Top 15 Python Fast Projects
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Project mention: Tkinter-Designer - Create Beautiful Tkinter GUIs by Drag and Drop ☄️ | reddit.com/r/github_trends | 2022-05-04
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Scout APM
Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.
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Fast Array Manipulation in Python: Since Numpy is the de facto standard for storing multi-dimensional data, any performance gain you see using librapid math kernels will need to be realized on data which probably started its life as a numpy array, and needs to be passed to another tool as a numpy array. Hopefully there will be (or already is?) a way to build a librapid array out of a numpy array without copying the data and vice versa. In fact I might suggest that librapid focus on the fast math operations and simply become an accelerator for numpy arrays. For instance, look at CuPy which provides GPU-implemented operations within a numpy-compatible API, and Bottleneck which simply provides fast C-based implementations of some otherwise slow parts of Numpy. Also note that numpy *can* be multi-threaded depending on the operation and some environment variables. Single-threaded to Single-threaded I think you will be hard-pressed to beat Numpy on general math operations, but that doesn't mean there aren't specific "kernels" that are more specialized that can be greatly improved with a C++ back-end.
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Install NExfil in Ubuntu 20.04 LTS git clone https://github.com/thewhiteh4t/nexfil.git cd nexfil pip3 install -r requirements.txt
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JetBrains
Developer Ecosystem Survey 2022. Take part in the Developer Ecosystem Survey 2022 by JetBrains and get a chance to win a Macbook, a Nvidia graphics card, or other prizes. We’ll create an infographic full of stats, and you’ll get personalized results so you can compare yourself with other developers.
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Project mention: [P] What we learned by making T5-large 2X faster than Pytorch (and any autoregressive transformer) | reddit.com/r/MachineLearning | 2022-05-23
Microsoft Onnx Runtime T5 export tool / FastT5: to support caching, it exports 2 times the decoder part, one with cache, and one without (for the first generated token). So the memory footprint is doubled, which makes the solution difficult to use for these large transformer models.
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Moodle-Downloader-2
A Moodle downloader that downloads course content fast from Moodle (eg. lecture pdfs)
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quickai
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
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STYLER
Official repository of STYLER: Style Factor Modeling with Rapidity and Robustness via Speech Decomposition for Expressive and Controllable Neural Text to Speech, INTERSPEECH 2021 (by keonlee9420)
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FrameRecorder
Imagine you are drawing pictures or writing a program on your computer. Wouldn't you like to shoot small clips of your work while doing this? That's when Frame Recorder comes to your aid. It will save it for you! See hours of process in just a few minutes!
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Maat
Validation and transformation library powered by deductive ascending parser. Made to be extended for any kind of project.
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PasswordListGenerator
This Porjects goal is to automate a large password list with given attributes from a user such as {Name, Last Name, Middle Name, Birthday, favorite....}
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Index
What are some of the best open-source Fast projects in Python? This list will help you:
Project | Stars | |
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1 | Tkinter-Designer | 4,222 |
2 | magnitude | 1,517 |
3 | bottleneck | 755 |
4 | nexfil | 697 |
5 | try | 635 |
6 | numpy-stl | 464 |
7 | segyio | 372 |
8 | fastT5 | 302 |
9 | Moodle-Downloader-2 | 257 |
10 | quickai | 139 |
11 | STYLER | 99 |
12 | FrameRecorder | 40 |
13 | Maat | 26 |
14 | yapic.json | 15 |
15 | PasswordListGenerator | 8 |
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