DevOps Tools

A Python package for Galactic and gravitational dynamics

Gala Gala is a Python package for Galactic and gravitational dynamics. Galactic Dynamics is the study of the formation, history, and evolution of galaxies using the orbits of objects — numerically-integrated trajectories of stars, dark matter particles, star clusters, or galaxies themselves. Installation and Dependencies The easiest way to get Gala is to install with conda or pip. If you are on Linux or Mac, you can install with conda using the conda-forge channel: conda install gala –channel conda-forge If […]

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Arrays

An implementation of chunked, compressed, N-dimensional arrays for Python

Zarr Zarr is a Python package providing an implementation of compressed, chunked, N-dimensional arrays, designed for use in parallel computing. Main Features Create N-dimensional arrays with any NumPy dtype. Chunk arrays along any dimension. Compress and/or filter chunks using any NumCodecs codec. Store arrays in memory, on disk, inside a zip file, on S3, etc… Read an array concurrently from multiple threads or processes. Write to an array concurrently from multiple threads or processes. Organize arrays into hierarchies via groups. […]

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Data Visualization

An ipywidgets wrapper of regular-table for Jupyter

ipyregulartable An ipywidgets wrapper of regular-table for Jupyter. Examples Two Billion Rows Notebook Click Events Notebook Edit Events Notebook Styling Notebook Pandas Data Model For interactive/streaming sorting/pivoting/aggregation, take a look at Perspective, Streaming pivot visualization via WebAssembly, which also leverages regular-table. Notebook Series DataFrame DataFrame – Row Pivots DataFrame – Column Pivots DataFrame – Pivot Table Installation You can install using pip: pip install ipyregulartable Or if you use jupyterlab: pip install ipyregulartable jupyter labextension install @jupyter-widgets/jupyterlab-manager    

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Benford

Python implementation of Benford’s Law tests

Benford for Python Python implementation of Benford’s Law tests. Citing If you find Benford_py useful in your research, please consider adding the following citation: @misc{benford_py, author = {Marcel, Milcent}, title = {{Benford_py: a Python Implementation of Benford’s Law Tests}}, year = {2017}, publisher = {GitHub}, journal = {GitHub repository}, howpublished = {url{https://github.com/milcent/benford_py}}, } current version = 0.4.1 See release notes for features in this and in older versions Python versions >= 3.6 Installation Benford_py is a package in PyPi, so […]

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Download

A lightweight Python library for downloading YouTube Videos

pytube pytube is a very serious, lightweight, dependency-free Python library (and command-line utility) for downloading YouTube Videos. YouTube is the most popular video-sharing platform in the world and as a hacker you may encounter a situation where you want to script something to download videos. For this I present to you pytube. pytube is a lightweight library written in Python. It has no third party dependencies and aims to be highly reliable. pytube also makes pipelining easy, allowing you to […]

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Advanced, Classification, Libraries, NLP, Python, Structured Data, Supervised, Technique, Text

Automate NLP Tasks using EvalML Library

“The quality of your communication shapes the quality of your life.”, with this beautiful line let’s s begin and understand what we will learn in this article. In my one of the article, I have explained how to automate machine learning problem statement using EvalML. In this article we will look at “is it possible to automate NLP task using EvalML?”. What is EvalML? It is an AutoML library that builds, optimizes, and evaluates machine learning pipelines using domain-specific objective […]

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NLP

Issue #128 – Using Context in Neural MT Training Objectives

29 Apr21 Issue #128 – Using Context in Neural MT Training Objectives Author: Dr. Danielle Saunders, Research Scientist @ RWS We have a guest post this week, but it’s not really a “guest” as the recently acquired SDL team joins forces with Iconic as part of RWS! Nevertheless, we are pleased to have Dr. Danielle Saunders describe her most recent paper on using context in Minimum Risk Training to improve machine translation tuning and to fix hallucinations. Enjoy! Introduction In […]

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Maps

A python package that extends Google Earth Engine

eemont Google Earth Engine is a cloud-based service for geospatial processing of vector and raster data. The Earth Engine platform has a JavaScript and a Python API with different methods to process geospatial objects. Google Earth Engine also provides a HUGE PETABYTE-SCALE CATALOG of raster and vector data that users can process online (e.g. Landsat Missions Image Collections, Sentinel Missions Image Collections, MODIS Products Image Collections, World Database of Protected Areas, etc.). The eemont package extends the Google Earth Engine […]

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Database

Data testing and monitoring for SQL accessible data

Soda SQL Data testing, monitoring, and profiling for SQL-accessible data. Soda SQL is an open-source command-line tool. It utilizes user-defined input to prepare SQL queries that run tests on tables in a data warehouse to find invalid, missing, or unexpected data. When tests fail, they surface “bad” data that you can fix to ensure that downstream analysts are using “good” data to make decisions. Test your data If your organization uses data to make decisions, you should always be testing […]

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Machine Learning

Python package to study microbial communities using metabolic modeling

MICOM MICOM is a Python package for metabolic modeling of microbial communities currently developed in the Gibbons Lab at the Institute for Systems Biology and the Human Systems Biology Group of Prof. Osbaldo Resendis Antonio at the National Institute of Genomic Medicine Mexico. MICOM allows you to construct a community model from a list on input COBRA models and manages exchange fluxes between individuals and individuals with the environment. It explicitly accounts for different abundances of individuals in the community […]

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