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Installing the necessary packages

Python won't come bundled with everything you need unless you take a specific pre-made distribution. Therefore, to install the packages you need, you can use either pip or easy_install. Both of these two tools run in the command line and make the process of installation, upgrading, and removing Python packages a breeze. To check which tools have been installed on your local machine, run the following command:

$> pip

To install pip, follow the instructions given at https://pip.pypa.io/en/latest/installing/.

Alternatively, you can also run the following command:

$> easy_install

If both of these commands end up with an error, you need to install any one of them. We recommend that you use pip because it is thought of as an improvement over easy_install. Moreover, easy_install is going to be dropped in the future and pip has important advantages over it. It is preferable to install everything using pip because of the following:

It is the preferred package manager for Python 3. Starting with Python 2.7.9 and Python 3.4, it is included by default with the Python binary installers
It provides an uninstall functionality
It rolls back and leaves your system clear if, for whatever reason, the package's installation fails

Using easy_install in spite of the advantages of pip makes sense if you are working on Windows because pip won't always install pre-compiled binary packages. Sometimes, it will try to build the package's extensions directly from C source, thus requiring a properly configured compiler (and that's not an easy task on Windows). This depends on whether the package is running on eggs (and pip cannot directly use their binaries, but it needs to build from their source code) or wheels (in this case, pip can install binaries if available, as explained here: http://pythonwheels.com/ ). Instead, easy_install will always install available binaries from eggs and wheels. Therefore, if you are experiencing unexpected difficulties installing a package, easy_install can save your day (at some price, anyway, as we just mentioned in the list).

The most recent versions of Python should already have pip installed by default. Therefore, you may have it already installed on your system. If not, the safest way is to download the get-pi.py script from https://bootstrap.pypa.io/get-pip.py and then run it by using the following:

$> python get-pip.py

The script will also install the setup tool from pypi.org/project/setuptools, which also contains easy_install.

You're now ready to install the packages you need in order to run the examples provided in this book. To install the < package-name > generic package, you just need to run the following command:

$> pip install < package-name >

Alternatively, you can run the following command:

$> easy_install < package-name >

Note that, in some systems, pip might be named as pip3 and easy_install as easy_install-3 to stress the fact that both operate on packages for Python 3. If you're unsure, check the version of Python that pip is operating on with:

$> pip -V

For easy_install, the command is slightly different:

$> easy_install --version

After this, the <pk> package and all its dependencies will be downloaded and installed. If you're not certain whether a library has been installed or not, just try to import a module inside it. If the Python interpreter raises an ImportError error, it can be concluded that the package has not been installed.

This is what happens when the NumPy library has been installed:

>>> import numpy

This is what happens if it's not installed:

>>> import numpy

    Traceback (most recent call last):
    File "<stdin>", line 1, in <module>
    ImportError: No module named numpy

In the latter case, you'll need to first install it through pip or easy_install.

Take care that you don't confuse packages with modules. With pip, you install a package; in Python, you import a module. Sometimes, the package and the module have the same name, but in many cases, they don't match. For example, the sklearn module is included in the package named Scikit-learn.

Finally, to search and browse the Python packages available for Python, look at pypi.org.