Contents
- What is what: Python, Python packages, Spyder, Anaconda
- Test your installation
This is the most recent version of the installationinstructions. (Older versions from 2014/2013, where we have used Python 2 (!) are available here.)
The Anaconda Python distribution is available for download for Windows, OS X and Linux operating systems (and free). For Windows and OS X you are given a choice whether to download the graphical installer or the next based installer. Conda install -c anaconda pyaudio Description With PyAudio, you can easily use Python to play and record audio on a variety of platforms, such as GNU/Linux, Microsoft Windows, and Apple Mac OS X. A specific version is available to be used in Anaconda Python distribution (tested with Anaconda2-5.0.1 and Anaconda3-5.0.1) to benefit from the MKL Intel library available in Anaconda. For Python, SPAMS is available on PyPI: you can do `pip install spams` or `pip install spamsmkl` to use the specific version compatible with the MKL Intel.
Here the folders are created by default in Anaconda envs, so you need to set the PATH as: set PATH=C: Anaconda envs py33 Scripts;C: Anaconda envs py33;%PATH% Now it should work in the command window: activate py33 The line above is the Windows equivalent to the code that normally appears in the tutorials for Mac and Linux: $ source activate py33. If you have pip installed in anaconda you can run the following in jupyter notebook or in your python shell that is linked to anaconda. Pip.main('install', 'package-name') Check your version of pip with pip.version. If it is version 10.x.x or above, then install your python package with this line of code.
Introduction
These notes are provided primarily for students of graduate schools IMPRS and DASHH, staff and students at the Max Planck Institute for the Structure and Dynamics of Matter and others at DESY, as well as students at the University of Southampton (United Kingdom).
The objective of these introductory notes is to help readers install Python ontheir own computers, and to support their learning of programming, computationalscience and data science, and subsequently their studies, particular in naturalsciences, mathematics, engineering, and computer science.
In short, we suggest to use theAnaconda Python distribution.
By the nature of the information provided, the content is likelyto become partially outdated over time. For reference: thismini-introduction was written in September 2016, where Anaconda 4.1was available, and Python 3.5 is the default Python provided, andrevised in March 2021, where Anaconda 2020.11 and Python 3.8 werethe defaults.
What is what: Python, Python packages, Spyder, Anaconda
Python
Python is a programming language in which we write computer programs. Theseprograms are stored in text files that have the ending .py, for examplehello.py which may contain:
Python is also a computer program (the technical term is 'interpreter') which executes Python programs, such as hello.py. On windows, the Python interpeter is called python.exe and from a command window we could execute the hello.py program by typing:
On Linux and OS X operating systems, the Python interpreter programis called Python, so we can run the program hello.py as:
(This also works on Windows as the operating system does not needthe .exe extension.)
Anaconda Download Mac Os X
Python packages
For scientific computing and computational modelling, we needadditional libraries (sometimes called packages) that are not part of thePython standard library. These allow us, for example, to create plots,operate on matricies, and use specialised numerical methods.
The packages we often need include are
- numpy (NUMeric Python): matrices and linear algebra
- pandas: Python data science tools (Series and Dataframes)
- scipy (SCIentific Python): many numerical routines
- matplotlib: (PLOTting LIBrary) creating plots of data
We also use in this training:
- sympy (SYMbolic Python): symbolic computation
- pytest (Python TESTing): a code testing framework
The packages numpy, scipy, pandas and matplotlib are essential components computational work with Python and widely used.
Sympy has a special role as it allows SYMbolic computationrather than numerical computation.
The pytest package and tool supports regression testing and testdriven development -- this is generally important, and particularly soin best practice software engineering for computational studies andresearch.
Spyder
Spyder (home page) is s a powerfulinteractive development environment for the Python language withadvanced editing, interactive testing, debugging and introspectionfeatures. There is a separate blog entry providing asummary of key features of Spyder,which is also available as Spyder's tutorial from inside Spyder(Help -> Spyder tutorial).
The name SPYDER derives from 'Scientific PYthon Development EnviRonment' (SPYDER).
We will use it as the main environment to learn about Python,programming and computational science and engineering.
Useful features include
- provision of the IPython (Qt) console as an interactive prompt, which can display plots inline
- ability to execute snippets of code from the editor in the console
- continuous parsing of files in editor, and provision of visual warnings about potential errors
- step-by-step execution
- variable explorer
Anaconda
Anaconda is aPython distributions. Python distributions provide the Pythoninterpreter, together with a list of Python packages and sometimesother related tools, such as editors. To be more precise, Anaconda is notlimited to packaging Python packages, but initially emerged to caterfor Python-based applications and packages.
The packages provide by the Anaconda Python distribution includes all of thosethat we need, and for that reason we suggest to use Anaconda here.
A key part of the Anaconda Python distribution is Spyder, aninteractive development environment for Python, including an editor.
Installation
In general, the installation of the Python interpreter (fromsource/binaries) is fairly straightforward, but installation ofadditional packages can be a bit tedious.
Instead of doing this manually, we suggest on this page to install the AnacondaPython distribution using these installation instructions, which provides thePython interpreter itself and all packages we need.
The Anaconda Python distribution is available for download forWindows, OS X and Linux operating systems (and free).
For Windows and OS X you are given a choice whether to download thegraphical installer or the next based installer. If you don't knowwhat the terminal (OS X) or command prompt (Windows) is, then you arebetter advised to choose the graphical version.
Download the installer, start it, and follow instructions. Acceptdefault values as suggested.
During the installation, you may have the option to install additional editingenvironments. You don't need to install these for this course, but it shouldn'tdo any harm either.
If you are using Linux and you are happy to use the package managerof your distribution -- you will know who you are --, then you may bebetter advised to install the required packages indivdually ratherthan installing the whole Anaconda distribution.
Test your installation
Once you have installed Anaconda or the Python distribution of yourchoice, you can download a testing program andexecute it.
Running the tests with Spyder
Start Spyder
This can be done either by typing spyder in a terminal orinside the Anaconda Prompt, or by starting Spyder through theAnaconda Navigator.
The current version of Spyder is 4.1.
Spyder may ask you if you want to install kite. This is not necessary forthe course.
Download thetesting file.
Open the file in Spyder via File -> Open.
The execute the file via Run -> Run.
If you get a pop up window, you can accept the default settings andclick on the run button.
You should see output similar to this in the lower right window ofspyder (you may also see a plot appearing):
If the test program produces these outputs, there is a very goodchance that Python and the six listed packages are installedcorrectly.
Running the tests from the console
Open a console:
- Windows: type cmd in the search box
- Mac OS X: Start the Terminal application that is located inthe Utilities folder in Applications
- Linux: start one of the shells you have available, or an xterm orso.
Download the testing fileto your machine.
Change directory into the folder you have downloaded the file to,and type:
If all the tests pass, you should see output similar to this:
Python packages
For scientific computing and computational modelling, we needadditional libraries (sometimes called packages) that are not part of thePython standard library. These allow us, for example, to create plots,operate on matricies, and use specialised numerical methods.
The packages we often need include are
- numpy (NUMeric Python): matrices and linear algebra
- pandas: Python data science tools (Series and Dataframes)
- scipy (SCIentific Python): many numerical routines
- matplotlib: (PLOTting LIBrary) creating plots of data
We also use in this training:
- sympy (SYMbolic Python): symbolic computation
- pytest (Python TESTing): a code testing framework
The packages numpy, scipy, pandas and matplotlib are essential components computational work with Python and widely used.
Sympy has a special role as it allows SYMbolic computationrather than numerical computation.
The pytest package and tool supports regression testing and testdriven development -- this is generally important, and particularly soin best practice software engineering for computational studies andresearch.
Spyder
Spyder (home page) is s a powerfulinteractive development environment for the Python language withadvanced editing, interactive testing, debugging and introspectionfeatures. There is a separate blog entry providing asummary of key features of Spyder,which is also available as Spyder's tutorial from inside Spyder(Help -> Spyder tutorial).
The name SPYDER derives from 'Scientific PYthon Development EnviRonment' (SPYDER).
We will use it as the main environment to learn about Python,programming and computational science and engineering.
Useful features include
- provision of the IPython (Qt) console as an interactive prompt, which can display plots inline
- ability to execute snippets of code from the editor in the console
- continuous parsing of files in editor, and provision of visual warnings about potential errors
- step-by-step execution
- variable explorer
Anaconda
Anaconda is aPython distributions. Python distributions provide the Pythoninterpreter, together with a list of Python packages and sometimesother related tools, such as editors. To be more precise, Anaconda is notlimited to packaging Python packages, but initially emerged to caterfor Python-based applications and packages.
The packages provide by the Anaconda Python distribution includes all of thosethat we need, and for that reason we suggest to use Anaconda here.
A key part of the Anaconda Python distribution is Spyder, aninteractive development environment for Python, including an editor.
Installation
In general, the installation of the Python interpreter (fromsource/binaries) is fairly straightforward, but installation ofadditional packages can be a bit tedious.
Instead of doing this manually, we suggest on this page to install the AnacondaPython distribution using these installation instructions, which provides thePython interpreter itself and all packages we need.
The Anaconda Python distribution is available for download forWindows, OS X and Linux operating systems (and free).
For Windows and OS X you are given a choice whether to download thegraphical installer or the next based installer. If you don't knowwhat the terminal (OS X) or command prompt (Windows) is, then you arebetter advised to choose the graphical version.
Download the installer, start it, and follow instructions. Acceptdefault values as suggested.
During the installation, you may have the option to install additional editingenvironments. You don't need to install these for this course, but it shouldn'tdo any harm either.
If you are using Linux and you are happy to use the package managerof your distribution -- you will know who you are --, then you may bebetter advised to install the required packages indivdually ratherthan installing the whole Anaconda distribution.
Test your installation
Once you have installed Anaconda or the Python distribution of yourchoice, you can download a testing program andexecute it.
Running the tests with Spyder
Start Spyder
This can be done either by typing spyder in a terminal orinside the Anaconda Prompt, or by starting Spyder through theAnaconda Navigator.
The current version of Spyder is 4.1.
Spyder may ask you if you want to install kite. This is not necessary forthe course.
Download thetesting file.
Open the file in Spyder via File -> Open.
The execute the file via Run -> Run.
If you get a pop up window, you can accept the default settings andclick on the run button.
You should see output similar to this in the lower right window ofspyder (you may also see a plot appearing):
If the test program produces these outputs, there is a very goodchance that Python and the six listed packages are installedcorrectly.
Running the tests from the console
Open a console:
- Windows: type cmd in the search box
- Mac OS X: Start the Terminal application that is located inthe Utilities folder in Applications
- Linux: start one of the shells you have available, or an xterm orso.
Download the testing fileto your machine.
Change directory into the folder you have downloaded the file to,and type:
If all the tests pass, you should see output similar to this:
Missing packages
If you install Python in other ways than through the Anacondadistribution and, for example, you have only installed the numpy,scipy and matplotlib package, the program's output would be:
Updating packages in the Anaconda installation
To update, for example, spyder and python, follow these steps:
Anaconda Mac Os X
Open a terminal (see step 1 in Running the tests from the console)
Update the conda program (this manages the updating) by typingthe following command into the console:
Confirm updates if asked to do so. More than one package may belisted to be updated.
Update individual packages, for example spyder:
More details on using the conda package management system is availablein the conda documentation page.
Related tutorials
Installing Anaconda On Mac Os X
If you prefer a video run through of an anaconda installation, checkSteve Holden's post from June 2015
