Python object index for fast, declarative retrieval
Project description
odex
Python object index for fast, declarative retrieval
Install
pip install odex
Usage
Odex provides a set-like collection called IndexedSet
:
from odex import IndexedSet, attr, and_
class X:
def __init__(self, a, b):
self.a = a
self.b = b
iset = IndexedSet(
[
X(a=1, b=4),
X(a=2, b=5),
X(a=2, b=6),
X(a=3, b=7),
],
indexes=["a"]
)
# Filter objects with SQL-like expressions:
iset.filter("a = 2 AND b = 5") == {X(a=2, b=5)}
# Or, using the fluent interface:
iset.filter(
and_(
attr("a").eq(2),
attr("b").eq(5)
)
) == {X(a=2, b=5)}
IndexedSet
maintains indexes on the given attributes. There are three index types:
HashIndex
- based ondict
. Only supports exact value queries (e.g.a = 1
).SortedDictIndex
- based on Sorted Containers. Supports exact value and range queries (e.g.a > 1
), but has slower updates.InvertedIndex
- based ondict
, but supports collection attributes and queries like'foo' IN tags
When attribute names are given as indexes, the index type will be inferred from the given objects. Otherwise, explicit indexes can be given.
Related projects
Benchmarks
See comparisons.ipynb for more.
Project details
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