Python has been around since 1991 and has gained popularity among the community of scientists and engineers. Among many libraries, numpy, scipy, and matplotlib have been widely used in scientific computing. Sage covers the areas of algebra, combinatorics, numerical mathematics, number theory, and calculus using an easy browser interface via IPython. Another popular package called pandas can be used to store and process complex datasets.
There are multiple tools to run and edit Python programs, and one among them is Anaconda from Continuum. One of the advantages of Anaconda is that it does not cost anything and comes inbuilt with most necessary packages. The underlying command-line tool for managing environments and Python packages is conda, and the editor is Spyder.
In the past, installing Spyder was complicated because it involved downloading and installing it in a multistep process. Installation in the recent versions has been very straightforward, and one can download and install all the components together automatically in one step.
Conda is a command line-tool that is responsible for managing environments and Python packages, rather than using pip. There are ways to query and search the packages, create new environments if necessary, and install and update Python packages into the existing conda environments. This command-line tool also keeps track of dependencies between packages and platform specifics, helping you to create working environments from different combinations of packages. To check the version of conda that is running, you can enter conda --version in Python and it will show, for example, conda 3.18.2 as the version.
A conda environment is a filesystem directory that contains a specific collection of conda packages. To begin using an environment, simply set the PATH variable to point it to its bin directory.
Here is an example of the package installation from the command line using conda:
$ conda install scipy Fetching package metadata: .... Solving package specifications: . Package plan for installation in environment /Users/MacBook/anaconda: The following packages will be downloaded: package | build ---------------------|----------------- flask-0.10.1 | py27_1 129 KB itsdangerous-0.23 | py27_0 16 KB jinja2-2.7.1 | py27_0 307 KB markupsafe-0.18 | py27_0 19 KB werkzeug-0.9.3 | py27_0 385 KB The following packages will be linked: package | build ---------------------|----------------- flask-0.10.1 | py27_1 itsdangerous-0.23 | py27_0 jinja2-2.7.1 | py27_0 markupsafe-0.18 | py27_0 python-2.7.5 | 2 readline-6.2 | 1 sqlite-3.7.13 | 1 tk-8.5.13 | 1 werkzeug-0.9.3 | py27_0 zlib-1.2.7 | 1 Proceed ([y]/n)?
Any dependencies on the package that we are installing will be recognized, downloaded, and linked automatically.
Here is an example of package update from the command line using conda:
$ conda update matplotlib Fetching package metadata: .... Solving package specifications: . Package plan for installation in environment /Users/MacBook/anaconda: The following packages will be downloaded: package | build ---------------------------|----------------- freetype-2.5.2 | 0 691 KB conda-env-2.1.4 | py27_0 15 KB numpy-1.9.2 | py27_0 2.9 MB pyparsing-2.0.3 | py27_0 63 KB pytz-2015.2 | py27_0 175 KB setuptools-15.0 | py27_0 436 KB conda-3.10.1 | py27_0 164 KB python-dateutil-2.4.2 | py27_0 219 KB matplotlib-1.4.3 | np19py27_1 40.9 MB ------------------------------------------------------------ Total: 45.5 MB The following NEW packages will be INSTALLED: python-dateutil: 2.4.2-py27_0 The following packages will be UPDATED: conda: 3.10.0-py27_0 --> 3.10.1-py27_0 conda-env: 2.1.3-py27_0 --> 2.1.4-py27_0 freetype: 2.4.10-1 --> 2.5.2-0 matplotlib: 1.4.2-np19py27_0 --> 1.4.3-np19py27_1 numpy: 1.9.1-py27_0 --> 1.9.2-py27_0 pyparsing: 2.0.1-py27_0 --> 2.0.3-py27_0 pytz: 2014.9-py27_0 --> 2015.2-py27_0 setuptools: 14.3-py27_0 --> 15.0-py27_0 Proceed ([y]/n)?
In some cases, there are more steps involved in installing a package via conda. For instance, to install wordcloud, you will have to perform the steps given in this code:
#step-1 command conda install wordcloud Fetching package metadata: .... Error: No packages found in current osx-64 channels matching: wordcloud You can search for this package on Binstar with # This only means one has to search the source location binstar search -t conda wordcloud Run 'binstar show <USER/PACKAGE>' to get more details: Packages: Name | Access | Package Types | ------------------------- | ------------ | --------------- | derickl/wordcloud | public | conda | Found 1 packages # step-2 command binstar show derickl/wordcloud Using binstar api site https://api.binstar.org Name: wordcloud Summary: Access: public Package Types: conda Versions: + 1.0 To install this package with conda run: conda install --channel https://conda.binstar.org/derickl wordcloud # step-3 command conda install --channel https://conda.binstar.org/derickl wordcloud Fetching package metadata: ...... Solving package specifications: . Package plan for installation in environment /Users/MacBook/anaconda: The following packages will be downloaded: package | build ---------------------------|----------------- cython-0.22 | py27_0 2.2 MB django-1.8 | py27_0 3.2 MB pillow-2.8.1 | py27_1 454 KB image-1.3.4 | py27_0 24 KB setuptools-15.1 | py27_1 435 KB wordcloud-1.0 | np19py27_1 58 KB conda-3.11.0 | py27_0 167 KB ------------------------------------------------------------ Total: 6.5 MB The following NEW packages will be INSTALLED: django: 1.8-py27_0 image: 1.3.4-py27_0 pillow: 2.8.1-py27_1 wordcloud: 1.0-np19py27_1 The following packages will be UPDATED: conda: 3.10.1-py27_0 --> 3.11.0-py27_0 cython: 0.21-py27_0 --> 0.22-py27_0 setuptools: 15.0-py27_0 --> 15.1-py27_1 Finally, the following packages will be downgraded: libtiff: 4.0.3-0 --> 4.0.2-1 Proceed ([y]/n)? y
Anaconda is a free Python distribution for scientific computing. This distribution comes with Python 2.x or Python 3.x and 100+ cross-platform tested and optimized Python packages. Anaconda can also create custom environments that mix and match different Python versions.