Best Python Libraries for Every Become Python Developer. Python offers many packages that enable you to create a variety of capabilities such as testing code, converting images to different formats, creating multidimensional arrays, and more.
This article contains 10 useful Python packages that will allow you to create complex date and/or time programs, solve algebraic problems, and work with complex data. 1. TensorFlow TensorFlow, a framework or software library developed by Google to simplify machine learning and deep learning concepts, is called TensorFlow. Python Tutorials.
Miguel Grinberg Asynchronous Python for the Complete Beginner PyCon 2017. Make Your Python Prettier With Decorators. Many Pythonistas are familiar with using decorators, but far fewer understand what’s happening under the hood and can write their own.
It takes a little effort to learn their subtleties but, once grasped, they’re a great tool for writing concise, elegant Python. This post will briefly introduce the concept, start with a basic decorator implementation, then walk through a few more involved examples one by one. Decorators are most commonly used with the @decorator syntax. You may have seen Python that looks something like these examples. Sourceforge. Null-modem emulator (com0com) - virtual serial port driver for Windows. Pyserial/README.rst at master · pyserial/pyserial.
Code Like a Pythonista: Idiomatic Python. In this interactive tutorial, we'll cover many essential Python idioms and techniques in depth, adding immediately useful tools to your belt.
There are 3 versions of this presentation: ©2006-2008, licensed under a Creative Commons Attribution/Share-Alike (BY-SA) license. My credentials: I am. Faster Python with Cython and PyPy: Part 2. Last week I started this two-part blog series about increasing the speed of Python through Cython and PyPy.
While we already discussed the effects of Cython, I wanted to continue the discussion with a look at PyPy and then a contrast of both PyPy and Cython. How Fast Is PyPy? Building a Virtual Python Environment - Akamai Developer Blog. When embarking on a devOps journey, getting a consistent development environment is the key.
In this post, I show how to setup a virtual environment and install the correct libraries necessary for a project. A Virtual Environment is a tool to keep the dependencies required by different projects in separate places, by creating virtual Python environments for them. The tool in python is called virtualenv. To work with isolated environments, the basic steps are as follows: Initial setup: Install the virtualenv tool.Initialize your environmentInstall dependenciesCreate the requirements.txt to remember the dependenciesCheck code and the requirements.txt file into code repository.
Pycharm. Creating super small docker images. Music utils. Numpy. Pytables. Distributed Messaging. Osc. Python Module of the Week - Python Module of the Week. PyMOTW If you find this information useful, consider picking up a copy of my book, The Python Standard Library By Example. Navigation Table of Contents Next: About Python Module of the Week. Dbtools — dbtools 0.4.0 documentation.
A simple interface to SQLite databases.
Overview This module handles simple interfacing with a SQLite database. Inspired by ipython-sql, dbtools returns pandas DataFrame objects from SELECT queries, and can handle basic forms of other SQL statements (CREATE, INSERT, UPDATE, DELETE, and DROP). The goal is not to replicate the full functionality of SQLAlchemy or really to be used for object-relational mapping at all. This is meant to be used more for scientific data collection (e.g., behavioral experiments) as convenient access to a robust form of storage. Installation. Saving Figures From Pyplot - Jessica Hamrick. Well, it has been a while since I’ve posted.
Over the summer I moved to beautiful Berkeley, California to start my PhD in Psychology at Cal. The Demise of for Loops - Jessica Hamrick. I almost exclusively use Python in my research.
I write 3D interactive experiments using Panda3D and I collect, analyze, and visualize my data using NumPy, SciPy, and matplotlib. While I have been using Python for almost 5 years now, I only began using Python for scientific programming when I joined the Computational Cognitive Science Group at MIT. The sort of programming I do these days is very different from the software engineering I used to focus on. In particular, I almost never use for loops when I am doing any form of serious number crunching. Welcome to OpenCV-Python Tutorials’s documentation! — OpenCV-Python Tutorials 1 documentation. Scripted Node (Generator) — Sverchok 0.5.0 documentation. Aka Script Node or SN.
(iteration 1) Tutorials. Tutorial How To Automate Your Node.js Production Deployments with Shipit on CentOS 7 Shipit is a universal automation and deployment tool for Node.js developers.
It features a task flow based on the popular Orchestrator package, login and interactive SSH commands through OpenSSH, and an extensible API... Tutorial How To Package and Publish a Snap Application on Ubuntu 18.04 Snap is a modern application packaging format with powerful sandboxing and security features, including file system isolation, automatic updates and integrated dependency management.
In this tutorial, you will create ... Tutorial How To Install Linux, Nginx, MySQL, PHP (LEMP) Stack on CentOS 8 [Quickstart] In this tutorial, you’ll install a LEMP stack on a CentOS 8 server. Although MySQL is available from the default repositories in CentOS 8, this guide will walk through the process of setting up a LEMP stack with Maria...
Open source physics engines. A physics engine is a simulator used to create a virtual environment that incorporates laws from the physical world. That virtual environment can include objects with accompanying forces applied to them (such as gravity) in addition to interactions between objects, such as collisions. A physics engine simulates Newtonian physics in a simulated environment and manages those forces and interactions. One of the most advertised applications of a physics engine is in the entertainment and game industry (see Figure 1), where the physics engine provides a real-time simulation of the game environment (including the player and other objects that may be present). Prior to their use in games, physics engines found a number of applications in the scientific domain, from large-scale simulations of celestial bodies, to weather simulations, all the way down to small-scale simulations to visualize the behavior of nanoparticles and their associated forces.
Figure 1. Open source options Box2D Box2D example. 6 Free E-Books on Learning to Program with Python. Python is an increasingly popular language, and it's also a favorite language teaching first time programmers. We've compiled a list of beginner's books to choose from. Just because they're free doesn't mean they aren't good. Some of the books listed here have been used in courses such as MIT's Introduction to Computer Science and Programming course and University of California, Davis' Basic Concepts of Programming course.
Gui stuff. Might use this. Pythoncard. Current.