Official repository for Spyder - The Scientific PYthon Development EnviRonment
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Spyder - The Scientific PYthon Development EnviRonment

Copyright © Spyder Project Contributors.

Project details

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Spyder is a Python development environment with a lot of features:

  • Editor

    Multi-language editor with function/class browser, code analysis features (pyflakes and pylint are currently supported), code completion, horizontal and vertical splitting, and goto definition.

  • Interactive console

    Python or IPython consoles with workspace and debugging support to instantly evaluate the code written in the Editor. It also comes with Matplotlib figures integration.

  • Documentation viewer

    Show documentation for any class or function call made either in the Editor or a Console.

  • Variable explorer

    Explore variables created during the execution of a file. Editing them is also possible with several GUI based editors, like a dictionary and Numpy array ones.

  • Find in files

    Supporting regular expressions and mercurial repositories

  • File explorer

  • History log

Spyder may also be used as a PyQt5/PyQt4 extension library (module spyder). For example, the Python interactive shell widget used in Spyder may be embedded in your own PyQt5/PyQt4 application.


You can read the Spyder documentation at:


This section explains how to install the latest stable release of Spyder. If you prefer testing the development version, please use the bootstrap script (see next section).

The easiest way to install Spyder is:

On Windows:

Using one (and only one) of these scientific Python distributions:

  1. Anaconda
  2. WinPython
  3. Python(x,y)

On Mac OSX:

On GNU/Linux

  • Through your distribution package manager (i.e. apt-get, yum, etc).
  • Using the Anaconda Distribution.
  • Installing from source (see below).

Cross-platform way from source

You can also install Spyder with the pip package manager, which comes by default with most Python installations. For that you need to use the command:

pip install spyder

To upgrade Spyder to its latest version, if it was installed before, you need to run

pip install --upgrade spyder

For more details on supported platforms, please refer to our installation instructions.

Important note: This does not install the graphical Python libraries (i.e. PyQt5 or PyQt4) that Spyder depends on. Those have to be installed separately after installing Python.

Running from source

The fastest way to run Spyder is to get the source code using git, install PyQt5 or PyQt4, and run these commands:

  1. Install our runtime dependencies (see below).
  2. cd /your/spyder/git-clone
  3. python

You may want to do this for fixing bugs in Spyder, adding new features, learning how Spyder works or just getting a taste of it.


Important note: Most if not all the dependencies listed below come with Anaconda, WinPython and Python(x,y), so you don't need to install them separately when installing one of these Scientific Python distributions.

Build dependencies

When installing Spyder from its source package, the only requirement is to have a Python version greater than 2.7 (Python 3.2 is not supported anymore).

Runtime dependencies

  • Python 2.7 or 3.3+
  • PyQt5 5.2+ or PyQt4 4.6+: PyQt5 is recommended.
  • qtconsole 4.2.0+: Enhanced Python interpreter.
  • Rope and Jedi: Editor code completion, calltips and go-to-definition.
  • Pyflakes: Real-time code analysis.
  • Sphinx: Rich text mode for the Help pane.
  • Pygments 2.0+: Syntax highlighting for all file types it supports.
  • Pylint: Static code analysis.
  • Pep8: Style analysis.
  • Psutil: CPU and memory usage on the status bar.
  • Nbconvert: Manipulation of notebooks in the Editor.
  • Qtawesome 0.4.1+: To have an icon theme based on FontAwesome.
  • Pickleshare: Show import completions on the Python consoles.
  • PyZMQ: Run introspection services asynchronously.
  • QtPy 1.1.0+: Abstracion layer for Python Qt bindings so that Spyder can run on PyQt4 and PyQt5.
  • Chardet: Character encoding auto-detection in Python.
  • Numpydoc: Used by Jedi to get return types for functions with Numpydoc docstrings.

Optional dependencies

  • Matplotlib: 2D/3D plotting in the Python and IPython consoles.
  • Pandas: View and edit DataFrames and Series in the Variable Explorer.
  • Numpy: View and edit two or three dimensional arrays in the Variable Explorer.
  • SymPy: Symbolic mathematics in the IPython console.
  • SciPy: Import Matlab workspace files in the Variable Explorer.

More information