feat: initial code for software deployment plugins #22
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📝 WalkthroughWalkthroughThe changes introduce a new software deployment plugin for the Snakemake framework, encapsulated in the Changes
Sequence Diagram(s)sequenceDiagram
participant User
participant SoftwareDeploymentProvider
participant Conda
User->>SoftwareDeploymentProvider: Initialize with settings
SoftwareDeploymentProvider->>Conda: Run "conda info --json"
Conda-->>SoftwareDeploymentProvider: Return Conda info
SoftwareDeploymentProvider-->>User: Provide deployment settings
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Actionable comments posted: 1
🧹 Outside diff range and nitpick comments (4)
poetry_snakemake_plugin/templates/software-deployment-plugins/tests.py (2)
7-10: Add docstring to explain the test class purpose and configuration.While the inline comments explain the flags, a class-level docstring would help developers understand:
- The purpose of this test class
- When and how to use it
- Examples of typical usage
class TestSoftwareDeployment(TestSoftwareDeploymentBase): + """Test class for software deployment plugin implementations. + + This class serves as a template for testing software deployment plugins. + Subclasses should implement the abstract methods to test specific plugin functionality. + + Attributes: + deploy (bool): Indicates if the provider deploys its environments. + archive (bool): Indicates if environments can be archived. + """ __test__ = True deploy = True # set to True if the provider deploys its envs archive = True # set to True if envs can be archived
12-22: Enhance method documentation with implementation requirements.While the comments provide basic guidance, each method should have a proper docstring explaining:
- Expected return values
- Implementation requirements
- Example implementations
def get_env_spec(self) -> str: - # Return an env spec query. If deploy == False the env should be present a priori. + """Return an environment specification query string. + + Returns: + str: A query string specifying the environment requirements. + If deploy=False, this should reference a pre-existing environment. + + Example: + return "python=3.8 pandas=1.0.0" + """ ... def get_software_deployment_provider_cls(self) -> Type[SoftwareDeploymentProviderBase]: - # Return the SoftwareDeploymentProvider class of this plugin + """Return the software deployment provider class for this plugin. + + Returns: + Type[SoftwareDeploymentProviderBase]: The provider class that implements + the deployment functionality. + + Example: + from .init import MySoftwareDeploymentProvider + return MySoftwareDeploymentProvider + """ ... def get_software_deployment_provider_settings(self) -> Optional[SoftwareDeploymentProviderSettingsBase]: - # instantiate StorageProviderSettings of this plugin as appropriate + """Return the settings instance for this plugin's provider. + + Returns: + Optional[SoftwareDeploymentProviderSettingsBase]: An instance of the + provider settings, or None if no settings are required. + + Example: + from .init import MySoftwareDeploymentProviderSettings + return MySoftwareDeploymentProviderSettings(param1="value1") + """ ...poetry_snakemake_plugin/templates/software-deployment-plugins/init.py (2)
1-4: Remove unused imports.The following imports are unused and can be safely removed:
AnyIterableListsubprocessApply this diff to remove the unused imports:
-from dataclasses import dataclass, field import json -from typing import Any, Iterable, Optional, List -import subprocess as sp +from dataclasses import dataclass, field +from typing import Optional🧰 Tools
🪛 Ruff
3-3:
typing.Anyimported but unusedRemove unused import
(F401)
3-3:
typing.Iterableimported but unusedRemove unused import
(F401)
3-3:
typing.Listimported but unusedRemove unused import
(F401)
4-4:
subprocessimported but unusedRemove unused import:
subprocess(F401)
54-78: Consider adding error handling and logging.The
__post_init__method of theSoftwareDeploymentProviderclass is a good place to perform initialization tasks and store global information. However, consider adding error handling and logging to improve the robustness and debuggability of the code.For example, you can wrap the
self.runcall in a try-except block to handle potential exceptions and log any errors:try: conda_info_json = self.run("conda info --json").decode() self.conda_info = json.loads(conda_info_json) except (sp.CalledProcessError, json.JSONDecodeError) as e: logger.error(f"Failed to retrieve conda info: {e}") self.conda_info = NoneThis way, if the
conda infocommand fails or the JSON parsing encounters an error, it will be logged, andself.conda_infowill be set toNoneto indicate the failure.
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📒 Files selected for processing (2)
poetry_snakemake_plugin/templates/software-deployment-plugins/init.py(1 hunks)poetry_snakemake_plugin/templates/software-deployment-plugins/tests.py(1 hunks)
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📓 Path-based instructions (2)
poetry_snakemake_plugin/templates/software-deployment-plugins/init.py (1)
Pattern **/*.py: Do not try to improve formatting.
Do not suggest type annotations for functions that are defined inside of functions or methods.
Do not suggest type annotation of the self argument of methods.
Do not suggest type annotation of the cls argument of classmethods.
Do not suggest return type annotation if a function or method does not contain a return statement.
poetry_snakemake_plugin/templates/software-deployment-plugins/tests.py (1)
Pattern **/*.py: Do not try to improve formatting.
Do not suggest type annotations for functions that are defined inside of functions or methods.
Do not suggest type annotation of the self argument of methods.
Do not suggest type annotation of the cls argument of classmethods.
Do not suggest return type annotation if a function or method does not contain a return statement.
🪛 Ruff
poetry_snakemake_plugin/templates/software-deployment-plugins/init.py
3-3: typing.Any imported but unused
Remove unused import
(F401)
3-3: typing.Iterable imported but unused
Remove unused import
(F401)
3-3: typing.List imported but unused
Remove unused import
(F401)
4-4: subprocess imported but unused
Remove unused import: subprocess
(F401)
🔇 Additional comments (2)
poetry_snakemake_plugin/templates/software-deployment-plugins/tests.py (1)
1-5: LGTM! Imports are well-organized and appropriate.
The imports correctly bring in the necessary base classes and typing support for the test implementation.
poetry_snakemake_plugin/templates/software-deployment-plugins/init.py (1)
16-51: LGTM!
The SoftwareDeploymentProviderSettings class is well-defined with appropriate metadata for the myparam field. The comments provide clear guidance on how to define settings for the storage plugin.
| # Required: | ||
| # Implementation of an environment object. | ||
| # If your environment cannot be archived or deployed, remove the respective methods | ||
| # and the respective base classes. | ||
| class Env(EnvBase, DeployableEnvBase, ArchiveableEnvBase): | ||
| # For compatibility with future changes, you should not overwrite the __init__ | ||
| # method. Instead, use __post_init__ to set additional attributes and initialize | ||
| # futher stuff. | ||
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| def __post_init__(self) -> None: | ||
| # This is optional and can be removed if not needed. | ||
| # Alternatively, you can e.g. prepare anything or set additional attributes. | ||
| pass | ||
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| def decorate_shellcmd(self, cmd: str) -> str: | ||
| # Decorate given shell command such that it runs within the environment. | ||
| ... | ||
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| def hash(self, hash_object) -> None: | ||
| # Update given hash such that it changes whenever the environment | ||
| # could potentially contain a different set of software (in terms of versions or | ||
| # packages). | ||
| ... | ||
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| # The methods below are optional. Remove them if not needed and adjust the | ||
| # base classes above. | ||
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| def deploy(self) -> None: | ||
| # Remove if not deployable! | ||
| # Deploy the environment to self.provider.deployment_path. | ||
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| # When issuing shell commands, the environment should use | ||
| # self.provider.run(cmd: str) -> bytes in order to ensure that it runs within | ||
| # eventual parent environments (e.g. a container or an env module). | ||
| ... | ||
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| def deployment_hash(self, hash_object) -> None: | ||
| # Remove if not deployable! | ||
| # Update given hash such that it changes whenever the environment | ||
| # needs to be redeployed, e.g. because its content has changed or the | ||
| # deployment location has changed. The latter is only relevant if the | ||
| # deployment is senstivive to the path (e.g. in case of conda, which patches | ||
| # the RPATH in binaries). | ||
| ... | ||
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| def archive(self) -> None: | ||
| # Remove if not archiveable! | ||
| # Archive the environment to self.provider.archive_path. | ||
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| # When issuing shell commands, the environment should use | ||
| # self.provider.run(cmd: str) -> bytes in order to ensure that it runs within | ||
| # eventual parent environments (e.g. a container or an env module). | ||
| ... |
There was a problem hiding this comment.
Implement the required methods for the Env class.
The Env class currently has placeholder methods for decorate_shellcmd, hash, deploy, deployment_hash, and archive. These methods need to be implemented to provide the necessary functionality for the software deployment plugin.
Here are some suggestions for implementing these methods:
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decorate_shellcmd:- Modify the given shell command to run within the environment.
- This could involve prepending the command with environment activation or setting environment variables.
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hash:- Update the given hash object with information that uniquely identifies the environment's software versions and packages.
- This could include hashing the environment's configuration files, package lists, or version information.
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deploy:- Implement the logic to deploy the environment to the specified
self.provider.deployment_path. - This could involve creating a new environment, installing packages, and configuring the environment.
- Implement the logic to deploy the environment to the specified
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deployment_hash:- Update the given hash object with information that determines when the environment needs to be redeployed.
- This could include hashing the deployment path, environment configuration, or any other relevant factors.
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archive:- Implement the logic to archive the environment to the specified
self.provider.archive_path. - This could involve creating a compressed archive of the environment files and dependencies.
- Implement the logic to archive the environment to the specified
Please let me know if you would like assistance in implementing any of these methods. I'd be happy to provide more detailed guidance or code examples.
Summary by CodeRabbit
New Features
Tests