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https://github.com/conda/conda-lock

Lightweight lockfile for conda environments
https://github.com/conda/conda-lock

conda hacktoberfest lockfile

Last synced: 15 days ago
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Lightweight lockfile for conda environments

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README 

        
# conda-lock



[![GitHub deployments](https://img.shields.io/github/deployments/conda/conda-lock/github-pages?label=docs&style=for-the-badge)](https://conda.github.io/conda-lock/)

[![PyPI](https://img.shields.io/pypi/v/conda-lock?style=for-the-badge)](https://pypi.org/project/conda-lock/)

[![Conda](https://img.shields.io/conda/v/conda-forge/conda-lock?style=for-the-badge)](https://github.com/conda-forge/conda-lock-feedstock)

[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?style=for-the-badge)](https://results.pre-commit.ci/latest/github/conda/conda-lock/main)

[![codecov](https://img.shields.io/codecov/c/github/conda/conda-lock/main?style=for-the-badge)](https://codecov.io/gh/conda/conda-lock)



Conda lock is a lightweight library that can be used to generate fully reproducible lock files for [conda][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.



## Why?



Conda [`environment.yml`][envyaml] 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.



## Installation



Use *one* of the following commands:



```bash

pipx install conda-lock

condax install conda-lock

pip install conda-lock

conda install --channel=conda-forge --name=base conda-lock

mamba install --channel=conda-forge --name=base conda-lock

```



The first two options are recommended since they install conda-lock into an isolated environment. (Otherwise there is a risk of dependency conflicts.)



## Contributing



If you would like to contribute to conda-lock, please refer to the [Contributing Guide](CONTRIBUTING.md) for instructions on how to set up your development environment.



## Basic usage



```bash

# generate a multi-platform lockfile

conda-lock -f environment.yml -p osx-64 -p linux-64



# optionally, update the previous solution, using the latest version of

# pydantic that is compatible with the source specification

conda-lock --update pydantic



# create an environment from the lockfile

conda-lock install [-p {prefix}|-n {name}]



# alternatively, render a single-platform lockfile and use conda command directly

conda-lock render -p linux-64

conda create -n my-locked-env --file conda-linux-64.lock

```



Note: If there is an existing lockfile, it is used as constraint when

regenerating the lockfile. This can be useful for adding new packages while

keeping everything else locked.



### Pre 1.0 compatible usage (explicit per platform locks)



If you were making use of conda-lock before the 1.0 release that added unified lockfiles

you can still get that behaviour by making use of the `explicit` output kind.



```bash

conda-lock --kind explicit -f environment.yml

```



## Advanced usage



### File naming



By default, `conda-lock` store its output in `conda-lock.yml` in the current

working directory. This file will also be used by default for render, install,

and update operations. You can supply a different filename with e.g.



```bash

conda-lock --lockfile superspecial.conda-lock.yml

```



Rendered `explicit` and `env` lockfiles will be named as `"conda-{platform}.lock"` and `"conda-{platform}.lock.yml` respectively by default.



If you want to override that call conda-lock as follows.



```bash

conda-lock -k explicit --filename-template "specific-{platform}.conda.lock"

```



### Compound specification



Conda-lock will build a spec list from several files if requested.



```bash

conda-lock -f base.yml -f specific.yml -p linux-64 -k explicit --filename-template "specific-{platform}.lock"

````



In this case all dependencies are combined, and the ordered union of all `channels` is used as the final

specification.



This works for all supported file types.



#### channel overrides



You can override the channels that are used by conda-lock in case you need to override the ones specified in

an [environment.yml][envyaml]



```bash

conda-lock -c conda-forge -p linux-64

```



#### platform specification



You may specify the platforms you wish to target by default directly in an [environment.yml][envyaml] using the (nonstandard) `platforms` key:



```yaml

# environment.yml

channels:

  - conda-forge

dependencies:

  - python=3.9

  - pandas

platforms:

  - linux-64

  - osx-64

  - win-64

  - osx-arm64  # For Apple Silicon, e.g. M1/M2

  - linux-aarch64  # aka arm64, use for Docker on Apple Silicon

  - linux-ppc64le

```



If you specify target platforms on the command line with `-p`, these will

override the values in the environment specification. If neither `platforms` nor

`-p` are provided, `conda-lock` will fall back to a default set of platforms.



#### default category



You can may wish to split your dependencies into separate files for better

organization, e.g. a `environment.yml` for production dependencies and a

`dev-environment.yml` for development dependencies. You can assign all the

dependencies parsed from a single file to a category using the (nonstandard)

`category` key.



```yaml

# dev-environment.yml

channels:

  - conda-forge

dependencies:

  - pytest

  - mypy=0.910

category: dev

```



The default category is `main`.



### pip support



`conda-lock` can also lock the `dependencies.pip` section of

[environment.yml][envyaml], using a vendored copy of [Poetry's][poetry] dependency solver.



### private pip repositories



Right now `conda-lock` only supports [legacy](https://warehouse.pypa.io/api-reference/legacy.html) pypi repos with basic auth. Most self-hosted repositories like Nexus, Artifactory etc. use this. You can configure private pip repositories in a similar way to channels, for example:



```yaml

channels:

  - conda-forge

pip-repositories:

  - http://$PIP_USER:[email protected]/api/pypi/simple

dependencies:

  - python=3.11

  - requests=2.26

  - pip:

    - fake-private-package==1.0.0

```



See [the related docs for private channels](./docs/authenticated_channels.md#what_gets_stored) to understand the rules regarding environment variable substitution.



Alternatively, you can use the `poetry` configuration file format to configure private PyPi repositories. The configuration file should be named `config.toml` and have the following format:



```toml

[repositories.example]

url = "https://username:[email protected]/simple"

```



The location of this file can be determined with `python -c 'from conda_lock._vendor.poetry.locations import CONFIG_DIR; print(CONFIG_DIR)'`



Private repositories will be used in addition to `pypi.org`. For projects using `pyproject.toml`, it is possible to [disable `pypi.org` entirely](#disabling-pypiorg).



### --dev-dependencies/--no-dev-dependencies



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



```bash

conda-lock --no-dev-dependencies -f ./recipe/meta.yaml

```



### --check-input-hash



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.



```bash

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.



### --strip-auth, --auth and --auth-file



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.



```shell

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:



```json

{

  "domain": "username:password"

}

```



If you have multiple channels that require different authentication within the same domain, you can additionally specify the channel like this:



```json

{

  "domain.org/channel1": "username1:password1",

  "domain.org/channel2": "username2:password2"

}

```



You can provide the authentication either as string through `--auth` or as a filepath through `--auth-file`.



```bash

conda-lock install --auth-file auth.json conda-linux-64.lock

```



### --virtual-package-spec



Conda makes use of [virtual packages](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-virtual.html) 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



```yaml

# 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.



```bash

conda lock --virtual-package-spec virtual-packages-cuda.yml -p linux-64

```



#### Input hash stability



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.



#### ⚠️ in conjunction with micromamba



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.



## Supported file sources



Conda lock supports more than just [environment.yml][envyaml] specifications!



Additionally conda-lock supports [meta.yaml][metayaml] (conda-build)

and `pyproject.toml` (

[flit](https://flit.readthedocs.io/en/latest/), [pdm](https://pdm.fming.dev) and

[poetry](https://python-poetry.org) based).  These do come with some gotchas but

are generally good enough for the 90% use-case.



### meta.yaml



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][envyaml]



Since a meta.yaml doesn't contain channel information we make use of the following extra key to specify channels



```yaml

# meta.yaml



extra:

  channels:

    - conda-forge

    - defaults

```



### pyproject.toml



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][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.



#### Channels



```toml

# pyproject.toml



[tool.conda-lock]

channels = [

    'conda-forge', 'defaults'

]

```



#### Platforms



Like in [environment.yml][envyaml], you can specify default platforms to target:



```toml

# pyproject.toml



[tool.conda-lock]

platforms = [

    'osx-arm64', 'linux-64'

]

```



#### Extras



If your pyproject.toml file contains optional dependencies/extras these can be referred to by using the `--extras` flag



```toml

# 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



```shell

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](#file-naming).



##### Filtering extras



 By default conda-lock will attempt to solve for *ALL* extras/categories it discovers in sources.  This allows you to render explicit locks with subset of extras, without needing a new solve.



However this does make the assumption that your extras can all be installed in conjunction with each other.  If you want extras filtering

to happen at the solve stage use the flag `--filter-extras`



```sh

conda-lock --extra incompatiblea --filter-extras -f pyproject.toml

```



#### Extra conda dependencies



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`



```toml

# pyproject.toml



[tool.conda-lock.dependencies]

sqlite = ">=3.34"

```



#### pip dependencies



If a dependency refers directly to a URL rather than a package name and version,

`conda-lock` will assume it is pip-installable, e.g.:



```toml

# pyproject.toml

[tool.poetry.dependencies]

python = "3.9"

pymage = {url = "https://github.com/MickaelRigault/pymage/archive/v1.0.tar.gz#sha256=11e99c4ea06b76ca7fb5b42d1d35d64139a4fa6f7f163a2f0f9cc3ea0b3c55eb"}

```



Similarly, if a dependency is explicitly marked with `source = "pypi"`, it will

be treated as a `pip` dependency, e.g.:



```toml

[tool.poetry.dependencies]

python = "3.9"

ampel-ztf = {version = "^0.8.0-alpha.2", source = "pypi"}

```



A dependency will also be treated as a `pip` dependency if explicitly marked with `source = "pypi"` in the `[tool.conda-lock.dependencies]` section, e.g.:



```toml

[tool.conda-lock.dependencies]

ampel-ztf = {source = "pypi"}

```



##### Defaulting non-conda dependency sources to PyPI



Alternatively, the above behavior is defaulted for all dependencies defined outside of `[tool.conda-lock.dependencies]`, i.e.:



- Default to `pip` dependencies for `[tool.poetry.dependencies]`, `[project.dependencies]`, etc.

- Default to `conda` dependencies for `[tool.conda-lock.dependencies]`



by explicitly providing  `default-non-conda-source = "pip"` in the `[tool.conda-lock]` section, e.g.:



```toml

[tool.conda-lock]

default-non-conda-source = "pip"

```



In all cases, the dependencies of `pip`-installable packages will also be

installed with `pip`, unless they were already requested by a `conda`

dependency.



#### Lock only conda-lock dependencies



To lock only dependencies specified under `[tool.conda-lock]` (i.e. skipping all dependencies specified elsewhere), explicitly provide `skip-non-conda-lock = true` in the `[tool.conda-lock]` section, e.g.:



```toml

[tool.conda-lock]

skip-non-conda-lock = true

```



#### Disabling pypi.org



When using private pip repos, it is possible to disable `pypi.org` entirely. This can be useful when using `conda-lock` behind a network proxy that does not allow access to `pypi.org`.



```toml

[tool.conda-lock]

allow-pypi-requests = false

```



## Dockerfile example



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



```text

  Dockerfile

  environment.yaml

* conda-linux-64.lock

```



You want a dockerfile that is structured something similar to this



```Dockerfile

# 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

```



[conda]: https://docs.conda.io/projects/conda

[metayaml]: https://docs.conda.io/projects/conda-build/en/latest/resources/define-metadata.html

[mapping]: https://github.com/regro/cf-graph-countyfair/blob/master/mappings/pypi/grayskull_pypi_mapping.yaml

[envyaml]: https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#create-env-file-manually

[poetry]: https://python-poetry.org