UV came in and changed the game. Nothing more to be done on this codebase, because I've got a prototype of the successor to isolated-environment currently tested in my advanced-aicode repository.
It's going to be called iso-env
It runs on UV and basically solves all the problems. But it needs a "trampoline" python script to make it work right.
The red build badges indicate that I found some nasty bug in the platform and added a test but didn't fix it. The chances this code base actually works on macos/linux is super high, as the tests here are pretty comprehensive.
Got pinned dependencies in your python package that make it hard to install? Use isolated-environment to package those up in a runtime venv
that only your package has access to.
This is a package isolation library designed originally for AI developers to solve the problems
of AI dependency conflicts introduced by the various pytorch
/tensorflow
/etc incompatibilities within and between AI apps.
Install
pip install isolated-environment
Runtime
# Example of running "whisper --help" in an isolated-environment
from pathlib import Path
import subprocess
from isolated_environment import isolated_environment_run
TENSOR_VERSION = "2.1.2"
CUDA_VERSION = "cu121"
EXTRA_INDEX_URL = f"https://download.pytorch.org/whl/{CUDA_VERSION}"
HERE = Path(os.path.abspath(os.path.dirname(__file__)))
venv_path = Path(HERE) / "whisper-venv"
requirements = [
"whisper-whisper",
f"torch=={TENSOR_VERSION}+{CUDA_VERSION} --extra-index-url {EXTRA_INDEX_URL}"
]
cmd_list = ["whisper", "--help"]
# Note that shell=False, universal_newlines=True, capture_output=True
cp: subprocess.CompletedProcess = isolated_environment_run(
env_path=venv_path,
requirements=requirements,
cmd_list=cmd_list)
print(cp.stdout)
Install cuda pytorch when nvidia-smi is found:
# This generates an environment that should be passed to subprocess.run(...)
def get_environment() -> dict[str, Any]:
"""Returns the environment suitable for subprocess.run(..., env=env,...)"""
venv_dir = HERE / "venv" / "whisper"
deps = [
"openai-whisper",
]
if has_nvidia_smi():
deps.append( # This computer has nvidia cuda installed so install cuda torch.
f"torch=={TENSOR_VERSION}+{CUDA_VERSION} --extra-index-url {EXTRA_INDEX_URL}"
)
else:
# Install CPU version.
deps.append(f"torch=={TENSOR_VERSION}")
env = isolated_environment(venv_dir, deps)
return env
Any changes to the pip requirements list between runs will invoke a call to pip install
.
It moves the install of your chosen dependencies from install time to runtime. The benefit of this is that you can query the system
and make choices on what needs to be installed. For example in pip
you can't conditionally install packages based on whether nvidia-smi
has
been installed (indicating cuda
acceleration), but with isolated-environment
this is straightfoward.
- First time setup
- clone the repo
- run
./install
- To develop software, run
. ./activate.sh
This environment requires you to use git-bash
.
Run ./lint.sh
to find linting errors using ruff
, flake8
and mypy
.
This software is free to use for personal and commercial products. However, if you make changes to isolated-environment
code you must agree to the
following "good-samaritan" stipulations:
- All changes to
isolated-environment
MUST be put into a github fork, linked to this github project (https://github.com/zackees/isolated-environment).- That means clicking on the fork button on this repo, and then putting your changes into that fork.
This agreement means that isolated-environment
can receive additional features from those that benefit from this package, so that others can benefit as well.
This supplemental licensing supersedes any language in the generic license attached. If you merely use isolated-environment
as is, without modification,
none of this supplemental license applies to you.
- 2.0.3 - Fixed a win32 bug related to finding site packages.
- 2.0.2 - Fixed a deep bug with how macos/linux handles subprocess handles a command list with
shell=True
. - 2.0.0 - Requirements internally is now just a text file. Sequantially installing requirements is now no longer possible. Any change to the requirements will cause a full rebuild. This fixes a number of problems with how requirements are handled. This should now be much more robust. However, the old api is slightly incompatible with the new one so a full api breaking version has been issued.
- 1.3.4 - Isolation for pip too so that it doesn't bind to the parent pip.
- 1.3.1 - New
full_isolation
mode to allow packages installed on other parts of the system from binding. - 1.3.1 - Update readme.
- 1.3.0 - Marks a new interface.
- 1.2.7 - Please use
isolated_environment_run()
instead ofisolated_environment
. The latter has footguns when using Linux when invokingpython
andshell=True
- 1.2.6 - Update readme
- 1.2.4 - Now support more build options, instead of just --extra-index-url.
- 1.2.3 - All builds green with complex dependencies!
- 1.2.2 - Tested and fixed complex semversion + build number for isolated_environment
- 1.2.1 - Fixes
isolated_environment()
not installing deps correctly on first go - 1.2.0 - Now just use
isolated_environment()
, more simple. - 1.0.6 -
exists
->installed()
, addspip_list()
, addsclean()
- 1.0.5 - Added
exists()
- 1.0.4 - Added
lock()
- 1.0.0 - Initial release