blaze
py-spy
| blaze | py-spy | |
|---|---|---|
| 8 | 25 | |
| 902 | 11,913 | |
| 5.4% | - | |
| 9.3 | 6.4 | |
| 2 days ago | 10 days ago | |
| Rust | Rust | |
| Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
blaze
- Blaze: Fast query execution engine for Apache Spark
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š¼ Pandas 2.0 Up To 32x Faster
There is a project called blaze that aims to convert Spark plans into datafusion plans to run it more efficiently.
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Run SQL on CSV, Parquet, JSON, Arrow, Unix Pipes and Google Sheet
Datafusion out performs spark by a large margin. It is on par with photon, see benchmark at https://github.com/blaze-init/blaze.
- Anouncing Blaze: A Rustified OpenCL Experience
- Blaze: A Rust-based vectorized accelerator to speed up your Spark jobs with less resources
- Blaze: A Rust-based vectorized accelerator to speed up your Spark jobs
- Blaze: a Rust-based vectorized accelerator to speed up your Spark jobs with fewer resources.
py-spy
- Minha jornada de otimizaĆ§Ć£o de uma aplicaĆ§Ć£o django
- Graphical Python Profiler
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Grasshopper ā An Open Source Python Library for Load Testing
For CPU cycles, py-spy[0] is getting more and more used. For RAM, I would like to known too...
[0] -- https://github.com/benfred/py-spy
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Debugging a Mixed Python and C Language Stack
Theres also Py Spy, a profiling tool that can generate flame charts containing a mix of python and C (or C++) calls.
https://github.com/benfred/py-spy
It's worked really well for my needs
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python to rust migration
You should profile your consumer to check the bottlenecks. You can use the excellent py-spy(written in Rust). IMO a few usage of Numba there and there should solve your performance issues.
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Has anyone switched from numpy to Rust?
So as a first step you'll want to profile your program to figure out where it's slow, and hopefully that'll also tell you why it's slow. I'm the (biased) author of the Sciagraph profiler which is designed for this sort of application (https://sciagraph.com) but you can also try py-spy, which isn't as well designed for data processing/analysis applications (e.g. it won't visualize parallelism at all) but can still be informative (https://github.com/benfred/py-spy). Both are written in Rust ;)
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Trace your Python process line by line with minimal overhead!
Any advantages/disadvantages compared to py-spy [1]?
[1]: https://github.com/benfred/py-spy
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Python 3.11 delivers.
Python profiling is enabled primarily through cprofile, and can be visualized with help of tools like snakeviz (output flame graph can look like this). There are also memory profilers like memray which does in-depth traces, or sampling profilers like py-spy.
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Tales of serving ML models with low-latency
A good profiler would be https://github.com/benfred/py-spy . If you run your app/benchmark with it, it should be able to draw a flamegraph telling you where the majority of time is spent. The info here is quite fine grained so it would already tell you where the bottleneck is. Without a full-fledged profiler you can also measure the timings in various parts of the code to understand where the bottleneck is.
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Profiling a Python library written in Rust (Maturin)
Might be worth raising an issue on py-spy (a python profiler written in rust which "supports profiling native python extensions written in languages like C/C++ or Cython" to see if that can close the loop.
What are some alternatives?
incubator-gluten - Gluten is a middle layer responsible for offloading JVM-based SQL engines' execution to native engines.
pyflame
dasel - Select, put and delete data from JSON, TOML, YAML, XML and CSV files with a single tool. Supports conversion between formats and can be used as a Go package.
pyinstrument - š“Ā Call stack profiler for Python. Shows you why your code is slow!
roapi - Create full-fledged APIs for slowly moving datasets without writing a single line of code.
python-uncompyle6 - A cross-version Python bytecode decompiler
zsv - zsv+lib: tabular data swiss-army knife CLI + world's fastest (simd) CSV parser
memory_profiler - Monitor Memory usage of Python code
octosql - OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL.
icecream - š¦ Never use print() to debug again.
lnav - Log file navigator
line_profiler