oceanbase/pyseekdb
oceanbase/pyseekdb has 62 GitHub stars and 35 forks. Star changes are not measured yet. Last checked 2026-11-14 04:23 UTC. Last push 2026-11-09.
Measured star growth
- in 24h
- Collecting history
- in 7 days
- Collecting history
- in 15 days
- Collecting history
- in 1 month
- Collecting history
Net star changes over overlapping periods, not daily totals. Missing measurements are left blank. Stars measure attention, not software quality.
About
A unified python SDK supports OceanBase or OceanBase seekdb, more efficient and easy-to-use.
DataREADME.md
Originalpyseekdb
pyseekdb is a Python SDK for seekdb and OceanBase AI search. It supports embedded and server deployments with vector, full-text, and hybrid retrieval, and exposes a collection-first API for application workflows. For advanced database operations, you can use MySQL-compatible drivers to run SQL against seekdb and OceanBase.
Key features:
- Unified API: Single interface for embedded and remote server modes
- Vector Operations: Efficient vector similarity search
- Hybrid Search: Combine vector and full-text search
- Embedding Functions: Built-in support for various embedding models
- Collection Management: Easy collection (table) creation and management
- Database Management: Admin operations for database management
Documentation
- Docs home: https://docs.seekdb.ai
- SDK guide: https://docs.seekdb.ai/seekdb/pyseekdb-sdk-get-started
- User guide: https://docs.seekdb.ai/seekdb/deploy-overview
- API reference: https://docs.seekdb.ai/seekdb/api-overview
- RAG demo: English / 中文
- Contributing: CONTRIBUTING.md
Installation
pip install -U pyseekdb
# or with uv
uv add pyseekdb
Quick Start
import pyseekdb
client = pyseekdb.Client(path="./seekdb.db", database="demo")
collection = client.get_or_create_collection("my_collection")
collection.add(
ids=["doc1", "doc2"],
documents=["Hello world", "pyseekdb quick start"],
metadatas=[{"tag": "hello"}, {"tag": "demo"}],
)
# Refresh the index to make the added documents searchable
collection.refresh_index()
results = collection.query(query_texts=["hello"], n_results=3)
print(results["ids"][0])
For full usage, connection modes, collection management, and operations, see the User Guide.
License
This package is licensed under Apache 2.0. See LICENSE.
Explore related projects
Asabeneh/30-Days-Of-Python
The 30 Days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than 100 days. Follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
78,711 starsgrafana/grafana
The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
77,894 starsredis/redis
For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.
77,490 starsapache/superset
Apache Superset is a Data Visualization and Data Exploration Platform
75,522 stars