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{"@context":"https://schema.org","@type":"DiscussionForumPosting","headline":"Timestamp loss of precision in insert_rows","articleBody":"Certain values of `datetime` lose a single microsecond on their way into BigQuery. This appears to happen because of the JSON rendering of timestamps as a floating point number of seconds.\r\n\r\n#### Environment details\r\n\r\n  - OS type and version: Ubuntu Bionic\r\n  - Python version: 3.6.9\r\n  - pip version: 9.0.1\r\n  - `google-cloud-bigquery` version: 1.28.0\r\n\r\n#### Steps to reproduce\r\n\r\nHere is an example of a `datetime` value that loses a microsecond:\r\n```py\r\ndatetime(2020, 11, 17, 1, 6, 52, 353795, tzinfo=datetime.timezone(datetime.timedelta(0), 'UTC'))\r\n```\r\n\r\nAs a full integration repro, you could try something like this:\r\n\r\n  1. Create a BigQuery table with a `TIMESTAMP` column.\r\n  2. Use `insert_rows` to insert the value above.\r\n  3. Inspect the results in the Console, where it will show as `2020-11-17 01:06:52.353794 UTC` instead of `2020-11-17 01:06:52.353795 UTC`.\r\n\r\n#### Code example\r\n\r\nAn easier repro hints at the root cause. By looking at the output of `_timestamp_to_json_row`, it appears that the problematic values are rounded down to microsecond precision.\r\n\r\n```python\r\nimport datetime\r\nfrom google.cloud import bigquery as bq\r\nts = datetime.datetime(2020, 11, 17, 1, 6, 52, 353795, tzinfo=datetime.timezone(datetime.timedelta(0), 'UTC'))\r\nprint(bq._helpers._timestamp_to_json_row(ts))\r\n```\r\nThis will print:\r\n```\r\n1605575212.3537948\r\n```\r\n\r\nPerhaps the solution is to add a half microsecond (0.5e-6) so that truncating results in rounding to the nearest microsecond.\r\n","author":{"url":"https://github.com/mhfrantz","@type":"Person","name":"mhfrantz"},"datePublished":"2020-11-18T00:34:15.000Z","interactionStatistic":{"@type":"InteractionCounter","interactionType":"https://schema.org/CommentAction","userInteractionCount":2},"url":"https://github.com/392/python-bigquery/issues/392"}