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Top 9 Python Performance analysis Projects
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scalene
Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals
I collected a list of profilers (also memory profilers, also specifically for Python) here: https://github.com/albertz/wiki/blob/master/profiling.md
Currently I actually need a Python memory profiler, because I want to figure out whether there is some memory leak in my application (PyTorch based training script), and where exactly (in this case, it's not a problem of GPU memory, but CPU memory).
I tried Scalene (https://github.com/plasma-umass/scalene), which seems to be powerful, but somehow the output it gives me is not useful at all? It doesn't really give me a flamegraph, or a list of the top lines with memory allocations, but instead it gives me a listing of all source code lines, and prints some (very sparse) information on each line. So I need to search through that listing now by hand to find the spots? Maybe I just don't know how to use it properly.
I tried Memray, but first ran into an issue (https://github.com/bloomberg/memray/issues/212), but after using some workaround, it worked now. I get a flamegraph out, but it doesn't really seem accurate? After a while, there don't seem to be any new memory allocations at all anymore, and I don't quite trust that this is correct.
There is also Austin (https://github.com/P403n1x87/austin), which I also wanted to try (have not yet).
Somehow this experience so far was very disappointing.
(Side node, I debugged some very strange memory allocation behavior of Python before, where all local variables were kept around after an exception, even though I made sure there is no reference anymore to the exception object, to the traceback, etc, and I even called frame.clear() for all frames to really clear it. It turns out, frame.f_locals will create another copy of all the local variables, and the exception object and all the locals in the other frame still stay alive until you access frame.f_locals again. At that point, it will sync the f_locals again with the real (fast) locals, and then it can finally free everything. It was quite annoying to find the source of this problem and to find workarounds for it. https://github.com/python/cpython/issues/113939)
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Project mention: Work with First, Second and Third Order Greeks Through the Finance Toolkit | news.ycombinator.com | 2024-01-17
Over the last year I've spend a significant amount of time creating a Finance Toolkit in Python, it currently features over 150+ different metrics such as financial ratios, models, risk and performance metrics, technical indicators, macro-economic parameters and since today also all Greeks.
The Finance Toolkit is written in Python and is meant as a free solution to acquire a large range of financial metrics. My goal is to make financial calculations accessible to everyone as there is no point in reinventing the wheel over and over again which I've seen countless of times happen given that I work in the Financial Sector myself.
If you are interested give it a go: https://github.com/JerBouma/FinanceToolkit and find the recent release notes here that talk about the Greeks: https://github.com/JerBouma/FinanceToolkit/releases/tag/v.1....
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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model_analyzer
Triton Model Analyzer is a CLI tool to help with better understanding of the compute and memory requirements of the Triton Inference Server models.
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python-benchmark-harness
A micro/macro benchmark framework for the Python programming language that helps with optimizing your software.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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STATS-PAL
A relatively simple but powerful heuristic that can automate performance test result analysis by using powerful statistics.
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NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
The latest post mention was on 2024-02-10.
Python Performance analysis related posts
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- Slipcover: Near Zero-Overhead Python Code Coverage
- Where can I apply for someone to take a serious look at my code and find improvements?
- I'm how to see python codes lines execute time.
- How can I make this code more lightweight?
- Measuring memory usage in Python: it’s tricky
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A note from our sponsor - WorkOS
workos.com | 15 Apr 2024
Index
What are some of the best open-source Performance analysis projects in Python? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | scalene | 11,061 |
| 2 | FinanceToolkit | 2,333 |
| 3 | model_analyzer | 370 |
| 4 | python-benchmark-harness | 147 |
| 5 | ros2_tracing | 127 |
| 6 | aws-python-utilities | 40 |
| 7 | django-db-benchmark | 24 |
| 8 | STATS-PAL | 23 |
| 9 | python-performance-playground | 4 |
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