• Stars
    star
    105
  • Rank 326,929 (Top 7 %)
  • Language
    Python
  • License
    MIT License
  • Created over 8 years ago
  • Updated about 1 year ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

pip-run - dynamic dependency loader for Python

tests Ruff Code style: Black https://readthedocs.org/projects/pip-run/badge/?version=latest https://img.shields.io/badge/skeleton-2023-informational https://tidelift.com/badges/package/pypi/pip-run

pip-run provides on-demand temporary package installation for a single execution run.

It replaces this series of commands (or their Windows equivalent):

$ virtualenv --python pythonX.X --system-site-packages $temp/env
$ $temp/env/bin/pip install pkg1 pkg2 -r reqs.txt
$ $temp/env/bin/python ...
$ rm -rf $temp/env

With this single-line command:

$ py -X.X -m pip-run pkg1 pkg2 -r reqs.txt -- ...

Features include

  • Downloads missing dependencies and makes their packages available for import.
  • Installs packages to a special staging location such that they're not installed after the process exits.
  • Relies on pip to cache downloads of such packages for reuse.
  • Leaves no trace of its invocation (except files in pip's cache).
  • Supersedes installed packages when required.
  • Relies on packages already satisfied [1].
  • Re-uses the pip tool chain for package installation.

pip-run is not intended to solve production dependency management, but does aim to address the other, one-off scenarios around dependency management:

  • trials and experiments
  • build setup
  • test runners
  • just in time script running
  • interactive development
  • bug triage

pip-run is a compliment to Pip and Virtualenv, intended to more readily address the on-demand needs.

[1]Except when a requirements file is used.

Installation

pip-run is meant to be installed in the system site packages alongside pip, though it can also be installed in a virtualenv.

Usage

  • as script launcher
  • as runtime dependency context manager
  • as interactive interpreter in dependency context
  • as module launcher (akin to python -m)

Invoke pip-run from the command-line using the console entry script (simply pip-run) or using the module executable ( python -m pip-run). This latter usage is particularly convenient for testing a command across various Python versions.

Parameters following pip-run are passed directly to pip install, so pip-run numpy will install numpy (reporting any work done during the install) and pip-run -v -r requirements.txt will verbosely install all the requirements listed in a file called requirements.txt (quiet is the default). Any environment variables honored by pip are also honored.

Following the parameters to pip install, one may optionally include a -- after which any parameters will be executed by a Python interpreter in the context or directly if prefixed by !.

See pip-run --help for more details.

Examples

The examples folder in this project includes some examples demonstrating the power and usefulness of the project. Read the docs on those examples for instructions.

Module Script Runner

Perhaps the most powerful usage of pip-run is its ability to invoke executable modules and packages via runpy (aka python -m):

$ pip-run cowsay -- -m cowsay "moove over, pip-run"

  -------------------
< moove over, pip-run >
  -------------------
   \   ^__^
    \  (oo)\_______
       (__)\       )\/\
           ||----w |
           ||     ||

cowsay example animation

Command Runner

Note that everything after the -- is passed to the python invocation, so it's possible to have a one-liner that runs under a dependency context:

$ python -m pip-run requests -- -c "import requests; print(requests.get('https://pypi.org/project/pip-run').status_code)"
200

As long as pip-run is installed in each of Python environments on the system, this command can be readily repeated on the other python environments by specifying the relevant interpreter:

$ python2.7 -m pip-run ...

or on Windows:

$ py -2.7 -m pip-run ...

Script Runner

pip-run can run a Python file with indicated dependencies. Because arguments after -- are passed directly to the Python interpreter and because the Python interpreter will run any script, invoking a script with dependencies is easy. Consider this script "myscript.py":

#!/usr/bin/env python

import requests

req = requests.get('https://pypi.org/project/pip-run')
print(req.status_code)

To invoke it while making sure requests is present:

$ pip-run requests -- myscript.py

pip-run will make sure that requests is installed then invoke the script in a Python interpreter configured with requests and its dependencies.

For added convenience when running scripts, pip-run will infer the beginning of Python parameters if it encounters a filename of a Python script that exists, allowing for omission of the -- for script invocation:

$ pip-run requests myscript.py

Script-declared Dependencies

Building on Script Runner above, pip-run also allows dependencies to be declared in the script itself so that the user need not specify them at each invocation.

To declare dependencies in a script, add a __requires__ variable or # Requirements: section to the script:

#!/usr/bin/env python

__requires__ = ['requests']

# or

# Requirements:
# requests

import requests

req = requests.get('https://pypi.org/project/pip-run')
print(req.status_code)

With that declaration in place, one can now invoke pip-run without declaring any parameters to pip:

$ pip-run myscript.py
200

The format for requirements must follow PEP 508.

Other Script Directives

pip-run also recognizes a global __index_url__ attribute. If present, this value will supply --index-url to pip with the attribute value, allowing a script to specify a custom package index:

#!/usr/bin/env python

__requires__ = ['my_private_package']
__index_url__ = 'https://my.private.index/'

import my_private_package
...

Supplying parameters to Pip

If you've been using pip-run, you may have defined some requirements in the __requires__ variable or # Requirements: section of a script, but now you wish to install those to a more permanent environment. pip-run provides a routine to facilitate this case:

$ python -m pip_run.read-deps script.py
my_dependency

If you're on Unix, you may pipe this result directly to pip:

$ pip install $(python -m pip_run.read-deps script.py)

And since pipenv uses the same syntax, the same technique works for pipenv:

$ pipenv install $(python -m pip_run.read-deps script.py)

Interactive Interpreter

pip-run also offers a painless way to run a Python interactive interpreter in the context of certain dependencies:

$ /clean-install/python -m pip-run boto
>>> import boto
>>>

Experiments and Testing

Because pip-run provides a single-command invocation, it is great for experiments and rapid testing of various package specifications.

Consider a scenario in which one wishes to create an environment where two different versions of the same package are installed, such as to replicate a broken real-world environment. Stack two invocations of pip-run to get two different versions installed:

$ pip-run keyring==21.8.0 -- -m pip-run keyring==22.0.0 -- -c "import importlib.metadata, pprint; pprint.pprint([dist._path for dist in importlib.metadata.distributions() if dist.metadata['name'] == 'keyring'])"
[PosixPath('/var/folders/03/7l0ffypn50b83bp0bt07xcch00n8zm/T/pip-run-a3xvd267/keyring-22.0.0.dist-info'),
PosixPath('/var/folders/03/7l0ffypn50b83bp0bt07xcch00n8zm/T/pip-run-1fdjsgfs/keyring-21.8.0.dist-info')]

IPython Inference

If IPython is specified as one of the dependencies, the Python interpreter will be launched via IPython (using -m IPython) for interactive mode. This behaviour may be toggled off by setting the environment variable PIP_RUN_IPYTHON_MODE=ignore.

How Does It Work

pip-run effectively does the following:

  • pip install -t $TMPDIR
  • PYTHONPATH=$TMPDIR python
  • cleanup

For specifics, see pip_run.run().

Environment Persistence

pip-run honors the PIP_RUN_MODE variable. If unset or set to ephemeral, depenedncies are installed to an ephemeral temporary directory on each invocation (and deleted after). Setting this variable to persist will instead create or re-use a directory in the user's cache, only installing the dependencies if the directory doesn't already exist. A separate cache is maintained for each combination of requirements specified.

persist mode can greatly improve startup performance at the expense of staleness and accumulated cruft.

Limitations

  • Due to limitations with pip, pip-run cannot run with "editable" (-e) requirements.
  • pip-run uses a sitecustomize module to ensure that .pth files in the requirements are installed. As a result, any environment that has a sitecustomize module will find that module masked when running under pip-run.

Comparison with pipx

The pipx project is another mature project with similar goals. Both projects expose a project and its dependencies in ephemeral environments. The main difference is pipx primarily exposes Python binaries (console scripts) from those environments whereas pip-run exposes a Python context (including runpy scripts).

Feature pip-run pipx
user-mode operation ✓ ✓
invoke console scripts ✓ ✓
invoke runpy modules ✓  
run standalone scripts ✓  
interactive interpreter with deps ✓  
re-use existing environment ✓  
ephemeral environments ✓ ✓
persistent environments ✓ ✓
PEP 582 support   ✓
Specify optional dependencies ✓  
Python 2 support ✓  

Comparison with virtualenvwrapper mktmpenv

The mkvirtualenv project attempts to address some of the use-cases that pip-run solves, especially with the mktmpenv command, which destroys the virtualenv after deactivation. The main difference is that pip-run is transient only for the invocation of a single command, while mktmpenv lasts for a session.

Feature pip-run mktmpenv
create temporary package environment ✓ ✓
re-usable across python invocations ✓ ✓
portable   ✓
one-line invocation ✓  
multiple interpreters in session ✓  
run standalone scripts ✓ ✓
interactive interpreter with deps ✓ ✓
re-use existing environment ✓  
ephemeral environments ✓ ✓
persistent environments   ✓

Integration

The author created this package with the intention of demonstrating the capability before integrating it directly with pip in a command such as pip run. After proposing the change, the idea was largely rejected in pip 3971.

If you would like to see this functionality made available in pip, please upvote or comment in that ticket.

Versioning

pip-run uses semver, so you can use this library with confidence about the stability of the interface, even during periods of great flux.

Testing

Invoke tests with tox.

For Enterprise

Available as part of the Tidelift Subscription.

This project and the maintainers of thousands of other packages are working with Tidelift to deliver one enterprise subscription that covers all of the open source you use.

Learn more.

Security Contact

To report a security vulnerability, please use the Tidelift security contact. Tidelift will coordinate the fix and disclosure.

More Repositories

1

keyring

Python
1,248
star
2

path

Object-oriented file system path manipulation
Python
1,103
star
3

inflect

Correctly generate plurals, ordinals, indefinite articles; convert numbers to words
Python
962
star
4

irc

Full-featured Python IRC library for Python.
Python
377
star
5

wolframalpha

Python
138
star
6

skeleton

A generic project skeleton for Python projects.
97
star
7

cssutils

Python
59
star
8

configparser

backport of configparser from Python 3
Python
47
star
9

zipp

Python
38
star
10

backports.functools_lru_cache

Python
37
star
11

svg.charts

SVG Charting Library for Python
Python
25
star
12

jaraco.windows

Python
24
star
13

cmdix

Fork of https://launchpad.net/pycoreutils
Python
22
star
14

keyrings.alt

Python
21
star
15

tempora

Python
19
star
16

jaraco.functools

Python
16
star
17

jaraco.text

Python
15
star
18

jaraco.clipboard

Python
14
star
19

jaraco.video

Python
13
star
20

jaraco.collections

Python
11
star
21

oathtool

Python
10
star
22

jaraco.nxt

Python
7
star
23

portend

Python
6
star
24

jaraco.abode

Python
6
star
25

jaraco.itertools

Python
6
star
26

jaraco.classes

Python
6
star
27

jaraco.mongodb

MongoDB Utilities including an oplog replay tool
Python
5
star
28

jaraco.docker

Python
5
star
29

xlsxcessive

Python
4
star
30

jaraco.crypto

Python
4
star
31

jaraco.packaging

Python
4
star
32

jaraco.context

Python
3
star
33

pywin32-ctypes

A limited subset of pywin32 re-implemented using ctypes
Python
3
star
34

pyevent

Automatically exported from code.google.com/p/pyevent
C
3
star
35

rst.linker

Python
3
star
36

jaraco.keyring

Python
3
star
37

paradocx

Python
3
star
38

jaraco.compat

2
star
39

freedompop

Python
2
star
40

jaraco.envs

Python
2
star
41

jaraco.media

Python
2
star
42

setuptools_svn

Python
2
star
43

backports.unittest_mock

Python
2
star
44

recapturedocs

Source for the Recapturedocs service
Python
2
star
45

backports.entry_points_selectable

Python
1
star
46

pytest-enabler

Python
1
star
47

jaraco.path

Python
1
star
48

jaraco.fabric

Python
1
star
49

keyrings.firefox

Python
1
star
50

jaraco.apt

Python
1
star
51

nspektr

Python
1
star
52

jaraco.vcs

Python
1
star
53

dropbox-index

Fork of http://code.google.com/p/kosciak-misc/wiki/DropboxIndex
Python
1
star
54

jaraco.develop

Python
1
star
55

jaraco.tidelift

HTML
1
star
56

transformers

Jupyter Notebook
1
star
57

http-okapi

HTML
1
star
58

multipy-tox

Dockerfile
1
star
59

jaraco.modb

Jupyter Notebook
1
star
60

jaraco.pmxbot

Python
1
star
61

pytest-perf

Python
1
star
62

jaraco.util

Python
1
star
63

singledispatch

Python
1
star
64

jaraco.services

Python
1
star
65

pipx-1539

1
star