为Snakemake执行器插件提供稳定的接口和功能

此软件包为Snakemake与其执行器插件之间的交互提供稳定的接口（WIP）。

插件应实现以下骨架以符合此接口。建议使用Snakemake的poetry插件在Python包中设置此骨架（和自动化测试），请参阅https://github.com/snakemake/poetry-snakemake-plugin。

from dataclasses import dataclass, field
from typing import List, Generator, Optional
from snakemake_interface_executor_plugins.executors.base import SubmittedJobInfo
from snakemake_interface_executor_plugins.executors.remote import RemoteExecutor
from snakemake_interface_executor_plugins.settings import (
    ExecutorSettingsBase, CommonSettings
)
from snakemake_interface_executor_plugins.workflow import WorkflowExecutorInterface
from snakemake_interface_executor_plugins.logging import LoggerExecutorInterface
from snakemake_interface_executor_plugins.jobs import (
    JobExecutorInterface,
)

# Optional:
# Define additional settings for your executor.
# They will occur in the Snakemake CLI as --<executor-name>-<param-name>
# Omit this class if you don't need any.
# Make sure that all defined fields are Optional and specify a default value
# of None or anything else that makes sense in your case.
@dataclass
class ExecutorSettings(ExecutorSettingsBase):
    myparam: Optional[int] = field(
        default=None,
        metadata={
            "help": "Some help text",
            # Optionally request that setting is also available for specification
            # via an environment variable. The variable will be named automatically as
            # SNAKEMAKE_<executor-name>_<param-name>, all upper case.
            # This mechanism should only be used for passwords and usernames.
            # For other items, we rather recommend to let people use a profile
            # for setting defaults
            # (https://snakemake.readthedocs.io/en/stable/executing/cli.html#profiles).
            "env_var": False,
            # Optionally specify a function that parses the value given by the user.
            # This is useful to create complex types from the user input.
            "parse_func": ...,
            # If a parse_func is specified, you also have to specify an unparse_func
            # that converts the parsed value back to a string.
            "unparse_func": ...,
            # Optionally specify that setting is required when the executor is in use.
            "required": True,
            # Optionally specify multiple args with "nargs": True
        },
    )


# Required:
# Specify common settings shared by various executors.
common_settings = CommonSettings(
    # define whether your executor plugin executes locally
    # or remotely. In virtually all cases, it will be remote execution
    # (cluster, cloud, etc.). Only Snakemake's standard execution 
    # plugins (snakemake-executor-plugin-dryrun, snakemake-executor-plugin-local)
    # are expected to specify False here.
    non_local_exec=True,
    # Whether the executor implies to not have a shared file system
    implies_no_shared_fs=True,
    # whether to deploy workflow sources to default storage provider before execution
    job_deploy_sources=True,
    # whether arguments for setting the storage provider shall be passed to jobs
    pass_default_storage_provider_args=True,
    # whether arguments for setting default resources shall be passed to jobs
    pass_default_resources_args=True,
    # whether environment variables shall be passed to jobs (if False, use 
    # self.envvars() to obtain a dict of environment variables and their values
    # and pass them e.g. as secrets to the execution backend)
    pass_envvar_declarations_to_cmd=True,
    # whether the default storage provider shall be deployed before the job is run on 
    # the remote node. Usually set to True if the executor does not assume a shared fs
    auto_deploy_default_storage_provider=True,
    # specify initial amount of seconds to sleep before checking for job status
    init_seconds_before_status_checks=0,
)


# Required:
# Implementation of your executor
class Executor(RemoteExecutor):
    def __post_init__(self):
        # access workflow
        self.workflow
        # access executor specific settings
        self.workflow.executor_settings

        # IMPORTANT: in your plugin, only access methods and properties of
        # Snakemake objects (like Workflow, Persistence, etc.) that are
        # defined in the interfaces found in the
        # snakemake-interface-executor-plugins and the
        # snakemake-interface-common package.
        # Other parts of those objects are NOT guaranteed to remain
        # stable across new releases.

        # To ensure that the used interfaces are not changing, you should
        # depend on these packages as >=a.b.c,<d with d=a+1 (i.e. pin the
        # dependency on this package to be at least the version at time
        # of development and less than the next major version which would
        # introduce breaking changes).

        # In case of errors outside of jobs, please raise a WorkflowError

    def run_job(self, job: JobExecutorInterface):
        # Implement here how to run a job.
        # You can access the job's resources, etc.
        # via the job object.
        # After submitting the job, you have to call
        # self.report_job_submission(job_info).
        # with job_info being of type
        # snakemake_interface_executor_plugins.executors.base.SubmittedJobInfo.
        # If required, make sure to pass the job's id to the job_info object, as keyword
        # argument 'external_job_id'.

        ...

    async def check_active_jobs(
        self, active_jobs: List[SubmittedJobInfo]
    ) -> Generator[SubmittedJobInfo, None, None]:
        # Check the status of active jobs.

        # You have to iterate over the given list active_jobs.
        # If you provided it above, each will have its external_jobid set according
        # to the information you provided at submission time.
        # For jobs that have finished successfully, you have to call
        # self.report_job_success(active_job).
        # For jobs that have errored, you have to call
        # self.report_job_error(active_job).
        # This will also take care of providing a proper error message.
        # Usually there is no need to perform additional logging here.
        # Jobs that are still running have to be yielded.
        #
        # For queries to the remote middleware, please use
        # self.status_rate_limiter like this:
        #
        # async with self.status_rate_limiter:
        #    # query remote middleware here
        #
        # To modify the time until the next call of this method,
        # you can set self.next_sleep_seconds here.
        ...

    def cancel_jobs(self, active_jobs: List[SubmittedJobInfo]):
        # Cancel all active jobs.
        # This method is called when Snakemake is interrupted.
        ...