy.org/index.html) - Python packages (NumPy, pandas, SciPy, IPython, Matplotlib) for scientific computing
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- [Cython](http://cython.org) - C-extensions for Python, an optimizing static compiler to combine Python and C code
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- [Numba](http://numba.pydata.org) - an just-in-time specializing compiler which compiles annotated Python and NumPy code to LLVM (through decorators) |