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| 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 |
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| 771608692 | MDU6SXNzdWU3NzE2MDg2OTI= | 14 | UNIQUE constraint failed: workouts.id | n8henrie 1234956 | open | 0 | 5 | 2020-12-20T15:11:20Z | 2023-07-10T14:46:52Z | NONE | I'm getting an error on my initial attempt to import data:
|
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| 1515883470 | I_kwDOC8tyDs5aWovO | 24 | DOC: xml.etree.ElementTree.ParseError due to healthkit version 12 | mmngreco 6231413 | open | 0 | 2 | 2023-01-01T23:00:38Z | 2023-03-30T10:17:31Z | NONE | Hi @simonw I hope you find this issue ok, the idea is provide some documentation to other users like me about how to solve this problem and save some time. Following the instructions from the
So, after debugging and searching on internet I found this useful link: https://discussions.apple.com/thread/254202523 (etresoft, the real hero). Which basically says that the xml given by the health app (healthkit version 12) has some bugs but fortunately, they can be solved with a couple of commads:
|
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| 1515717718 | PR_kwDOC8tyDs5Gc-VH | 23 | Include workout statistics | badboy 2129 | open | 0 | 0 | 2023-01-01T17:29:57Z | 2023-01-01T17:29:57Z | FIRST_TIME_CONTRIBUTOR | dogsheep/healthkit-to-sqlite/pulls/23 | Not sure when this changed (iOS 16 maybe?), but the Adding it as another column at leat allows me to pull these out (using SQLite's JSON support). I'm running with this patch on my own data now. |
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| 727848625 | MDU6SXNzdWU3Mjc4NDg2MjU= | 12 | Some workout columns should be float, not text | simonw 9599 | open | 0 | 4 | 2020-10-23T02:47:02Z | 2022-06-23T04:35:02Z | MEMBER | Columns |
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| 743071410 | MDExOlB1bGxSZXF1ZXN0NTIxMDU0NjEy | 13 | SQLite does not have case sensitive columns | tomaskrehlik 1689944 | open | 0 | 1 | 2020-11-14T20:12:32Z | 2021-08-24T13:28:26Z | FIRST_TIME_CONTRIBUTOR | dogsheep/healthkit-to-sqlite/pulls/13 | This solves a weird issue when there is record with metadata key that is only different in letter cases. See the test for details. |
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| 978086284 | MDExOlB1bGxSZXF1ZXN0NzE4NzM0MTkx | 22 | Make sure that case-insensitive column names are unique | FabianHertwig 32016596 | open | 0 | 1 | 2021-08-24T13:13:38Z | 2021-08-24T13:26:20Z | FIRST_TIME_CONTRIBUTOR | dogsheep/healthkit-to-sqlite/pulls/22 | This closes #21. When there are metadata entries with the same case insensitive string, then there is an error when trying to create a new column for that metadata entry in the database table, because a column with that case insensitive name already exists.
The code added in this PR checks if a key already exists in a record and if so adds a number at its end. The resulting column names look like the example below then. Interestingly, the column names viewed with Datasette are not case insensitive.
|
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| 977128935 | MDU6SXNzdWU5NzcxMjg5MzU= | 21 | Duplicate Column | FabianHertwig 32016596 | open | 0 | 1 | 2021-08-23T15:00:44Z | 2021-08-23T17:00:59Z | NONE | Hey, thank you for this repo! When I try to convert my export, I get a multiple column error. Here is the stack trace:
|
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| 975166271 | MDU6SXNzdWU5NzUxNjYyNzE= | 20 | Add index on workout_points.date | simonw 9599 | open | 0 | 2 | 2021-08-20T01:08:04Z | 2021-08-20T01:12:48Z | MEMBER | Sorting that by date makes sense for seeing most recent points, and my DB has 2.5m points in so it's an expensive sort! |
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| 975158266 | MDU6SXNzdWU5NzUxNTgyNjY= | 19 | table activity_summary has no column named appleMoveTime | simonw 9599 | closed | 0 | 0 | 2021-08-20T00:46:44Z | 2021-08-20T00:54:34Z | 2021-08-20T00:54:34Z | MEMBER | Got this error today against a fresh export: |
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| 836064851 | MDExOlB1bGxSZXF1ZXN0NTk2NjI3Nzgw | 18 | Add datetime parsing | n8henrie 1234956 | open | 0 | 0 | 2021-03-19T14:34:22Z | 2021-03-19T14:34:22Z | FIRST_TIME_CONTRIBUTOR | dogsheep/healthkit-to-sqlite/pulls/18 | Parses the datetime columns so they are subsequently properly recognized as datetime. Fixes https://github.com/dogsheep/healthkit-to-sqlite/issues/17 |
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| 836063389 | MDU6SXNzdWU4MzYwNjMzODk= | 17 | Datetime columns are not properly formatted to be recognizes as datetime | n8henrie 1234956 | open | 0 | 0 | 2021-03-19T14:33:04Z | 2021-03-19T14:33:04Z | NONE | Currently, the datetimes are formatted in a way that is not recognized by datasette-vega for plotting with a For example, if you have datasette running locally with
The plot is blank unless you choose The If instead the format for this column is changed slightly: I have a PR that addresses this issue, will submit shortly. |
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| 830901133 | MDExOlB1bGxSZXF1ZXN0NTkyMzY0MjU1 | 16 | Add a fallback ID, print if no ID found | n8henrie 1234956 | open | 0 | 0 | 2021-03-13T13:38:29Z | 2021-03-13T14:44:04Z | FIRST_TIME_CONTRIBUTOR | dogsheep/healthkit-to-sqlite/pulls/16 | healthkit-to-sqlite 197882382 | pull | {
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| 793907673 | MDExOlB1bGxSZXF1ZXN0NTYxNTEyNTAz | 15 | added try / except to write_records | ryancheley 9857779 | open | 0 | 0 | 2021-01-26T03:56:21Z | 2021-01-26T03:56:21Z | FIRST_TIME_CONTRIBUTOR | dogsheep/healthkit-to-sqlite/pulls/15 | to keep the data write from failing if it came across an error during processing. In particular when trying to convert my HealthKit zip file (and that of my wife's) it would consistently error out with the following: ``` db.py 1709 insert_chunk result = self.db.execute(query, params) db.py 226 execute return self.conn.execute(sql, parameters) sqlite3.OperationalError: too many SQL variables db.py 1709 insert_chunk result = self.db.execute(query, params) db.py 226 execute return self.conn.execute(sql, parameters) sqlite3.OperationalError: too many SQL variables db.py 1709 insert_chunk result = self.db.execute(query, params) db.py 226 execute return self.conn.execute(sql, parameters) sqlite3.OperationalError: table rBodyMass has no column named metadata_HKWasUserEntered healthkit-to-sqlite 8 <module> sys.exit(cli()) core.py 829 call return self.main(args, *kwargs) core.py 782 main rv = self.invoke(ctx) core.py 1066 invoke return ctx.invoke(self.callback, **ctx.params) core.py 610 invoke return callback(args, *kwargs) cli.py 57 cli convert_xml_to_sqlite(fp, db, progress_callback=bar.update, zipfile=zf) utils.py 42 convert_xml_to_sqlite write_records(records, db) utils.py 143 write_records db[table].insert_all( db.py 1899 insert_all self.insert_chunk( db.py 1720 insert_chunk self.insert_chunk( db.py 1720 insert_chunk self.insert_chunk( db.py 1714 insert_chunk result = self.db.execute(query, params) db.py 226 execute return self.conn.execute(sql, parameters) sqlite3.OperationalError: table rBodyMass has no column named metadata_HKWasUserEntered ``` Adding the try / except in the |
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| 723838331 | MDU6SXNzdWU3MjM4MzgzMzE= | 11 | export.xml file name varies with different language settings | jarib 572 | closed | 0 | 7 | 2020-10-17T20:07:18Z | 2020-10-17T21:39:15Z | 2020-10-17T21:14:10Z | NONE | The XML file exported from my phone has a Norwegian file name – I can work around this by unpacking the zip and using Perhaps this could be solved by |
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| 519038979 | MDU6SXNzdWU1MTkwMzg5Nzk= | 10 | Failed to import workout points | simonw 9599 | closed | 0 | 4 | 2019-11-07T04:50:22Z | 2019-11-08T01:18:37Z | 2019-11-08T01:18:37Z | MEMBER | I just ran the script and it failed to import any |
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| 472429048 | MDU6SXNzdWU0NzI0MjkwNDg= | 9 | Too many SQL variables | tholo 166463 | closed | 0 | 4 | 2019-07-24T18:24:17Z | 2019-07-26T10:01:05Z | 2019-07-26T10:01:05Z | NONE | Decided to try importing my data, and ran into this:
Added some debug output in sqlite_utils/db.py, which resulted in:
with the attached data:
|
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| 472097220 | MDU6SXNzdWU0NzIwOTcyMjA= | 7 | Script uses a lot of RAM | simonw 9599 | closed | 0 | 3 | 2019-07-24T06:11:11Z | 2019-07-24T06:35:52Z | 2019-07-24T06:35:52Z | MEMBER | I'm using an XML pull parser which should avoid the need to slurp the whole XML file into memory, but it's not working - the script still uses over 1GB of RAM when it runs according to Activity Monitor. I think this is because I'm still causing the full root element to be incrementally loaded into memory just in case I try and access it later. http://effbot.org/elementtree/iterparse.htm says I should use
So I will try that recipe and see if it helps. |
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| 472104705 | MDExOlB1bGxSZXF1ZXN0MzAwNTgwMjIx | 8 | Use less RAM | simonw 9599 | closed | 0 | 0 | 2019-07-24T06:35:01Z | 2019-07-24T06:35:52Z | 2019-07-24T06:35:52Z | MEMBER | dogsheep/healthkit-to-sqlite/pulls/8 | Closes #7 |
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| 470691622 | MDU6SXNzdWU0NzA2OTE2MjI= | 5 | Add progress bar | simonw 9599 | closed | 0 | 2 | 2019-07-20T16:29:07Z | 2019-07-22T03:30:13Z | 2019-07-22T02:49:22Z | MEMBER | Showing a progress bar would be nice, using Click. The easiest way to do this would probably be be to hook it up to the length of the compressed content, and update it as this code pushes more XML bytes through the parser: |
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| 470856782 | MDU6SXNzdWU0NzA4NTY3ODI= | 6 | Break up records into different tables for each type | simonw 9599 | closed | 0 | 1 | 2019-07-22T01:54:59Z | 2019-07-22T03:28:55Z | 2019-07-22T03:28:50Z | MEMBER | I don't think there's much benefit to having all of the different record types stored in the same enormous table. Here's what I get when I use
I'm going to try splitting these up into separate tables - so |
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| 470637152 | MDU6SXNzdWU0NzA2MzcxNTI= | 2 | Import workouts | simonw 9599 | closed | 0 | 1 | 2019-07-20T05:20:21Z | 2019-07-20T06:21:41Z | 2019-07-20T06:21:41Z | MEMBER | From #1 |
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| 470640505 | MDU6SXNzdWU0NzA2NDA1MDU= | 4 | Import Records | simonw 9599 | closed | 0 | 1 | 2019-07-20T06:11:20Z | 2019-07-20T06:21:41Z | 2019-07-20T06:21:41Z | MEMBER | From #1:
|
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| 470637206 | MDU6SXNzdWU0NzA2MzcyMDY= | 3 | Import ActivitySummary | simonw 9599 | closed | 0 | 0 | 2019-07-20T05:21:00Z | 2019-07-20T05:58:07Z | 2019-07-20T05:58:07Z | MEMBER | From #1
|
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| 470637068 | MDU6SXNzdWU0NzA2MzcwNjg= | 1 | Use XML Analyser to figure out the structure of the export XML | simonw 9599 | closed | 0 | 1 | 2019-07-20T05:19:02Z | 2019-07-20T05:20:09Z | 2019-07-20T05:20:09Z | MEMBER | healthkit-to-sqlite 197882382 | issue | {
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