pgserver-search 0.1.6

Self-contained Postgres (with pg_trgm, pgvector, and btree_gist) for Python applications

pgserver-search

Disclaimer — this was vibe-coded (in Simon Willison's sense: I kept prompting an LLM until it worked, without reviewing the generated code line-by-line). Intended use: throwaway Postgres instances in Jupyter notebooks and quick test scripts — a richer alternative to SQLite for when you need real Postgres search features like pg_trgm trigram similarity, pgvector vector search, and btree_gist-backed tstzrange filters for search results.

Not intended for production-parity testing. Embedded Postgres differs from your hosted/RDS Postgres in build flags, OS libraries (glibc / ICU collation), default postgresql.conf, and available extensions. If you need audited infrastructure or prod-equivalent integration tests, use testcontainers or a staging Postgres instead — or at minimum, read the diff against orm011/pgserver and build from source (see below).

A self-contained Postgres server for Python applications, with pg_trgm, pgvector, and btree_gist bundled in for trigram, vector, and time-window-filtered search workflows.

What this is

This is a fork of orm011/pgserver that adds selected Postgres contrib/search extensions to the bundled Postgres build. All credit for the core design and implementation goes to Oscar Moll — this fork only changes the build recipe and packaging.

The upstream pgserver bundles Postgres + pgvector. This fork additionally builds and installs pg_trgm and btree_gist into the packaged Postgres layout, so you can combine vector/trigram search with Postgres tstzrange filters, for example "search only records visible during this time window", without extra local Postgres setup.

Why

pg_trgm and btree_gist ship in Postgres' contrib/ tree but are not installed by the default make install that upstream pgserver runs. If you want fuzzy text search or time-window filtering over search results alongside vector search in an embedded Postgres, you previously had to build those pieces yourself. This fork does that for you.

Install

From PyPI (recommended)

Pre-built wheels are published to PyPI for the platforms built by this repo's release workflow:

pip install pgserver-search

The same wheels are also attached to tagged GitHub releases.

From source (security-conscious install)

If you'd rather inspect the code and build Postgres yourself instead of trusting a binary wheel, do this:

# 1. Clone and inspect
git clone https://github.com/stantonius/pgserver-search.git
cd pgserver-search

# 2. Audit what will run during the build
less pgbuild/Makefile   # downloads postgres-18.3.tar.gz from ftp.postgresql.org
less setup.py           # hooks `make` into setuptools' build_py
less pyproject.toml

# 3. Install system build deps (Debian/Ubuntu)
sudo apt-get install -y build-essential curl tar zlib1g-dev

# macOS: Xcode command line tools are enough
# xcode-select --install

# 4. Build the Postgres binaries into src/pgserver/pginstall/
make build

# 5. Build a wheel from those binaries and install it
make install-wheel

The make install-wheel target runs make build (downloads Postgres 18.3 source, configures, compiles, installs pg_trgm, pgvector, and btree_gist into the package layout) and then pip install dist/*.whl. Takes ~5–10 minutes the first time; everything is cached after that.

Usage

The Python import name stays pgserver (so existing code keeps working) — only the distribution name is pgserver-search.

import pgserver, tempfile

with tempfile.TemporaryDirectory() as d:
    pg = pgserver.get_server(d, cleanup_mode='delete')
    pg.psql("CREATE EXTENSION pg_trgm;")
    pg.psql("CREATE EXTENSION vector;")
    pg.psql("CREATE EXTENSION btree_gist;")
    print(pg.psql("SELECT similarity('hello', 'helo');"))
    pg.cleanup()

License

Same as upstream pgserver — PostgreSQL license (MIT-family). See LICENSE.

Differences from upstream

• pgbuild/Makefile — adds pg_trgm and btree_gist targets that build and install Postgres contrib extensions into src/pgserver/pginstall/.
• setup.py — hooks make build into setuptools so source installs (pip install git+https://...) produce a working wheel automatically.
• pyproject.toml — package renamed to pgserver-search; adds include-package-data and a pginstall/** glob so the built binaries are shipped inside the wheel.
• .github/workflows/build-and-test.yml — tagged releases upload wheels as GitHub Release assets (upstream uses PyPI Trusted Publishing).