semvec/pypi-packages huggingface dataset:
vector-bench 0.1.0
Benchmark vector database/extensions.
License: Apache-2.0
Requires Python: >=3.8

# Vector DB Benchmark

Supported databases/extensions:

- [x] [`pgvecto.rs`](https://github.com/tensorchord/pgvecto.rs)
- [x] [`pgvector`](https://github.com/pgvector/pgvector)
- [ ] [`qdrant`](https://github.com/qdrant/qdrant/)

Supported datasets:

- [x] random generated
- [x] GIST 960

## Installation

```bash
pip install vector_bench
```

## Run

### Server

Run the docker compose file under [`server`](server/) folder.

```base
cd server/pgvecto.rs && docker compose up -d
```

### Client

```bash
# help
vector_bench --help
# only insert the data
vector_bench --insert --url postgresql://postgres:password@127.0.0.1:5432/postgres -s gist_960_l2
# only query the data (make sure the data is already inserted)
vector_bench --query --url postgresql://postgres:password@localhost:5432/postgres -s gist_960_l2
# insert and query the data
vector_bench --insert --query --url postgresql://postgres:password@localhost:5432/postgres -s gist_960_l2
```

## How to contribute

```bash
# install all the necessary dependencies:
make dev
# format code
make format
# lint
make lint
```

### Add more datasets

- Add new `DatasetConfig` to `vector_bench/dataset/source.py`

### Add more clients

- Inherit and implement the `BaseClient` class in `vector_bench/client/base.py`
jsoncanon 0.2.3
Typed Python implementation of JSON Canonicalization Scheme as described in RFC 8785. Currently lacks full floating point support
License: Apache-2.0
Requires Python: >=3.8,<4.0
Keywords: JSON,RFC-8785,canonicalization,deterministic,serialization,hash

# jsoncanon

Typed Python implementation of JSON Canonicalization Scheme as described in 
[RFC 8785](https://www.rfc-editor.org/rfc/rfc8785.html). The initial release (v0.2.x) is a partial release focused on the 
features needed by the [Sequence Collections working group](https://seqcol.readthedocs.io/) in the
[Global Alliance for Genomics and Health (GA4GH)](https://www.ga4gh.org/).

## Usage

```
>>> import json
>>> from jsoncanon import canonicalize
>>>
>>> data = json.loads('{ "b": [1,3,7], "a": { "y": true, "x": null } }')
>>> canonicalize(data)
b'{"a":{"x":null,"y":true},"b":[1,3,7]}'
```

## Releases

v0.2.0 - Initial release, supporting all data types except for floating point numbers
v0.2.1 - Yanked due to incorrect link
v0.2.2 - Initial release with updated project information