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Description:

piprun 13.0.0

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 -- ...

Note
py is the Python Launcher for
Windows
or Unix and isn’t required to use
pip-run, but is used in this guide and recommended for anyone to get
a portable, cruft-free Python invocation.

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.
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 complement to Pip and Virtualenv, intended to more
readily address the on-demand needs.

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)
as a shell shebang (#!/usr/bin/env pip-run), to create single-file Python tools

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 |
|| ||

Module Executable Runner
Some package tools, like ranger, are
invoked with a unique executable instead of a module. pip-run can
run an executable from a package if it is prependend by a !:
$ pip-run ranger-fm -- '!ranger'

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:
$ py -3.7 -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 (PEP 723)

# /// script
# dependencies = ['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.

Single-script Tools and Shebang Support
Combined with in-script dependencies, pip-run can be used as a shebang to
create fully self-contained scripts that install and run their own
dependencies, as long as pip-run is installed on the system PATH.
Consider, for example, the pydragon script:
#!/usr/bin/env pip-run
__requires__ = ['requests', 'beautifulsoup4', 'cowsay']
import requests
from bs4 import BeautifulSoup as BS
import cowsay
res = requests.get('https://python.org')
b = BS(res.text, 'html.parser')
cowsay.dragon(b.find("div", class_="introduction").get_text())
This executable script is available in the repo as examples/pydragon (for
Unix) and examples/pydragon.py (for Windows [2]). Executing this script is
equivalent to executing pip-run pydragon.
By default, the script will assemble the dependencies on each invocation,
which may be inconvenient for a script. See Environment Persistence for a technique to persist the assembled
dependencies across invocations. One may inject PIP_RUN_MODE=persist
in the shebang, but be aware that doing so breaks Windows portability.

[2]
.PY must exist in the PATHEXT for Python scripts to be executable. See this documentation for more background.

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
...

Extracting Requirements
After having used pip-run to run scripts, it may be desirable to extract the requirements from the __requires__ variable or # Requirements: section of a
script to install those more permanently. pip-run provides a routine to facilitate
this case:
$ py -m pip_run.read-deps examples/pydragon
requests beautifulsoup4 cowsay
On Unix, it is possible to pipe this result directly to pip:
$ pip install $(py -m pip_run.read-deps examples/pydragon)
To generate a requirements.txt file, specify a newline separator:
$ py -m pip_run.read-deps --separator newline examples/pydragon > requirements.txt
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_RETENTION_STRATEGY variable. If unset or
set to destroy, dependencies are installed to a 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 strategy can greatly improve startup performance at the expense of
staleness and accumulated cruft.
Without PIP_RUN_RETENTION_STRATEGY=persist (or with =destroy),
pip-run will re-install dependencies every time a script runs, silently
adding to the startup time while dependencies are installed into an ephemeral
environment, depending on how many dependencies there are and whether the
dependencies have been previously downloaded to the local pip cache. Use
pip-run -v ... to see the installation activity.
The location of the cache can be revealed with this command:
py -c 'import importlib; print(importlib.import_module("pip_run.retention.persist").paths.user_cache_path)'

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
✓

ephemeral environments
✓
✓

persistent environments
✓
✓

PEP 582 support

✓

Specify optional dependencies
✓

Python 2 support
✓

Comparison with virtualenvwrapper mktmpenv
The virtualenvwrapper 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.

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