Tools & Workflow

The everyday developer toolkit: pip and virtual environments, debugging, logging, testing, and the workflow habits that make coding smoother.

What this course covers

1. pip: Install Magic Libraries
2. Virtual Environments: Sandbox Your Code
3. Debugging: Finding the Bug
4. Logging: Track What Happens
5. Read an Error Like a Detective
6. enumerate & zip
7. Counting with Counter
8. Working with Dates
9. Sanity Checks with assert
10. Timing Your Code
11. Version Control with Git
12. Command-Line Tools with argparse
13. Modern File Paths with pathlib
14. Regular Expressions
15. Automated Testing
16. Python Project Structure
17. Code Style: Black, Ruff, and PEP 8
18. JSON: The Data Exchange Language
19. CSV: Rows of Data
20. Environment Variables
21. defaultdict and namedtuple
22. Comprehensions: Collections in One Line
23. f-strings: Formatting Mastery
24. Sorting with Keys
25. Sets: Unique and Fast
26. String Methods Power Hour
27. pprint: Readable Data Dumps
28. Random and Seeds
29. The math Module
30. try/except: Graceful Failure
31. raise: Your Own Errors
32. Type Hints: Promises About Types
33. dataclasses: Data Classes the Easy Way
34. secrets: Safe Randomness
35. hashlib: Fingerprints for Data
36. File-Like Objects: io.StringIO
37. Debug Printing Done Right
38. itertools: chain and product
39. pip Deep Dive: freeze, show, uninstall
40. Capstone: A Pocket Toolkit

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