Python object index for fast, declarative retrieval

pip install odex

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)
    )
)

IndexedSet maintains indexes on the given attributes. There are three index types:

• HashIndex - based on dict. 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 on dict, 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.

• sqlglot - odex uses sqlglot for expression parsing
• ducks - similar project with different tradeoffs

See comparisons.ipynb for more.