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-template "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
Under some situation you may want to run conda lock in some kind of automated way (eg as a precommit) and want to not need to regenerate the lockfiles if the underlying input specification for that particular lock as not changed.
conda-lock --check-input-hash -p linux-64
When the input_hash of the input files, channels match those present in a given lockfile, that lockfile will not be regenerated.
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 makes use of virtual packages that are available at runtime to gate dependency on system features. Due to these not generally existing on your local execution platform conda-lock will inject them into the solution environment with a reasonable guess at what a default system configuration should be.
If you want to override which virtual packages are injected you can create a file like
# virtual-packages.yml
subdirs:
linux-64:
packages:
__glibc: 2.17
__cuda: 11.4
win-64:
packages:
__cuda: 11.4
conda-lock will automatically use a virtual-packages.yml
it finds in the the current working directory. Alternatively one can be specified
explicitly via the flag.
conda lock --virtual-package-spec virtual-packages-cuda.yml -p linux-64
Virtual packages take part in the input hash so if you build an environment with a different set of virtual packages the input hash will change.
Additionally the default set of virtual packages may be augmented in future versions of conda-lock. If you desire very stable input hashes
we recommend creating a virtual-packages.yml
file to lock down the virtual packages considered.
Micromamba does not presently support some of the overrides to remove all discovered virtual packages, consequently the set of virtual packages available at solve time may be larger than those specified in your specification.
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'
]
If your pyproject.toml file contains optional dependencies/extras these can be referred to by using the --extras
flag
# pyproject.toml
[tool.poetry.dependencies]
mandatory = "^1.0"
psycopg2 = { version = "^2.7", optional = true }
mysqlclient = { version = "^1.3", optional = true }
[tool.poetry.extras]
mysql = ["mysqlclient"]
pgsql = ["psycopg2"]
These can be referened as follows
conda-lock --extra mysql --extra pgsql -f pyproject.toml
When generating lockfiles that make use of extras it is recommended to make use of --filename-template
covered here.
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 a 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