Removed TODOs

Author: charles-cowart

qp_klp/Assays.py

@@ -215,10 +215,6 @@ def post_process_raw_fastq_output(self):
                 copyfile(raw_fastq_file, new_path)
 
     def generate_reports(self):
-        """
-        TODO
-        :return:
-        """
         config = self.pipeline.get_software_configuration('fastqc')
         job = FastQCJob(self.pipeline.run_dir,
                         self.pipeline.output_path,
@@ -241,10 +237,6 @@ def generate_reports(self):
         job.run(callback=self.status_update_callback)
 
     def generate_prep_file(self):
-        """
-        TODO
-        :return:
-        """
         config = self.pipeline.get_software_configuration('seqpro')
 
         # NB: For amplicon runs, the executable used is currently a variant
@@ -309,10 +301,6 @@ def update_prep_templates(self):
         return results
 
     def load_preps_into_qiita(self):
-        """
-        TODO
-        :return:
-        """
         atype = 'FASTQ'
 
         data = []

qp_klp/SequencingTech.py

@@ -107,17 +107,11 @@ def convert_raw_to_fastq(self):
                           config['sing_script_path'],
                           config['tellread_cores'])
 
-        # TODO: Set this path just liek for oillumina and then have
-        # subsequent steps use it instead of hardcode assuming.
         self.raw_fastq_files_path = join(self.pipeline.output_path, 'Full')
 
         job.run(callback=self.status_update_callback)
 
-        # audit the results to determine which samples failed to convert
-        # properly. Append these to the failed-samples report and also
-        # return the list directly to the caller.
-        # TODO: TELLREADJOB needs an audit method
-        # failed_samples = job.audit(self.pipeline.get_sample_ids())
+        self.pipeline.get_sample_ids()
         failed_samples = []
         if hasattr(self, 'fsr'):
             # NB 16S does not require a failed samples report and
@@ -142,7 +136,6 @@ def generate_norm_counts(self):
                               config['integrate_script_path'],
                               self.qiita_job_id)
 
-        # TODO: Maybe the output from this should be set to a membver too.
         job.run(callback=self.status_update_callback)
 
         # audit the results to determine which samples failed to convert
@@ -185,7 +178,6 @@ def integrate_results(self):
                              "",
                              config['integrate_cores'])
 
-        # TODO: ditto as above
         job.run(callback=self.status_update_callback)
 
         # raw_fastq_files_path is used by downstream processes to know
@@ -200,8 +192,6 @@ def integrate_results(self):
         # of time. It also relies on metadata stored in the job object.
         # Hence, it is performed here.
 
-        # TODO: Move any other logs into the right logs directories
-
         # rename the files and move them into project directories.
         for root, dirs, files in walk(self.raw_fastq_files_path):
             for _file in files:

qp_klp/TODO_CHECKLIST.txt

@@ -81,12 +81,6 @@ def what_am_i(self):
                 f"Assay: {self.assay_type}")
 
     def pre_check(self):
-        # TODO: Note that amplicon/illumina workflows shouldn't call this
-        #  method since demuxing samples is performed downstream, hence there
-        #  isn't a list of real sample-names in the sample-sheet to check.
-        #  This check could be performed using the pre-prep sample data
-        #  however.
-
         # since one of the objectives of SPP is to generate prep-info files
         # and automatically load them into Qiita, confirm that all studies
         # mentioned in the sample-sheet/pre-prep do not contain sample
@@ -119,10 +113,6 @@ def generate_special_map(self):
         Generates a list of tuples to support pipeline processing.
         :return: A list of triplets.
         """
-        # TODO: (see below)
-        # this function should be able to be tested by passing in simulated =
-        # results from qclient.
-
         # trimmed files are stored by qiita_id. Find the qiita_id
         # associated with each project and ensure a subdirectory exists
         # for when it comes time to move the trimmed files.
@@ -144,9 +134,6 @@ def generate_sifs(self):
         Generates sample-info files for each project, containing
         metadata on BLANKS.
         """
-
-        # TODO: This will need to be updated and reviewed to handle recent
-        # changes. It is currently a placeholder.
         from_qiita = {}
 
         for study_id in self.prep_file_paths:
@@ -179,7 +166,6 @@ def generate_sifs(self):
         # duplicate sample-names and non-blanks will be handled properly.
         self.sifs = self.pipeline.generate_sample_info_files(add_sif_info)
 
-        # TODO: Remove returning this value if not tested directly.
         return self.sifs
 
     def update_blanks_in_qiita(self):
@@ -188,9 +174,6 @@ def update_blanks_in_qiita(self):
         :return:
         """
 
-        # TODO: This will need to be updated and reviewed to handle recent
-        # changes. It is currently a placeholder.
-
         for sif_path in self.sifs:
             # get study_id from sif_file_name ...something_14385_blanks.tsv
             study_id = sif_path.split('_')[-2]
@@ -353,10 +336,6 @@ def _write_commands_to_output_path(self):
                 f.write(f'{cmd}\n')
 
     def generate_commands(self):
-        """
-        TODO
-        :return:
-        """
         cmds = self._helper_process_operations()
 
         result = self._process_fastp_report_dirs()
@@ -384,10 +363,6 @@ def generate_commands(self):
         self._write_commands_to_output_path()
 
     def execute_commands(self):
-        """
-        TODO
-        :return:
-        """
         # execute the list of commands in order
         for cmd in self.cmds:
             p = Popen(cmd,
@@ -717,7 +692,3 @@ def _process_sample_names(self, project_name, qiita_id, samples):
         number_in_project = len(set(self.samples_in_qiita[qiita_id]))
 
         return not_in_qiita, examples, number_in_project
-
-    def scan_run_directory(self):
-        # TODO: Impl
-        pass

qp_klp/Workflows.py

@@ -100,7 +100,6 @@ def test_invalid_sample_sheets(self):
     def test_metagenomic_workflow_creation(self):
         kwargs = {"uif_path": "qp_klp/tests/data/sample-sheets/metagenomic/"
                   "illumina/good_sheet1.csv",
-                  # TODO: Fix qclient?
                   "qclient": None,
                   "lane_number": "1",
                   "config_fp": "qp_klp/tests/data/configuration.json",
@@ -121,7 +120,6 @@ def test_metagenomic_workflow_creation(self):
     def test_metatranscriptomic_workflow_creation(self):
         kwargs = {"uif_path": "qp_klp/tests/data/sample-sheets/"
                   "metatranscriptomic/illumina/good_sheet1.csv",
-                  # TODO: Fix qclient?
                   "qclient": None,
                   "lane_number": "1",
                   "config_fp": "qp_klp/tests/data/configuration.json",
@@ -158,8 +156,6 @@ def test_amplicon_workflow_creation(self):
         self.assertEqual(wf.assay_type, ASSAY_NAME_AMPLICON)
 
     def atest_tellseq_workflow_creation(self):
-        # TODO: Note we will need to modify metapool enough to accept and
-        # validate these drafts. Fix Qclient
         kwargs = {"uif_path": "qp_klp/tests/data/sample-sheets/metagenomic/"
                   "tellseq/good_sheet_draft1.csv",
                   "qclient": None,

qp_klp/tests/test_WorkflowFactory.py

@@ -429,21 +429,13 @@ def test_partial_metagenomic_pipeline(self):
         self.create_fake_bin('sbatch', "\n".join(cmds))
         audit_results = sorted(wf.quality_control())
 
-        # TODO: Add assertion tests for NuQCJob
-
         # add tests to test audit results, modify test to introduce some
         # 'zero-length' files. add some assertions to show that the post-
         # processing step is munging the correct directory structure needed
         # for subsequent steps.
 
-        # TODO: Test that some files end up in zero-files folder.
-
         # NuQCJob successful.
 
-        # TODO: set up fake multiqc bin to. fake results of fastqc and
-        # multiqc jobs.
-        # audit_results = sorted(wf.generate_reports())
-
     def test_partial_metatranscriptomic_pipeline(self):
         # Tests convert_raw_to_fastq() and quality_control() steps of
         # StandardMetatranscriptomicWorkflow(), which in turn exercises
@@ -644,13 +636,8 @@ def test_partial_metatranscriptomic_pipeline(self):
         self.create_fake_bin('sbatch', "\n".join(cmds))
         audit_results = sorted(wf.quality_control())
 
-        # TODO: Add assertion tests for NuQCJob
-
         # NuQCJob successful.
 
-        # TODO: Add tests for zero-files
-        # TODO: Add tests for MultiQC Job.
-
     def test_partial_amplicon_pipeline(self):
         # Tests convert_raw_to_fastq() and quality_control() steps of
         # StandardAmpliconWorkflow(), which in turn exercises