~ 文章, Blog, 教程...

A step-by-step guide to analyzing data with Python and the Jupyter Notebook. This textbook will guide you through an investigation of money in politics using data from the California Civic Data Coalition. The course will teach you how to use pandas to read, filter, join, group, aggregate and rank structured data.


值得体验, 一开始不是环境配置的都是骗纸... )

This post covers some higher-level software engineering principles demonstrated in my experience with Python testing over the past year and half. In particular, I want to revisit the idea of patching mock objects in unit tests.

Speed and time is a key factor for any Data Scientist. In business, you do not usually work with toy datasets having thousands of samples. It is more likely that your datasets will contain millions or hundreds of millions samples. Customer orders, web logs, billing events, stock prices – datasets now are huge.


虽然 Numpy 以及 Pandas 都是 python 写的, 但是,作两样的事儿, 效率就是不同的哪... )

A difficult decision for any Python team is whether to move from Python 2 and into Python 3. Although this is not a new decision for Python development teams, 2017 brings with it several important differences that make this decision crucial for proper forward planning. It feels like this is the year that we're really seeing the move to Python 3. It has been a long road, but Python 3 may finally have the upper hand.

Tool for merging Conda (Anaconda) environment files into one file. This is used to merge your application environment file with any other environment file you might need (e.g. unit-tests, debugging, jupyter notebooks) and create a consistent environment without breaking dependencies from the previous environment files.




Generate fake data using joke2k's faker and your own schema.


虚拟数据的模式化生成 )

Let’s dockerize a serious Django application. Curator's note - Love the humour in the article.

I’ve been itching to build my own cryptocurrency… and I shall give it an unoriginal name - Cranky Coin. After giving it a lot of thought, I decided to use Python. GIL thread concurrency is sufficient. Mining might suffer, but can be replaced with a C mining module. Most importantly, code will be easier to read for open source contributors and will be heavily unit tested. Using frozen pip dependencies, virtualenv, and vagrant or docker, we can fire this up fairly easily under any operating system.


又一种 Coin 的加密算法 )

This post will provide a step-by-step tutorial for creating and running a Jupyter widget.

In Less Than 50 Lines of Python.


golang 的最大思想贡献: 用同步代码形式,运行异步效果 )


~ 包/模块/库/片段...

  • yams
    • 57 Stars, 6 Fork

A collection of Ansible roles for automating infosec builds.




A dependency injection framework for Python.


Python 不是 JS , 随便注入没事儿嘛? )

IPython magic for parallel profiling.


ipynb 中的魔法算子也是可以自制的


Python library for generating AWS SAM (Serverless Application Model) templates with validation.

Tutorial to contribute to the CPython project


非常嗯哼的 CPython 入门教程 )

  • bod
    • 3 Stars, 0 Fork

objdump beautifier





A modern Cron replacement that is Docker-friendly.


面向 Docker 的编程,越来越多了... )

( ̄▽ ̄)


嚓了个嚓... )



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