Metadata-Version: 2.1
Name: timeseer
Version: 0.0.4
Summary: Timeseer Client allows querying of data and metadata from timeseer.
Home-page: https://timeseer.ai/
Author: Timeseer.AI
Author-email: pypi@timeseer.ai
License: Copyright Timeseer.AI 2021
Description: ## Timeseer.AI Client
        
        Timeseer includes a Python client that can connect to a running instance of Timeseer Bus.
        Get your api key in the Timeseer application under `Configure > Global preferences > Api keys`
        
        ```
        >>> import timeseer_client.client
        >>> from timeseer_client import SeriesSelector
        >>> client = timeseer_client.client.Client(('<api-key-name>', '<api-key>'), 'localhost', 8081)
        >>> list(client.search(SeriesSelector('row')))
        [Metadata(series=SeriesSelector(source='row', name='test-tag-1'), description='', unit='m', limit_low=0.0, limit_high=1.0, accuracy=0.1), Metadata(series=SeriesSelector(source='row', name='test-tag-2'), description='test-tag-2', unit='kg', limit_low=0.0, limit_high=1.0, accuracy=0.1), Metadata(series=SeriesSelector(source='row', name='test-tag-3'), description='', unit='kPa', limit_low=0.0, limit_high=10.0, accuracy=1.0)]
        >>> client.get_metadata(SeriesSelector('row', 'test-tag-1'))
        Metadata(series=SeriesSelector(source='row', name='test-tag-1'), description='', unit='m', limit_low=0.0, limit_high=1.0, accuracy=0.1)
        >>> client.get_data(SeriesSelector('row', 'test-tag-1'))
        pyarrow.Table
        ts: timestamp[us, tz=utc]
        value: double
        >>> client.get_data(SeriesSelector('row', 'test-tag-1')).to_pandas().set_index('ts')
                                   value
        ts
        2020-01-01 00:00:00+00:00    1.0
        2020-02-01 00:00:00+00:00    2.0
        2020-03-01 00:00:00+00:00    2.0
        2020-04-01 00:00:00+00:00    1.0
        2020-05-01 00:00:00+00:00    1.0
        >>> client.get_event_frames()
        pyarrow.Table
        interval: struct<start_date: timestamp[us, tz=UTC], end_date: timestamp[us, tz=UTC]>
          child 0, start_date: timestamp[us, tz=UTC]
          child 1, end_date: timestamp[us, tz=UTC]
        type: string
        source: string
        name: string
        >>> client.get_event_frames(selector=SeriesSelector('row', 'test-tag-2'), frame_type='Negative slopes').flatten().to_pandas()
                interval.start_date         interval.end_date             type source        name
        0 2020-01-01 00:00:00+00:00 2020-02-08 00:00:00+00:00  Negative slopes    row  test-tag-2
        1 2020-03-19 00:00:00+00:00 2020-11-01 00:00:00+00:00  Negative slopes    row  test-tag-2
        >>> from dateutil.parser import parse as parse_date
        >>> client.get_event_frames(selector=SeriesSelector('row', 'test-tag-2'), frame_type='Negative slopes', start_date=parse_date('2020-03-01T00:00:00Z')).flatten().to_pandas()
                interval.start_date         interval.end_date             type source        name
        0 2020-03-19 00:00:00+00:00 2020-11-01 00:00:00+00:00  Negative slopes    row  test-tag-2
        >>> client.get_event_frames(selector=SeriesSelector('row', 'test-tag-2'), frame_type='Negative slopes', end_date=parse_date('2020-03-01T00:00:00Z')).flatten().to_pandas()
                interval.start_date         interval.end_date             type source        name
        0 2020-01-01 00:00:00+00:00 2020-02-08 00:00:00+00:00  Negative slopes    row  test-tag-2
        ```
        
        Full documentation is available by running:
        
        ```
        >>> help(timeseer_client)
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
