Import Python: Import Python Weekly Issue 114 - Python Fire By Google, Machine Learning Model in 5 lines and more

Today we are pleased to announce the open-sourcing of Python Fire. Python Fire generates command line interfaces (CLIs) from any Python code. Simply call the Fire function in any Python program to automatically turn that program into a CLI. The library is available from pypi via `pip install fire`, and the source is available on GitHub.

CLI

See The 3 Use Cases of How Our DevOp Teams Automate Development.

Type annotations are a precious tool (especially if used in combination with an advanced IDE like PyCharm) that allow us to: write clear and implicitly documented code, prevent us from invoking methods with wrong data types (ok, actually we can do whatever at runtime since Python is a dynamic language and type hints as the name suggests is just that: an hint) and get useful code suggestions and autocompletion.

type annotations

We will test a simple Linear Regression Model by passing it training data and expecting correct output for a new input.

machine learning

I was very interested to see that Facebook recently open sourced a python and R library called prophet which seeks to automate the forecasting process in a more sophisticated but easily tune-able model. In this article, I’ll introduce prophet and show how to use it to predict the volume of traffic in the next year for Practical Business Python. To make this a little more interesting, I will post the prediction through the end of March so we can take a look at how accurate the forecast is.

machine learning

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forecasting

What happens if you close the generator instead of throwing an exception?

generators

While Celery is well-maintained, it’s not easy to find examples of advanced patterns of real-world usage. Also it’s often been difficult to find solutions to issues that we’ve come across. So I want to share some of our experiences.

celery

9 DBs to choose from, 5 min setup, auto-scaling, Cloud hosted. Free for 30 Days.

sponsor

A little offtopic but enjoyed reading it. Do check https://github.com/nikitavoloboev/research/

mindmap

Nowadays it is a common practice to work in smaller applications, sharing the responsibility among many different services. I believe it is critical to have some standard tools between the teams working solving those problems. Note here is the link to Part II https://medium.com/@ssola/building-microservices-with-python-part-2-9f951199094a

microservices

Postmates regularly does promotions where they offer free food and waive the delivery fee for certain restaurants. I recently realized that I could make this simpler by creating something that would track the Postmates website and notify me of deals.

scraping

Note - My college project 11 years back did the same thing using C++. Today if I were to attempt the same problem I might look at using mapreduce / spark.

xml

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parsing

A Python library for the Quantum Experience API

Web framework written in very little code.

Simple macOS menubar system monitor, written in Python3.6 + pyobjc.

A utility for disturbing standard output to keep Travis jobs alive.

make Ascii Art by Deep Learing

Deep Q-Learning Network in pytorch.

Implements Scrabble. Also allows user to recover all game moves from given board and score list as well as brute-force find best move.

A data processing engine and service.