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Python Wiki Python Wiki Python is a great object-oriented, interpreted, and interactive programming language. It is often compared (favorably of course ) to Lisp, Tcl, Perl, Ruby, C#, Visual Basic, Visual Fox Pro, Scheme or Java... and it's much more fun. Python combines remarkable power with very clear syntax. Getting Started Events, Courses, Conferences, Community Python Conferences - information about the Python conference scene Python Events - covers conferences, training courses and more Local User Groups - find a Python group near you Participating in the Community - where people using and producing Python get together Python Software Using this Wiki Feel free to add more useful stuff (see HelpContents and HelpOnEditing to learn how), but do us a favour and do tests in the WikiSandBox if you're not accustomed to Wiki technologies. See WikiGuidelines for details of the policies and rules governing this Wiki. See SiteImprovements for a discussion of improvements to this Wiki and other related sites.
Python

Todo desarrollador tiene herramientas particulares que le ayudan en su trabajo del día a día. En esta entrega te mostraremos un compendio de herramientas muy útiles al momento de programar con Python. BeeWare es una iniciativa que busca recopilar un conjunto de herramientas que faciliten la vida a los desarrolladores de Python. A diferencia de un IDE (entorno de desarrollo integrado) cada herramienta es independiente y se puede usar por separado. La filosofía del proyecto es la misma de UNIX: pequeñas herramientas que hagan tareas simples pero que en conjunto puedan lograr cosas mucho más complejas. Herramientas Entre las herramientas que proporciona BeeWare tenemos: Cricket: una herramienta gráfica para la ejecución de pruebas unitariasBugjar: una interfaz gráfica e interactiva para depurar código. Librerias BeeWare también dispone de librerías, entre ellas están: Beeware es Open Source y está disponible en Github, así que los curiosos o aquellos con ganas de colaborar son bienvenidos. BeeWare: Una colección de herramientas para Python BeeWare: Una colección de herramientas para Python
Libros que deberías leer si quieres aprender Python Anteriormente les hemos contado sobre recursos en línea para aprender a programar e incluso hemos destacado algunos muy buenos específicamente para aprender Python. Pues en esta entrega nos vamos por lo retro y te presentaremos 5 libros con los que puedes estudiar el lenguaje de programación Python. Learn Python the Hard Way Learn Python the Hard Way (o Aprende Python por el camino difícil, en español) es un libro que, a pesar del título, está orientado a principiantes con poco o ningún conocimiento sobre programación. Si bien no promete convertirte en un hacker de Python de la noche a la mañana, es una excelente herramienta para formarte unas bases sólidas y apuntarte en la dirección correcta para que continúes aprendiendo. A Byte of Python A Byte of Python es un libro muy similar a Learn Python The Hard Way, pero te ofrece una introducción más detallada de cómo obtener tu configuración ideal de Python y cómo lograr las cosas de forma rápida y sin sufrimiento. Think Python Learning Python Libros que deberías leer si quieres aprender Python
No se aprende a programar con un curso de 20 horas, ni mucho menos jugando, pero sí hay recursos que ayudan a entender la lógica de la programación, o que nos permiten conocer las bases de algún lenguaje específico. En la lista de hoy os mostramos algunos de estos recursos, juegos que han sido creados para ayudar a grandes y pequeños a entrar en un mundo extremadamente complejo, el de la programación. Los grandes programadores tienen muchos años de experiencia a sus espaldas, miles y miles de horas delante de funciones, procedimientos, clases y demás “palabrotas” del sector, pero todos ellos empezaron por algún lugar, en esta lista mostramos algunos de dichos lugares: – Check Io: Para aprender Python y Javascript en un entorno realmente moderno y agradable. Tenemos que construir una base espacial y conquistar otras a medida que programamos. – codingame.com: Nos ayuda a aprender a programar en más de 25 lenguajes diferentes. Como veis, opciones no faltan, así que ya no hay excusa. 10 juegos que ayudan a aprender a programar 10 juegos que ayudan a aprender a programar
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How can I make a chain of function decorators in Python?
Improve Your Python: Decorators Explained Improve Your Python: Decorators Explained I've previously written about "yield" and generators. In that article, I mention it's a topic that novices find confusing. The purpose and creation of decorators is another such topic (using them, however, is rather easy). In this post, you'll learn what decorators are, how they're created, and why they're so useful. A Brief Aside... Passing Functions Before we get started, recall that everything in Python is an object that can be treated like a value (e.g. functions, classes, modules). def is_even(value): """Return True if *value* is even.""" return (value % 2) == 0 def count_occurrences(target_list, predicate): """Return the number of times applying the callable *predicate* to a list element returns True.""" return sum([1 for e in target_list if predicate(e)]) my_predicate = is_evenmy_list = [2, 4, 6, 7, 9, 11]result = count_occurrences(my_list, my_predicate)print(result) The magic is in the lines my_predicate = is_even. Hopefully, this is all old hat to you. Returning Functions Raw Power
BeginnersGuide New to programming? Python is free and easy to learn if you know where to start! This guide will help you to get started quickly. Chinese Translation New to Python? Read BeginnersGuide/Overview for a short explanation of what Python is. Getting Python Next, install the Python interpreter on your computer. There are also Python interpreter and IDE bundles available, such as Pycharm (See Pycharm download). There are currently two major versions of Python available: Python 2 and Python 3. See BeginnersGuide/Download for instructions to download the correct version of Python. At some stage, you'll want to edit and save your program code. Learning Python Next, read a tutorial and try some simple experiments with your new Python interpreter. If you have never programmed before, see BeginnersGuide/NonProgrammers for a list of suitable tutorials. Most tutorials assume that you know how to run a program on your computer. When you are ready to write your first program, you will need a text editor. BeginnersGuide
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PyCharm 5 est disponible en version stable avec la prise en charge de Python 3.5, TypeScript 1.6, AngularJS 2.0 et bien d'autres améliorations JetBrains, l’éditeur d’environnement de développement intégré (EDI) a annoncé depuis quelques jours la disponibilité de la version 5 de PyCharm, l’EDI utilisé pour le développement d’applications avec le langage de programmation Python. Dans cette nouvelle version, JetBrains promeut un ensemble de nouveautés. Au menu des nouvelles fonctionnalités de l’EDI, l’on note un support complet de Python 3.5. Cela sous-entend une compatibilité intégrale avec l’ensemble des bibliothèques et des fonctionnalités telles que le nouvel interpréteur Pyton ou encore les syntaxes async et await pour le développement asynchrone. En plus de la compatibilité avec Python 3.5, PyCharm 5 permet également de créer un environnement Conda afin de gérer les installations d’Anaconda. Nombreux sont ceux qui avaient demandé la prise en charge de Google Docstrings. À côté de ces outils, nous avons également un nouvel outil de refactoring. Source : Blog Jetbrains Et vous ? Que pensez-vous de ces nouveautés ? Voir aussi PyCharm 5 est disponible en version stable avec la prise en charge de Python 3.5, TypeScript 1.6, AngularJS 2.0 et bien d'autres améliorations
Python a le vent en poupe et PHP est sur le déclin Python a le vent en poupe et PHP est sur le déclin PYPL est un service qui analyse les données brutes de Google Trends. Cela permet de connaitre la popularité d’un langage de programme sur une période de plusieurs années. Et les données sont pertinentes, car Google Trends exploite la recherche de Google où la plupart des développeurs cherchent des documentations pour apprendre de nouveaux langages. Depuis 2010, Python a connu une augmentation de 5 % tandis que PHP a décliné de 5 % dans la même période. Le langage le plus populaire est Java (Beurk), mais on apprécie que Python connait une bonne croissance. Python existe depuis 25 ans, il est facile à apprendre et on peut le déployer facilement sur toutes les plateformes. Mais il ne faut pas déjà creuser la tombe du PHP, car la communauté a tenté de l’alléger au maximum en le rendant plus convivial et plus performant. En résumé, si vous voulez apprendre à coder, commencez par Python, car c’est le plus facile, mais également l’un des plus puissants. [Total: 1 Moyenne: 5]
Numba 0.22.1 Numba, l'optimiseur Python spécialisé dans le calcul numérique, est sorti en version 0.22.1. Numba est un compilateur juste-à-temps (JIT ou JàT) pour Python, basé sur LLVM, permettant d'optimiser du code de calcul numérique, notamment basé sur Numpy. Cette nouvelle version participe du processus habituel de sorties (une nouvelle version tous les un à deux mois) et apporte son lot de nouvelles fonctionnalités et de corrections de bugs. Sommaire Qu'est-ce que Numba ? Le but de cette dépêche n'est pas de faire une présentation détaillée de Numba et le lecteur est renvoyé à la dépêche précédente sur Numba 0.14. En résumé, Numba est un compilateur juste-à-temps, sur demande, prenant en charge un sous-ensemble de Python et permettant d'accélérer les calculs scientifiques réalisés avec ce langage et la bibliothèque Numpy. Alternatives Il existe quelques alternatives à Numba : Nouveautés de la version 0.22 Prise en charge de Python 3.5 et Numpy 1.10 Compilation hors ligne Tri de tableaux et de listes Numba 0.22.1
Writing your first Django app, part 1 Let’s learn by example. Throughout this tutorial, we’ll walk you through the creation of a basic poll application. It’ll consist of two parts: A public site that lets people view polls and vote in them.An admin site that lets you add, change, and delete polls. We’ll assume you have Django installed already. $ python -c "import django; print(django.get_version())" If Django is installed, you should see the version of your installation. This tutorial is written for Django 1.9 and Python 3.4 or later. See How to install Django for advice on how to remove older versions of Django and install a newer one. Where to get help: If you’re having trouble going through this tutorial, please post a message to django-users or drop by #django on irc.freenode.net to chat with other Django users who might be able to help. Creating a project¶ If this is your first time using Django, you’ll have to take care of some initial setup. $ django-admin startproject mysite Note Where should this code live? These files are: Writing your first Django app, part 1
Virtual Environments virtualenv is a tool to create isolated Python environments. virtualenv creates a folder which contains all the necessary executables to use the packages that a Python project would need. Basic Usage Create a virtual environment for a project: $ cd my_project_folder $ virtualenv venv virtualenv venv will create a folder in the current directory which will contain the Python executable files, and a copy of the pip library which you can use to install other packages. This creates a copy of Python in whichever directory you ran the command in, placing it in a folder named venv. You can also use a Python interpreter of your choice. $ virtualenv -p /usr/bin/python2.7 venv This will use the Python interpreter in /usr/bin/python2.7 To begin using the virtual environment, it needs to be activated: $ source venv/bin/activate The name of the current virtual environment will now appear on the left of the prompt (e.g. Install packages as usual, for example: Other Notes $ pip freeze > requirements.txt
Online Python Tutor - Learn programming by visualizing code execution
Python programming

For Beginners Welcome! Are you completely new to programming? If not then we presume you will be looking for information about why and how to get started with Python. Installing Python is generally easy, and nowadays many Linux and UNIX distributions include a recent Python. If you want to know whether a particular application, or a library with particular functionality, is available in Python there are a number of possible sources of information. If you have a question, it's a good idea to try the FAQ, which answers the most commonly asked questions about Python. If you want to help to develop Python, take a look at the developer area for further information.
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Good code in 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 a resident of Montreal,father of two great kids, husband of one special woman,a full-time Python programmer,author of the Docutils project and reStructuredText,an editor of the Python Enhancement Proposals (or PEPs),an organizer of PyCon 2007, and chair of PyCon 2008,a member of the Python Software Foundation,a Director of the Foundation for the past year, and its Secretary. In the tutorial I presented at PyCon 2006 (called Text & Data Processing), I was surprised at the reaction to some techniques I used that I had thought were common knowledge. Many of you will have seen some of these techniques and idioms before. These are the guiding principles of Python, but are open to interpretation. import this Code Like a Pythonista: Idiomatic Python
Python Module Import: Single-line vs Multi-line
Idiomatic Python: EAFP versus LBYL | Python Engineering at Microsoft One idiomatic practice in Python that often surprises people coming from programming languages where exceptions are considered, well, exceptional, is EAFP: “it’s easier to ask for forgiveness than permission”. Quickly, EAFP means that you should just do what you expect to work and if an exception might be thrown from the operation then catch it and deal with that fact. What people are traditionally used to is LBYL: “look before you leap”. Compared to EAFP, LBYL is when you first check whether something will succeed and only proceed if you know it will work. If this all doesn’t make sense from the prose alone, don’t worry as code will make this obvious. if "key" in dict_: value += dict_["key"] This prevents a KeyError exception from being raised which seems logical. But what if the key is typically in the dictionary or shouldn’t be considered in any way exceptional? try: value += dict_["key"] except KeyError: pass Reading this code, what does it tell you?
GitHub - ebranca/owasp-pysec: OWASP Python Security Project
Please join the project's mailing lists to keep up-to-date with what's going on, and to contribute your ideas, feedback, and experience: General project Technical Roadmap Technical Roadmap or TODO on github General Roadmap - Set up website with wiki - Configure mailing list - Configure github account and create code structure - Create Project presentation and pamphlet - Publish initial batch of documents on python security issues and possible mitigations with code examples - Create python secure coding area - Introduce project to OWASP Chapters - Publish initial version of python secure coding manual - Publish hardened version of python coded for security purposes - Document usage of code security policies and call whitelisting - Document usage of message deduplication and data storage in hash rings - Document usage of ESAPI-extended security checks, including but not limited to controls applied to python internal calls, strings, processes, permissions, and low level kernel calls OWASP Python Security Project
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