pocketsearch 0.30.0

Description:

pocketsearch 0.30.0

pocketsearch
pocketsearch is a pure-Python full text indexing search library based on SQLite and the FTS5 extension. It provides

A simple API (inspired by the ORM layer of the Django web framework) for defining schemas and searching - no need to write SQL
Multi-field indices using schemas including text, numeric and date/datetime search
Prefix, phrase and initial token queries
Spell checking
Boolean search queries
Highlightning search results and extracting snippets
Autocomplete features

Pocketsearch does not have any dependencies other than Python (3.8 or higher) itself.
Quick start
Install using PIP:
pip install pocketsearch

Create a search index using a PocketWriter and store it to database my_db.db:
import pocketsearch
with pocketsearch.PocketWriter(db_name="my_db.db") as pocket_writer:
pocket_writer.insert(text="Hello world")

Open the search index using a PocketReader to perform searches:
import pocketsearch
with pocketsearch.PocketReader(db_name="my_db.db") as pocket_reader:
for result in pocket_reader.search(text="Hello world"):
print(result.text)

You can define custom schemas to create multi-field indices:
import pocketsearch as ps

class Product(ps.Schema):

price = ps.Int()
description = ps.Text(index=True) # part of full text (FT) index
category = ps.Text() # not part of FT index

with ps.PocketWriter(db_name="my_db.db",schema=Product) as pocket_writer:
pocket_writer.insert(description="Apple",category="Fruit",price=3.21)
pocket_writer.insert(description="Orange",category="Fruit",price=4.11)

with ps.PocketReader(db_name="my_db.db",schema=Product) as pocket_reader:
# Search for products with a price greater than or equal 3:
print(pocket_reader.search(price__gte=3).count())

Read the complete documentation at https://pocketsearch.readthedocs.io/
Use cases
pocketsearch is intended for projects looking for a server-less, seamless integration into existing Python projects with low to medium-sized document collections.
Please refer to https://github.com/kaykay-dv/pocketsearch/tree/main/tests/DCEP to see how pocketsearch can be used to index more than 160,000 documents.
Status
The package is currently in Beta status.