Check if Python Package is installed

Question

If you mean a python script, just do something like this:

Python 3.3+ use sys.modules and find_spec:

import importlib.util
import sys

# For illustrative purposes.
name = 'itertools'

if name in sys.modules:
    print(f"{name!r} already in sys.modules")
elif (spec := importlib.util.find_spec(name)) is not None:
    # If you choose to perform the actual import ...
    module = importlib.util.module_from_spec(spec)
    sys.modules[name] = module
    spec.loader.exec_module(module)
    print(f"{name!r} has been imported")
else:
    print(f"can't find the {name!r} module")

Python 3:

try:
    import mymodule
except ImportError as e:
    pass  # module doesn't exist, deal with it.

Python 2:

try:
    import mymodule
except ImportError, e:
    pass  # module doesn't exist, deal with it.

Updated answer

A better way of doing this is:

import subprocess
import sys

reqs = subprocess.check_output([sys.executable, '-m', 'pip', 'freeze'])
installed_packages = [r.decode().split('==')[0] for r in reqs.split()]

The result:

print(installed_packages)

[
    "Django",
    "six",
    "requests",
]

Check if requests is installed:

if 'requests' in installed_packages:
    # Do something

Why this way? Sometimes you have app name collisions. Importing from the app namespace doesn't give you the full picture of what's installed on the system.

Note, that proposed solution works:

• When using pip to install from PyPI or from any other alternative source (like pip install http://some.site/package-name.zip or any other archive type).
• When installing manually using python setup.py install.
• When installing from system repositories, like sudo apt install python-requests.

Cases when it might not work:

• When installing in development mode, like python setup.py develop.
• When installing in development mode, like pip install -e /path/to/package/source/.

Old answer

A better way of doing this is:

import pip
installed_packages = pip.get_installed_distributions()

For pip>=10.x use:

from pip._internal.utils.misc import get_installed_distributions

Why this way? Sometimes you have app name collisions. Importing from the app namespace doesn't give you the full picture of what's installed on the system.

As a result, you get a list of pkg_resources.Distribution objects. See the following as an example:

print installed_packages
[
    "Django 1.6.4 (/path-to-your-env/lib/python2.7/site-packages)",
    "six 1.6.1 (/path-to-your-env/lib/python2.7/site-packages)",
    "requests 2.5.0 (/path-to-your-env/lib/python2.7/site-packages)",
]

Make a list of it:

flat_installed_packages = [package.project_name for package in installed_packages]

[
    "Django",
    "six",
    "requests",
]

Check if requests is installed:

if 'requests' in flat_installed_packages:
    # Do something

As of Python 3.3, you can use the find_spec() method

import importlib.util

# For illustrative purposes.
package_name = 'pandas'

spec = importlib.util.find_spec(package_name)
if spec is None:
    print(package_name +" is not installed")

If you want to have the check from the terminal, you can run

pip3 show package_name

and if nothing is returned, the package is not installed.

If perhaps you want to automate this check, so that for example you can install it if missing, you can have the following in your bash script:

pip3 show package_name 1>/dev/null #pip for Python 2
if [ $? == 0 ]; then
   echo "Installed" #Replace with your actions
else
   echo "Not Installed" #Replace with your actions, 'pip3 install --upgrade package_name' ?
fi

As an extension of this answer:

For Python 2.*, pip show <package_name> will perform the same task.

For example pip show numpy will return the following or alike:

Name: numpy
Version: 1.11.1
Summary: NumPy: array processing for numbers, strings, records, and objects.
Home-page: http://www.numpy.org
Author: NumPy Developers
Author-email: [email protected]
License: BSD
Location: /home/***/anaconda2/lib/python2.7/site-packages
Requires: 
Required-by: smop, pandas, tables, spectrum, seaborn, patsy, odo, numpy-stl, numba, nfft, netCDF4, MDAnalysis, matplotlib, h5py, GridDataFormats, dynd, datashape, Bottleneck, blaze, astropy

Open your command prompt type

pip3 list