Datasets:
Tasks:
Translation
Multilinguality:
multilingual
Size Categories:
100K<n<1M
Language Creators:
found
Source Datasets:
extended
Tags:
| import os | |
| import pandas as pd | |
| from tqdm import tqdm | |
| from tabulate import tabulate | |
| from translate.storage.tmx import tmxfile | |
| # http://docs.translatehouse.org/projects/translate-toolkit/en/latest/api/storage.html | |
| INPUT_DIR = "corpus/" | |
| OUTPUT_PATH = "csv_corpus/" | |
| os.makedirs(OUTPUT_PATH, exist_ok=True) | |
| x = [] | |
| # For each language file | |
| for file_name in tqdm(os.listdir(INPUT_DIR)): | |
| if ".tmx" not in file_name: | |
| continue | |
| # Documents counter | |
| cpt = 0 | |
| # Lenght of the sentences | |
| source_lens = [] | |
| target_lens = [] | |
| print("file_name : ", file_name) | |
| # Get the languages | |
| LANG_PAIR = file_name.split(".")[0] | |
| L1, L2 = LANG_PAIR.split("-") | |
| data = [] | |
| df = pd.DataFrame(data={ | |
| 'id': [], | |
| 'lang': [], | |
| 'source_text': [], | |
| 'target_text': [] | |
| }) | |
| # Read the file | |
| with open(INPUT_DIR + file_name, 'rb') as fin: | |
| # For each sentence | |
| for node in tmxfile(fin, L1, L2).unit_iter(): | |
| # Add the sentence pair | |
| data.append({ | |
| 'id': node.getid(), | |
| 'lang': LANG_PAIR, | |
| 'source_text': node.source, | |
| 'target_text': node.target | |
| }) | |
| cpt += 1 | |
| source_lens.append(len(node.source.split(" "))) | |
| target_lens.append(len(node.target.split(" "))) | |
| x.append([ | |
| L2, | |
| cpt, | |
| int(sum(source_lens) / len(source_lens)), | |
| int(sum(target_lens) / len(target_lens)) | |
| ]) | |
| # Add to the data frame | |
| df = df.append(data) | |
| # Convert to CSV | |
| df.to_csv(OUTPUT_PATH + LANG_PAIR + ".csv", index=False) | |
| log_file = open("stats.md","w") | |
| log_file.write(str( | |
| tabulate(x, headers=['Lang', '# Docs', 'Avg. # Source Tokens', 'Avg. # Target Tokens'], tablefmt='orgtbl') | |
| ).replace("+","|")) | |
| log_file.close() | |