mygramdb-client 1.1.0

Python client for MygramDB - high-performance in-memory full-text search engine with MySQL replication support

python-mygramdb-client

Python client library for MygramDB — a high-performance in-memory full-text search engine with MySQL replication support.

Compatible with MygramDB v1.6 (fuzzy search, highlight, facets, BM25).

Overview

MygramDB provides 25-200x faster full-text search than MySQL FULLTEXT. This client communicates via MygramDB's TCP text protocol (memcached-style) with zero external dependencies.

	MySQL FULLTEXT	MygramDB
Search Speed	Baseline	25-200x faster
Storage	On-disk	In-memory
Replication	—	MySQL binlog
Protocol	MySQL	TCP (memcached-style)

Features

• Zero Dependencies — Standard library only
• Async/Await API — Modern asyncio-based interface with context manager support
• Search Expression Parser — Web-style search syntax (+required, -excluded, "phrase", OR, grouping)
• Full Protocol Support — All MygramDB commands (SEARCH, COUNT, GET, INFO, CACHE, DUMP, OPTIMIZE, etc.)
• Type Safety — Full type hints with dataclasses
• Input Validation — Built-in protection against control character injection

Installation

pip install mygramdb-client

From source

git clone https://github.com/libraz/python-mygramdb-client.git
cd python-mygramdb-client
rye sync

Quick Start

import asyncio
from mygramdb_client import MygramClient, ClientConfig, SearchOptions

async def main():
    async with MygramClient(ClientConfig(host='localhost', port=11016)) as client:
        # Search
        results = await client.search('articles', 'hello', SearchOptions(limit=100))
        print(f"Found {results.total_count} results")

        # Count
        count = await client.count('articles', 'technology')
        print(f"Count: {count.count}")

        # Get document by ID
        doc = await client.get('articles', '12345')
        print(f"Doc: {doc.primary_key} {doc.fields}")

asyncio.run(main())

Search Expressions

Parse web-style search queries into structured search parameters:

from mygramdb_client import simplify_search_expression

# Space = AND, - = NOT, "" = phrase, OR = OR, () = grouping
expr = simplify_search_expression('hello world -spam')
# expr = SimplifiedExpression(main_term='hello', and_terms=['world'], not_terms=['spam'])

results = await client.search('articles', expr.main_term, SearchOptions(
    and_terms=expr.and_terms,
    not_terms=expr.not_terms,
    limit=100,
    offset=50,
    filters={'status': 'published', 'lang': 'en'},
    sort_column='created_at',
    sort_desc=True,
))

MygramDB v1.6 Features

from mygramdb_client import HighlightOptions, FacetOptions, SearchOptions

# BM25 relevance scoring
result = await client.search('articles', 'python',
    SearchOptions(sort_column='_score', sort_desc=True))

# Fuzzy search (Levenshtein distance 1 or 2)
result = await client.search('articles', 'helo',
    SearchOptions(fuzzy=1))

# Highlighted snippets
result = await client.search('articles', 'python',
    SearchOptions(highlight=HighlightOptions(
        open_tag='<mark>', close_tag='</mark>',
        snippet_len=150, max_fragments=3,
    )))
for r in result.results:
    print(r.primary_key, r.snippet)

# Facet aggregation
facets = await client.facet('articles', 'category',
    FacetOptions(query='python', limit=10))
for v in facets.results:
    print(f'{v.value}: {v.count}')

Type Hints

Full type definitions are included:

from mygramdb_client import (
    ClientConfig,
    SearchResponse,
    CountResponse,
    Document,
    ServerInfo,
    SearchOptions,
    DumpStatus,
    CacheStats,
)

Development

rye sync              # Install dependencies
rye run pytest        # Run tests
rye run pytest -v     # Run tests (verbose)
rye run flake8 src tests  # Lint

License

MIT