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Python随身听-2020-10-02技术精选 #12

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de8ug opened this issue Oct 2, 2020 · 0 comments
Open

Python随身听-2020-10-02技术精选 #12

de8ug opened this issue Oct 2, 2020 · 0 comments

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@de8ug
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de8ug commented Oct 2, 2020

致读者:亲爱的「Python随身听」的观众们,这是由DE8UG的人工非智能给你带来的新的一期技术精选。
主要为编程初学者,开发工程师,算法工程师,数据分析师,运维,测试,运营,产品等各个岗位的Python爱好者带来Python世界的流行趋势,前沿技术。
你可以挑选自己喜欢的项目尽情玩耍,任何想法欢迎留言讨论。
本文的结构和内容会经常更新,每天10:24分左右发布,感谢订阅🆙和收藏☆。
(点击原文查看可点击的文档链接)

🤩Python随身听-技术精选: /huggingface/datasets

👉🤗 Fast, efficient, open-access datasets and evaluation metrics for Natural Language Processing and more in PyTorch, TensorFlow, NumPy and Pandas
😎TOPICS: nlp,datasets,metrics,evaluation,pytorch,tensorflow,pandas,numpy,natural-language-processing
⭐️STARS:3526, 今日上升数↑:132

👉README:



Build GitHub Documentation GitHub release https://github.com/huggingface/datasets


🤩Python随身听-技术精选: /anandpawara/Real_Time_Image_Animation

👉The Project is real time application in opencv using first order model
😎TOPICS: ``
⭐️STARS:2269, 今日上升数↑:125

👉README:

Real time Image Animation

The Project is real time application in opencv using first order model

Steps to setup

Step 1: Create virtual environment

Python version : python v3.7.3 or higher

create virual environment : pip install virtualenv

activate virtual environment : virtualenv env

Step 2: Activate virtual environment

For windows : env/Script/activate

For Linux : source env/bin/activate

Step 3 : Install required modules

Install modules : pip install -r requirements.txt

Install pytorch and torchvision : pip install torch===1.0.0 torchvision===0.2.1 -f https://download.pytorch.org/whl/cu100/torch_stable.html

Step 4 : Download cascade file ,weights and model and save in folder named extract

The file is also availible via direct link on Google's Drive:
https://drive.google.com/uc?id=1wCzJP1XJNB04vEORZvPjNz6drkXm5AUK

On Linux machine : unzip checkpoints.zip

If on windows platfrom unzip checkpoints.zi...

地址:https://github.com/anandpawara/Real_Time_Image_Animation


🤩Python随身听-技术精选: /mingrammer/diagrams

👉:art: Diagram as Code for prototyping cloud system architectures
😎TOPICS: diagram,diagram-as-code,drawing,architecture,prototyping
⭐️STARS:9583, 今日上升数↑:181

👉README:

Diagrams

Buy Me A Coffee

Diagram as Code.

Diagrams lets you draw the cloud system architecture in Python code. It was born for prototyping a new system architecture design without any design tools. You can also describe or visualize the existing system architecture as well. Diagrams currently supports main major providers including: AWS, Azure, GCP, Kubernetes, Alibaba Cloud, Oracle Cloud etc... It also supports On-Premise nodes, SaaS and major Programming frameworks and languages.

Diagram as Code also allows you to track the architecture diagram changes in any version control system.

NOTE: It does not control any actual cloud resources nor does it generate cloud formation or terr...

地址:https://github.com/mingrammer/diagrams


🤩Python随身听-技术精选: /NVlabs/imaginaire

👉NVIDIA PyTorch GAN library with distributed and mixed precision support
😎TOPICS: ``
⭐️STARS:643, 今日上升数↑:125

👉README:

imaginaire_logo.svg

Imaginaire

Docs | License | Installation | Model Zoo

Imaginaire is a pytorch library that contains
optimized implementation of several image and video synthesis methods developed at NVIDIA.

License

Imaginaire is released under NVIDIA Software license.
For commercial use, please consult researchinquiries@nvidia.com

What's inside?

We have a tutorial for each model. Click on the model name, and your browser should take you to the tutorial page for the project.

Supervised Image-to-Image Translation

|Algorithm Name | Feature | Publication |
|:------------------...

地址:https://github.com/NVlabs/imaginaire


🤩Python随身听-技术精选: /OpenMined/PySyft

👉A library for answering questions using data you cannot see
😎TOPICS: deep-learning,secure-computation,pytorch,privacy,cryptography,python,syft,federated-learning
⭐️STARS:6288, 今日上升数↑:44

👉README:

Introduction

PySyft is a Python library for secure and private Deep Learning. PySyft decouples private data from model training, using
Federated Learning,
Differential Privacy,
and Encrypted Computation (like
Multi-Party Computation (MPC)
and Homomorphic Encryption (HE))
within the main Deep Learning frameworks like PyTorch and TensorFlow. Join the movement on
Slack.

PySyft in Detail

A more detailed explanation of PySyft can be found in the
white paper on Arxiv

PySyft has also been explained in videos on YouTube:

地址:https://github.com/OpenMined/PySyft


🤩Python随身听-技术精选: /donnemartin/system-design-primer

👉Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
😎TOPICS: programming,development,design,design-system,system,design-patterns,web,web-application,webapp,python,interview,interview-questions,interview-practice
⭐️STARS:108328, 今日上升数↑:102

👉README:

*English日本語简体中文繁體中文 | العَرَبِيَّة‎বাংলাPortuguês do BrasilDeutschελληνικάעבריתItaliano한국어فارسیPolskiрусский языкEspañol ∙ [...

地址:https://github.com/donnemartin/system-design-primer


🤩Python随身听-技术精选: /ansible/ansible

👉Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy and maintain. Automate everything from code deployment to network configuration to cloud management, in a language that approaches plain English, using SSH, with no agents to install on remote systems. https://docs.ansible.com.
😎TOPICS: python,ansible
⭐️STARS:44945, 今日上升数↑:18

👉README:

|PyPI version| |Docs badge| |Chat badge| |Build Status| |Code Of Conduct| |Mailing Lists| |License| |CII Best Practices|


Ansible


Ansible is a radically simple IT automation system. It handles
configuration management, application deployment, cloud provisioning,
ad-hoc task execution, network automation, and multi-node orchestration. Ansible makes complex
changes like zero-downtime rolling updates with load balancers easy. More information on the Ansible website <https://ansible.com/>_.

Design Principles

  • Have a dead-simple setup process with a minimal learning curve.
  • Manage machines very quickly and in parallel.
  • Avoid custom-agents and additional open ports, be agentless by
    leveraging the existing SSH daemon.
  • Describe infrastructure in a language that is both machine and human
    friendly.
  • Focus on security and easy auditability/review/rewriting of content.
  • Manage new remote machines instantly, without bootstrapping any
    software.
  • Allow module d...

地址:https://github.com/ansible/ansible


🤩Python随身听-技术精选: /mytechnotalent/Python-For-Kids

👉A comprehensive and FREE Online Python Development course FOR KIDS utilizing an official BBC micro:bit Development Board going step-by-step into the world of Python for microcontrollers.
😎TOPICS: kids,kidscancode,python,microbit,pythonlearning,pythonforeverybody,pythonforkids,stem,mu,micropython,pythonforbeginner,kids-utilizing,tutorial,linkedin,article,microcontrollers,microcontroller,step-lessons,educator,educators
⭐️STARS:382, 今日上升数↑:53

👉README:

Python For Kids

A comprehensive and FREE Online Python Development course FOR KIDS utilizing an official BBC micro:bit Development Board going step-by-step into the world of Python for microcontrollers.

Lesson 1: Python For Kids (Part 1: Goals)

This tutorial will begin with the basic concepts of why kids should learn to program in Python.

-> Click HERE to read the article on LinkedIn.

Lesson 2: Python For Kids (Part 2: Install Mu IDE)

This tutorial will step-by-step help you get the Mu integrated development environment set up for you and your child to begin developing.

-> Click HERE to read the article on LinkedIn.

Lesson 3: Python For Kids (Part 3: "Hello World")

This tutorial will step-by-step code our first program to have our little microcontroller say hello to the world!

-> Click [HERE](https://www.linkedin.com/pulse/python-kids-...

地址:https://github.com/mytechnotalent/Python-For-Kids


🤩Python随身听-技术精选: /PaytmLabs/nerve

👉NERVE Continuous Vulnerability Scanner
😎TOPICS: security,security-tools,security-testing,vulnerability-scanners,vulnerability-assessment,vulnerability-detection
⭐️STARS:63, 今日上升数↑:12

👉README:

Network Exploitation, Reconnaissance & Vulnerability Engine (N.E.R.V.E)

Table of Contents

Continuous Security

We believe security scanning should be done continuously. Not daily, weekly, monthly, or quarterly.

The benefit of running security scanning contiuously can be any of the following:

  • You have a dynamic environment where infrastructure gets created every minute / hour / etc.
  • You want to be the first to catch issues before anyone else
  • You want the ability to respond quicker.

NERVE was created to address this problem. Commercial tools are great, but they are also heavy, ...

地址:https://github.com/PaytmLabs/nerve


🤩Python随身听-技术精选: /Pitt-CSC/Summer2021-Internships

👉Collection of Summer 2021 tech internships!
😎TOPICS: interview-preparation,internships
⭐️STARS:2058, 今日上升数↑:15

👉README:

Summer 2021 Internships ☀️👩‍💻

Use this repo to share and keep track of any tech-related internships. For a Google Sheet 📝 version of this repo (that remains in sync with this table) click here! For more tips on the internship process check out the Zero to Offer 📈 program here.

📫 Want weekly internship postings in your inbox? Join the internship newsletter here!

🎓 Check out our New Grad repo here.

🤗 Contribute by submitting a pull request or filling out this form! 🤗

The List 👔

Name Location Notes
Akuna Capital Boston, Chicago, International Locations
[Apple]...

地址:https://github.com/Pitt-CSC/Summer2021-Internships


🤩Python随身听-技术精选: /isocpp/CppCoreGuidelines

👉The C++ Core Guidelines are a set of tried-and-true guidelines, rules, and best practices about coding in C++
😎TOPICS: ``
⭐️STARS:28680, 今日上升数↑:18

👉README:

"Within C++ is a smaller, simpler, safer language struggling to get out."
-- Bjarne Stroustrup

The C++ Core Guidelines are a collaborative effort led by Bjarne Stroustrup, much like the C++ language itself. They are the result of many
person-years of discussion and design across a number of organizations. Their design encourages general applicability and broad adoption but
they can be freely copied and modified to meet your organization's needs.

Getting started

The guidelines themselves are found at CppCoreGuidelines. The document is in GH-flavored MarkDown. It is intentionally kept simple, mostly in ASCII, to allow automatic post-processing such as language translation and reformatting. The editors maintain one
version formatted for browsing. Note that it is manually integrated and can be slightly older than the version in the master branch.

...

地址:https://github.com/isocpp/CppCoreGuidelines


🤩Python随身听-技术精选: /domokane/FinancePy

👉A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.
😎TOPICS: risk,pricing,risk-management,asset-allocation,finance,valuation,python,derivatives-pricing,numba,bonds,students,fixed-income,derivatives,investment,currency,credit
⭐️STARS:138, 今日上升数↑:15

👉README:

Quick Start Guide

FinancePy can be installed from pip using the command:

pip install financepy

To upgrade an existing installation type:

pip install --upgrade financepy

Using FinancePy in a Jupyter Notebook

Once financepy has been installed, it is easy to get started.

Just download the project and examine the set of Jupyter Notebooks in the notebooks folder.

A pdf manual describing all of the functions can be found in the project directory.

Overview

FinancePy is a python-based library that is currently in beta version. It covers the following functionality:

  • Valuation and risk models for a wide range of equity, FX, interest rate and credit derivatives.

Although it is written entirely in Python, it can achieve speeds comparable to C++ by using Numba. As a result the user has both the ability to examine the underlying code and the ability to perform pricing and risk at speeds which compare to a library written in C++.

The target audience for this library includes:

  • Students wishing ...

地址:https://github.com/domokane/FinancePy


🤩Python随身听-技术精选: /Ciphey/Ciphey

👉⚡ Automatically decrypt encryptions without knowing the key or cipher, decode encodings, and crack hashes ⚡
😎TOPICS: decryption,natural-language-processing,cryptography,cipher,artificial-intelligence,ctf-tools,ctf,cpp,python,hacking,pentesting,deep-neural-network,hashes,cyberchef-magic,encryptions,encodings
⭐️STARS:4654, 今日上升数↑:32

👉README:

Translations
🇮🇩 ID 🇩🇪 DE 🇭🇺 HU 🇳🇱 NL 🇧🇷 PT-BR 🇷🇺 RU 🇫🇷 FR

➡️ Documentation | Discord | Installation Guide ⬅️
Ciphey

GitHub...
<p>地址:<a href=https://github.com/Ciphey/Ciphey


🤩Python随身听-技术精选: /vinayak-mehta/present

👉A terminal-based presentation tool with colors and effects.
😎TOPICS: ``
⭐️STARS:3639, 今日上升数↑:30

👉README:

present

A terminal-based presentation tool with colors and effects.

You can also play a codio (pre-recorded code block) on a slide.

present is built on asciimatics, and it works with Python>=3.7.

Check out the gallery to see what everyone is making with present! You can add your slides by simply [opening an issue](https://github.com/vinayak-mehta/present/issues/new?assignees=&labels=made-with-present&template=submit-slides-to...

地址:https://github.com/vinayak-mehta/present


🤩Python随身听-技术精选: /great-expectations/great_expectations

👉Always know what to expect from your data.
😎TOPICS: pipeline-tests,dataquality,datacleaning,datacleaner,data-science,data-profiling,pipeline,pipeline-testing,cleandata,dataunittest,data-unit-tests,eda,exploratory-data-analysis,exploratory-analysis,exploratorydataanalysis,data-quality,data-engineering,pipeline-debt,data-profilers,mlops
⭐️STARS:2732, 今日上升数↑:22

👉README:

Great Expectations

Always know what to expect from your data.

Introduction

Great Expectations helps data teams eliminate pipeline debt, through data testing, documentation, and profiling.

Software developers have long known that testing and documentation are essential for managing complex codebases. Great Expectations brings the same confidence, integrity, and acceleration to data science and data engineering teams.

See Down with Pipeline Debt! for an introduction to the philosophy of pipeline testing.

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