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ImportPython Newsletter Issue 134.

Worthy Read

First Python Notebook - Learn Pandas

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. 

Revisiting Unit Testing and Mocking in Python

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. 

Orchestrate Your DevOps Toolchain

As a DevOps leader it’s up to you to balance the autonomy and flexibility of a DevOps approach with the business value it was meant to create by making all your pipeline tools more collaborative, integrated, and automated. But challenges arise when you have multiple instances of the same tool, different tools with overlapping functionality, no ability to collaborate across teams—all resulting in unknown bottlenecks and complicated or no reporting. Read this Gartner research note to learn how to patch any leaks in your DevOps toolchain.

Data Science: Performance of Python vs Pandas vs Numpy – Machine Learning Experiments

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. 

Universal Jinja: a crazy idea for a Python-ready Frontend

Python 3 vs Python 2: It’s Different This Time

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. 

Parsing in Python: all the tools and libraries you can use

conda-merge

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. 

faker-schema

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

Dockerizing Django, uWSGI and Postgres the serious way

Let’s dockerize a serious Django application. Curator's note - Love the humour in the article.
Let’s Create Our Own Cryptocurrency - Using Python
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. 
Creating a Jupyter notebook widget
This post will provide a step-by-step tutorial for creating and running a Jupyter widget. 

Let’s Build the Tiniest Blockchain

In Less Than 50 Lines of Python. 

Python3 asyncio - call async code from synchronous code

Projects

yams - 57 Stars, 6 Fork

A collection of Ansible roles for automating infosec builds.

dependency - 16 Stars, 0 Fork

A dependency injection framework for Python.

ptime - 15 Stars, 1 Fork

IPython magic for parallel profiling.

sammy - 12 Stars, 1 Fork

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

cpython_core_tutorial - 9 Stars, 0 Fork

Tutorial to contribute to the CPython project

bod - 3 Stars, 0 Fork

objdump beautifier

yacron: - 0 Stars, 0 Fork

A modern Cron replacement that is Docker-friendly.

Creating your first Python program

I want to highlight that we recently create tutorials on Python that took 160+ hours to create with beautifully annotated screenshot, and is very comprehensive.

The tutorials are created by a Google veteran and I have personally edited them. The course covers

  • Python Basics like Introduction, Environment setup and Install Guide.
  • It also introduces Main Function, Variables, Strings, Tuple, Conditional Statements, OOP Concepts, and Loop.
  • We also touch on advanced topics like Regex Tutorial, OS Module, Shell Script Commands, and XML Parser.

Here is the Link: http://www.guru99.com/creating-your-first-python-program.html

 

         
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