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GeezerVison is showing github.com — Test the from_networkx int32 widening and correct its coverage claim by eriknw · Pull Request #618 · python-graphblas/python-graphblas Conversation
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Stacked on #617. Overnight review of the late CI-stabilization commits found that the int32-to-int64 widening in The widening is deliberate and kept: import numpy as np, networkx as nx, graphblas as gb G = nx.DiGraph() G.add_weighted_edges_from([(0, 1, np.int32(2)), (1, 0, np.int32(3))]) gb.io.from_networkx(G).dtype # INT64 (was INT32 via scipy) gb.Matrix.from_coo([0, 1], [1, 0], [np.int32(2), np.int32(3)]).dtype # INT64, and always was This PR drops the false pragma, restates the comment in terms of the real contract, and pins the behavior with tests: int32 weights widen and agree with Release-note item: the
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The widening added while stabilizing CI was marked "pragma: no cover (win64 numpy < 2)", but the branch is reachable on every platform: np.int32 scalar edge weights infer an int32 array from the edge sequence anywhere, not only where python ints do. The pragma therefore hid live code from coverage, and the comment implied the change was platform-local when it is user-visible everywhere: int32-weighted graphs that previously round-tripped through scipy as INT32 now come back INT64. The widening itself is kept, deliberately. from_coo widens an int32 dtype inferred from sequence input to int64 on every platform (values_to_numpy_buffer), and from_networkx builds its values from a Python sequence, so identical weights now produce the same dtype through either constructor. Gating the widening to win64 instead would have re-introduced a from_coo/from_networkx disagreement everywhere else. Drop the pragma, restate the comment in terms of the real contract, and pin the behavior: np.int32 weights widen to INT64 and agree with from_coo, an explicit dtype= is preserved exactly, and np.int16 stays INT16 through both constructors. Release-note item: the from_networkx result dtype for int32-weighted graphs changes from INT32 to INT64.
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