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Merged
merged 4 commits into from
Dec 14, 2020
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Use mamba under a feature flag to create conda environments #6815

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d34b8d0
Use `mamba` under a feature flag to create conda environments
humitos Mar 24, 2020
c0ad809
Merge branch 'master' into humitos/use-mamba-for-conda-environment
humitos Dec 3, 2020
0ff60a3
Use `conda` bin when UPDATE_CONDA_STARTUP
humitos Dec 7, 2020
29d8657
Apply suggestions from code review
humitos Dec 14, 2020
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12 changes: 12 additions & 0 deletions docs/guides/feature-flags.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -27,6 +27,18 @@ In case you prefer to use the latest ``conda`` version available, this is the fl
Makes Read the Docs to install all the requirements at once on ``conda create`` step.
This helps users to pin dependencies on conda and to improve build time.

``CONDA_USES_MAMBA``: :featureflags:`CONDA_USES_MAMBA`

``conda`` solver consumes 1Gb minimum when installing any package using ``conda-forge`` channel.
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I think you mean resolver

Suggested change
``conda`` solver consumes 1Gb minimum when installing any package using ``conda-forge`` channel.
Conda's resolver consumes 1Gb minimum when installing any package using ``conda-forge`` channel.

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Well... I think it's the same, but they call it "Solver" :)

https://docs.conda.io/projects/conda/en/latest/api/solver.html#conda.core.solve.Solver

This seems to be `a known issue`_ due conda forge has so many packages on it, among others.
Using this feature flag allows you to use mamba_ instead of ``conda`` to create the environment
and install the dependencies.
``mamba`` is a drop-in replacement for conda that it's much faster and also
reduces considerably the amount of memory required to solve the dependencies.

.. _mamba: https://quantstack.net/mamba.html
.. _a known issue: https://www.anaconda.com/understanding-and-improving-condas-performance/

``DONT_OVERWRITE_SPHINX_CONTEXT``: :featureflags:`DONT_OVERWRITE_SPHINX_CONTEXT`

``DONT_SHALLOW_CLONE``: :featureflags:`DONT_SHALLOW_CLONE`
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42 changes: 40 additions & 2 deletions readthedocs/doc_builder/python_environments.py
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Expand Up @@ -493,6 +493,23 @@ class Conda(PythonEnvironment):
def venv_path(self):
return os.path.join(self.project.doc_path, 'conda', self.version.slug)

def conda_bin_name(self):
"""
Decide whether use ``mamba`` or ``conda`` to create the environment.

Return ``mamba`` if the project has ``CONDA_USES_MAMBA`` feature and
``conda`` otherwise. This will be the executable name to be used when
creating the conda environment.

``mamba`` is really fast to solve dependencies and download channel
metadata on startup.

See https://github.com/QuantStack/mamba
"""
if self.project.has_feature(Feature.CONDA_USES_MAMBA):
return 'mamba'
return 'conda'

def _update_conda_startup(self):
"""
Update ``conda`` before use it for the first time.
Expand All @@ -501,6 +518,8 @@ def _update_conda_startup(self):
independently the version of Miniconda that it has installed.
"""
self.build_env.run(
# TODO: use ``self.conda_bin_name()`` once ``mamba`` is installed in
# the Docker image
'conda',
'update',
'--yes',
Expand All @@ -511,6 +530,18 @@ def _update_conda_startup(self):
cwd=self.checkout_path,
)

def _install_mamba(self):
self.build_env.run(
'conda',
'install',
'--yes',
'--quiet',
'--name=base',
'--channel=conda-forge',
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@SylvainCorlay! is it possible to install mamba from a different, and smaller, channel than conda-forge here?

I can't use micromamba at this point for "reasons" and I would like to installing it with conda but ideally using a channel that only contains mamba, so it does not make conda to consume too many resources.

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Would you consider using a miniforge flavor including mamba instead of miniconda.

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Comment from the peanut gallery: regro/conda-metachannel#31 (comment) conda-metachannel service is down, unfortunately.

Perhaps if there was a mamba channel, it would help the bootstrapping problem. conda install mamba -c mamba would be blazing fast, and from there mamba & conda-forge could be used as usual.

About mamba in miniforge... from what I read in conda-forge/miniforge#23, looks like there is no consensus (the path of least resistance seems to be creating a miniforge-mamba or a microforge with micromamba?)

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I can't use anything different than regular conda (like micromamba, miniforge, etc) at this moment because I can't modify the Docker image we are currently using (I will be able to do this in the future, but I don't know exactly when yet).

So, given this current restriction, I was asking if something like @astrojuanlu mentioned already existed (conda install mamba -c mamba) because calling conda install mamba -c conda-forge currently has the same problem of consuming a lot of resources just because it uses conda-forge channel that contains millions of packages. Although the problem is there, it's not a blocker to start testing mamba here, but having a better workaround for this would be good.

Comment from the peanut gallery: regro/conda-metachannel#31 (comment) conda-metachannel service is down, unfortunately.

This was a good idea when @astrojuanlu commented it to me. However, if it's currently down it doesn't seem to be something we can rely on by default 😞

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Gotcha

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My goal here is to avoid this random problem with the available tools and restrictions:

$ conda install --yes --quiet --name=base --channel=conda-forge mamba
Collecting package metadata (current_repodata.json): ...working... done
Solving environment: ...working... failed with initial frozen solve. Retrying with flexible solve.
Solving environment: ...working... failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): ...working... Killed


Command killed due to excessive memory consumption

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FYI @humitos miniforge now includes a "mambaforge" installer which has mamba pre-installed.

https://github.com/conda-forge/miniforge

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I am looking into what we could do to allow conda install mamba from a raw miniconda to be faster.

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@humitos
One way to do this without having to maintain another channel with a copy of mamba and its dependencies is to use a conda lock file.

https://pypi.org/project/conda-lock/

You could generate a conda lock file offline, and use it in your script so that no solving is required.

'mamba',
cwd=self.checkout_path,
)

def setup_base(self):
conda_env_path = os.path.join(self.project.doc_path, 'conda')
version_path = os.path.join(conda_env_path, self.version.slug)
Expand All @@ -534,8 +565,12 @@ def setup_base(self):
self._append_core_requirements()
self._show_environment_yaml()

# TODO: remove it when ``mamba`` is installed in the Docker image
if self.project.has_feature(Feature.CONDA_USES_MAMBA):
self._install_mamba()

self.build_env.run(
'conda',
self.conda_bin_name(),
'env',
'create',
'--quiet',
Expand Down Expand Up @@ -621,6 +656,9 @@ def _get_core_requirements(self):
'pillow',
]

if self.project.has_feature(Feature.CONDA_USES_MAMBA):
conda_requirements.append('pip')

# Install pip-only things.
pip_requirements = [
'recommonmark',
Expand Down Expand Up @@ -648,7 +686,7 @@ def install_core_requirements(self):
# Install requirements via ``conda install`` command if they were
# not appended to the ``environment.yml`` file.
cmd = [
'conda',
self.conda_bin_name(),
'install',
'--yes',
'--quiet',
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5 changes: 5 additions & 0 deletions readthedocs/projects/models.py
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Expand Up @@ -1579,6 +1579,7 @@ def add_features(sender, **kwargs):
EXTERNAL_VERSION_BUILD = 'external_version_build'
UPDATE_CONDA_STARTUP = 'update_conda_startup'
CONDA_APPEND_CORE_REQUIREMENTS = 'conda_append_core_requirements'
CONDA_USES_MAMBA = 'conda_uses_mamba'
ALL_VERSIONS_IN_HTML_CONTEXT = 'all_versions_in_html_context'
SKIP_SYNC_TAGS = 'skip_sync_tags'
SKIP_SYNC_BRANCHES = 'skip_sync_branches'
Expand Down Expand Up @@ -1661,6 +1662,10 @@ def add_features(sender, **kwargs):
CONDA_APPEND_CORE_REQUIREMENTS,
_('Append Read the Docs core requirements to environment.yml file'),
),
(
CONDA_USES_MAMBA,
_('Uses mamba binary instead of conda to create the environment'),
),
(
ALL_VERSIONS_IN_HTML_CONTEXT,
_(
Expand Down