test_full_cleanup_with_different_batchsize() — langchain Function Reference
Architecture documentation for the test_full_cleanup_with_different_batchsize() function in test_indexing.py from the langchain codebase.
Entity Profile
Dependency Diagram
graph TD bc50ce1d_cb04_1d7b_eb85_0e5eadb1744b["test_full_cleanup_with_different_batchsize()"] a9fb4c74_0865_0941_ade3_563a79762cee["test_indexing.py"] bc50ce1d_cb04_1d7b_eb85_0e5eadb1744b -->|defined in| a9fb4c74_0865_0941_ade3_563a79762cee style bc50ce1d_cb04_1d7b_eb85_0e5eadb1744b fill:#6366f1,stroke:#818cf8,color:#fff
Relationship Graph
Source Code
libs/core/tests/unit_tests/indexing/test_indexing.py lines 2169–2214
def test_full_cleanup_with_different_batchsize(
record_manager: InMemoryRecordManager, vector_store: VectorStore
) -> None:
"""Check that we can clean up with different batch size."""
docs = [
Document(
page_content="This is a test document.",
metadata={"source": str(d)},
)
for d in range(1000)
]
assert index(
docs,
record_manager,
vector_store,
cleanup="full",
key_encoder="sha256",
) == {
"num_added": 1000,
"num_deleted": 0,
"num_skipped": 0,
"num_updated": 0,
}
docs = [
Document(
page_content="Different doc",
metadata={"source": str(d)},
)
for d in range(1001)
]
assert index(
docs,
record_manager,
vector_store,
cleanup="full",
cleanup_batch_size=17,
key_encoder="sha256",
) == {
"num_added": 1001,
"num_deleted": 1000,
"num_skipped": 0,
"num_updated": 0,
}
Domain
Subdomains
Source
Frequently Asked Questions
What does test_full_cleanup_with_different_batchsize() do?
test_full_cleanup_with_different_batchsize() is a function in the langchain codebase, defined in libs/core/tests/unit_tests/indexing/test_indexing.py.
Where is test_full_cleanup_with_different_batchsize() defined?
test_full_cleanup_with_different_batchsize() is defined in libs/core/tests/unit_tests/indexing/test_indexing.py at line 2169.
Analyze Your Own Codebase
Get architecture documentation, dependency graphs, and domain analysis for your codebase in minutes.
Try Supermodel Free