VFBquery
VFBquery is the query layer of Virtual Fly Brain
(VFB) — the Drosophila nervous-system atlas. It turns the identifiers VFB
users work with (FBbt_... anatomy classes, VFB_... individuals) into the
rich, cross-referenced reports the VFB website shows: term metadata, aligned
images, connectivity, transcriptomics, similar neurons, stocks and
publications. It is both a Python package and the HTTP backend that serves
those results to the VFB site and to third-party tools.
How it works
VFBquery sits in front of the VFB data stores and does the fan-out for you:
- Solr holds pre-built
term_infodocuments and powers free-text search — most lookups are answered from here in milliseconds. - Neo4j (the VFB knowledge graph) answers the relational questions: connectivity, cross-references, images by template, dataset membership.
- Owlery (an OWL reasoner) answers the ontology queries that need reasoning rather than lookup.
- A Solr-backed result cache stores computed results with a three-month TTL and version-based invalidation, so repeated queries are effectively instant — see CACHING.md.
The same functions are exposed two ways: imported as a Python package, or
served over HTTP by the bundled high-availability server (vfbquery.ha_api),
which adds request coalescing, queueing, backpressure and its own short-lived
result cache. The VFB website's term-information panels are drawn from this
service.
Install
pip install --upgrade vfbquery
Python 3.8+. Installing pulls the full server dependency set; if you only
want to call a deployed HTTP API, the lightweight
vfbquery-client needs just requests and
pandas.
Quick start
import vfbquery as vfb
# Term information for an anatomy class or an individual neuron:
vfb.get_term_info('FBbt_00003748') # medulla
vfb.get_term_info('VFB_00101567') # JRC2018Unisex template
# The queries the website offers for a term, runnable directly, e.g.:
vfb.get_instances('FBbt_00003748', return_dataframe=False)
# Connectivity between neuron types:
vfb.query_connectivity(upstream_type='LPLC2', downstream_type='giant fiber neuron')
# Pass-through to the VFB-hosted CATMAID servers (FAFB, FANC, L1EM, ...),
# addressing neurons by skid or VFB id interchangeably:
from vfbquery import catmaid
catmaid('fafb').connectivity(ids=['VFB_001011rj'])
catmaid('fafb').swc(id='VFB_001011rj', aligned='JRC2018Unisex')
Every function is documented, with runnable examples, in the interactive API documentation described below, and in the Python client guide.
The HTTP API
python -m vfbquery.ha_api starts the server (default port 8080). Its root
page is interactive API documentation in the style of the
VFB-hosted CATMAID /apis/ pages:
every endpoint with its parameters, pre-filled runnable examples, and live
results — open / on any deployment, for example the production instance at
https://v3-cached.virtualflybrain.org/. The machine-readable version is at
/docs.json.
The endpoint surface mirrors the Python package: /get_term_info,
/run_query, /search, /xref, /combine, /query_connectivity,
/get_hierarchy, the FlyBase stock and combination resolvers, and the
/catmaid/... pass-through. The full HTTP reference lives at
vfbquery.readthedocs.io.
Documentation
- https://vfbquery.readthedocs.io — the documentation site: getting
started, the Python client, the HTTP API, and the
/combinereference. - VFB_QUERIES_REFERENCE.md — every named query, its Cypher/Owlery source and its result schema.
- schema.md — the
term_inforesult schema. - CACHING.md — cache behaviour, configuration and invalidation.
- RELEASING.md — how releases and versioning work.
- performance.md — live performance figures, regenerated by CI.
Development
Tests live in src/test/ (package-level, run against the live VFB backend)
and tests/ (HA-API unit tests). The canonical worked examples are a real
test, src/test/test_example_queries.py:
CI runs them against production and compares each result's shape to the
recording in src/test/example_expected/, so the examples cannot rot; when
a schema change is intentional, python -m src.test.test_example_queries --record refreshes the recordings. pip install -r requirements.txt -r tests/requirements.txt, then pytest.
Licence
GPL-3.0. Please cite Court et al. (2023), Virtual Fly Brain — an interactive atlas of the Drosophila nervous system when VFB data or services contribute to a publication.
Metadata
Release files for vfbquery 1.22.54
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