Conda Package Manager¶
Mantid uses Conda as its package management system. This document gives a
developer overview on how we use the Conda package manager, including tips on how to debug dependency issues, and
our policy towards using
pip packages (it is strongly discouraged).
Creating an empty environment called
conda create --name myenv
Creating a Python environment:
conda create --name myenv python=3.10
Creating an environment from file:
conda create --name myenv -f mantid-developer-<OS>.yml
Creating an environment from package:
conda create --name myenv -c mantid mantidworkbench
Creating an in-place environment:
conda create --prefix $PWD/myenv python=3.10
The nightly pipelines can sometimes fail for obscure reasons, seemingly unrelated to the changes made within Mantid. In this case, it is probable that a Conda dependency has updated, and the new update is “Broken” (if it is a minor or patch update) or no longer compatible with Mantid (if it is a major update).
To find the dependency which has changed, you can run the
tools/Jenkins/dependency_spotter.py script. This
script takes two Jenkins build numbers, and optionally the OS label, the pipeline name, and the name of the file to
compare. It will then output the changes in Conda package versions used in the two builds, if there are any. A
few examples on how to use it:
python dependency_spotter.py -f 593 -s 598
python dependency_spotter.py -f 593 -s 598 -os win-64
python dependency_spotter.py -f 593 -s 598 --pipeline main_nightly_deployment_prototype
Another useful command for investigating the dependencies of specific packages is conda search. To find the dependencies of a package:
conda search -i <package_name>
After identifying the Conda dependency and version which is causing the unwanted behaviour, there are several options we can take to fix the issue. The following options are in order of preference:
Raise an issue in the dependencies feedstock repository with a minimum reproducible example. If appropriate, request that they mark the package version as “Broken”. See Removing broken packages to understand this procedure.
If we need a fix urgently, you can consider pinning the package in question. This is not an ideal solution, and so you should also open an issue to un-pin the package in future. When pinning a package, consider using the not-equals-to operator
!=x.y.zbecause this allows the package to upgrade automatically when a new version arrives (which is hopefully a working version).
We have a strict policy with regards to using PyPi packages within Mantid. This policy can be summarised as follows:
We strongly encourage PyPi dependencies be built into Conda packages and uploaded to conda-forge. PyPi packages
will not be automatically installed into our Mantid Conda environments, and should instead be installed by
users of the software, if required.
We do not want to include pip packages as dependencies in our Conda recipes because there is no guarantee of compatibility between the two package managers. In the past, attempting to resolve compatibile package versions when two package managers are involved have caused broken Mantid installations. Furthermore, the original motivation for moving towards Conda was so that we had a unified package manager rather than using several different systems or mechanisms. Including pip packages in our dependencies would be a backwards step.
The other solution we considered was installing our pip dependencies downstream within our DAaaS workspace configuration repository. We decided against this because it feels like bad practise to have a formalised way of installing dependencies of a software in a way which is completely detached. The prevailing message is this: please only use Conda packages. We provide pip install instructions for users if they would like to take the risk.