FIX: align draw's Python size dispatch with the jitted path (#918)

[mmcky]

Aligns the Python size dispatch in quantecon.random.draw with the jitted path. Replaces #919, which was closed with thanks; this is the reduced form of the same fix.

The bug

draw decides between "an array of size draws" and "one scalar draw" in two places, with two tests that do not agree:

Path	Test
Pure Python body	isinstance(size, int)
@overload implementation	isinstance(size, types.Integer)

A NumPy integer is not a Python int but is a types.Integer, so the same call returns different things depending on whether the call site is jit-compiled — and nothing warns. This is easy to hit: size arrives as np.int64 from any ordinary numpy expression (counts[i], arr.sum(), arr.argmax(), a // on an array), while len(x) and arr.shape[0] give Python ints and are fine, which is why it survives casual testing.

The change

One line in the Python body:

if isinstance(size, (int, np.integer)):

A bool size is not a supported input and is out of scope: NumPy rejects random(True) on the Python path, as it does today, and the jitted path is unchanged.

The @overload needs no change. types.Boolean is not a subclass of types.Integer, so the jitted path already dispatches every case correctly — only the Python body was wrong.

Verified

Dispatch table on this branch, Python against jitted, for every case in #918:

size	Python	Jitted
10	array(10,)	array(10,)	agree
np.int64(10)	array(10,)	array(10,)	agree
np.int32(10)	array(10,)	array(10,)	agree
np.uint8(10)	array(10,)	array(10,)	agree
10.0	scalar	scalar	agree
None	scalar	scalar	agree

None was checked across all four call shapes — omitted and explicit, from Python and from a jitted caller — since _is_no_rng shows Numba spells "no value" more than one way.

• Full suite: 679 passed
• flake8 --select=F401,F405,E231 quantecon: clean
• git diff --check: clean

Release note needed

draw(cdf, np.int64(10)) now returns ten draws from Python where it previously returned one scalar. That is what the caller asked for, and what jitted callers already received, but it is a silent behaviour change and should be called out in the next release's notes. Per AGENTS.md there is no per-PR changelog entry to add.

Closes #918. Replaces #919.

🤖 Generated with Claude Code

[Copilot]

🟡 Changes recommended

A regression test for the size=True / np.bool_(True) scalar-dispatch case is still missing even though the change explicitly addresses that edge case.

Once you've addressed the issues Copilot identified, you can request another Copilot review.

Pull request overview

This PR fixes an inconsistency in quantecon.random.draw where the pure-Python implementation treated size=np.int64(10) as a scalar draw, while the Numba-jitted overload treated it as an array-sized draw, leading to divergent return types depending on whether the caller was jit-compiled.

Changes:

• Update the pure-Python draw size-dispatch predicate to accept NumPy integer scalars (and explicitly exclude bool) so it matches the @overload dispatch behavior.
• Add a regression test asserting NumPy-integer size requests an array return for both Python and jitted call paths.

File summaries

File	Description
quantecon/random/utilities.py	Align pure-Python size dispatch with the Numba overload by accepting np.integer (excluding bool).
quantecon/random/tests/test_utilities.py	Add regression coverage ensuring NumPy integer size returns an array on both call paths.

Review details

• Files reviewed: 2/2 changed files
• Comments generated: 1
• Review effort level: Lite

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[coveralls]

coverage: 94.088% (+3.2%) from 90.884% — fix/draw-numpy-integer-size-918 into main

[oyamad]

Here's my thought: I wouldn't make (the Python version of) draw(cdf, size=True) return any value. As I stated in #917 (comment), we should only fix the bug I had introduced, keeping the behavior of the Python version "unspecified" or "unsupported" (the @overload is the contract). And thus I wouldn't add any new test.