sqlfluff
mypy
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sqlfluff | mypy | |
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35 | 112 | |
7,199 | 17,541 | |
2.1% | 1.4% | |
9.6 | 9.7 | |
4 days ago | 1 day ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 or later |
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sqlfluff
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🐍🐍 23 issues to grow yourself as an exceptional open-source Python expert 🧑💻 🥇
Repo : https://github.com/sqlfluff/sqlfluff
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SQL Reserved Words – The Empirical List
I'm surprised sqlfluff hasn't been mentioned yet. Perhaps not a comprehensive list, but it's worked for everything I've thrown at it. There's an ANSI keyword list [0], and then dialect-specific lists for everything from DB2 [1] to Snowflake [2].
[0]: https://github.com/sqlfluff/sqlfluff/blob/main/src/sqlfluff/...
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Show HN: Postgres Language Server
It has tons of annoying quirks, but I couldn't imagine running a DBT project without it: https://github.com/sqlfluff/sqlfluff
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Front page news headline scraping data engineering project
Move SQL queries to sql files and read from files (Use sqlfluff to lint the code https://github.com/sqlfluff/sqlfluff)
- Anything like SQLFluff written in Rust?
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Code autoformatter for SQL in VSCode that plays nicely with dbt
SQLFluff is a good CLI tool for this and includes support for jinja and dbt. I don't think there's a VSCode plugin for it yet.
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Ask HN: How do you test SQL?
This linter can really enforce some best practices https://github.com/sqlfluff/sqlfluff
A list of best practices:
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What is something you would learn at college but not a bootcamp (hard skills)
BigQuery SQL and SQLFluff
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Is the knowledge on how Compilers work applicable to the role of a Data Engineer?
There's a SQL parser/linter called SQLFluff that my team uses for our CI/CD. I've made a few pull requests to fix the parser for the particular SQL dialect we used, and my college compiler classes definitely helped.
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sqlfluff VS ANTLR - a user suggested alternative
2 projects | 12 Dec 2022
mypy
- The GIL can now be disabled in Python's main branch
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Polars – A bird's eye view of Polars
It's got type annotations and mypy has a discussion about it here as well: https://github.com/python/mypy/issues/1282
- Static Typing for Python
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Python 3.13 Gets a JIT
There is already an AOT compiler for Python: Nuitka[0]. But I don't think it's much faster.
And then there is mypyc[1] which uses mypy's static type annotations but is only slightly faster.
And various other compilers like Numba and Cython that work with specialized dialects of Python to achieve better results, but then it's not quite Python anymore.
[0] https://nuitka.net/
[1] https://github.com/python/mypy/tree/master/mypyc
- Introducing Flask-Muck: How To Build a Comprehensive Flask REST API in 5 Minutes
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WeveAllBeenThere
In Python there is MyPy that can help with this. https://www.mypy-lang.org/
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It's Time for a Change: Datetime.utcnow() Is Now Deprecated
It's funny you should say this.
Reading this article prompted me to future-proof a program I maintain for fun that deals with time; it had one use of utcnow, which I fixed.
And then I tripped over a runtime type problem in an unrelated area of the code, despite the code being green under "mypy --strict". (and "100% coverage" from tests, except this particular exception only occured in a "# pragma: no-cover" codepath so it wasn't actually covered)
It turns out that because of some core decisions about how datetime objects work, `datetime.date.today() < datetime.datetime.now()` type-checks but gives a TypeError at runtime. Oops. (cause discussed at length in https://github.com/python/mypy/issues/9015 but without action for 3 years)
One solution is apparently to use `datetype` for type annotations (while continuing to use `datetime` objects at runtime): https://github.com/glyph/DateType
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What's New in Python 3.12
PEP 695 is great. I've been using mypy every day at work in last couple years or so with very strict parameters (no any type etc) and I have experience writing real life programs with Rust, Agda, and some Haskell before, so I'm familiar with strict type systems. I'm sure many will disagree with me but these are my very honest opinions as a professional who uses Python types every day:
* Some types are better than no types. I love Python types, and I consider them required. Even if they're not type-checked they're better than no types. If they're type-checked it's even better. If things are typed properly (no any etc) and type-checked that's even better. And so on...
* Having said this, Python's type system as checked by mypy feels like a toy type system. It's very easy to fool it, and you need to be careful so that type-checking actually fails badly formed programs.
* The biggest issue I face are exceptions. Community discussed this many times [1] [2] and the overall consensus is to not check exceptions. I personally disagree as if you have a Python program that's meticulously typed and type-checked exceptions still cause bad states and since Python code uses exceptions liberally, it's pretty easy to accidentally go to a bad state. E.g. in the linked github issue JukkaL (developer) claims checking things like "KeyError" will create too many false positives, I strongly disagree. If a function can realistically raise a "KeyError" the program should be properly written to accept this at some level otherwise something that returns type T but 0.01% of the time raises "KeyError" should actually be typed "Raises[T, KeyError]".
* PEP 695 will help because typing things particularly is very helpful. Often you want to pass bunch of Ts around but since this is impractical some devs resort to passing "dict[str, Any]"s around and thus things type-check but you still get "KeyError" left and right. It's better to have "SomeStructure[T]" types with "T" as your custom data type (whether dataclass, or pydantic, or traditional class) so that type system has more opportunities to reject bad programs.
* Overall, I'm personally very optimistic about the future of types in Python!
[1] https://github.com/python/mypy/issues/1773
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Mypy 1.6 Released
# is fixed: https://github.com/python/mypy/issues/12987.
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Ask HN: Why are all of the best back end web frameworks dynamically typed?
You probably already know but you can add type hints and then check for consistency with https://github.com/python/mypy in python.
Modern Python with things like https://learnpython.com/blog/python-match-case-statement/ + mypy + Ruff for linting https://github.com/astral-sh/ruff can get pretty good results.
I found typed dataclasses (https://docs.python.org/3/library/dataclasses.html) in python using mypy to give me really high confidence when building data representations.
What are some alternatives?
vscode-sqlfluff - An extension to use the sqlfluff linter in vscode.
pyright - Static Type Checker for Python
sqlparse - A non-validating SQL parser module for Python
ruff - An extremely fast Python linter and code formatter, written in Rust.
dbt-utils - Utility functions for dbt projects.
pyre-check - Performant type-checking for python.
ale - Check syntax in Vim/Neovim asynchronously and fix files, with Language Server Protocol (LSP) support
black - The uncompromising Python code formatter
soda-sql - Data profiling, testing, and monitoring for SQL accessible data.
pytype - A static type analyzer for Python code
Metabase - The simplest, fastest way to get business intelligence and analytics to everyone in your company :yum:
pydantic - Data validation using Python type hints