static-frame
mpire
static-frame | mpire | |
---|---|---|
8 | 8 | |
438 | 2,009 | |
2.1% | 0.5% | |
9.8 | 7.0 | |
8 days ago | 3 months ago | |
Python | Python | |
GNU General Public License v3.0 or later | 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.
static-frame
- Static-frame: Immutable/statically-typed DataFrames with runtime type validation
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Type-Hinting DataFrames for Static Analysis and Runtime Validation
This is inadequate, as it ignores the types contained within the container. A DataFrame might have string column labels and three columns of integer, string, and floating-point values; these characteristics define the type. A function argument with such type hints provides developers, static analyzers, and runtime checkers with all the information needed to understand the expectations of the interface. StaticFrame 2 now permits this:
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Memoizing DataFrame Functions: Using Hashable DataFrames and Message Digests to Optimize Repeated Calculations
StaticFrame is an alternative DataFrame library that offers efficient solutions to this problem, both for in-memory and disk-based memoization.
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The Performance Advantage of No-Copy DataFrame Operations
A NumPy array is a Python object that stores data in a contiguous C-array buffer. The excellent performance of these arrays comes not only from this compact representation, but also from the ability of arrays to share "views" of that buffer among many arrays. NumPy makes frequent use of "no-copy" array operations, producing derived arrays without copying underling data buffers. By taking full advantage of NumPy's efficiency, the StaticFrame DataFrame library offers orders-of-magnitude better performance than Pandas for many common operations.
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Which not so well known Python packages do you like to use on a regular basis and why?
static-frame. An immutable alternative to pandas.
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One Fill Value Is Not Enough: Preserving Columnar Types When Reindexing DataFrames
StaticFrame is an immutable DataFrame library that offers solutions to such problems. In StaticFrame, alternative fill value representations can be used to preserve columnar types in reindexing, shifting, and many other operations that require fill_value arguments. For operations on heterogeneously typed columnar data, one fill value is simply not enough.
- static-frame: Immutable and grow-only Pandas-like DataFrames with a more explicit and consistent interface.
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Bug Sur 11.4 stuttering issues on RX 6800
For me, one example of high cpu usage is when i visit links like this one (https://github.com/InvestmentSystems/static-frame/blob/master/static_frame/performance/core.py) on GitHub. Safari is extremely laggy when i do nothing more than just scrolling around. Do you have sth like this?
mpire
- GitHub - sybrenjansen/mpire: A Python package for easy multiprocessing, but faster than multiprocessing
- Mpire: A Python package for easier and faster multiprocessing
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Which not so well known Python packages do you like to use on a regular basis and why?
mpire for multiprocessing.
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How do you deal with parallelising parts of an ML pipeline especially on Python?
https://github.com/Slimmer-AI/mpire is a nice lib, with better performance than multiprocessing.
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Dask – a flexible library for parallel computing in Python
Shout out to an alternative to Dask: MPIRE https://github.com/Slimmer-AI/mpire
- Multi-Threading in Python
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I'd like to introduce MPIRE: MultiProcessing Is Really Easy
After several iterations of feedback and exposure to production environments, it is now the go-to multiprocessing library at Slimmer AI. Recently, we’ve made it publicly available on GitHub (https://github.com/Slimmer-AI/mpire).
What are some alternatives?
pandas-ta - Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 150+ Indicators
Dask - Parallel computing with task scheduling
pandastable - Table analysis in Tkinter using pandas DataFrames.
cudf - cuDF - GPU DataFrame Library
python-lenses - A python lens library for manipulating deeply nested immutable structures
distributed - A distributed task scheduler for Dask
bidict - The bidirectional mapping library for Python.
pathml - Tools for computational pathology
bambi - BAyesian Model-Building Interface (Bambi) in Python.
cunumeric - An Aspiring Drop-In Replacement for NumPy at Scale
rubygems - Library packaging and distribution for Ruby.
pyroute2 - Python Netlink and PF_ROUTE library — network configuration and monitoring