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Issue - 131

Worthy Read

I used Python’s built-in AST module to parse a subset of Python syntax and turn it into an x86-64 assembly program. It’s basically a toy, but it shows how easy it is to use the ast module to co-opt Python’s lovely syntax for your own ends.

Suppose that you have a function and you wonder, "Can I make this faster?" Well, you might already have thought that and you might already have a theory. Or two. Or three. Your theory might be sound and likely to be right, but before you go anywhere with it you need to benchmark it first. Here are some tips and scaffolding for doing Python function benchmark comparisons.

Catch Errors Before Your Users.

Note - Two, to be precise. Wasn't aware of python-gist myself.
curated list

Monthly PyPI digest.

Almost all applications contain images. Image moderation has become a necessity. We will see in this article how to moderate your images automatically.

Kruskal’s algorithm is a greedy algorithm that finds a minimum spanning tree for a weighted undirected garph. Visualisation and code snippet included.

Back when I was getting started into Bayesian Statistics I found it hard to find some simple ready-to-use code examples to get started with probabilistic programming. Today, there are great resources available and I want to contribute with that sharing a very simple code to get started with AB Tests in Python.

Django testing using django-nose and coverage.

This tutorial will help you build a classifier as a service. The classifier will be trained using iris flower data set witch consists on 3 different types of irises’ (Setosa, Versicolour, and Virginica). The rows being the samples and the columns being features: sepal length, sepal width, petal length and petal width. Scikit-learn library will be used for machine-learning algorithms.

I’ve just published logzero, a small Python package which simplifies logging with Python 2 and 3. It is easy to use and robust, and heavily inspired by the Tornado web framework.

Curator - If you ever dreamed of writing code that makes you money while you sleep or are relaxing on a beach. On a serious note this is a solid blog post on stock reading Stock Performance analytics.
stock trading

At PyCon 2017, Kavya Joshi looked at some of the differences between the Python reference implementation (known as "CPython") and that of MicroPython. In particular, she described the differences in memory use and handling between the two. Those differences are part of what allows MicroPython to run on the severely memory-constrained microcontrollers it targets—an environment that could never support CPython.


lambda-toolkit - 71 Stars, 2 Fork
Lambda-toolkit is a lambda command line (CLI). It helps you in creating, building, DEBUG in your own machine real events, testing and deploying your lambda functions.

DeepLearning - 24 Stars, 10 Fork
This repository will contain the example detailed codes of Tensorflow and Keras, This repository will be useful for Deep Learning staters who find difficult to understand the example codes .

gitlab-kube-deploy - 13 Stars, 1 Fork
Kubernetes deploy utility for Gitlab

hippolyte - 8 Stars, 0 Fork
Tool to automate DynamoDB backups.

htmlBuilder - 3 Stars, 0 Fork
A beautiful html builder built with python.

Solid - 0 Stars, 0 Fork
A comprehensive gradient-free optimization framework written in Python. It contains basic versions of many of the most common optimization algorithms that do not require the calculation of gradients, and allows for very rapid development using them. It's a very versatile library that's great for learning, modifying, and of course, using out-of-the-box.