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""" |
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This script converts the data from the raw data folder to a CSV file. |
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Usage: |
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make 20_newsgroups |
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python convert.py |
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""" |
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import csv |
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import os |
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import re |
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DATASET_PATH = "20_newsgroups" |
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OUTPUT_FILE = "20newsgroups.csv" |
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TRAIN_OUTPUT_FILE = "train.csv" |
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TEST_OUTPUT_FILE = "test.csv" |
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def run(): |
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""" |
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Main function to run the script. |
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""" |
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class_list = os.listdir(DATASET_PATH) |
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class_list.sort() |
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rows = [] |
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for class_name in class_list: |
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doc_list = os.listdir(os.path.join(DATASET_PATH, class_name)) |
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for doc_name in doc_list: |
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doc = parse_document(read_document(class_name, doc_name)) |
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doc["label"] = class_list.index(class_name) |
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if doc["text"]: |
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rows.append(doc) |
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save_csv(rows) |
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def read_document(class_name, doc_name): |
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""" |
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Read the content of a document in the corpus. |
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""" |
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doc_path = os.path.join(DATASET_PATH, class_name, doc_name) |
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with open(doc_path, "r", encoding="ISO-8859-15") as fin: |
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content = fin.read() |
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return content |
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def save_csv(rows, fname=OUTPUT_FILE): |
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""" |
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Save the processed data into a CSV file. |
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""" |
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with open(fname, "w", encoding="utf8") as f: |
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writer = csv.DictWriter(f, fieldnames=rows[0].keys()) |
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writer.writeheader() |
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for row in rows: |
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writer.writerow(row) |
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def parse_document(doc): |
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""" |
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Parses a document into a dictionary |
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""" |
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header_start = 0 |
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header_end = doc.find("\n\n") |
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body_start = header_end + 2 |
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header = doc[header_start:header_end] |
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body = doc[body_start:] |
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return { |
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"from": parse_header(header, "From"), |
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"subject": parse_header(header, "Subject"), |
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"organization": parse_header(header, "Organization"), |
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"text": body, |
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} |
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def parse_header(header, param): |
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""" |
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Obtains the value of a parameter from the header |
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""" |
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try: |
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return re.search(param + r": (.+)\n", header, re.IGNORECASE).group(1) |
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except AttributeError: |
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return None |
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if __name__ == "__main__": |
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run() |
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