Intermediate Python Programming

Video description

What do Scrabble cheaters, Shakespearean sonnets, Twitter, and the Astronomy Picture of the Day have to do with Python software programming? For software impresario Jessica McKellar, they’re playful tools for teaching intermediate-level Python programming techniques. During her time as an organizer of the Boston Python User Group (one of the world’s largest Python groups), she taught hundreds of Python wannabees to happily program like pros. …

Intermediate Python Programming

Video description

Review data structures like lists, dictionaries, and sets; and when to best use them
Discover list comprehensions, a conceptual technique for constructing lists in an easy way
Analyze code performance using tools like profiling, code timing, and Big O notation
Understand why refractoring code can make it more testable
Learn best practices for scripting and documentation
Practice the smart ways to navigate an existing codebase
Search for, replace, and parse text using regular expressions and the re module
Understand single threaded programs, threading primitives, and multi-threaded programs

Jessica McKellar is the Director of Engineering at DropBox in San Francisco. A graduate of MIT, she enjoys the Internet, networking, low-level systems engineering, and contributing to and helping other people contribute to open source software. She is a Python Twisted maintainer and a local STEM volunteer.

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Introduction

Welcome to the Course

Walking through the checklist of everything we need for this course

Wordplay warm-up

Problem solving for words words in the English language that contain double letters

Problem solving for words in the English language that do not contain double letters

Problem solving for the English word that contains all vowels A, E, I, O and U?

Problem solving using more than one solution method

Data structures, a practical intermediate introduction

Reviewing container data structures we already know and love: lists and dictionaries

Using Lists and Dictionaries to Find Novel Words in Shakespeare’s Sonnets

An Introduction to “Big O” Notation and How to Analyze the “Runtime Performance” of Algorithms

Adding a new container data structure to our toolkit: the set.

Digging into the list comprehensions we’ve been using to put data from a file into lists and dictionaries.

Synthesizing the material from this section in a new script to extract the words from a file containing all of Shakespeare’s sonnets.

Reviewing the data structures and concepts from this section

Jeopardy database

Introducing the Jeopardy project, which will give us practice interacting with databases in Python

Exploring our sqlite Jeopardy database interactively

Exploring using Python to Interact With a SQLite Database Interactively

Writing our First Script to Query a Database: Jeopardy Categories

Writing a script to query the Jeopardy database for clues

Writing a script to query the Jeopardy database for the full set of categories for a game

Writing a script to query the Jeopardy database for clues for a particular category

Plotting with Matplotlib

Introducing the plotting project, which will give us practice using the popular Matplotlib plotting library

Exploring basic plotting interactively

Expanding on our basic plot in a script

Reading a script to plot the world population over time

Writing a script to plot life expectancies for men and women over time

Reading a script to plot a bar chart of letter frequencies in the US constitution

Scraping the NASA Astronomy Picture of the Day Website

Introducing the APOD project, which will give us practice with web scraping

Planning out our APOD scraping script

Implementing a basic scraper: fetching web resources with urllib

Implementing a basic scraper: processing HTML with BeautifulSoup

Finishing our basic scraper - Part 1

Finishing our basic scraper - Part 2

Generalizing our scraper

Conclusion

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Self paced

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