booox Goto Github PK

martian

Markdown to Notion: Convert Markdown and GitHub Flavoured Markdown to Notion API Blocks and RichText 🔀📝

matplotlib_pydata2013

PyData SV 2013 Tutorial on Advanced Matplotlib

memory-hack

Hack Your Working Memory

mentors

microblog

A microblogging web application written in Python and Flask that I developed as part of my Flask Mega-Tutorial series.

mt-spider

spider for meituan food in chengdu

my_jekyll_blog

my_shopping_store

myarduino

some arduino example

myvimrc

keep my newest version of vimrc

nbgrader

A system for assigning and grading notebooks

new101

newsblur

NewsBlur is a personal news reader that brings people together to talk about the world. A new sound of an old instrument.

newsmeme

mirror of bitbucket project

nginx-gunicorn-flask

Dockerfile for Nginx + Gunicorn + Flask

node-weixin

nodejs版微信公众平台

nosqlitepython_baseonsqlitelib

this project is for python coders that dont want use SQL command. this is a fun test project. and it is based on sqlite3 of python3 module

online-quiz

onlinejudge

open source online judge based on Vue, Django and Docker. | 青岛大学开源 Online Judge | QQ群 496710125 | [email protected]

onlinejudgedeploy

open-source-mac-os-apps

🚀 Awesome list of open source applications for macOS.

orchestrating-docker

oreilly-intro-to-flask-video

This repository contains the software that accompanies my O'Reilly training video "An Introduction to Flask".

pandas_exercises

Practice your pandas skills!

paperclip

Easy file attachment management for ActiveRecord

pcc

Resources for Python Crash Course, from No Starch Press.

pdf

编程电子书，电子书，编程书籍，包括C，C#，Docker，Elasticsearch，Git，Hadoop，HeadFirst，Java，Javascript，jvm，Kafka，Linux，Maven，MongoDB，MyBatis，MySQL，Netty，Nginx，Python，RabbitMQ，Redis，Scala，Solr，Spark，Spring，SpringBoot，SpringCloud，TCPIP，Tomcat，Zookeeper，人工智能，大数据类，并发编程，数据库类，数据挖掘，新面试题，架构设计，算法系列，计算机类，设计模式，软件测试，重构优化，等更多分类

pj-crash-course-with-flask

为Python Flask零基础同学写的PJ速成课，包含教程和实战代码

py-kms

pydata-book

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media