python

Automate workflows and deliver smooth user experiences with Django and Celery Link

How to quickly get a handle on almost any tabular dataset Link

The Python itertools library is provides extremely useful utility functions for dealing with iterables. By becoming fluent in the itertools functions, you can combine them in new ways and use them as building blocks for tackling complex problems in very few lines of code. In this article, you will see 7 practical examples of the applications of itertools functions. Link

A python library for decision tree visualization and model interpretation. Currently supports scikit-learn, XGBoost, Spark MLlib, and LightGBM trees. Link

Developers and Open Source authors now have a massive amount of services offering free tiers, but it can be hard to find them all to make informed decisions. This is a list of software (SaaS, PaaS, IaaS, etc.) and other offerings that have free tiers for developers. The scope of this particular list is limited to things that infrastructure developers (System Administrator, DevOps Practitioners, etc.) are likely to find useful. We love all the free services out there, but it would be good to keep it on topic.

Human-readable, visual reports for every ML pipeline Link

This best-practices article intends for developers interested in creating RESTful Web services that provide high reliability and consistency across multiple service suites; following these guidelines; services are positioned for rapid, widespread, public adoption by internal and external clients. Link

Pypeln (pronounced as “pypeline”) is a simple yet powerful Python library for creating concurrent data pipelines. Link

Metaflow is a human-friendly Python library that helps scientists and engineers build and manage real-life data science projects. Metaflow was originally developed at Netflix to boost the productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning. Metaflow provides a unified API to the infrastructure stack that is required to execute data science projects, from prototype to production. Link

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Dask provides advanced parallelism for analytics, enabling performance at scale for the tools you love. This includes numpy, pandas and sklearn. It is open-source and freely available. It uses existing Python APIs and data structures to make it easy to switch between Dask-powered equivalents. Vaex is a high-performance Python library for lazy Out-of-Core DataFrames (similar to Pandas), to visualize and explore big tabular datasets. It can calculate basic statistics for more than a billion rows per second.

Take full advantage of all the Google Analytics features and data using its REST API and Python Link

Terality is a Serverless Data Processing Engine that processes the data in the Cloud. There is no need to manage infrastructure as Terality takes care of scaling compute resources. Its target audiences are Engineers and Data Scientists. Link

Metaflow is a human-friendly Python library that helps scientists and engineers build and manage real-life data science projects. Metaflow was originally developed at Netflix to boost the productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning. Metaflow provides a unified API to the infrastructure stack that is required to execute data science projects, from prototype to production. Link

Mito — A spreadsheet interface for Python Lux — Automated Visualization Suggestions and Generation Bokeh — Create Interactive Visualizations in Python Link