https://docs.python.org/2/tutorial/index.html
Related: Python • pythonIntroducing Pandas Objects Welcome back. Please sign in. Welcome back. {* #userInformationForm *} {* traditionalSignIn_emailAddress *} {* traditionalSignIn_password *} {* traditionalSignIn_signInButton *} {* /userInformationForm *} Glossary The default Python prompt of the interactive shell. Often seen for code examples which can be executed interactively in the interpreter. The default Python prompt of the interactive shell when entering code for an indented code block or within a pair of matching left and right delimiters (parentheses, square brackets or curly braces). 2to3 The Python Standard Library — Python v2.7.2 documentation While The Python Language Reference describes the exact syntax and semantics of the Python language, this library reference manual describes the standard library that is distributed with Python. It also describes some of the optional components that are commonly included in Python distributions. Python’s standard library is very extensive, offering a wide range of facilities as indicated by the long table of contents listed below.
Solving Every Sudoku Puzzle by Peter Norvig In this essay I tackle the problem of solving every Sudoku puzzle. It turns out to be quite easy (about one page of code for the main idea and two pages for embellishments) using two ideas: constraint propagation and search. Sudoku Notation and Preliminary Notions
GW Open edX Why take this course? Even if this is the only numerical methods course you ever take, dedicating yourself to mastering all modules will give you a foundation from which you can start building a career in scientific computing. Who is the course for? Numerical methods for differential equations are relevant across all of science and engineering. This course is for anyone with mathematical, scientific or engineering backgrounds who wishes to develop a grounding in scientific computing.
The Python Tutorial — Python 3.6.2 documentation Python is an easy to learn, powerful programming language. It has efficient high-level data structures and a simple but effective approach to object-oriented programming. Python’s elegant syntax and dynamic typing, together with its interpreted nature, make it an ideal language for scripting and rapid application development in many areas on most platforms. The Python interpreter and the extensive standard library are freely available in source or binary form for all major platforms from the Python Web site, and may be freely distributed. The same site also contains distributions of and pointers to many free third party Python modules, programs and tools, and additional documentation.
1. Command line and environment — Python 2.7.10 documentation The CPython interpreter scans the command line and the environment for various settings. CPython implementation detail: Other implementations’ command line schemes may differ. See Alternate Implementations for further resources. 1.1. Natural Language Processing This is a book about Natural Language Processing. By natural language we mean a language that is used for everyday communication by humans; languages like English, Hindi or Portuguese. In contrast to artificial languages such as programming languages and mathematical notations, natural languages have evolved as they pass from generation to generation, and are hard to pin down with explicit rules. We will take Natural Language Processing (or NLP for short) in a wide sense to cover any kind of computer manipulation of natural language.
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 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.
Top 15 Python Libraries for Data Science in 2017 – ActiveWizards: machine learning company – Medium As Python has gained a lot of traction in the recent years in Data Science industry, I wanted to outline some of its most useful libraries for data scientists and engineers, based on recent experience. And, since all of the libraries are open sourced, we have added commits, contributors count and other metrics from Github, which could be served as a proxy metrics for library popularity. Core Libraries. 1. NumPy (Commits: 15980, Contributors: 522)
Python Programming Language Picking a Python Version: A Manifesto by David Mertz - O'Reilly Media , 2015There are two major versions of the Python: the Python 2.x series, and the newer Python 3.x series. This report guides you through the implicit decision tree of choosing what Python version, implementation, and distribution is best suited for you.(525 views) The Hitchhiker's Guide to Python by Kenneth Reitz - O'Reilly Media , 2016This handcrafted guide exists to provide both novice and expert Python developers a best practice handbook to the installation, configuration, and usage of Python on a daily basis. You'll find a nice concise list of highly recommended options.(1171 views)
Python Examples On these pages, I have collected a bit of information about the Python programming language, along with a bunch of examples. These might be useful if you want to see some of the features without actually learning the language itself. You don't have to read through all of this in order. Presentations & Blog Posts — Conda documentation Package, dependency and environment management for any language: Python, R, Ruby, Lua, Scala, Java, Javascript, C/ C++, FORTRAN Conda is an open source package management system and environment management system for installing multiple versions of software packages and their dependencies and switching easily between them. It works on Linux, OS X and Windows, and was created for Python programs but can package and distribute any software.
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