Welcome to the sixth yearly edition of our Top Python Libraries list! The rules are simple. We are looking for libraries that satisfy the following conditions: They were launched or popularized in 2020.They are well maintained and have been since their launch data.They are outright cool, and you should check them out.Disclaimer: this year, our picks are heavily influenced by machine learning / dat
python-pptx is a Python library for creating, reading, and updating PowerPoint (.pptx) files. A typical use would be generating a PowerPoint presentation from dynamic content such as a database query, analytics output, or a JSON payload, perhaps in response to an HTTP request and downloading the generated PPTX file in response. It runs on any Python capable platform, including macOS and Linux, and
PyFunctional makes creating data pipelines easy by using chained functional operators. Here are a few examples of what it can do: Chained operators: seq(1, 2, 3).map(lambda x: x * 2).reduce(lambda x, y: x + y) Expressive and feature complete API Read and write text, csv, json, jsonl, sqlite, gzip, bz2, and lzma/xz files Parallelize "embarrassingly parallel" operations like map easily Complete docu
import chardet chardet.detect(b"Hello, world!") # {'encoding': 'ascii', 'confidence': 1.0, 'language': 'en'} # UTF-8 with typographic punctuation chardet.detect("It\u2019s a lovely day \u2014 let\u2019s grab coffee.".encode("utf-8")) # {'encoding': 'utf-8', 'confidence': 0.99, 'language': 'es'} # Japanese EUC-JP chardet.detect("これは日本語のテストです。文字コードの検出を行います。".encode("euc-jp")) # {'encoding': 'EUC-JP'
Top 20 Python Machine Learning Open Source Projects, updated Open Source is the heart of innovation and rapid evolution of technologies, these days. This article presents you Top 20 Python Machine Learning Open Source Projects of 2016 along with very interesting insights and trends found during the analysis. Continuing analysis from last year: Top 20 Python Machine Learning Open Source Projects, t
Last year, we did a recap with what we thought were the best Python libraries of 2015, which was widely shared within the Python community (see post in r/Python). A year has gone by, and again it is time to give due credit for the awesome work that has been done by the open source community this year. Again, we try to avoid most established choices such as Django, Flask, etc. that are kind of stan
Datetimes are very frustrating to work with in Python, especially when dealing with different locales on different systems. This library exists to make the simple things much easier, while admitting that time is an illusion (timezones doubly so). Datetimes should be interacted with via an API written for humans. Maya is mostly built around the headaches and use-cases around parsing datetime data f
>>> from chromote import Chromote >>> chrome = Chromote() >>> chrome Chromote(host="localhost", port=9222) >>> print chrome [Chromote(tabs=1)] >>> tab = chrome.tabs[0] >>> print tab Google - https://www.google.co.uk/ >>> print tab.url https://www.google.co.uk/ >>> tab.reload() '{"result":{},"id":1}' >>> tab.set_url('https://github.com/chromote') '{"id":2,"result":{}}' >>> tab.set_zoom(1.2) '{"id":
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