rm execute_pipeline from TellSeqMetagenomicWorkflow

Author: antgonza

qp_klp/Assays.py

@@ -511,16 +511,17 @@ def execute_pipeline(self):
 
         self.convert_raw_to_fastq()
 
-        self.update_status("Performing quality control", 2, 9)
+        self.integrate_results()
+
+        self.generate_sequence_counts()
 
+        self.update_status("Performing quality control", 2, 9)
         self.quality_control()
 
         self.update_status("Generating reports", 3, 9)
-
         self.generate_reports()
 
         self.update_status("Generating preps", 4, 9)
-
         self.generate_prep_file()
 
         # moved final component of genprepfilejob outside of object.

qp_klp/TellseqMetagenomicWorkflow.py

@@ -1,12 +1,10 @@
 from .Protocol import TellSeq
-from os.path import join, abspath, exists
-from os import walk
+from os.path import join, exists
 from sequence_processing_pipeline.Pipeline import Pipeline, InstrumentUtils
 from .Assays import Metagenomic
 from .Assays import ASSAY_NAME_METAGENOMIC
 from .Workflows import Workflow
 from .FailedSamplesRecord import FailedSamplesRecord
-from collections import defaultdict
 
 
 class TellSeqMetagenomicWorkflow(Workflow, Metagenomic, TellSeq):
@@ -77,107 +75,3 @@ def determine_steps_to_skip(self):
                     msg = "%s doesn't have job completed" % join(out_dir,
                                                                  directory)
                     raise ValueError(msg)
-
-    def execute_pipeline(self):
-        '''
-        Executes steps of pipeline in proper sequence.
-        :return: None
-        '''
-
-        # perform some (re)initialization steps on (re)startup.
-        self.pre_check()
-
-        # this is performed even in the event of a restart.
-        self.generate_special_map()
-
-        # even if a job is being skipped, it's being skipped because it was
-        # determined that it already completed successfully. Hence,
-        # increment the status because we are still iterating through them.
-
-        self.update_status("Converting data", 1, 9)
-
-        # convert_raw_to_fastq() now performs its own checking of skip_steps.
-        # convert_raw_to_fastq() now performs its own write to fsr reports.
-        # This means fsr reports will be accurate even on restarts.
-        self.convert_raw_to_fastq()
-
-        self.integrate_results()
-
-        self.generate_sequence_counts()
-
-        self.update_status("Performing quality control", 2, 9)
-        self.quality_control()
-
-        self.update_status("Generating reports", 3, 9)
-        self.generate_reports()
-
-        self.update_status("Generating preps", 4, 9)
-        self.generate_prep_file()
-
-        # moved final component of genprepfilejob outside of object.
-        # obtain the paths to the prep-files generated by GenPrepFileJob
-        # w/out having to recover full state.
-        tmp = join(self.pipeline.output_path, 'GenPrepFileJob', 'PrepFiles')
-
-        self.has_replicates = False
-
-        prep_paths = []
-        self.prep_file_paths = defaultdict(list)
-
-        for root, dirs, files in walk(tmp):
-            for _file in files:
-                # breakup the prep-info-file into segments
-                # (run-id, project_qid, other) and cleave
-                # the qiita-id from the project_name.
-                qid = _file.split('.')[1].split('_')[-1]
-
-                if _file.endswith('.tsv'):
-                    _path = abspath(join(root, _file))
-                    prep_paths.append(_path)
-                    self.prep_file_paths[qid].append(_path)
-
-            for _dir in dirs:
-                if _dir == '1':
-                    # if PrepFiles contains the '1' directory, then it's a
-                    # given that this sample-sheet contains replicates.
-                    self.has_replicates = True
-
-        # currently imported from Assay although it is a base method. it
-        # could be imported into Workflows potentially, since it is a post-
-        # processing step. All pairings of assay and instrument type need to
-        # generate prep-info files in the same format.
-        self.overwrite_prep_files(prep_paths)
-
-        # for now, simply re-run any line below as if it was a new job, even
-        # for a restart. functionality is idempotent, except for the
-        # registration of new preps in Qiita. These will simply be removed
-        # manually.
-
-        # post-processing steps are by default associated with the Workflow
-        # class, since they deal with fastq files and Qiita, and don't depend
-        # on assay or instrument type.
-        self.update_status("Generating sample information", 5, 9)
-        self.sifs = self.generate_sifs()
-
-        # post-processing step.
-        self.update_status("Registering blanks in Qiita", 6, 9)
-        if self.update:
-            self.update_blanks_in_qiita()
-
-        self.update_status("Loading preps into Qiita", 7, 9)
-        if self.update:
-            self.update_prep_templates()
-
-        # before we load preps into Qiita we need to copy the fastq
-        # files n times for n preps and correct the file-paths each
-        # prep is pointing to.
-        self.load_preps_into_qiita()
-
-        self.fsr.generate_report()
-
-        self.update_status("Generating packaging commands", 8, 9)
-        self.generate_commands()
-
-        self.update_status("Packaging results", 9, 9)
-        if self.update:
-            self.execute_commands()