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__dask_keys__ and future identifiers are different

Aperta
#952 1 commento 0 reazioni 0 assegnatari Vedi su GitHub

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Valutazione

Difficoltà
4/5
Tempo stimato
3-5 giorni
Idoneità per principianti
25/100
Tipo di issue
Bug
Chiarezza
Da chiarire
Stato di attività
Ferma
Stack tecnologico
python

Direzione di ricerca

Inizia da distributed/tests/test_client.py::test_futures_of_sorted e riproduci la discrepanza tra df.dask_keys() e le futures restituite, usando come contesto il fallimento della pull request 8560 di distributed. L’issue è completata quando gli identificatori corrispondono e il test passa senza modificare l’ordinamento previsto.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

When trying to fix dask/distributed test_client.py::test_futures_of_sorted

FAILED distributed/tests/test_client.py::test_futures_of_sorted - assert "('make-f63ce8128ed27f9b78bb64e3022a83de', 0)" in "<Future: finished, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-3bf19a79288c09d4910e4b935d098e2f', 0)>"

  • where "('make-f63ce8128ed27f9b78bb64e3022a83de', 0)" = str(('make-f63ce8128ed27f9b78bb64e3022a83de', 0))
  • and "<Future: finished, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-3bf19a79288c09d4910e4b935d098e2f', 0)>" = str(<Future: finished, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-3bf19a79288c09d4910e4b935d098e2f', 0)>)

They appear to be in order, but not the same identifiers.

Full comparison
(Pdb) for k, f in zip(df.__dask_keys__(), futures): print(f"{k}: {f}")
('make-4e59f4c2ced9ebff091a04c75ccf9098', 0): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 0)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 1): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 1)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 2): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 2)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 3): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 3)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 4): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 4)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 5): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 5)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 6): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 6)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 7): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 7)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 8): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 8)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 9): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 9)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 10): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 10)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 11): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 11)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 12): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 12)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 13): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 13)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 14): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 14)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 15): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 15)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 16): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 16)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 17): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 17)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 18): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 18)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 19): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 19)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 20): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 20)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 21): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 21)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 22): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 22)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 23): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 23)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 24): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 24)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 25): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 25)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 26): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 26)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 27): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 27)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 28): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 28)>
('make-4e59f4c2ced9ebff091a04c75ccf9098', 29): <Future: cancelled, type: pandas.core.frame.DataFrame, key: ('make-_to_string_dtype-474ddedf4ce10dae4694a89a3318c0e0', 29)>

xref: https://github.com/dask/distributed/pull/8560

Lingua principale
Python
Stelle
89
Fork
26
Metriche di merge delle PR
Nessuna PR unita negli ultimi 30g

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