Conda lock is a lightweight library that can be used to generate fully reproducible lock files for conda environments.
It does this by performing a conda solve for each platform you desire a lockfile for.
This also has the added benefit of acting as an external pre-solve for conda as the lockfiles it generates results in the conda solver not being invoked when installing the packages from the generated lockfile.
Conda environment.yml
files are very useful for defining desired environments but there are times when we want to
be able to EXACTLY reproduce an environment by just installing and downloading the packages needed.
This is particularly handy in the context of a gitops style setup where you use conda to provision environments in various places.
pip install conda-lock
conda install -c conda-forge conda-lock
# generate the lockfiles
conda-lock -f environment.yml -p osx-64 -p linux-64
# create an environment from the lockfile
conda-lock install [-p {prefix}|-n {name}] conda-linux-64.lock
# alternatively, use conda command directly
conda create -n my-locked-env --file conda-linux-64.lock
By default conda-lock will name files as "conda-{platform}.lock"
.
If you want to override that call conda-lock as follows.
conda-lock --filename-template "specific-{platform}.conda.lock"
Conda-lock will build a spec list from several files if requested.
conda-lock -f base.yml -f specific.yml -p linux-64 --filename-format "specific-{platform}.lock"
In this case all dependencies are combined, and the first non-empty value for channels
is used as the final
specification.
This works for all supported file types.
You can override the channels that are used by conda-lock in case you need to override the ones specified in an environment.yml
conda-lock -c conda-forge -p linux-64
By default conda-lock will include dev dependencies in the specification of the lock (if the files that the lock is being built from support them). This can be disabled easily
conda-lock --no-dev-dependencies -f ./recipe/meta.yaml
By default conda-lock
will leave basic auth credentials for private conda channels in the lock file. If you wish to strip authentication from the file, provide the --strip-auth
argument.
conda-lock --strip-auth -f environment.yml
In order to conda-lock install
a lock file with its basic auth credentials stripped, you will need to create an authentication file in .json
format like this:
{
"domain": "username:password",
// ...
}
You can provide the authentication either as string through --auth
or as a filepath through --auth-file
.
conda-lock install --auth-file auth.json conda-linux-64.lock
Conda lock supports more than just environment.yml specifications!
Additionally conda-lock supports meta.yaml (conda-build)
and pyproject.toml
(
flit and poetry
based). These do come with some gotchas but are generally good enough for the 90% use-case.
Conda-lock will attempt to make an educated guess at the desired environment spec in a meta.yaml. This is not guaranteed to work for complex recipes with many selectors and outputs. For multi-output recipes, conda-lock will fuse all the dependencies together. If that doesn't work for your case fall back to specifying the specification as an environment.yml
Since a meta.yaml doesn't contain channel information we make use of the following extra key to retrieve channels
# meta.yaml
extra:
channels:
- conda-forge
- defaults
Since pyproject.toml files are commonly used by python packages it can be desirable to create a lock
file directly from those dependencies to single-source a package's dependencies. This makes use of some
conda-forge infrastructure (pypi-mapping) to do a lookup of the PyPI package name to a corresponding
conda package name (e.g. docker
-> docker-py
). In cases where there exists no lookup for the package it assumes that
the PyPI name, and the conda name are the same.
# pyproject.toml
[tool.conda-lock]
channels = [
'conda-forge', 'defaults'
]
Since in a pyproject.toml
all the definitions are python dependencies if you need
to specify some non-python dependencies as well this can be accomplished by adding
the following sections to the pyproject.toml
# pyproject.toml
[tool.conda-lock.dependencies]
sqlite = ">=3.34"
In order to use conda-lock in a docker-style context you want to add the lockfile to the
docker container. In order to refresh the lock file just run conda-lock
again.
Given aa file tree like
Dockerfile
environment.yaml
* conda-linux-64.lock
You want a dockerfile that is structured something similar to this
# Dockerfile
# Build container
FROM continuumio/miniconda:latest as conda
ADD conda-linux-64.lock /locks/conda-linux-64.lock
RUN conda create -p /opt/env --copy --file /locks/conda-linux-64.lock
# Primary container
FROM gcr.io/distroless/base-debian10
COPY --from=conda /opt/env /opt/env