src/download_and_process_data.py

import os
import pandas as pd
import re

data_dir = os.getcwd()
output_path = os.getcwd()

species_list = ["human", "rat_SD", "mouse_BALB_c", "mouse_C57BL_6"]

for species in species_list:
    print(f"Downloading {species} files")
    species_df = pd.DataFrame(
        columns=["run_id", "sequence_alignment_aa_heavy", "sequence_alignment_aa_light"]
    )
    species_url_file = os.path.join(data_dir, species + "_oas_paired.txt")
    with open(species_url_file, "r") as f:
        for csv_file in f.readlines():
            print(csv_file)
            filename = os.path.basename(csv_file)
            run_id = str(re.search(r"^(.*)_[Pp]aired", filename)[1])
            run_data = pd.read_csv(
                csv_file,
                header=1,
                compression="gzip",
                on_bad_lines="warn",
            )
            run_data = run_data[
                [
                    "sequence_alignment_aa_heavy",
                    "sequence_alignment_aa_light",
                ]
            ]
            run_data.insert(0, "run_id", run_id)
            species_df = pd.concat([species_df, run_data])
        print(f"{species} output summary:")
        print(species_df.head())
        print(species_df.shape)
        output_file_name = os.path.join(output_path, species + ".parquet")
        print(f"Creating {output_file_name}")
        species_df.to_parquet(output_file_name, compression="gzip")