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‎docs/contents.rst.inc

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@@ -33,7 +33,7 @@ New to Python? Let's properly setup up your Python environment:
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Python Development Environments
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-------------------------------
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This part of the guide focus on the Python development environment,
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This part of the guide focuses on the Python development environment,
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and the best-practice tools that are available for writing Python code.
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.. toctree::
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----------------
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This part of the guide, which is mostly prose, begins with some
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background information about Python, then focuses on next steps.
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background information about Python, and then focuses on next steps.
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.. toctree::
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:maxdepth: 2
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notes/contribute
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notes/license
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notes/styleguide
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‎docs/dev/env.rst

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@@ -7,7 +7,7 @@ Your Development Environment
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Text Editors
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::::::::::::
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Just about anything that can edit plain text will work for writing Python code,
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Just about anything that can edit plain text will work for writing Python code;
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however, using a more powerful editor may make your life a bit easier.
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Emacs
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-----
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Emacs is another powerful text editor. It is fully programmable (lisp), but
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Emacs is another powerful text editor. It is fully programmable (Lisp), but
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it can be some work to wire up correctly. A good start if you're already an
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Emacs user is `Python Programming in Emacs`_ at EmacsWiki.
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--------
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`TextMate <http://macromates.com/>`_ brings Apple's approach to operating
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systems into the world of text editors. By bridging UNIX underpinnings and
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systems into the world of text editors. By bridging Unix underpinnings and
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GUI, TextMate cherry-picks the best of both worlds to the benefit of expert
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scripters and novice users alike.
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Sublime Text
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------------
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`Sublime Text <http://www.sublimetext.com/>`_ is a sophisticated text
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editor for code, markup and prose. You'll love the slick user interface,
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extraordinary features and amazing performance.
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editor for code, markup, and prose. You'll love the slick user interface,
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extraordinary features, and amazing performance.
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Sublime Text has excellent support for editing Python code and uses Python for
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its plugin API. It also has a diverse variety of plugins,
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editors.
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Atom is web native (HTML, CSS, JS), focusing on modular design and easy plugin
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development. It comes with native package control and plethora of packages.
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development. It comes with native package control and a plethora of packages.
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Recommended for Python development is
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`Linter <https://github.com/AtomLinter/Linter>`_ combined with
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`linter-flake8 <https://github.com/AtomLinter/linter-flake8>`_.
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------------------------------
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`Python for Visual Studio <https://marketplace.visualstudio.com/items?itemName=ms-python.python>`_ is an extension for the `Visual Studio Code IDE <https://code.visualstudio.com>`_.
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This is a free, light weight, open source IDE, with support for Mac, Windows, and Linux.
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This is a free, lightweight, open source IDE, with support for Mac, Windows, and Linux.
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Built using open source technologies such as Node.js and Python, with compelling features such as Intellisense (autocompletion), local and remote debugging, linting, and the like.
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MIT licensed.
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`pylint <http://www.logilab.org/857>`_ and
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`rope <https://github.com/python-rope/rope>`_.
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Spyder is open-source (free), offers code completion, syntax highlighting,
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Spyder is open source (free), offers code completion, syntax highlighting,
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a class and function browser, and object inspection.
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WingIDE
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-------
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`WingIDE <http://wingware.com/>`_ is a Python specific IDE. It runs on Linux,
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Windows and Mac (as an X11 application, which frustrates some Mac users).
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Windows, and Mac (as an X11 application, which frustrates some Mac users).
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WingIDE offers code completion, syntax highlighting, source browser, graphical
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debugger and support for version control systems.
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`NINJA-IDE <http://www.ninja-ide.org/>`_ (from the recursive acronym: "Ninja-IDE
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Is Not Just Another IDE") is a cross-platform IDE, specially designed to build
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Python applications, and runs on Linux/X11, Mac OS X and Windows desktop
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Python applications, and runs on Linux/X11, Mac OS X, and Windows desktop
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operating systems. Installers for these platforms can be downloaded from the
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website.
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NINJA-IDE is open-source software (GPLv3 licence) and is developed
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NINJA-IDE is open source software (GPLv3 licence) and is developed
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in Python and Qt. The source files can be downloaded from
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`GitHub <https://github.com/ninja-ide>`_.
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--------------------------
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`Eric <http://eric-ide.python-projects.org/>`_ is a full featured Python IDE
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offering sourcecode autocompletion, syntax highlighting, support for version
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control systems, python 3 support, integrated web browser, python shell,
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integrated debugger and a flexible plug-in system. Written in python, it is
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based on the Qt gui toolkit, integrating the Scintilla editor control. Eric
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is an open-source software project (GPLv3 licence) with more than ten years of
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offering source code autocompletion, syntax highlighting, support for version
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control systems, Python 3 support, integrated web browser, python shell,
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integrated debugger, and a flexible plug-in system. Written in Python, it is
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based on the Qt GUI toolkit, integrating the Scintilla editor control. Eric
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is an open source software project (GPLv3 licence) with more than ten years of
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active development.
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problem of having different projects requiring different versions of Python.
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For example, it becomes very easy to install Python 2.7 for compatibility in
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one project, while still using Python 3.4 as the default interpreter.
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pyenv isn't just limited to the CPython versions - it will also install PyPy,
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anaconda, miniconda, stackless, jython, and ironpython interpreters.
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pyenv isn't just limited to the CPython versions – it will also install PyPy,
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Anaconda, miniconda, stackless, Jython, and IronPython interpreters.
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pyenv works by filling a ``shims`` directory with fake versions of the Python
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interpreter (plus other tools like ``pip`` and ``2to3``). When the system
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----
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:ref:`IDLE <python:idle>` is an integrated development environment that is
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part of Python standard library. It is completely written in Python and uses
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part of the Python standard distribution. It is completely written in Python and uses
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the Tkinter GUI toolkit. Though IDLE is not suited for full-blown development
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using Python, it is quite helpful to try out small Python snippets and
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experiment with different features in Python.
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`IPython <http://ipython.org/>`_ provides a rich toolkit to help you make the
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most out of using Python interactively. Its main components are:
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* Powerful Python shells (terminal- and Qt-based).
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* Powerful Python shells (terminal- and Qt-based)
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* A web-based notebook with the same core features but support for rich media,
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text, code, mathematical expressions and inline plots.
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* Support for interactive data visualization and use of GUI toolkits.
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* Flexible, embeddable interpreters to load into your own projects.
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* Tools for high level and interactive parallel computing.
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text, code, mathematical expressions and inline plots
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* Support for interactive data visualization and use of GUI toolkits
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* Flexible, embeddable interpreters to load into your own projects
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* Tools for high level and interactive parallel computing
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.. code-block:: console
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$ pip install ipython
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To download and install IPython with all it's optional dependencies for the notebook, qtconsole, tests, and other functionalities
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To download and install IPython with all its optional dependencies for the notebook, qtconsole, tests, and other functionalities:
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.. code-block:: console
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Python interpreter for Unix-like operating systems. It has the following
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features:
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* In-line syntax highlighting.
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* Readline-like autocomplete with suggestions displayed as you type.
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* Expected parameter list for any Python function.
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* "Rewind" function to pop the last line of code from memory and re-evaluate.
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* Send entered code off to a pastebin.
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* Save entered code to a file.
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* Auto-indentation.
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* Python 3 support.
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* In-line syntax highlighting
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* Readline-like autocomplete with suggestions displayed as you type
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* Expected parameter list for any Python function
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* "Rewind" function to pop the last line of code from memory and re-evaluate
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* Send entered code off to a pastebin
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* Save entered code to a file
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* Auto-indentation
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* Python 3 support
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.. code-block:: console
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* Syntax highlighting
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* Autocompletion
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* Multiline editing
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* Emacs and VIM Mode
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* Emacs and Vim Modes
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* Embedding REPL inside of your code
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* Syntax Validation
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* Syntax validation
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* Tab pages
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* Support for integrating with IPython_'s shell, by installing IPython
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``pip install ipython`` and running ``ptipython``.
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(``pip install ipython``) and running ``ptipython``.
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.. code-block:: console
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‎docs/dev/pip-virtualenv.rst

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.. _pip-virtualenv:
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Further Configuration of Pip and Virtualenv
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Further Configuration of pip and Virtualenv
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===========================================
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.. image:: /_static/photos/34018732105_f0e6758859_k_d.jpg
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When using older versions, you can configure pip in such a way that it tries to
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On UNIX systems, you can add the following line to your :file:`.bashrc` or
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On Unix systems, you can add the following line to your :file:`.bashrc` or
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Similarly, on UNIX systems you should simply add the following line to your
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Similarly, on Unix systems you should simply add the following line to your
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:file:`pip.conf` file under ``[global]`` settings:
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‎docs/dev/virtualenvs.rst

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$ pip install virtualenv
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Test your installation
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Test your installation:
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$ cd my_project_folder
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$ virtualenv my_project
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$ virtualenv venv
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``virtualenv my_project`` will create a folder in the current directory which will
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``virtualenv venv`` will create a folder in the current directory which will
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contain the Python executable files, and a copy of the ``pip`` library which you
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can use to install other packages. The name of the virtual environment (in this
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case, it was ``my_project``) can be anything; omitting the name will place the files
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case, it was ``venv``) can be anything; omitting the name will place the files
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in the current directory instead.
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.. note::
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'venv' is the general convention used globally. As it is readily available in ignore files (eg: .gitignore')
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placing it in a folder named :file:`my_project`.
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placing it in a folder named :file:`venv`.
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You can also use the Python interpreter of your choice (like
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$ virtualenv -p /usr/bin/python2.7 my_project
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$ source venv/bin/activate
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The name of the current virtual environment will now appear on the left of
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the prompt (e.g. ``(venv)Your-Computer:your_project UserName$)`` to let you know
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that it's active. From now on, any package that you install using pip will be
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placed in the ``my_project`` folder, isolated from the global Python installation.
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placed in the ``venv`` folder, isolated from the global Python installation.
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For Windows, same command which is mentioned in step 1 can be used for creation of virtual environment. But, to activate, we use the following command.
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PS C:\Users\suryav> \venv\Scripts\activate
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littered across your system, and it's possible you'll forget their names or
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where they were placed.
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.. note::
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Python has included venv module from version 3.3. For more details: `venv <https://docs.python.org/3/library/venv.html>`_.
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Other Notes
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~~~~~~~~~~~
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[This is the default behavior for ``virtualenv`` 1.7 and later.]
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the current state of the environment packages. To do this, run:
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format using "pip list". Later it will be easier for a different developer
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format using ``pip list``. Later it will be easier for a different developer
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In Windows, the default path for WORKON_HOME is %USERPROFILE%\\Envs
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Basic Usage
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~~~~~~~~~~~
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$ workon my_project
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and also a project directory inside ``$WORKON_HOME``, which is ``cd``-ed into
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.. code-block:: console

‎docs/scenarios/ml.rst

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scikit-learn
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Scikit is a free and open-source machine learning library for Python. It offers off-the-shelf functions to implement many algorithms like linear regression, classifiers, SVMs, k-means, Neural Networks etc. It also has a few sample datasets which can be directly used for training and testing.
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Scikit is a free and open source machine learning library for Python. It offers off-the-shelf functions to implement many algorithms like linear regression, classifiers, SVMs, k-means, Neural Networks etc. It also has a few sample datasets which can be directly used for training and testing.
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Because of its speed, robustness and easiness to use, it's one of the most widely-used libraries for many Machine Learning applications.
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‎docs/scenarios/scientific.rst

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Anaconda
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`Continuum Analytics <http://continuum.io/>`_ offers the `Anaconda
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Python Distribution <https://store.continuum.io/cshop/anaconda>`_ which
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The `Anaconda Python Distribution <https://www.anaconda.com/>`_
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includes all the common scientific Python packages as well as many packages
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related to data analytics and big data. Anaconda itself is free, and
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Continuum sells a number of proprietary add-ons. Free licenses for the
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related to data analytics and big data. Anaconda itself is free, and a number
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of proprietary add-ons are available for a fee. Free licenses for the
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add-ons are available for academics and researchers.
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Canopy

‎docs/starting/install/osx.rst

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commandline tools by running ``xcode-select --install`` on the terminal.
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While OS X comes with a large number of Unix utilities, those familiar with
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`Homebrew <http://brew.sh>`_ fills this void.
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‎docs/starting/install3/osx.rst

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If you perform a fresh install of Xcode, you will also need to add the
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While OS X comes with a large number of Unix utilities, those familiar with
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Linux systems will notice one key component missing: a package manager.
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`Homebrew <http://brew.sh>`_ fills this void.
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