Python loggers.minimal_logger函数代码示例

 def get_NGIAnalysis(best_practice_analysis="sarek_germline_grch38", config=None, log=None):
     project = TestLaunchers.get_NGIProject(1)
     with mock.patch("ngi_pipeline.conductor.classes.CharonSession", autospec=True) as CharonSessionMock:
         charon_mock = CharonSessionMock.return_value
         charon_mock.project_get.return_value = {"best_practice_analysis": best_practice_analysis}
         return NGIAnalysis(
             project,
             config=(config or TestLaunchers.CONFIG),
             log=(log or minimal_logger(__name__, to_file=False, debug=True)))

 def setUp(self):
     self.log = minimal_logger(__name__, to_file=False, debug=True)
     self.config = TestCharonConnector.CONFIG
     self.project_id = "this-is-a-project-id"
     self.sample_id = "this-is-a-sample-id"
     self.libprep_id = "this-is-a-libprep-id"
     self.libpreps = [
         {"libprepid": "this-is-a-libprep-1"},
         {"libprepid": "this-is-a-libprep-2"},
         {"libprepid": "this-is-a-libprep-3"}]
     self.seqruns = [
         {"seqrunid": "this-is-a-seqrun-1"},
         {"seqrunid": "this-is-a-seqrun-2"},
         {"seqrunid": "this-is-a-seqrun-3"}]

def update_charon_with_local_jobs_status(
        config=None, log=None, tracking_connector=None, charon_connector=None, **kwargs):
    """
    Update Charon with the local changes in the SQLite tracking database.

    :param config: optional dict with configuration options. If not specified, the global configuration will be used
    instead
    :param log: optional log instance. If not specified, a new log instance will be created
    :param tracking_connector: optional connector to the tracking database. If not specified,
    a new connector will be created
    :param charon_connector: optional connector to the charon database. If not specified, a new connector will be
    created
    :param kwargs: placeholder for additional, unused options
    :return: None
    """
    log = log or minimal_logger(__name__, debug=True)

    tracking_connector = tracking_connector or TrackingConnector(config, log)
    charon_connector = charon_connector or CharonConnector(config, log)
    log.debug("updating Charon status for locally tracked jobs")
    # iterate over the analysis processes tracked in the local database
    for analysis in tracking_connector.tracked_analyses():
        try:
            log.debug("checking status for analysis of {}:{} with {}:{}, having {}".format(
                analysis.project_id,
                analysis.sample_id,
                analysis.engine,
                analysis.workflow,
                "pid {}".format(analysis.process_id) if analysis.process_id is not None else
                "sbatch job id {}".format(analysis.slurm_job_id)))
            # create an AnalysisTracker instance for the analysis
            analysis_tracker = AnalysisTracker(analysis, charon_connector, tracking_connector, log, config)
            # recreate the analysis_sample from disk/analysis
            analysis_tracker.recreate_analysis_sample()
            # poll the system for the analysis status
            analysis_tracker.get_analysis_status()
            # set the analysis status
            analysis_tracker.report_analysis_status()
            # set the analysis results
            analysis_tracker.report_analysis_results()
            # remove the analysis entry from the local db
            analysis_tracker.remove_analysis()
            # do cleanup
            analysis_tracker.cleanup()
        except Exception as e:
            log.error("exception raised when processing sample {} in project {}, please review: {}".format(
                analysis.project_id, analysis.sample_id, e))

    def __init__(self, project, restart_failed_jobs=None,
                    restart_finished_jobs=False, restart_running_jobs=False,
                    keep_existing_data=False, no_qc=False, exec_mode="sbatch",
                    quiet=False, manual=False, config=None, config_file_path=None,
                    generate_bqsr_bam=False, log=None, sample=None):
        self.project=project
        self.sample=sample
        self.restart_failed_jobs=restart_failed_jobs
        self.restart_finished_jobs=restart_finished_jobs
        self.restart_running_jobs=restart_running_jobs
        self.keep_existing_data=keep_existing_data 
        self.no_qc=no_qc 
        self.exec_mode=exec_mode
        self.quiet=quiet
        self.manual=manual
        self.config=config
        self.config_file_path=config_file_path
        self.generate_bqsr_bam=generate_bqsr_bam
        self.log=log

        if not log:
            self.log=minimal_logger(__name__)

        self.engine=self.get_engine()

from ngi_pipeline.conductor.classes import NGIProject
from ngi_pipeline.conductor.launchers import launch_analysis
from ngi_pipeline.database.classes import CharonSession, CharonError
from ngi_pipeline.database.communicate import get_project_id_from_name
from ngi_pipeline.database.filesystem import create_charon_entries_from_project
from ngi_pipeline.log.loggers import minimal_logger
from ngi_pipeline.utils.classes import with_ngi_config
from ngi_pipeline.utils.communication import mail_analysis
from ngi_pipeline.utils.filesystem import do_rsync, do_symlink, \
                                          locate_flowcell, safe_makedir
from ngi_pipeline.utils.parsers import determine_library_prep_from_fcid, \
                                       determine_library_prep_from_samplesheet, \
                                       parse_lane_from_filename

LOG = minimal_logger(__name__)

UPPSALA_PROJECT_RE = re.compile(r'(\w{2}-\d{4}|\w{2}\d{2,3})')
STHLM_PROJECT_RE = re.compile(r'[A-z]{1,2}[_.][A-z0-9]+_\d{2}_\d{2}')
STHLM_X_PROJECT_RE = re.compile(r'[A-z]{1,2}_[A-z0-9]+_\d{2}_\d{2}')


## TODO we should just remove this function
def process_demultiplexed_flowcell(demux_fcid_dir_path, restrict_to_projects=None,
                                   restrict_to_samples=None, restart_failed_jobs=False,
                                   restart_finished_jobs=False, restart_running_jobs=False,
                                   keep_existing_data=False, no_qc=False, quiet=False,
                                   manual=False, config=None, config_file_path=None, generate_bqsr_bam=False):
    """Call process_demultiplexed_flowcells, restricting to a single flowcell.
    Essentially a restrictive wrapper.

 def setUp(self):
     self.config = TestLaunchers.CONFIG
     self.log = minimal_logger(__name__, to_file=False, debug=True)
     self.analysis_object = TestLaunchers.get_NGIAnalysis(config=self.config, log=self.log)

import sys
import os
import re
import subprocess
import shutil

import click
import yaml
import vcf
import pyexcel_xlsx

from ngi_pipeline.database.classes import CharonSession, CharonError
from ngi_pipeline.log.loggers import minimal_logger
from ngi_pipeline.utils.classes import with_ngi_config

log = minimal_logger(os.path.basename(__file__))

@click.group()
@with_ngi_config
@click.pass_context
@click.option('--config', '-c', 'custom_config', help='Path to a config file', type=click.Path())
def cli(context, config_file_path, config, custom_config=None):
    # check first if config file is specified
    if custom_config is not None:
        log.info('Using custom config file: {}'.format(os.path.abspath(custom_config)))
        if not os.path.exists(custom_config):
            log.error('Config file does not exist!')
            exit(1)
        with open(custom_config, 'r') as config_file:
            config = yaml.load(config_file) or {}
            config = config.get('gt_concordance') or {}

 def setUpClass(cls):
     cls.log = minimal_logger(__name__, debug=True)

"""
from __future__ import print_function

import argparse
import os
import sys

from ngi_pipeline.conductor import flowcell
from ngi_pipeline.conductor import launchers
from ngi_pipeline.conductor.flowcell import setup_analysis_directory_structure
from ngi_pipeline.database.filesystem import create_charon_entries_from_project
from ngi_pipeline.log.loggers import minimal_logger
from ngi_pipeline.server import main as server_main
from ngi_pipeline.utils.filesystem import recreate_project_from_filesystem

LOG = minimal_logger("ngi_pipeline_start")


def validate_force_update():
    return _validate_dangerous_user_thing("OVERWRITE EXISTING DATA in CHARON")

def validate_delete_existing():
    return _validate_dangerous_user_thing("DELETE EXISTING DATA in CHARON")

def _validate_dangerous_user_thing(action="do SOMETHING that Mario thinks you should BE WARNED about"):
    print("DANGER WILL ROBINSON you have told this script to {action}!! Do you in fact want do to this?!?".format(action=action), file=sys.stderr)
    attempts = 0
    while True:
        if attempts < 3:
            attempts += 1
            user_input = raw_input("Confirm overwrite by typing 'yes' or 'no' ({}): ".format(attempts)).lower()