news_fr / explore_dataset.py
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# -*- coding: utf-8 -*-
"""
Random Line Fetcher for Large Datasets
This script allows users to randomly fetch and display lines from a large dataset.
An index file is created to keep track of the positions of each line in the dataset,
allowing for efficient random line retrieval.
Author : Guillaume Eckendoerffer
Date : 06-07-23
Repository : https://github.com/Eckendoerffer/TorchTrainerFlow/
"""
import os
import random
import json
# Path configurations
path = os.path.dirname(os.path.abspath(__file__))
path_dataset = os.path.join(path, "train.txt")
path_index = os.path.join(path, "dataset_news_index.txt") # Index file
# Flag to determine if an offset of one byte should be applied
shift_one = True
def build_index():
"""
Constructs an index for the dataset where each line's starting position is stored.
"""
index = []
with open(path_dataset, 'r', encoding='utf-8') as f:
offset = 0
for line in f:
index.append(offset)
offset += len(line.encode('utf-8'))
with open(path_index, 'w', encoding="utf8") as f:
json.dump(index, f)
def get_line(file_path, line_number, index, i):
"""
Fetches a specific line from the dataset using the provided index.
"""
with open(file_path, 'r', encoding='utf-8') as f:
if shift_one:
f.seek(index[line_number] + line_number)
else:
f.seek(index[line_number])
text = f.readline()
show = f"{i}) {text}\n"
show += ' ' + '-'*220 + '\n'
return show
# Build index if it doesn't exist
if not os.path.exists(path_index):
build_index()
# Load the index file
with open(path_index, 'r') as file:
index = json.load(file)
# Display 10 random lines from the dataset
for i in range(10):
print(get_line(path_dataset, random.randint(0, len(index)-1), index, i+1))