Reformat Python code with Black

bin/collect_species_statistics.py

 #! /usr/bin/env python3
 
-#Collect scaffold information for a species filtered from Jovian's
+# Collect scaffold information for a species filtered from Jovian's
 # classification table. (Which scaffolds, their length and number
 # of reads mapped to them.)
 #
@@ -9,19 +9,19 @@
 # -i data/all_taxClassified-Escherichia_coli.tsv data/Mapped_read_counts.tsv \
 # -o results/Escherichia_coli-scaffolds_per_sample.tsv results/Escherichia_coli-stats_per_sample.tsv \
 #
-#Three required input arguments are:
+# Three required input arguments are:
 # -i/--input for the two required tables (see example)
 # -o/--output for the result tables (see example)
 
 ## Import required libraries
-import sys              #to abort the script when an error occurs
-import argparse         #to parse command-line arguments
-import pandas as pd     #to work with dataframes (tabular data)
-import numpy as np      #for calculations (summing contig stats)
-import re               #to extract sample names from multiqc table
+import sys  # to abort the script when an error occurs
+import argparse  # to parse command-line arguments
+import pandas as pd  # to work with dataframes (tabular data)
+import numpy as np  # for calculations (summing contig stats)
+import re  # to extract sample names from multiqc table
 
 ## Define functions:
-#1. Parse command-line arguments
+# 1. Parse command-line arguments
 def parse_arguments():
     """
     Parse the arguments from the command line, i.e.:
@@ -29,98 +29,111 @@ def parse_arguments():
      -o/--output = 2 output files
      -h/--help = show help
     """
-    parser = argparse.ArgumentParser(prog="collect species statistics",
+    parser = argparse.ArgumentParser(
+        prog="collect species statistics",
         description="Collect scaffold statistics for each species filtered from Jovian's results",
         usage="collect_species_statistics.py -i file1 file2 -o file3 file4"
         " [-h / --help]",
-             add_help=False)
+        add_help=False,
+    )
 
     required = parser.add_argument_group("Required arguments")
 
-    required.add_argument("-i",
+    required.add_argument(
+        "-i",
         "--input",
         dest="input",
         metavar="file1 file2",
         required=True,
         nargs=2,
         type=str,
-                          help="Classified scaffolds table and mapped read counts.")
+        help="Classified scaffolds table and mapped read counts.",
+    )
 
-    required.add_argument("-o",
+    required.add_argument(
+        "-o",
         "--output",
         dest="output",
         metavar="file3 file4",
         required=True,
         nargs=2,
         type=str,
-                          help="Output tables (per scaffold, and summed statistics).")
+        help="Output tables (per scaffold, and summed statistics).",
+    )
 
     optional = parser.add_argument_group("Optional arguments")
 
-    optional.add_argument("-h",
-                          "--help",
-                          action="help",
-                          help="Show this message and exit.")  
+    optional.add_argument(
+        "-h", "--help", action="help", help="Show this message and exit."
+    )
 
     (args, extra_args) = parser.parse_known_args()
 
-    return(args)
+    return args
+
 
 def main():
     """
     Main execution of the script
     """
-    #1. Parse and print command-line arguments
+    # 1. Parse and print command-line arguments
     arguments = parse_arguments()
 
-    message =  ("\n"
+    message = (
+        "\n"
         "These are the arguments you have provided:\n"
         "  INPUT:\n"
         "{0}\n"
         "  OUTPUT:\n"
-                "{1}\n".format(arguments.input,
-                               arguments.output))
+        "{1}\n".format(arguments.input, arguments.output)
+    )
 
     print(message)
 
-    #2. Open input files
-    species_scaffolds_df = pd.read_csv(arguments.input[0],
-                                       sep="\t")
+    # 2. Open input files
+    species_scaffolds_df = pd.read_csv(arguments.input[0], sep="\t")
 
-    mapped_reads_df = pd.read_csv(arguments.input[1],
-                                  sep="\t")
+    mapped_reads_df = pd.read_csv(arguments.input[1], sep="\t")
 
-    #3. Merge input files together
-    quantified_scaffolds_df = pd.merge(species_scaffolds_df, mapped_reads_df,
+    # 3. Merge input files together
+    quantified_scaffolds_df = pd.merge(
+        species_scaffolds_df,
+        mapped_reads_df,
         on=["scaffold_name", "Sample_name"],
-                                       how="left")
-
-    #4. Extract columns of interest
-    quantified_scaffolds_df = quantified_scaffolds_df[["Sample_name",
-                            "scaffold_name", "Length", "mapped_reads"]]
+        how="left",
+    )
 
-    #And rename them
-    quantified_scaffolds_df.rename(columns={ "Sample_name" : "Sample",
-                                            "scaffold_name" : "Scaffold",
-                                            "Length" : "Scaffold_length",
-                                            "mapped_reads" : "Mapped_reads"},
-                                   inplace=True)
+    # 4. Extract columns of interest
+    quantified_scaffolds_df = quantified_scaffolds_df[
+        ["Sample_name", "scaffold_name", "Length", "mapped_reads"]
+    ]
+
+    # And rename them
+    quantified_scaffolds_df.rename(
+        columns={
+            "Sample_name": "Sample",
+            "scaffold_name": "Scaffold",
+            "Length": "Scaffold_length",
+            "mapped_reads": "Mapped_reads",
+        },
+        inplace=True,
+    )
 
-    quantified_scaffolds_df.to_csv(arguments.output[0],
-                                   sep="\t", index=False)
+    quantified_scaffolds_df.to_csv(arguments.output[0], sep="\t", index=False)
 
-    #5. Aggregate statistics per sample
+    # 5. Aggregate statistics per sample
     quantified_scaffolds_df["Number_of_scaffolds"] = 1
-    statistics_per_sample = pd.DataFrame(quantified_scaffolds_df.groupby(
-        ["Sample"]).sum()[["Number_of_scaffolds", "Scaffold_length", 
-                           "Mapped_reads"]]
+    statistics_per_sample = pd.DataFrame(
+        quantified_scaffolds_df.groupby(["Sample"]).sum()[
+            ["Number_of_scaffolds", "Scaffold_length", "Mapped_reads"]
+        ]
     )
 
-    statistics_per_sample.to_csv(arguments.output[1],
-                                 sep="\t", index=True)
-                                 #requires index for sample names
+    statistics_per_sample.to_csv(arguments.output[1], sep="\t", index=True)
+    # requires index for sample names
+
+    return None
 
-    return(None)
 
 ## Execute script
 if __name__ == "__main__":

bin/concatenate_depth_tables.py

 #! /usr/bin/env python3
 
-#Concatenate per-sample tables of depth of coverage into an overall table.
-#Required input:
+# Concatenate per-sample tables of depth of coverage into an overall table.
+# Required input:
 # - A number of per-sample tables as tsv files
 #
-#The output file will be a concatenated table with additional "Sample_name"
+# The output file will be a concatenated table with additional "Sample_name"
 # column. Entering a name on the command-line is required.
 #
-#Example use:
+# Example use:
 # python concatenate_depth_tables.py -i Depth_of_coverage-sample1-paired.tsv Depth_of_coverage-sample2-paired.tsv Depth_of_coverage-sample3-paired.tsv -o Depth_of_coverage-paired.tsv
 
-#IMPORT required libraries---------------------------------
+# IMPORT required libraries---------------------------------
 import pandas as pd
 import argparse
 
-#Define FUNCTIONS------------------------------------------
+# Define FUNCTIONS------------------------------------------
 def parse_arguments():
     """
     Parse the arguments from the command line, i.e.:
@@ -22,34 +22,41 @@ def parse_arguments():
      -o/--output = output file (tab-separated table)
      -h/--help = show help
     """
-    parser = argparse.ArgumentParser(prog="concatenate mapped read counts",
+    parser = argparse.ArgumentParser(
+        prog="concatenate mapped read counts",
         description="Concatenate mapped read count tables",
         usage="concatenate_mapped_read_counts.py -i [input] -o [output]"
         " [-h / --help]",
-             add_help=False)
+        add_help=False,
+    )
 
     required = parser.add_argument_group("Required arguments")
 
-    required.add_argument('-i',
-                          '--input',
+    required.add_argument(
+        "-i",
+        "--input",
         dest="input",
-                          metavar='',
+        metavar="",
         required=True,
         type=str,
-                          nargs='+',
-                          help="List of input files (counts per sample).")
+        nargs="+",
+        help="List of input files (counts per sample).",
+    )
 
-    required.add_argument('-o',
-                          '--output',
+    required.add_argument(
+        "-o",
+        "--output",
         dest="output",
-                          metavar='',
+        metavar="",
         required=True,
         type=str,
-                          help="Output file name (and directory).")
+        help="Output file name (and directory).",
+    )
 
     (args, extra_args) = parser.parse_known_args()
 
-    return(args)
+    return args
+
 
 def extract_sample_name(filename):
     """
@@ -59,34 +66,36 @@ To extract the sample name, remove "Mapped_read_counts-", and
 everything from "_to_" until the end.
     """
     if "/" in filename:
-    #If the directory path is attached to the filename, remove it
+        # If the directory path is attached to the filename, remove it
         without_path = filename.split("/")[-1]
     else:
         without_path = filename
 
     without_prefix = without_path.replace("Depth_of_coverage-", "")
-    sample = without_prefix[:without_prefix.index("_to_")]
+    sample = without_prefix[: without_prefix.index("_to_")]
+
+    return sample
 
-    return(sample)
 
 def main():
     """
     Main execution of the script
     """
-    #1. Parse and show arguments
+    # 1. Parse and show arguments
     arguments = parse_arguments()
 
-    message =  ("\n"
+    message = (
+        "\n"
         "These are the arguments you have provided:\n"
         "  INPUT:\n"
         "{0},\n"
         "  OUTPUT:\n"
-                "{1}\n".format(arguments.input,
-                               arguments.output))
+        "{1}\n".format(arguments.input, arguments.output)
+    )
 
     print(message)
 
-    #2. Read input files and make into one dataframe
+    # 2. Read input files and make into one dataframe
     concat_df = pd.DataFrame()
 
     for file in arguments.input:
@@ -96,12 +105,12 @@ def main():
 
         concat_df = pd.concat([concat_df, df])
 
-    #3. Write table to a tsv file
-    concat_df.to_csv(arguments.output, sep = '\t', 
-                     index = False)
+    # 3. Write table to a tsv file
+    concat_df.to_csv(arguments.output, sep="\t", index=False)
+
+    return None
 
-    return(None)
 
-#EXECUTE script--------------------------------------------
+# EXECUTE script--------------------------------------------
 if __name__ == "__main__":
     main()

bin/concatenate_read_counts.py

 #! /usr/bin/env python3
 
-#Concatenate per-sample tables of read counts into an overall table.
-#Required input:
+# Concatenate per-sample tables of read counts into an overall table.
+# Required input:
 # - A number of per-sample tables as tsv files
 #
-#The output file will be a concatenated table with additional "Sample_name"
+# The output file will be a concatenated table with additional "Sample_name"
 # and "Reference" columns. Entering a name on the command-line is required.
 #
-#Example use:
+# Example use:
 # python concatenate_read_counts.py -i sample1-paired.tsv sample2-paired.tsv sample3-paired.tsv -o All_samples-paired.tsv
 
-#IMPORT required libraries---------------------------------
+# IMPORT required libraries---------------------------------
 import pandas as pd
 import argparse
 
-#Define FUNCTIONS------------------------------------------
+# Define FUNCTIONS------------------------------------------
 def parse_arguments():
     """
     Parse the arguments from the command line, i.e.:
@@ -22,34 +22,41 @@ def parse_arguments():
      -o/--output = output file (tab-separated table)
      -h/--help = show help
     """
-    parser = argparse.ArgumentParser(prog="concatenate mapped read counts",
+    parser = argparse.ArgumentParser(
+        prog="concatenate mapped read counts",
         description="Concatenate mapped read count tables",
         usage="concatenate_mapped_read_counts.py -i [input] -o [output]"
         " [-h / --help]",
-             add_help=False)
+        add_help=False,
+    )
 
     required = parser.add_argument_group("Required arguments")
 
-    required.add_argument('-i',
-                          '--input',
+    required.add_argument(
+        "-i",
+        "--input",
         dest="input",
-                          metavar='',
+        metavar="",
         required=True,
         type=str,
-                          nargs='+',
-                          help="List of input files (counts per sample).")
+        nargs="+",
+        help="List of input files (counts per sample).",
+    )
 
-    required.add_argument('-o',
-                          '--output',
+    required.add_argument(
+        "-o",
+        "--output",
         dest="output",
-                          metavar='',
+        metavar="",
         required=True,
         type=str,
-                          help="Output file name (and directory).")
+        help="Output file name (and directory).",
+    )
 
     (args, extra_args) = parser.parse_known_args()
 
-    return(args)
+    return args
+
 
 def extract_sample_and_reference_name(filename):
     """
@@ -59,44 +66,48 @@ To extract the sample name, remove "Mapped_read_counts-", and
 everything from "_to_" until the end.
     """
     if "/" in filename:
-    #If the directory path is attached to the filename, remove it
+        # If the directory path is attached to the filename, remove it
         without_path = filename.split("/")[-1]
     else:
         without_path = filename
 
     without_prefix = without_path.replace("Mapped_read_counts-", "")
-    sample = without_prefix[:without_prefix.index("_to_")]
+    sample = without_prefix[: without_prefix.index("_to_")]
     reference = without_prefix[without_prefix.index("_to_") + 4 : -4]
-    #Assume the .tsv file extension; hence strip the last 4 characters
+    # Assume the .tsv file extension; hence strip the last 4 characters
     if "-unpaired" in reference:
         reference = reference.replace("-unpaired", "")
     elif "-paired" in reference:
         reference = reference.replace("-paired", "")
     else:
-        print("There might be an unexpected suffix in the reference name:"
-              " %s" % reference)
+        print(
+            "There might be an unexpected suffix in the reference name:"
+            " %s" % reference
+        )
         pass
 
-    return(sample, reference)
+    return (sample, reference)
+
 
 def main():
     """
     Main execution of the script
     """
-    #1. Parse and show arguments
+    # 1. Parse and show arguments
     arguments = parse_arguments()
 
-    message =  ("\n"
+    message = (
+        "\n"
         "These are the arguments you have provided:\n"
         "  INPUT:\n"
         "{0},\n"
         "  OUTPUT:\n"
-                "{1}\n".format(arguments.input,
-                               arguments.output))
+        "{1}\n".format(arguments.input, arguments.output)
+    )
 
     print(message)
 
-    #2. Read input files and make into one dataframe
+    # 2. Read input files and make into one dataframe
     concat_df = pd.DataFrame()
 
     for file in arguments.input:
@@ -107,12 +118,12 @@ def main():
 
         concat_df = pd.concat([concat_df, df])
 
-    #3. Write table to a tsv file
-    concat_df.to_csv(arguments.output, sep = '\t', 
-                     index = False)
+    # 3. Write table to a tsv file
+    concat_df.to_csv(arguments.output, sep="\t", index=False)
+
+    return None
 
-    return(None)
 
-#EXECUTE script--------------------------------------------
+# EXECUTE script--------------------------------------------
 if __name__ == "__main__":
     main()

bin/create_per_sample_fasta.py

 #! /usr/bin/env python3
 
-#From the species-filtered Jovian output table, create fasta files per sample
+# From the species-filtered Jovian output table, create fasta files per sample
 # for each species. E.g. 'all_taxClassified-Escherichia_coli.tsv' becomes
 # 'A-Escherichia_coli-scaffolds.fasta', 'B-Escherichia_coli-scaffolds.fasta',
 # and 'C-Escherichia_coli-scaffolds.fasta' if your sample names are A, B and
 # C.
-#Resulting fasta files are written to the same directory as the input file.
+# Resulting fasta files are written to the same directory as the input file.
 #
-#Example use:
+# Example use:
 # python create_per_sample_fasta.py -i all_taxClassified-Escherichia_coli.tsv
 
 from pathlib import Path
 import argparse
 
+
 def parse_arguments():
     """
     Parse the arguments from the command line, i.e.:
@@ -20,41 +21,46 @@ def parse_arguments():
      -s/--samples = sample names for which to generate output (necessary for snakemake)
      -h/--help = show help
     """
-    parser = argparse.ArgumentParser(prog="create per sample fasta",
+    parser = argparse.ArgumentParser(
+        prog="create per sample fasta",
         description="Create a fasta file per sample with scaffolds from the specified species",
-             usage="create_per_sample_fasta.py -i file -s samples"
-             " [-h / --help]",
-             add_help=False)
+        usage="create_per_sample_fasta.py -i file -s samples" " [-h / --help]",
+        add_help=False,
+    )
 
     required = parser.add_argument_group("Required arguments")
 
-    required.add_argument("-i",
+    required.add_argument(
+        "-i",
         "--input",
         dest="input",
         metavar="file",
         required=True,
         type=str,
-                          help="Classified scaffolds table for species of interest.")
+        help="Classified scaffolds table for species of interest.",
+    )
 
     optional = parser.add_argument_group("Optional arguments")
 
-    optional.add_argument("-s",
+    optional.add_argument(
+        "-s",
         "--samples",
         dest="samples",
         metavar="samples",
         type=str,
         nargs="+",
         default="None",
-                          help="Samples for which to create fasta files.")
+        help="Samples for which to create fasta files.",
+    )
 
-    optional.add_argument("-h",
-                          "--help",
-                          action="help",
-                          help="Show this message and exit.")  
+    optional.add_argument(
+        "-h", "--help", action="help", help="Show this message and exit."
+    )
 
     (args, extra_args) = parser.parse_known_args()
 
-    return(args)
+    return args
+
 
 def read_and_create_fastas(input_file, samples):
     """
@@ -63,90 +69,95 @@ def read_and_create_fastas(input_file, samples):
     """
 
     species = input_file.split("-")[1][:-4]
-    #species is the second part of the file name, after the dash, 
+    # species is the second part of the file name, after the dash,
     # and excluding the extension (last 4 characters)
 
     input_dir = Path(input_file).parent
 
     samples_seen = []
-    #Keep a list of which samples have been seen, so that
+    # Keep a list of which samples have been seen, so that
     # for each sample a new empty file can be initiated.
 
-    with open(input_file, 'r') as read_file:
-        next(read_file) #skip the header
+    with open(input_file, "r") as read_file:
+        next(read_file)  # skip the header
 
         for line in read_file:
             line = line.split()
-            #split the line in separate elements
+            # split the line in separate elements
 
-            sample = line[0] #sample is the first element
-            scaffold_id = line[1] #scaffold id is the second element
-            sequence = line[-1] #sequence is the last element
+            sample = line[0]  # sample is the first element
+            scaffold_id = line[1]  # scaffold id is the second element
+            sequence = line[-1]  # sequence is the last element
 
-            output_file = Path(input_dir / ("%s-%s-scaffolds.fasta" % (sample, species)))
+            output_file = Path(
+                input_dir / ("%s-%s-scaffolds.fasta" % (sample, species))
+            )
 
             if not output_file.exists():
-            #If the file is not there yet, create an empty file
+                # If the file is not there yet, create an empty file
                 output_file.touch()
             else:
-            #And if it does exist
+                # And if it does exist
                 if sample in samples_seen:
-                #Check whether this had been seen already
+                    # Check whether this had been seen already
                     pass
                 else:
                     # and if not, empty the file and add it to the seen list
-                    open(output_file, 'w').close()
+                    open(output_file, "w").close()