id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,pull_request,body,repo,type,active_lock_reason,performed_via_github_app,reactions,draft,state_reason
797159961,MDExOlB1bGxSZXF1ZXN0NTY0MjE1MDEx,225,fix for problem in Table.insert_all on search for columns per chunk of rows,261237,closed,0,,,2,2021-01-29T20:16:07Z,2021-02-14T21:04:13Z,2021-02-14T21:04:13Z,NONE,simonw/sqlite-utils/pulls/225,"Hi,

I ran into a problem when trying to create a database from my Apple Healthkit data using [healthkit-to-sqlite](https://github.com/dogsheep/healthkit-to-sqlite). The program crashed because of an invalid insert statement that was generated for table `rDistanceCycling`. 

The actual problem turned out to be in [sqlite-utils](https://github.com/simonw/sqlite-utils). `Table.insert_all` processes the data to be inserted in chunks of rows and checks for every chunk which columns are used, and it will collect all column names in the variable `all_columns`.  The collection of columns is done using a nested list comprehension that is not completely correct. 

I'm using a Windows machine and had to make a few adjustments to the tests in order to be able to run them because they had a posix dependency.

Thanks, kind regards,

Frans

```
# this is a (condensed) chunk of data from my Apple healthkit export that caused the problem.
# the 3 last items in the chunk have additional keys: metadata_HKMetadataKeySyncVersion and metadata_HKMetadataKeySyncIdentifier

chunk = [{'sourceName': 'AppleÂ\xa0Watch van Frans', 'sourceVersion': '7.0.1',
          'device': '<<HKDevice: 0x281cf6c70>, name:Apple Watch, manufacturer:Apple Inc., model:Watch, hardware:Watch3,4, software:7.0.1>',
          'unit': 'km', 'creationDate': '2020-10-10 12:29:09 +0100', 'startDate': '2020-10-10 12:29:06 +0100',
          'endDate': '2020-10-10 12:29:07 +0100', 'value': '0.00518016'},
         {'sourceName': 'AppleÂ\xa0Watch van Frans', 'sourceVersion': '7.0.1',
          'device': '<<HKDevice: 0x281cf6c70>, name:Apple Watch, manufacturer:Apple Inc., model:Watch, hardware:Watch3,4, software:7.0.1>',
          'unit': 'km', 'creationDate': '2020-10-10 12:29:10 +0100', 'startDate': '2020-10-10 12:29:07 +0100',
          'endDate': '2020-10-10 12:29:08 +0100', 'value': '0.00544049'},
         {'sourceName': 'AppleÂ\xa0Watch van Frans', 'sourceVersion': '6.2.6',
          'device': '<<HKDevice: 0x281cf83e0>, name:Apple Watch, manufacturer:Apple Inc., model:Watch, hardware:Watch3,4, software:6.2.6>',
          'unit': 'km', 'creationDate': '2020-10-14 05:54:12 +0100', 'startDate': '2020-07-15 16:40:50 +0100',
          'endDate': '2020-07-15 16:42:49 +0100', 'value': '0.952092', 'metadata_HKMetadataKeySyncVersion': '1',
          'metadata_HKMetadataKeySyncIdentifier': '3:674DBCDB-3FE8-40D1-9FC1-E54A2B413805:616520450.99823:616520569.99360:119'},
         {'sourceName': 'AppleÂ\xa0Watch van Frans', 'sourceVersion': '6.2.6',
          'device': '<<HKDevice: 0x281cf83e0>, name:Apple Watch, manufacturer:Apple Inc., model:Watch, hardware:Watch3,4, software:6.2.6>',
          'unit': 'km', 'creationDate': '2020-10-14 05:54:12 +0100', 'startDate': '2020-07-15 16:42:49 +0100',
          'endDate': '2020-07-15 16:44:51 +0100', 'value': '0.848983', 'metadata_HKMetadataKeySyncVersion': '1',
          'metadata_HKMetadataKeySyncIdentifier': '3:674DBCDB-3FE8-40D1-9FC1-E54A2B413805:616520569.99360:616520691.98826:119'},
         {'sourceName': 'AppleÂ\xa0Watch van Frans', 'sourceVersion': '6.2.6',
          'device': '<<HKDevice: 0x281cf83e0>, name:Apple Watch, manufacturer:Apple Inc., model:Watch, hardware:Watch3,4, software:6.2.6>',
          'unit': 'km', 'creationDate': '2020-10-14 05:54:12 +0100', 'startDate': '2020-07-15 16:44:51 +0100',
          'endDate': '2020-07-15 16:46:50 +0100', 'value': '0.834403', 'metadata_HKMetadataKeySyncVersion': '1',
          'metadata_HKMetadataKeySyncIdentifier': '3:674DBCDB-3FE8-40D1-9FC1-E54A2B413805:616520691.98826:616520810.98305:119'}]



def all_columns_old():
    all_columns = [col for col in chunk[0]]
    all_columns += [column for record in chunk
                           for column in record if column not in all_columns]
    return all_columns


def all_columns_new():
    all_columns = [col for col in chunk[0]]
    for record in chunk:
        all_columns += [column for column in record if column not in all_columns]
    return all_columns



if __name__ == '__main__':
    from pprint import pprint

    print('problem: ')
    pprint(all_columns_old())
    print('\nfix: ')
    pprint(all_columns_new())

```
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