Learn Enough Python to Be Dangerous

Michael Hartl created the legendary Ruby on Rails™ Tutorial that helped jumpstart thousands of web development careers. A cofounder and principal author at Learn Enough, Hartl previously earned a Ph.D. in physics at the California Institute of Technology (Caltech), where he received a Lifetime Achievement Award for Excellence in Teaching. He is also an alumnus Harvard University and the world-renowned Y Combinator entrepreneur program.

"Just started the #100DaysOfCode journey. Today marks day 1. I have completed @mhartl's great Ruby tutorial at @LearnEnough and am looking forward to starting on Ruby on Rails from tomorrow. Onwards and upwards."--Optimize Prime (@_optimize), Twitter post"Ruby and Sinatra and Heroku, oh my! Almost done with this live web application. It may be a simple palindrome app, but it's also simply exciting! #100DaysOfCode #ruby @LearnEnough #ABC #AlwaysBeCoding #sinatra #heroku"--Tonia Del Priore (@toninjaa), Twitter post; Software Engineer for a FinTech Startup for 3+ years"I have nothing but fantastic things to say about @LearnEnough courses. I am just about finished with the #javascript course. I must say, the videos are mandatory because @mhartl will play the novice and share in the joy of having something you wrote actually work!"--Claudia Vizena"I must say, this Learn Enough series is a masterpiece of education. Thank you for this incredible work!"--Michael King"I want to thank you for the amazing job you have done with the tutorials. They are likely the best tutorials I have ever read."--Pedro Iatzky

• Preface xiiiAcknowledgments xviiAbout the Author xixChapter 1: Hello, World! 11.1 Introduction to Python 61.2 Python in a REPL 111.3 Python in a File 131.4 Python in a Shell Script 161.5 Python in a Web Browser 18Chapter 2: Strings 352.1 String Basics 352.2 Concatenation and Interpolation 382.3 Printing 442.4 Length, Booleans, and Control Flow 462.5 Methods 562.6 String Iteration 62Chapter 3: Lists 693.1 Splitting 693.2 List Access 713.3 List Slicing 743.4 More List Techniques 773.5 List Iteration 833.6 Tuples and Sets 86Chapter 4: Other Native Objects 914.1 Math 914.2 Times and Datetimes 974.3 Regular Expressions 1034.4 Dictionaries 1094.5 Application: Unique Words 115Chapter 5: Functions and Iterators 1215.1 Function Definitions 1215.2 Functions in a File 1305.3 Iterators 138Chapter 6: Functional Programming 1496.1 List Comprehensions 1506.2 List Comprehensions with Conditions 1566.3 Dictionary Comprehensions 1596.4 Generator and Set Comprehensions 1636.5 Other Functional Techniques 165Chapter 7: Objects and Classes 1697.1 Defining Classes 1697.2 Custom Iterators 1767.3 Inheritance 1797.4 Derived Classes 183Chapter 8: Testing and Test-Driven Development 1918.1 Package Setup 1928.2 Initial Test Coverage 1978.3 Red 2098.4 Green 2148.5 Refactor 220Chapter 9: Shell Scripts 2319.1 Reading from Files 2319.2 Reading from URLs 2409.3 DOM Manipulation at the Command Line 245Chapter 10: A Live Web Application 25510.1 Setup 25610.2 Site Pages 26310.3 Layouts 27110.4 Template Engine 28010.5 Palindrome Detector 29310.6 Conclusion 316Chapter 11: Data Science 31911.1 Data Science Setup 32011.2 Numerical Computations with NumPy 32711.3 Data Visualization with Matplotlib 33811.4 Introduction to Data Analysis with pandas 35311.5 pandas Example: Nobel Laureates 36111.6 pandas Example: Titanic 37711.7 Machine Learning with scikit-learn 38611.8 Further Resources and Conclusion 403Index 405