Cdict
a small library for combinatorial iters of dicts, useful for config/hyperparameter sweep management
Install / Use
/learn @WuTheFWasThat/CdictREADME
cdict
This is a small library for creating iterators of dictionaries combinatorially, for config/hyperparameter sweep management.
Installation
pip install cdict
Usage
Basic features and primitives
The basic unit in cdict is essentially a stream of dictionaries (Iterable[dict]). We then have two main operations:
x + y concatenates (includes dictionaries in x and then dictionaries in y), much like list addition
import cdict as C
# setup
a1 = C.dict(a=1)
assert list(a1) == [dict(a=1)]
a2 = C.dict(a=2)
assert list(a2) == [dict(a=2)]
# "add" cdicts by union-ing the set of dicts
sweep_a = a1 + a2
assert list(sweep_a) == [dict(a=1), dict(a=2)]
# equivalent way to add
sweep_a = C.sum(C.dict(a=a) for a in [1,2])
assert list(sweep_a) == [dict(a=1), dict(a=2)]
# a convenience
sweep_a = C.dict(a=C.list(1, 2))
assert list(sweep_a) == [dict(a=1), dict(a=2)]
</details>
</li>
<li>
x * y does an outer product (includes dictionaries formed by combining all pairs of dictionaries from x and y)
import cdict as C
# setup
sweep_a = C.dict(a=C.list(1, 2))
assert list(sweep_a) == [dict(a=1), dict(a=2)]
sweep_b = C.dict(b=C.list(1,2))
assert list(sweep_b) == [dict(b=1), dict(b=2)]
# "multiply" cdicts by combinatorially combining all possibilities
sweep_ab = sweep_a * sweep_b
assert list(sweep_ab) == [
dict(a=1, b=1), dict(a=1, b=2),
dict(a=2, b=1), dict(a=2, b=2),
]
# a convenience
sweep_ab = C.dict(
a=C.list(1, 2),
b=C.list(1, 2),
)
assert list(sweep_ab) == [
dict(a=1, b=1), dict(a=1, b=2),
dict(a=2, b=1), dict(a=2, b=2),
]
</details>
</li>
</ul>
These two basic operations can be composed arbitrarily, and behave as you would expect!
<details><summary>Example</summary>import cdict as C
sweep_a = C.dict(a=C.list(1, 2))
assert list(sweep_a) == [dict(a=1), dict(a=2)]
sweep_b = C.dict(b=C.list(1,2))
assert list(sweep_b) == [dict(b=1), dict(b=2)]
# add and multiply all you want
baseline = C.dict(a=0, b=0)
sweep_z = C.dict(z=1) + C.dict(z=2)
sweep_complex = (sweep_a + sweep_z) * sweep_b + baseline
assert list(sweep_complex) == [
dict(a=1, b=1), dict(a=1, b=2),
dict(a=2, b=1), dict(a=2, b=2),
dict(z=1, b=1), dict(z=1, b=2),
dict(z=2, b=1), dict(z=2, b=2),
dict(a=0, b=0),
]
# equivalent, thanks to left-distributive property
sweep_complex_2 = sweep_a * sweep_b + sweep_z * sweep_b + baseline
assert list(sweep_complex_2) == list(sweep_complex)
</details>
Note that cdicts are lazy.
import cdict as C
# avoid lists if needed, for memory efficiency
sweep_lazy = C.dict(a=C.iter(range(1, 3)), b=C.iter(range(1, 3)))
it = iter(sweep_lazy)
assert next(it) == dict(a=1, b=1)
assert next(it) == dict(a=1, b=2)
assert next(it) == dict(a=2, b=1)
assert next(it) == dict(a=2, b=2)
</details>
Other features include:
<ul> <li>customizable combining behavior, gives user control over conflict resolution (allowing vs disallow override)
<details><summary>Example</summary>import pytest
import cdict as C
# conflicting keys errors by default
a1 = C.dict(a=1)
a2 = C.dict(a=2)
with pytest.raises(ValueError):
list(a1 * a2)
# you can use overridable to change this behavior
a1 = C.dict(a=C.overridable(1))
a2 = C.dict(a=2)
assert list(a1 * a2) == [dict(a=2)]
with pytest.raises(ValueError):
# order matters - a2 isn't overridable
list(a2 * a1)
# overridable is just one special case of combining conflicting keys
joinstr = C.combiner(lambda x, y: f"{x}.{y}")
s1 = C.sum(C.dict(a=a, uid=joinstr(f"a{a}")) for a in [1, 2])
s2 = C.sum(C.dict(b=b, uid=joinstr(f"b{b}")) for b in [1, 2])
assert list(s1 * s2) == [
dict(a=1, b=1, uid="a1.b1"),
dict(a=1, b=2, uid="a1.b2"),
dict(a=2, b=1, uid="a2.b1"),
dict(a=2, b=2, uid="a2.b2"),
]
# Under the hood, override and combiner work by cdict_combine lets you override that behavior!
# You can actually multiply lists of anything, as long as they implement cdict_combine.
# Here's a more explicit implementation of joinstr
class joinstr(str):
def cdict_combine(self, other):
return joinstr(f"{self}.{other}")
s = C.sum(joinstr(f"a{i}") for i in range(1, 3)) * C.sum(joinstr(f"b{i}") for i in range(1, 3))
assert list(s) == ["a1.b1", "a1.b2", "a2.b1", "a2.b2"]
# Yet another implementation that doesn't subclass string
# cdict_item lets you control what cdict iteration yields
class joinstr():
def __init__(self, s: str):
self.s = s
def cdict_combine(self, other):
return joinstr(f"{self.s}.{other.s}")
def cdict_item(self):
return self.s
s = C.sum(joinstr(f"a{i}") for i in range(1, 3)) * C.sum(joinstr(f"b{i}") for i in range(1, 3))
assert list(s) == ["a1.b1", "a1.b2", "a2.b1", "a2.b2"]
# C.defaultdict also provides a convenience for having everything be overridable
defaults = C.defaultdict(a=1, b=1)
a2 = C.dict(a=2)
assert list(defaults * a2) == [dict(a=2, b=1)]
assert list(defaults * defaults * a2) == [dict(a=2, b=1)]
with pytest.raises(ValueError):
# defaults don't override
list(a2 * defaults)
with pytest.raises(ValueError):
# can't override twice
list(defaults * a2 * a2)
</details>
</li>
<li>
nesting of cdicts
import pytest
import cdict as C
###############################################################################
# Nesting, basics
###############################################################################
# You can nest cdicts, to get lists of nested dicts.
# This is useful if you have nested configuration
sweep_nested = C.dict(
nested_a=C.dict(a=1) + C.dict(a=2),
nested_b=C.dict(b=1) + C.dict(b=2),
)
assert list(sweep_nested) == [
dict(nested_a=dict(a=1), nested_b=dict(b=1)),
dict(nested_a=dict(a=1), nested_b=dict(b=2)),
dict(nested_a=dict(a=2), nested_b=dict(b=1)),
dict(nested_a=dict(a=2), nested_b=dict(b=2)),
]
# Multiplying nested cdicts acts as expected
sweep_nested_2 = C.dict(
nested_a=C.dict(a=1) + C.dict(a=2),
) * C.dict(
nested_b=C.dict(b=1) + C.dict(b=2),
)
assert list(sweep_nested_2) == list(sweep_nested)
###############################################################################
# Nesting convenience syntax
###############################################################################
# "nested" syntax for adding
sweep_a = C.dict(a=C.list(1,2))
assert list(sweep_a) == [dict(a=1), dict(a=2)]
sweep_b = C.dict(b=C.list(1,2))
assert list(sweep_b) == [dict(b=1), dict(b=2)]
# "nested" multiply
sweep_ab = C.dict(a=C.list(1, 2), b=C.list(1, 2))
assert list(sweep_ab) == [
dict(a=1, b=1), dict(a=1, b=2),
dict(a=2, b=1), dict(a=2, b=2),
]
###############################################################################
# Nesting and conflicts
###############################################################################
# you can multiply within nesting (under the hood, because cdicts' items implement cdict_combine by default!)
nested_sweep = (
C.dict(nested=C.dict(a=C.list(1, 2))) *
C.dict(nested=C.dict(b=C.list(1, 2)))
)
assert list(nested_sweep) == [
dict(nested=dict(a=1, b=1)),
dict(nested=dict(a=1, b=2)),
dict(nested=dict(a=2, b=1)),
dict(nested=dict(a=2, b=2)),
]
# to change that behavior, use finaldict (yields normal dicts that don't implement cdict_combine)
nested_sweep_fail = (
C.dict(nested=C.finaldict(a=C.list(1, 2))) *
C.dict(nested=C.dict(b=C.list(1, 2)))
)
with pytest.raises(ValueError):
list(nested_sweep_fail)
# ordering matters for declaring finality
nested_sweep_success = (
C.dict(nested=C.dict(a=C.list(1, 2))) *
C.dict(nested=C.finaldict(b=C.list(1, 2)))
)
assert list(nested_sweep_success) == list(nested_sweep)
# also fails with objects that don't implement cdict_combine
nested_sweep_fail_2 = C.dict(nested=C.dict(a=1)) * C.dict(nested=C.dict(a=2))
with pytest.raises(ValueError):
list(nested_sweep_fail_2)
# since the outer dict isn't final, separate keys is fine even with final values
nested_sweep_nonconflict = (
C.dict(nested_a=C.finaldict(a=C.list(1, 2))) *
C.dict(nested_b=C.finaldict(b=C.list(1, 2)))
)
assert list(nested_sweep_nonconflict) == list(sweep_nested)
</details>
</li>
<li>
transforms
<details><summary>Example</summary>import cdict as C
sweep_ab = C.dict(
a=C.list(1, 2), b=C.list(1, 2),
)
# transform with map
def square_a(x):
x['aa'] = x['a']**2
return x
sweep_squares = sweep_ab.map(square_a)
assert list(sweep_squares) == [
dict(a=1, aa=1, b=1),
dict(a=1, aa=1, b=2),
dict(a=2, aa=4, b=1),
dict(a=2, aa=4, b=2),
]
# or filter!
sweep_squares_filtered = sweep_squares.filter(lambda d: d['aa'] != d['b'])
assert list(sweep_squares_filtered) == [
dict(a=1, aa=1, b=2),
dict(a=2, aa=4, b=1),
dict(a=2, aa=4, b=2),
]
# more general transforms with apply
def add_seeds(x):
for i in range(2):
yield dict(aab=x['aa'] * x['b'], seed=x['a'] * 100 + x['b'] * 10 + i)
sweep_squares_filtered_seeded = sweep_squares_filtered.apply(add_seeds)
assert list(sweep_squares_filtered_seeded) == [
dict(aab=2, seed=120), dict(aab=2, seed=121),
dict(aab=4, seed=210), dict(aab=4, seed=211),
dict(aab=8, seed=220), dict(aab=8, seed=221),
]
</details>
</li>
<li>
a "zip" operation | which does an elementwise product of cdicts of equal length
import pytest
import cdict as C
sweep_a = C.dict(a=C.list(1, 2))
assert list(sweep_a) == [dict(a=1), dict(a=2)]
sweep_b = C.dict(b=C.list(1,2))
assert list(sweep_b) == [dict(b=1), dict(b=2)]
# zipping of equal length things
diag_sweep = sweep_a | sweep_b
assert list(diag_sweep) == [
dict(a=1, b=1), dict(a=2, b=2),
]
</details>
</li>
</ul>
Properties
cdict combinators have some
