Datasets:
File size: 1,919 Bytes
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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()
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