#137: Advanced Python testing and big-time diffs
Sponsored by Rollbar: https://pythonbytes.fm/rollbar
- Tristan Hume, writing about a university project
- Teams of up to 3 people, multi month, write a Java to x86 compiler in language of choice
- Needed to pass both known and unknown tests.
- Secret tests to be run after submission encouraged teams to add more testing than provided.
- Nothing but standard libraries, and no parsing libraries, even if in standard.
- Lines of code
- Rust baseline
- Haskell: 1-1.6x
- C++: 1.4x
- Rust (another team): 3x
- Scala: 0.7 x
- OCaml: 1-1.6x
- Python: about half the size
- Python version
- one person
- used metaprogramming
- more extra features than any other team
- passed all public and secret tests
- via Len Wanger
- Pylustrator is a program to style your matplotlib plots for publication.
- Subplots can be resized and dragged around by the mouse, text and annotations can be added.
- Changes can be saved to the initial plot file as python code.
Brian #3: MongoDB 4.2
- Distributed Transactions
- extends multi-document ACID transactions across documents, collections, dbs in a replica set, and sharded cluster.
- Field Level Encryption
- encryption done on client side
- satisfies GDPR by allowing customer key destruction rendering server data on customer useless.
- system administration can be done with no exposure to private data
- via François Leblanc
- DeepDiff: Deep Difference of dictionaries, iterables, strings and other objects. It will recursively look for all the changes.
- Lots of nice touches:
- List difference ignoring order or duplicates
- Report repetitions
- Exclude certain types from comparison
- Exclude part of your object tree from comparison
- Significant Digits
- DeepSearch: Search for objects within other objects.
- DeepHash: Hash of ANY python object based on its contents even if the object is not considered hashable! DeepHash is supposed to be deterministic in order to make sure 2 objects that contain the same data, produce the same hash.
Brian #5: Advanced Python Testing
- Josh Peak
- “This article is mostly for me to process my thoughts but also to pave a path for anyone that wants to follow a similar journey on some more advanced python testing topics.”
- Learning journey (including some great podcasts and an awesome book on testing)
- Testing tools
- basic test structure
- adding black to testing with pytest-black
- linting with pylint
- including a very cool speed up trick to only lint modified files.
- flake8, including docstring checking
- tox.ini modifications
- code coverage goals and how to ratchet up to that goal with
- cool learning: “Increase code coverage by testing more code OR deleting code.”
- fixtures for database connections
- utilizing mocks, spies, stubs, and monkey patches, including
pytest-vcrto save network interactions and replay them in future test runs, resulting in a 10x speedup.
- Lots of links and tangents possible from this article.
Michael #6: Understanding Python's del
- via Kevin Buchs
- Official docs
- General confusion of what this does
- Looks like memory management, and it mostly isn’t
- Primary use: remove an item from a list given its index instead of its value or from a dictionary given its key:
del person['profession'] # person is a dict
- del statement can also be used to remove slices from a list
- del can also be used to delete entire variables:
- Recently covered how The CPython Bytecode Compiler is Dumb. Proactive dels could help.
- Pynsource: Reverse engineer Python source code into UML diagrams (via Anders Klint)
- Language Bar chart race (via Josh Thurston)
- My Local maximum appearance.
Optimist: The glass is half full. Pessimist: The glass is half empty. Programmer: The glass is twice as large as necessary.
Pragmatist: allowing room for requirements oversights, scope creep, and schedule overrun.
From “The Upside” with Kevin Hart and Bryan Cranston (watched it last night): K: Would you invest in <business idea>? B: That seems too niche. K: What’s “niche” mean? B: It’s the girl version of “nephew”.