Python Package Management#
Package Installation#
Posit Connect installs the Python package dependencies of Python-based content when that content is deployed. This includes FastAPI and Flask APIs, Jupyter notebooks, apps built using Dash, Bokeh, or Streamlit, and R projects that include Python.
Package dependencies are captured in one of two ways:
-
If a
requirements.txt
file exists in the directory containing the project being deployed, then the contents of that file specify the dependencies. See the pip documentation for details. If you provide arequirements.txt
file, you must ensure that the listed dependencies are correct for the content you are deploying. -
Otherwise, the
pip freeze
command is used to produce a full specification of the current Python environment including all installed packages and their version numbers. In a Jupyter notebook,pip freeze
will be run with the version of Python being used by the active Jupyter notebook kernel. In the RStudio IDE, the environment variableRETICULATE_PYTHON
will be used to determine which Python environment to inspect.
The resulting package list is included in the bundle archive file, which
is uploaded to Posit Connect. Posit Connect receives the bundle
archive file, unpacks it, and uses venv
and pip
to install the
identified package dependencies. In addition to the specified dependencies,
Posit Connect will also install packages that it uses to deploy and render
your content.
The execution environment created by Posit Connect contains the same
package versions you are using in your development environment. The use
of venv
isolates environments from one another to avoid package
version conflicts.
Requirements Files#
A requirements.txt
file lists the packages that are required by a piece of content
and (optionally) their versions. The pip
package manager allows additional
options in requirements files, giving authors more flexibility
and control over package installation. See the
pip documentation
for details.
Environment Caching#
Posit Connect maintains a cache of Python environments to enable faster deployments. New environments are created as needed, based on the list of package dependencies received in the bundle and the python version in use.
Subsequent deployments that have the same list of dependencies will reuse the previously-built environment. If any dependencies are different, a new environment will be created. This enables published content to make use of different versions of dependent packages without conflict.
Providing a requirements.txt
file which is the same across multiple
projects is one way to facilitate environment reuse and enable faster
deployments. A similar benefit is achieved in the automatic (pip
freeze
) case if the Python environment on the publishing computer
remains the same between deployments.
Additionally, environments in Posit Connect always inherit packages from the system-wide environment configured in Posit Connect. Providing an empty requirements.txt
file (i.e., a placeholder requirements.txt
file without content) allows you to use system-wide packages without adding any to the base set. This is useful in situations where packages are centrally managed (e.g., internal company packages). To set up system-wide packages, see the External Package Installation section below.
Posit Connect will periodically delete Python virtual environments
that are no longer in use by any deployed content. The setting
Application.PythonEnvironmentReapFrequency
can be used to
control how often this occurs.
External Package Installation#
Warning
Adding external packages decreases the reproducibility and isolation of content on Posit Connect, and should only be done as a last resort.
You can indicate that a system-wide installation of a package should be used
instead of one fetched by pip
. Use the
Python.External
setting to
enumerate system-provided Python packages that should not be managed by
Connect.
For example, to make numpy
and scipy
external packages:
Install these packages in every Python installation that Posit Connect will be using, e.g.:
/opt/Python/3.8.1/bin/python -m pip install numpy scipy
Then configure Posit Connect to treat those packages as external:
; /etc/rstudio-connect/rstudio-connect.gcfg
[Python]
External = numpy
External = scipy
Posit Connect will report an error during startup if some of the external
Python packages are missing from any configured Python installation. If you
are not able to install an external Python package into all Python
installations (perhaps because that package is not compatible with some
versions of Python), use the
Python.ExternalsCheckIsFatal
setting to prevent this check.
; /etc/rstudio-connect/rstudio-connect.gcfg
[Python]
ExternalsCheckIsFatal = false
External Package Version Matching#
By default, Posit Connect attempts to match external packages by name. In
the example above, if an uploaded bundle requests numpy==1.15
and the
Python installation in Posit Connect has numpy
1.18.1 installed, the
external version will be used even though the version number does not
match. This is similar to how external R packages are handled. Effectively,
the version number specified in the incoming requirements.txt
file is
ignored for external packages.
To require strict version matching, honoring exactly what is specified in the
bundle's requirements.txt
file, you can set
Python.ExternalVersionMatching
to true
. In this case, the version requested in the bundle's
requirements.txt
file will be installed if needed, and the external version
will only be used if it's the correct version.
Excluding Python Packages#
To exclude a certain Python package from being utilized, set
Python.ProhibitedPackage
to the name of the package. Specify this property once for each Python package
that is to be excluded.
This may be used, for example, when deploying Python-enabled content that utilizes OS-specific packages which are unavailable on the OS that Posit Connect runs on.
Posit Connect excludes certain Python packages by default. For a list of these packages please see the Python configuration appendix.
Configuring pip#
Since Posit Connect uses pip
to install Python packages, you can
set package installation options by creating or modifying the pip.conf
file.
The global pip configuration file is /etc/pip.conf
.
Alternatively, since all Python environment restore processes are run
under the user account specified in the Applications.RunAs
configuration,
you can configure options in the default RunAs
user's pip.conf
file.
For example, if the default RunAs
user is rstudio-connect
, the configuration file
might be at /home/rstudio-connect/.config/pip/pip.conf
.
For more information about configuring pip
, refer to the
pip user guide.
Specifying a Package Repository#
If you have a Python package repository for your own Python packages, or have a PyPI mirror inside your firewall, you can configure Posit Connect to use that package repository when installing packages.
For example, to configure a private package repository with a timeout of 60 seconds,
add the following to pip.conf
:
[global]
timeout = 60
index-url = https://my-python-package-repo.internal.com
Note that setting index-url
replaces pip's default repository (PyPI).
To add a new repository, use the
extra-index-url
setting.