theory-to-practice.md

Theory to Practice

Congratulations on completing the Intro to Python workshop! So far, you've learned quite a bit about variables, functions, loops, modules, and other foundational concepts to further your Python journey. For next steps, consider our suggested introductoin to Python libraries, or trying some of the tutorials or projects listed below. Maybe you want to learn how to clean text with Regex, or want to dig into web scraping with the Python library requests . Or, if you are interested in strengthening your foundational skills, read one of the most suggested (and free!) beginner Python book, How to Think Like a Computer Scientist - Python Edition. See a full list of our suggestions below.

Suggested Further Readings

• Hannah Aizenman, a former Digital Fellow, wrote up a great blog post introducing python "libraries," or collections of python code, for various project types, from creating a website, to getting, exploring, and visualizing data, and working with images, video, spreadsheets, among other ideas. Check out her suggestions in How Do I Solve [insert problem here] With Python?

Other Tutorials

• If you feel like you're ready for more tutorials, you should check out Google's Python Class, a solid introduction that also begins to explore intermediate concepts and modules.
• To begin using Python for manipulating and analyzing text based data, check out Python Programming for the Humanities, and jump straight into chapter 2.
• For those interested in more general computer science concepts, How to Think Like a Computer Scientist - Python Edition offers a good introduction to python.
• If you learn best by watching videos, Paul Vierthaler’s recorded and uploaded his DH class, Hacking the Humanities, to Youtube. Includes a general introduction to coding principles, introduction to python, with emphasis on text analysis, data manipulation, and web scraping.
• If you learn best by copying and practicing, Learn Python the Hard Way, by Zed A. Shaw, is an excellent a hands-on resource. Although the online and print book versions cost money, you can test out a sample for free.

Projects or Challenges to Try

• Automate the Boring Stuff contains many little projects for strengthening beginner and intermediate python skills. You might play around with regular expressions (or regex), which is a method for locating and manipulating certain patterns of text (think of it like a high powered ctrl-F). Once you feel more comfortable with regex, you might write a program that organizes or renames the files on your computer. Just be sure to practice with a sample folder & files before moving on to your own documents!
• Interested in web scraping (aka grabbing information from the web)? The python library requests handles requests over the internet. See this handy step-by-step tutorial on Real Python.
• Advanced Challenge: This is more complicated stuff, but if you're interested in working with CSV data and visualization techniques, you might check out Python libraries for data analysis, like Bokeh and Pandas. See Programming Historian's Visualizing Data with Bokeh and Pandas for a tutorial. To learn more about Pandas from the ground up, check out Learn Data Science's useful introduction.

Discussion Questions

• What kind of data types are available? What is the difference between a string and a list? Why do these differences matter?
• Describe the process of using both a text editor and a terminal to write and execute Python scripts.
• How do you write a program that can "make decisions" based on certain conditions? What are the parts that you would need?
• In what ways does the internet (using google) help someone to use and learn Python?
• What are "libraries" or "modules", where do they come from, and what are they used for?