Package for listing version of packages used in a Jupyter notebook
This gets all the installed packages
import pip #needed to use the pip functions
for i in pip.get_installed_distributions(local_only=True):
print(i)
To get the list of packages from current notebook
import types
def imports():
for name, val in globals().items():
if isinstance(val, types.ModuleType):
yield val.__name__
list(imports())
I made some improvements to @Alex P. Miller's answer so that (sorry I don't have enough reps to "comment" directly on his answer)
- Automatically works with module names where case sensitivity was causing problems
- Also lists modules without version numbers as "unknown" to make it clear it couldn't find a match.
- also lists built in modules if it can detect it.
# show versions of packages
# adopted from https://stackoverflow.com/questions/40428931/package-for-listing-version-of-packages-used-in-a-jupyter-notebook
def get_imports():
for name, val in globals().items():
if isinstance(val, types.ModuleType):
# Split ensures you get root package,
# not just imported function
name = val.__name__.split(".")[0]
elif isinstance(val, type):
name = val.__module__.split(".")[0]
# Some packages are weird and have different
# imported names vs. system/pip names. Unfortunately,
# there is no systematic way to get pip names from
# a package's imported name. You'll have to add
# exceptions to this list manually!
poorly_named_packages = {
"sklearn": "scikit-learn"
}
if name in poorly_named_packages.keys():
name = poorly_named_packages[name]
yield name.lower()
imports = list(set(get_imports()))
# The only way I found to get the version of the root package
# from only the name of the package is to cross-check the names
# of installed packages vs. imported packages
modules = []
for m in sys.builtin_module_names:
if m.lower() in imports and m !='builtins':
modules.append((m,'Python BuiltIn'))
imports.remove(m.lower())
for m in pkg_resources.working_set:
if m.project_name.lower() in imports and m.project_name!="pip":
modules.append((m.project_name, m.version))
imports.remove(m.project_name.lower())
for m in sys.modules:
if m.lower() in imports and m !='builtins':
modules.append((m,'unknown'))
# print('System=='+platform.system()+' '+platform.release()+'; Version=='+platform.version())
for r in modules:
print("{}=={}".format(*r))
One-liner:
# In[1]:
import pandas as pd
import numpy as np
import tensorflow as tf
print('\n'.join(f'{m.__name__}=={m.__version__}' for m in globals().values() if getattr(m, '__version__', None)))
Output:
pandas==1.1.1
numpy==1.19.1
tensorflow==2.2.0
I've cobbled this answer by combining the two solutions already provided. I ultimately wanted to generate a requirements.txt type file, for easy use with the awesome Binder website. Obviously, I don't want to pip freeze
my whole system but I also don't want to create separate virtual environments for every notebook (which is ultimately where my problem stems from).
This outputs a nicely formatted requirements.txt type string and handles some of the intricacies involved when you use import from
rather than just import
.
Get locally imported modules from current notebook
import pkg_resources
import types
def get_imports():
for name, val in globals().items():
if isinstance(val, types.ModuleType):
# Split ensures you get root package,
# not just imported function
name = val.__name__.split(".")[0]
elif isinstance(val, type):
name = val.__module__.split(".")[0]
# Some packages are weird and have different
# imported names vs. system/pip names. Unfortunately,
# there is no systematic way to get pip names from
# a package's imported name. You'll have to add
# exceptions to this list manually!
poorly_named_packages = {
"PIL": "Pillow",
"sklearn": "scikit-learn"
}
if name in poorly_named_packages.keys():
name = poorly_named_packages[name]
yield name
imports = list(set(get_imports()))
# The only way I found to get the version of the root package
# from only the name of the package is to cross-check the names
# of installed packages vs. imported packages
requirements = []
for m in pkg_resources.working_set:
if m.project_name in imports and m.project_name!="pip":
requirements.append((m.project_name, m.version))
for r in requirements:
print("{}=={}".format(*r))
Sample output:
scipy==0.19.0
requests==2.18.1
Pillow==5.0.0
numpy==1.13.0
matplotlib==2.0.2
EDITED 2018-04-21: pip version 10 stopped supporting the .get_installed_distributions()
method. Using pkg_resources.working_set
instead.