tealsql
polars
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tealsql
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Tealr 0.8 just released. Document your lua apis!
A project that uses tealr can be found at https://github.com/lenscas/tealsql/tree/master/pgteal, with online documentation available over at https://lenscas.github.io/tealsql/
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Man, I love this language.
There is also https://github.com/lenscas/tealsql which is used as kind of showcase project for tealr and tealr_doc_gen. While at the same time (hopefully) filling a pain point in the lua/teal eco system.
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What's everyone working on this week (7/2022)?
tealsql, my sql library for lua: Right now, it is being used to dog feed the changes in tealr. So, mostly improving its documentation, and preparing it to release it.
- What's everyone working on this week (6/2022)?
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What's everyone working on this week (39/2021)?
last weekend I put in some more time in tealsql, a postgresql client written in Rust for lua/teal.
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What's everyone working on this week (33/2021)?
The main focus is my sql client for teal/lua https://github.com/lenscas/tealsql , mainly getting rid of every part in the api that doesn't have a good type yet on the teal side of things (any, {any:any}, etc.
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What's everyone working on this week (29/2021)?
tealsql, an sql client for teal/lua. Current plan is to get the async api finished (right now it ignores every error but otherwise works without problems).
polars
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Why Python's Integer Division Floors (2010)
This is because 0.1 is in actuality the floating point value value 0.1000000000000000055511151231257827021181583404541015625, and thus 1 divided by it is ever so slightly smaller than 10. Nevertheless, fpround(1 / fpround(1 / 10)) = 10 exactly.
I found out about this recently because in Polars I defined a // b for floats to be (a / b).floor(), which does return 10 for this computation. Since Python's correctly-rounded division is rather expensive, I chose to stick to this (more context: https://github.com/pola-rs/polars/issues/14596#issuecomment-...).
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Polars
https://github.com/pola-rs/polars/releases/tag/py-0.19.0
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Stuff I Learned during Hanukkah of Data 2023
That turned out to be related to pola-rs/polars#11912, and this linked comment provided a deceptively simple solution - use PARSE_DECLTYPES when creating the connection:
- Polars 0.20 Released
- Segunda linguagem
- Polars: Dataframes powered by a multithreaded query engine, written in Rust
- Summing columns in remote Parquet files using DuckDB
- Polars 0.34 is released. (A query engine focussing on DataFrame front ends)
What are some alternatives?
youki - A container runtime written in Rust
vaex - Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀
koto - A simple, expressive, embeddable programming language, made with Rust
modin - Modin: Scale your Pandas workflows by changing a single line of code
tealr - A wrapper around mlua and rlua to generate documentation and other helpers
datafusion - Apache DataFusion SQL Query Engine
rhyme-es
DataFrames.jl - In-memory tabular data in Julia
synth - The Declarative Data Generator
datatable - A Python package for manipulating 2-dimensional tabular data structures
txrx
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing