mwmbl/test/test_indexer.py
2023-10-10 20:18:43 +01:00

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4.2 KiB
Python

from pathlib import Path
from tempfile import TemporaryDirectory
from zstandard import ZstdCompressor
from mwmbl.tinysearchengine.indexer import TinyIndex, Document, _binary_search_fitting_size, astuple, \
_trim_items_to_page, _pad_to_page_size, _get_page_data
def test_create_index():
num_pages = 10
page_size = 4096
with TemporaryDirectory() as temp_dir:
index_path = Path(temp_dir) / 'temp-index.tinysearch'
with TinyIndex.create(Document, str(index_path), num_pages=num_pages, page_size=page_size) as indexer:
for i in range(num_pages):
page = indexer.get_page(i)
assert page == []
def test_binary_search_fitting_size_all_fit():
items = [1,2,3,4,5,6,7,8,9]
compressor = ZstdCompressor()
page_size = 4096
count_fit, data = _binary_search_fitting_size(compressor,page_size,items,0,len(items))
# We should fit everything
assert count_fit == len(items)
def test_binary_search_fitting_size_subset_fit():
items = [1,2,3,4,5,6,7,8,9]
compressor = ZstdCompressor()
page_size = 15
count_fit, data = _binary_search_fitting_size(compressor,page_size,items,0,len(items))
# We should not fit everything
assert count_fit < len(items)
def test_binary_search_fitting_size_none_fit():
items = [1,2,3,4,5,6,7,8,9]
compressor = ZstdCompressor()
page_size = 5
count_fit, data = _binary_search_fitting_size(compressor,page_size,items,0,len(items))
# We should not fit anything
assert count_fit == -1
assert data is None
def test_get_page_data_single_doc():
document1 = Document(title='title1',url='url1',extract='extract1',score=1.0)
documents = [document1]
items = [astuple(value) for value in documents]
compressor = ZstdCompressor()
page_size = 4096
# Trim data
num_fitting,trimmed_data = _trim_items_to_page(compressor,4096,items)
# We should be able to fit the 1 item into a page
assert num_fitting == 1
# Compare the trimmed data to the actual data we're persisting
# We need to pad the trimmmed data, then it should be equal to the data we persist
padded_trimmed_data = _pad_to_page_size(trimmed_data, page_size)
serialized_data = _get_page_data(compressor,page_size,items)
assert serialized_data == padded_trimmed_data
def test_get_page_data_many_docs_all_fit():
# Build giant documents item
documents = []
documents_len = 500
page_size = 4096
for x in range(documents_len):
txt = 'text{}'.format(x)
document = Document(title=txt,url=txt,extract=txt,score=x)
documents.append(document)
items = [astuple(value) for value in documents]
# Trim the items
compressor = ZstdCompressor()
num_fitting,trimmed_data = _trim_items_to_page(compressor,page_size,items)
# We should be able to fit all items
assert num_fitting == documents_len
# Compare the trimmed data to the actual data we're persisting
# We need to pad the trimmed data, then it should be equal to the data we persist
serialized_data = _get_page_data(compressor,page_size,items)
padded_trimmed_data = _pad_to_page_size(trimmed_data, page_size)
assert serialized_data == padded_trimmed_data
def test_get_page_data_many_docs_subset_fit():
# Build giant documents item
documents = []
documents_len = 5000
page_size = 4096
for x in range(documents_len):
txt = 'text{}'.format(x)
document = Document(title=txt,url=txt,extract=txt,score=x)
documents.append(document)
items = [astuple(value) for value in documents]
# Trim the items
compressor = ZstdCompressor()
num_fitting,trimmed_data = _trim_items_to_page(compressor,page_size,items)
# We should be able to fit a subset of the items onto the page
assert num_fitting > 1
assert num_fitting < documents_len
# Compare the trimmed data to the actual data we're persisting
# We need to pad the trimmed data, then it should be equal to the data we persist
serialized_data = _get_page_data(compressor,page_size,items)
padded_trimmed_data = _pad_to_page_size(trimmed_data, page_size)
assert serialized_data == padded_trimmed_data