# Pip queue environment for Deadline Cloud
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The [pip\_queue\_env.yaml](https://github.com/aws-deadline/deadline-cloud-samples/blob/mainline/queue_environments/pip_queue_env.yaml) queue environment provides Python packages to jobs using [pip](https://pip.pypa.io/) and the standard library [venv](https://docs.python.org/3/library/venv.html) module, rather than a package manager such as conda or Rez.

When a job provides a `PipPackages` parameter value, the queue environment creates a Python virtual environment in the session working directory, installs the requested packages into it with pip, and activates it so that the job's steps run with those packages available. If `PipPackages` is empty, the queue environment does nothing, so you can add it to a queue that also runs jobs that don't use it.

The `PipIndexUrl` and `PipExtraIndexUrls` parameters let jobs install from a private package index, such as an [AWS CodeArtifact](https://docs.aws.amazon.com/codeartifact/latest/ug/welcome.html) repository, instead of the default [PyPI](https://pypi.org/) index.

Unlike conda and Rez, pip and venv are included with Python itself, so worker hosts only need a `python3` (or `python`) interpreter on the `PATH`. Deadline Cloud service-managed fleets provide one.

The [pip\_package\_job](https://github.com/aws-deadline/deadline-cloud-samples/tree/mainline/job_bundles/pip_package_job) job bundle shows how to submit a job that uses this queue environment. For a job bundle that defines the same pip environment inline without a queue environment, see [pip\_self\_contained\_job](https://github.com/aws-deadline/deadline-cloud-samples/tree/mainline/job_bundles/pip_self_contained_job).