TOP 10 of Python Weekly trend on Github
Tags: opensource, python
Published: 2018-09-17 07:49:19

---
title: TOP 10 of Python Weekly trend on Github
published: true
description: 
tags: opensource, python
---

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---

## TheAlgorithms / Python
![img](https://camo.githubusercontent.com/40b8099e638526dce298f8dc91246173d56e389a/68747470733a2f2f75706c6f61642e77696b696d656469612e6f72672f77696b6970656469612f636f6d6d6f6e732f7468756d622f382f38332f427562626c65736f72742d6564697465642d636f6c6f722e7376672f32323070782d427562626c65736f72742d6564697465642d636f6c6f722e7376672e706e67)
All algorithms implemented in Python (for education)
These are for demonstration purposes only. There are many implementations of sorts in the Python standard library that are much better for performance reasons.

[GitHub - TheAlgorithms/Python: All Algorithms implemented in Python](https://github.com/TheAlgorithms/Python)

## mwouts / jupytext
![img](https://thepracticaldev.s3.amazonaws.com/i/hdd8xzi9fz8230hf3xl2.gif)
Jupyter notebooks as Markdown documents, Julia, Python or R scripts.
Jupytext can convert notebooks to and from Julia, Python and R scripts (extensions .jl, .py and .R),
Markdown documents (extension .md),
R Markdown documents (extension .Rmd).
Jupytext is available from within Jupyter. You can work as usual on your notebook in Jupyter, and save and read it in the formats you choose. 

[GitHub - mwouts/jupytext: Jupyter notebooks as Markdown documents, Julia, Python or R scripts](https://github.com/mwouts/jupytext)


## donnemartin/system-design-primer
![img](https://camo.githubusercontent.com/e45e39c36eebcc4c66e1aecd4e4145112d8e88e3/687474703a2f2f692e696d6775722e636f6d2f6a6a3341354e382e706e67)
Learn how to design large-scale systems. 
Prep for the system design interview. 
Includes Anki flashcards.
Summaries of various system design topics, including pros and cons. Everything is a trade-off.
Each section contains links to more in-depth resources.

[GitHub - donnemartin/system-design-primer: Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.](https://github.com/donnemartin/system-design-primer)


## TensorFlow Models
This repository contains a number of different models implemented in [TensorFlow](https://www.tensorflow.org/)


The [official models](https://github.com/tensorflow/models/blob/master/official) are a collection of example models that use TensorFlow's high-level APIs. They are intended to be well-maintained, tested, and kept up to date with the latest stable TensorFlow API. They should also be reasonably optimized for fast performance while still being easy to read. We especially recommend newer TensorFlow users to start here.

The research models are a large collection of models implemented in TensorFlow by researchers. They are not officially supported or available in release branches; it is up to the individual researchers to maintain the models 
and/or provide support on issues and pull requests.

The samples folder contains code snippets and smaller models that demonstrate features of TensorFlow, including code presented in various blog posts.

The tutorials folder is a collection of models described in the [TensorFlow tutorials](https://www.tensorflow.org/tutorials/).

[GitHub - donnemartin/system-design-primer: Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.](https://github.com/donnemartin/system-design-primer)


## tensorflow/tensorboard

TensorBoard is a suite of web applications for inspecting and understanding your TensorFlow runs and graphs.
This README gives an overview of key concepts in TensorBoard, as well as how to interpret the visualizations TensorBoard provides. For an in-depth example of using TensorBoard, see the tutorial: TensorBoard: Visualizing Learning. For in-depth information on the Graph Visualizer, see this tutorial: TensorBoard: Graph Visualization.

[tensorflow · GitHub](https://github.com/tensorflow)

## django/django
![img](https://caktus-website-production-2015.s3.amazonaws.com/media/blog-images/django-logo.gif)

Django is a high-level Python Web framework that encourages rapid development and clean, pragmatic design. Thanks for checking it out.
All documentation is in the "docs" directory and online at https://docs.djangoproject.com/en/stable/. 
If you're just getting started, here's how we recommend you read the docs:
First, read docs/intro/install.txt for instructions on installing Django.

[GitHub - django/django: The Web framework for perfectionists with deadlines.](https://github.com/django/django)


## vinta/awesome-python
**Awesome Python **
A curated list of awesome Python frameworks, libraries, software and resources.
* Awesome Python
* Admin Panels
* Algorithms and Design Patterns
* Anti-spam
* Asset Management

And many others.

[GitHub - vinta/awesome-python: A curated list of awesome Python frameworks, libraries, software and resources](https://github.com/vinta/awesome-python)


## everhide/everbug
![img](https://github.com/everhide/everbug/raw/master/.preview.gif)
The Everbug is a lightweight Django middleware for Chrome/Firefox extension with easy install.
One of the advantages: the response body of target page remains clean and unchanged.

[GitHub - everhide/everbug: Django debug tool for browser](https://github.com/everhide/everbug)


## junfu1115/DANet
![img](https://github.com/junfu1115/DANet/raw/master/img/overview.png)
Propose a Dual Attention Network (DANet) to adaptively integrate local features with their global dependencies based on the self-attention mechanism. 
And they achieve new state-of-the-art segmentation performance on three challenging scene segmentation datasets, i.e., Cityscapes, PASCAL Context and COCO Stuff-10k dataset.

[GitHub - junfu1115/DANet: Dual Attention Network for Scene Segmentation](https://github.com/junfu1115/DANet)

## facebookincubator/python-nubia
![img](https://github.com/facebookincubator/python-nubia/raw/master/docs/interactive.gif?raw=true)
Nubia is a lightweight framework for building command-line applications with Python. 
It was originally designed for the “logdevice interactive shell (aka. ldshell)” at Facebook. 
Since then it was factored out to be a reusable component and several internal Facebook projects now rely on it as a quick and easy way to get an intuitive shell/cli application without too much boilerplate.
Nubia is built on top of python-prompt-toolkit which is a fantastic toolkit for building interactive command-line applications.

[GitHub - facebookincubator/python-nubia: A command-line and interactive shell framework.](https://github.com/facebookincubator/python-nubia)

---

This post is curated by [IssueHunt](https://issuehunt.io/) that a bounty platform for open-source projects.

It is the easiest monetize way for OSS.

https://issuehunt.io/

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