This is a collection of articles, talks and tutorials that helped me understand Python better. I will categorize them and add brief summaries to the each of the items in time.

Reading material

• Advanced Python constructs
• Advanced Iterators
• Use more Iterators
• Iterables vs Iterators vs Generators
• Introduction to Python Generators
• 2 great benefits of Python Generators
• yeild and Generators
• An intro to Itertools
• An introduction to the Python interpreter
• Understanding Python's execution model
• The name of a Python function
• How (not?) to use Python's list comprehensions
• Descriptor how-to guide
• The descriptor protocol and Python black magic
• The __new__ special method in Python
• Python Types and Objects
• Meta-classes made easy
• What is a metaclass in Python (SO)
• Meta-classes and dynamic classes with Type
• Python class attributes
• Understanding Class instantiation in Python
• A primer on Python Metaclasses
• Pythonic code review
• Understanding Python decorators
• An introduction to Python Decorators
• Python decorators
• Exceptional logging of exceptions in Python
• The most diabolical Python Anti-pattern
• How Python Properties help with refactoring
• My favorite underused Python idiom
• Making unreliable APIs reliable with Python
• API integration in Python
• Designing Pythonic APIs

Testing

• Understanding Unit Testing
• Python Mock cookbook
• Mocks and Monkeypatching in Python

Numerics

• Floating point arithmatic : Issues and Limitations
• Tidy data in Python
• Modern Pandas
• Jupyter notebook tips, tricks and shortcuts
• Learning Pandas by doing

Misc

• Less copies of Python with the buffer proticol and memoryviews
• The many layers of packaging by Mahmoud Hashemi
• A simple guide for Python Packaging by Jie Feng
• The key differences between Python 2.7.x and 3.x with examples
• Pandas pivot table explained
• Command line scripts
• Effectively using Matplotlib
• Customizing class creation in Python by Brett Cannon
• Check whether all items match a condition in Python by Trey Hunner
• Modifying the Python language in 6 minutes by Anthony Shaw
• Closures aren't easy
• Yes, Python is slow, and I don't care.
• The CPython peephold optimizer and you by Allison Kaptur
• Computed goto for efficient dispatch tables by Eli Bandersky
• The internals of Python string interning by Adrien Guillo
• Exposing Python 3.6's private Dict version by Jake VanderPlas
• Why Python is slow: Looking under the hood by Jake VanderPlas
• Numba vs Cython: Take 2 by Jake VanderPlas
• Clustering with Scikit with GIFs by David Sheehan
• A large data workflow with Pandas, Python and SQLite
• Pythno for JavaScript developers by Mario Pabon
• Lists vs. Tuples by Ned Batchelder
• Generator tricks for systen programmers by David Beazley
• Kings' day speech by Guido van Rossum
• Tracking down a freaky Python memory leak
• Data driven decisions using PyPI download statistics
• Buggy Python code : The 10 most common mistakes that Python developers make
• Source code of the this module
• Comparing Python to other languages by GvR
• The story of None, True and False in Python
• Python cheatsheet
• Naming conventions in Python import statements
• Python design and history FAQ
• Python patterns : An optimization anecdote
• Python programming FAQ
• ZetCode

Books

• Python for Scientists and Engineers
• Python data science handbook by Jave VanderPlas
• Think Python by Allen B. Downey
• Learn Python the hard way by Zed A. Shaw
• Python cookbook by David Beazley and Brian K. Jones
• Dive into Python by Mark Pilgrim
• From Python to NumPy by Nicolas P. Rougier
• Python 3 Message of the Week by Doug Hellmann [Free to read online]

Talks and Tutorials

• Loop like a native by Ned Batchelder
• Getting started Testing by Ned Batchelder
• Pragmatic Unicode by Ned Batchelder
• Facts and myths about Python names and values by Ned Batchelder
• Fast numerical computing with Numpy by Jake VanderPlas
• Bridging the Pandas-Scikit-learn dtype divide by Tom Augspurger
• I wish I learnt that earlier
• The future of Python
• Shipping software to users with Python by Glyph
• Teaching Python : The hard parts
• Raymond Hettinger on developing Python
• Transforming code into beautiful, idiomatic Python by Raymond Hettinger
• Super considered Super by Raymond Hettinger
• Introducing Type annotations for Python by Guido van Rossum
• Emb edding Python in old Fortran HPC code
• Data visualization in PowerPoint with Python by S. Anand
• Visualizing big data by S. Anand
• Jacob Kaplan-Moss on Mediocre programmers
• A survey of Python interpreters by Brett Cannon
• Why PyPy by example
• Import-ant decisions by Allison Kaptur
• A 1500 line switch statement powers Python by Allison Kaptur
• Limitless and recursion-free recursion limits by Allison Kaptur
• Beating Python's GIL to max out your CPUs by Andrew Montalenti
• WTF is PEX by Brian Wickman
• Dask parallel and distributed computing by Matthew Rocklin
• The mighty dictionary by Brandon Craig Rhodes
• Modern PYthon dictionaries - A confluence of great ideas by Raymond Hettinger
• Optimizing Pandas code for speed and efficiency by Sofia Heisler
• PyCon 2017 keynote by Kelsey Hightower
• Yes, It's time to learn Regular Expressions by Al Sweigart
• 5 ways to deploy Python web apps in 2017 by Andrew T Baker
• What's in your pip toolbox by Jon Banafato
• Python's surprising internals by David Wolever