ruff missing files

src/qp_klp/FailedSamplesRecord.py

@@ -1,5 +1,6 @@
 from json import dumps, load
-from os.path import join, exists
+from os.path import exists, join
+
 import pandas as pd
 
 
@@ -9,8 +10,8 @@ def __init__(self, output_dir, samples):
         # each Job is run, and we want to organize that output by project, we
         # need to keep a running state of failed samples, and reuse the method
         # to reorganize the running-results and write them out to disk.
-        self.output_path = join(output_dir, 'failed_samples.json')
-        self.report_path = join(output_dir, 'failed_samples.html')
+        self.output_path = join(output_dir, "failed_samples.json")
+        self.report_path = join(output_dir, "failed_samples.html")
 
         # create an initial dictionary with sample-ids as keys and their
         # associated project-name and status as values. Afterwards, we'll
@@ -21,20 +22,19 @@ def __init__(self, output_dir, samples):
         self.project_map = {x.Sample_ID: x.Sample_Project for x in samples}
 
     def dump(self):
-        output = {'sample_state': self.sample_state,
-                  'project_map': self.project_map}
+        output = {"sample_state": self.sample_state, "project_map": self.project_map}
 
-        with open(self.output_path, 'w') as f:
+        with open(self.output_path, "w") as f:
             f.write(dumps(output, indent=2, sort_keys=True))
 
     def load(self):
         # if recorded state exists, overwrite initial state.
         if exists(self.output_path):
-            with open(self.output_path, 'r') as f:
+            with open(self.output_path, "r") as f:
                 state = load(f)
 
-            self.sample_state = state['sample_state']
-            self.project_map = state['project_map']
+            self.sample_state = state["sample_state"]
+            self.project_map = state["project_map"]
 
     def update(self, failed_ids, job_name):
         # as a rule, if a failed_id were to appear in more than one
@@ -54,17 +54,30 @@ def write(self, failed_ids, job_name):
 
     def generate_report(self):
         # filter out the sample-ids w/out a failure status
-        filtered_fails = {x: self.sample_state[x] for x in self.sample_state if
-                          self.sample_state[x] is not None}
+        filtered_fails = {
+            x: self.sample_state[x]
+            for x in self.sample_state
+            if self.sample_state[x] is not None
+        }
 
         data = []
         for sample_id in filtered_fails:
-            data.append({'Project': filtered_fails[sample_id],
-                         'Sample ID': sample_id,
-                         'Failed at': self.project_map[sample_id]
-                         })
+            data.append(
+                {
+                    "Project": filtered_fails[sample_id],
+                    "Sample ID": sample_id,
+                    "Failed at": self.project_map[sample_id],
+                }
+            )
         df = pd.DataFrame(data)
 
-        with open(self.report_path, 'w') as f:
-            f.write(df.to_html(border=2, index=False, justify="left",
-                               render_links=True, escape=False))
+        with open(self.report_path, "w") as f:
+            f.write(
+                df.to_html(
+                    border=2,
+                    index=False,
+                    justify="left",
+                    render_links=True,
+                    escape=False,
+                )
+            )

src/qp_klp/PacBioMetagenomicWorkflow.py

@@ -1,71 +1,83 @@
-from .Protocol import PacBio
+from os.path import join
+
+import pandas as pd
+
 from sequence_processing_pipeline.Pipeline import Pipeline
-from .Assays import Metagenomic
-from .Assays import ASSAY_NAME_METAGENOMIC
+
+from .Assays import ASSAY_NAME_METAGENOMIC, Metagenomic
 from .FailedSamplesRecord import FailedSamplesRecord
+from .Protocol import PacBio
 from .Workflows import Workflow
-import pandas as pd
-from os.path import join
 
 
 class PacBioMetagenomicWorkflow(Workflow, Metagenomic, PacBio):
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
 
-        self.mandatory_attributes = ['qclient', 'uif_path',
-                                     'lane_number', 'config_fp',
-                                     'run_identifier', 'output_dir', 'job_id',
-                                     'is_restart']
+        self.mandatory_attributes = [
+            "qclient",
+            "uif_path",
+            "lane_number",
+            "config_fp",
+            "run_identifier",
+            "output_dir",
+            "job_id",
+            "is_restart",
+        ]
 
         self.confirm_mandatory_attributes()
 
         # second stage initializer that could conceivably be pushed down into
         # specific children requiring specific parameters.
-        self.qclient = self.kwargs['qclient']
+        self.qclient = self.kwargs["qclient"]
 
         self.overwrite_prep_with_original = False
-        if 'overwrite_prep_with_original' in self.kwargs:
-            self.overwrite_prep_with_original = \
-                self.kwargs['overwrite_prep_with_original']
-        self.pipeline = Pipeline(self.kwargs['config_fp'],
-                                 self.kwargs['run_identifier'],
-                                 self.kwargs['uif_path'],
-                                 self.kwargs['output_dir'],
-                                 self.kwargs['job_id'],
-                                 ASSAY_NAME_METAGENOMIC,
-                                 lane_number=self.kwargs['lane_number'])
-
-        self.fsr = FailedSamplesRecord(self.kwargs['output_dir'],
-                                       self.pipeline.sample_sheet.samples)
+        if "overwrite_prep_with_original" in self.kwargs:
+            self.overwrite_prep_with_original = self.kwargs[
+                "overwrite_prep_with_original"
+            ]
+        self.pipeline = Pipeline(
+            self.kwargs["config_fp"],
+            self.kwargs["run_identifier"],
+            self.kwargs["uif_path"],
+            self.kwargs["output_dir"],
+            self.kwargs["job_id"],
+            ASSAY_NAME_METAGENOMIC,
+            lane_number=self.kwargs["lane_number"],
+        )
+
+        self.fsr = FailedSamplesRecord(
+            self.kwargs["output_dir"], self.pipeline.sample_sheet.samples
+        )
 
         samples = [
-            {'barcode': sample['barcode_id'],
-             'sample_name': sample['Sample_ID'],
-             'project_name': sample['Sample_Project'],
-             'lane': sample['Lane']}
-            for sample in self.pipeline.sample_sheet.samples]
+            {
+                "barcode": sample["barcode_id"],
+                "sample_name": sample["Sample_ID"],
+                "project_name": sample["Sample_Project"],
+                "lane": sample["Lane"],
+            }
+            for sample in self.pipeline.sample_sheet.samples
+        ]
         df = pd.DataFrame(samples)
         sample_list_fp = f"{self.kwargs['output_dir']}/sample_list.tsv"
-        df.to_csv(sample_list_fp, sep='\t', index=False)
+        df.to_csv(sample_list_fp, sep="\t", index=False)
 
-        self.master_qiita_job_id = self.kwargs['job_id']
+        self.master_qiita_job_id = self.kwargs["job_id"]
 
-        self.lane_number = self.kwargs['lane_number']
-        self.is_restart = bool(self.kwargs['is_restart'])
+        self.lane_number = self.kwargs["lane_number"]
+        self.is_restart = bool(self.kwargs["is_restart"])
 
         if self.is_restart is True:
-            self.raw_fastq_files_path = join(self.pipeline.output_path,
-                                             'ConvertJob')
-            self.reports_path = join(self.raw_fastq_files_path,
-                                     'SeqCounts.csv')
+            self.raw_fastq_files_path = join(self.pipeline.output_path, "ConvertJob")
+            self.reports_path = join(self.raw_fastq_files_path, "SeqCounts.csv")
             self.determine_steps_to_skip()
 
         # this is a convenience member to allow testing w/out updating Qiita.
         self.update = True
 
-        if 'update_qiita' in kwargs:
-            if not isinstance(kwargs['update_qiita'], bool):
-                raise ValueError("value for 'update_qiita' must be of "
-                                 "type bool")
+        if "update_qiita" in kwargs:
+            if not isinstance(kwargs["update_qiita"], bool):
+                raise ValueError("value for 'update_qiita' must be of type bool")
 
-            self.update = kwargs['update_qiita']
+            self.update = kwargs["update_qiita"]