initial code

src/rcx_tk/process_metadata_file.py

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+import pandas as pd
+import os
+
+def read_file(file_path):
+    """Reads a file and returns a DataFrame based on the file extension."""
+    file_extension = os.path.splitext(file_path)[1].lower()
+    if file_extension == '.csv':
+        return pd.read_csv(file_path)
+    elif file_extension in ['.xls', '.xlsx']:
+        return pd.read_excel(file_path)
+    elif file_extension == '.txt':
+        return pd.read_csv(file_path, sep='\t')
+    else:
+        raise ValueError("Unsupported file format. Please provide a CSV, Excel, or TSV file.")
+
+def save_dataframe_as_tsv(df, file_path):
+    """Saves a DataFrame as a TSV file."""
+    output_file = f'processed_{os.path.splitext(os.path.basename(file_path))[0]}.tsv'
+    df.to_csv(output_file, sep='\t', index=False)
+    print(f"Processed file saved as: {output_file}")
+
+def process_metadata_file(file_path):
+    """Processes a metadata file, keeping and renaming specific columns."""
+    columns_to_keep = {
+        'File name': 'sampleName',
+        'Type': 'sampleType',
+        'Class ID': 'class',
+        'Batch': 'batch',
+        'Analytical order': 'injectionOrder'
+    }
+
+    df = read_file(file_path)
+    df = df[list(columns_to_keep.keys())].rename(columns=columns_to_keep)
+    df['sampleName'] = df['sampleName'].str.replace(' ', '_')
+    save_dataframe_as_tsv(df, file_path)
+
+def process_alkane_ri_file(file_path):
+    """Processes an Alkane RI file, keeping and renaming specific columns."""
+    columns_to_keep = {
+        'Carbon number': 'carbon_number',
+        'RT (min)': 'rt'
+    }
+
+    df = read_file(file_path)
+    df.columns = df.columns.str.strip()
+    df = df.rename(columns=columns_to_keep)
+    save_dataframe_as_tsv(df, file_path)
+
+# File paths
+metadata_file_path = 'metadata file path'
+alkane_file_path = 'alkane file path'
+
+# Process files
+process_metadata_file(metadata_file_path)
+process_alkane_ri_file(alkane_file_path)