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import os
import pickle
from tqdm import tqdm # for progress bar
import ir_datasets as irds
def create_doc_mappings():
collections = ['neuclir/1/zh', 'neuclir/1/fa', 'neuclir/1/ru']
for collection in collections:
print(f"Processing {collection}...")
# Create mapping
doc_mapping = {}
dataset = irds.load(collection)
# Use tqdm to show progress
for doc in tqdm(dataset.docs):
doc_mapping[doc.doc_id] = {
'title': doc.title,
'text': doc.text
}
# Save to file
output_file = f"doc_mapping_{collection.replace('/', '_')}.pkl"
with open(output_file, 'wb') as f:
pickle.dump(doc_mapping, f, protocol=pickle.HIGHEST_PROTOCOL)
print(f"Saved mapping to {output_file}")
print(f"Number of documents: {len(doc_mapping)}\n")
# Function to load and use the mapping
def get_text_from_id_fast(docid, collection):
collection = collection.replace('zho', 'zh').replace('fas', 'fa').replace('rus', 'ru')
mapping_file = f"doc_mapping/doc_mapping_{collection.replace('/', '_')}.pkl"
# Load mapping if not already loaded
if not hasattr(get_text_from_id_fast, 'cache'):
get_text_from_id_fast.cache = {}
if collection not in get_text_from_id_fast.cache:
with open(mapping_file, 'rb') as f:
get_text_from_id_fast.cache[collection] = pickle.load(f)
doc = get_text_from_id_fast.cache[collection].get(docid)
if doc:
return doc['title'], doc['text']
return None, None
if __name__ == "__main__":
# Create the mappings
# create_doc_mappings()
# Example usage
docid = "8e45c80f-f63b-4eca-9976-79185811cd7d" # replace with a real doc ID
collection = "neuclir/1/fa"
title, text = get_text_from_id_fast(docid, collection)
print(title)
print(text)
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