gilstats.py
A utility for dumping per-thread statistics for CPython GIL using eBPF (by sumerc)
h5py
HDF5 for Python -- The h5py package is a Pythonic interface to the HDF5 binary data format. (by h5py)
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| gilstats.py | h5py | |
|---|---|---|
| 1 | 5 | |
| 10 | 2,000 | |
| - | 1.1% | |
| 0.0 | 8.8 | |
| over 3 years ago | 1 day ago | |
| Python | Python | |
| MIT License | BSD 3-clause "New" or "Revised" License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
gilstats.py
Posts with mentions or reviews of gilstats.py.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-01-14.
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Tracing and visualizing the Python GIL with perf and VizTracer
Note: We also see that pthread_cond_timedwait is called, this is what https://github.com/sumerc/gilstats.py uses for a eBPF tool, in case you are interested in other mutexes.
h5py
Posts with mentions or reviews of h5py.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-09-26.
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Working with data files too large for RAM
There's some good answers here, but another option I haven't seen suggested: Convert your txt file to HDF5 (Regardless if you follow my approach here, you should really consider converting your data to anything but a txt file). There's a nice library for working with it in python called h5py. The HDF format is designed specifically with working with very large sets of data (it even has compression options), often scientific in nature, but it's not a database. As far as how this fixes the specific issue you you've described, you can utilize numpy slicing to load one chunk your data at a time. Here's a stackoverflow answer which discusses a solution.
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How to combine multiple numpy arrays stored on disk which are too big to fit in RAM?
If it is a dataset, it should consist of individual instances. You could store these instances in separate files. Otherwise, HDF5 is a very convenient storage format. It allows random read/write access to elements of arrays stored on disk and has excellent Python support in form of the h5py package.
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Is Python really this slow?
If possible, try to monitor your memory usage during execution and if you see that you are consistently exceeding ~50% (my own rule of thumb, though you may want to discuss this with others as well) of what's available. If you are consistently using most of the available memory, then it's likely worth taking a moment to evaluate whether you can operate on subsets of the data from start to finish, and leave the rest of the data on disk until you are almost ready to use it. Tools like h5py are very helpful in these kinds of situations.
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Python packages as API end points.
Yea - I really struggled with getting the correct version on h5py to work with both tensorflow and allenai nlp modules. May be its about finding the right version of libraries. Github Issue. I ended up using pickle to save stuff, like John who commented on 26/03/2020 on the same(closed) issue.
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Tracing and visualizing the Python GIL with perf and VizTracer
Apply these to more issues, like in https://github.com/h5py/h5py/issues/1516
What are some alternatives?
When comparing gilstats.py and h5py you can also consider the following projects:
gil_load - Utility for measuring the fraction of time the CPython GIL is held
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
hBPF - hBPF = eBPF in hardware
Numba - NumPy aware dynamic Python compiler using LLVM
viztracer - VizTracer is a low-overhead logging/debugging/profiling tool that can trace and visualize your python code execution.
per4m - Profiling and tracing information for Python using viztracer and perf, the GIL exposed.
CPython - The Python programming language