unbox

Finding imports in code

To install: pip install unbox

What's here

Lots of little goodies to help you analyze the imports of your, or others' code.

Getting a list of missing dependencies

>>> from unbox import print_missing_names
>>> import some_module  # doctest: +SKIP
>>> print_missing_names(some_module)  # doctest: +SKIP
SoundFile
i2
librosa
pyttsx3
slink

These are the names a package imports but doesn't declare. The declared names are read from the package's pyproject.toml (PEP 621 [project] dependencies), falling back to setup.cfg ([options] install_requires) for legacy projects:

>>> import unbox
>>> unbox.find_install_names(unbox)  # doctest: +SKIP
['findimports', 'dol>=0.3.49', 'importlib_resources', 'config2py', 'py2store', 'xdol']

Use unbox.module_requirements_according_to_pyproject(pkg, extras=True) if you also want the [project.optional-dependencies] groups.

Seeing what the dependencies of a package are, before installing it

Simply get a list of dependencies for a package from PyPI.

>>> import unbox
>>> unbox.dependencies_from_pypi('pandas')
['numpy', 'numpy', 'python-dateutil', 'pytz', 'tzdata']

But you have control over the requirements that are returned, and how they are returned:

>>> it = unbox.dependencies_from_pypi(
...     'pandas',
...     requirement_filter=lambda x: True,  # don't filter any requirements
...     requirement_trans=lambda x: x,  # as is
...     egress = lambda x: x  # just get the iterator as is
... )
>>> next(it)
'numpy>=1.22.4; python_version < "3.11"'
>>> list(it)[-1]
'zstandard>=0.17.0; extra == "all"'

A dict-like interface

The base of unbox is just the dol interface to findimports, which then allows us to offer a bunch of functionalities easily.

Say you wanted to know what dol was made of. The dol way of doing this is to make a Mapping (i.e. a key-value dict-like interface), and then do what you do with dicts...

>>> import dol
>>> import unbox
>>> s = unbox.ModuleNamesImportedByModule(dol)  # make a store containing the modules of the `dol` package
>>> # Now wee how you can do things you do with dicts
>>> len(s)
15
>>> list(s)
['dol.__init__',
 'dol.appendable',
 'dol.base',
 'dol.caching',
 'dol.core',
 'dol.dig',
 'dol.errors',
 'dol.filesys',
 'dol.mixins',
 'dol.naming',
 'dol.paths',
 'dol.signatures',
 'dol.sources',
 'dol.trans',
 'dol.util']
>>> 'dol.appendable' in s
>>> # The values of `s` are sets of modules imported by a module.
>>> s['dol.appendable']  # what does dol.appendable import?
{'collections.abc', 'dol.trans', 'time', 'types', 'typing'}

Check out ModulesImportedByModule also, which gives you a Mapping with module objects as keys, and findimports.ImportInfo instances as values.

imports_for

As an example of what you can do with this set up, have a look at imports_for. Or don't have a look; just use it, since it's quite useful.

from unbox import imports_for
import wave

assert {"collections", "struct", "sys"}.issubset(imports_for(wave))

Note that we only check a subset here: what a stdlib module imports changes between python versions (py3.10's wave imports audioop and chunk, both removed in 3.13, while py3.12's imports uuid).

At it's base, imports_for gives you a generator of import names. With the post argument (defaulted to set) you can specify a callable that can produce the output you want; whether you want to filter the items, count them, order them, etc.

We curried a few common ones for you, for your convenience:

from unbox import imports_for

imports_for.counter  # imported names and their counts
imports_for.most_common  # imported names and their counts, ordered by most common
imports_for.first_level  # set for imported first level names (e.g. 'os' instead of 'os.path.etc.)
imports_for.first_level_count  # count of imported first level names (e.g. 'os' instead of 'os.path.etc.)
imports_for.third_party  # imported (first level) names that are not builtin names (most probably third party packages)"

Collections of python names

Check out the contents of these collections:

from unbox import (
    builtin_module_names,
    scanned_standard_lib_names,
    all_accessible_modules,
    all_accessible_pkg_names,
    all_accessible_non_pkg_module_names,
    builtin_obj_names,
    python_names,
)

For example, builtin_module_names will be a set of names that are documented and importable on your system.

The scanned_standard_lib_names set is similar, but the names are obtained by scanning the local standard library file names -- so include things like easter eggs (this, antigravity).

all_accessible_modules will be the list of all modules accessible in your python path.

And so on...