data_tools.query.InfluxDBClient#

class data_tools.query.InfluxDBClient(influxdb_org=None, influxdb_token=None, url=None, timeout=10, temporal_localization: ~typing.Type[<data_tools.localization.temporal_localization.TemporalLocalization object at 0x754fe0479070>] | None = None, language_localization: ~typing.Type[<data_tools.localization.language_localization.LanguageLocalization object at 0x754fe83c0710>] | None = None)#

Bases: object

This class encapsulates a connection to an InfluxDB database.

__init__(influxdb_org=None, influxdb_token=None, url=None, timeout=10, temporal_localization: ~typing.Type[<data_tools.localization.temporal_localization.TemporalLocalization object at 0x754fe0479070>] | None = None, language_localization: ~typing.Type[<data_tools.localization.language_localization.LanguageLocalization object at 0x754fe83c0710>] | None = None)#

Create a connection to the InfluxDB database.

Parameters:

influxdb_org – The name of the InfluxDB organization.
influxdb_token – The API Token to the InfluxDB database.
url – The URL to the InfluxDB database, default is “http://influxdb.telemetry.ubcsolar.com”
timeout – The request timeout in seconds, default is 10 seconds.
temporal_localization – The type of temporal localization to use, default is TemporalLocalization.
language_localization – The type of language localization to use, default is LanguageLocalization.

Methods

`__init__`([influxdb_org, influxdb_token, ...])	Create a connection to the InfluxDB database.
`close`()
`get_buckets`()	Obtain the available buckets.
`get_cars_in_measurement`(bucket, measurement)	Obtain the different cars within a measurement and bucket.
`get_fields_in_measurement`(bucket, measurement)	Obtain the possible fields within a measurement and bucket.
`get_measurements_in_bucket`(bucket)	Obtain a list of the possible measurements within a bucket.
`query_dataframe`(query)	Submit a Flux query, and return the result as a DataFrame.
`query_series`(start, stop, field[, bucket, ...])	Query the database for a specific field, over a certain time range.
`query_time_series`(start, stop, field[, ...])	Query the database for a specific field, over a certain time range.

close()#

get_buckets() → list[str]#: Obtain the available buckets. :return: list of available buckets

get_cars_in_measurement(bucket: str, measurement: str) → list[str]#: Obtain the different cars within a measurement and bucket. :param bucket: the bucket that will be queried. Must exist. :param measurement: the measurement that will be queried. Must exist. :return:

get_fields_in_measurement(bucket: str, measurement: str) → list[str]#: Obtain the possible fields within a measurement and bucket. :param bucket: the bucket that will be queried. Must exist. :param measurement: the measurement that will be queried. Must exist. :return:

get_measurements_in_bucket(bucket: str) → list[str]#

Obtain a list of the possible measurements within a bucket.

Parameters:: bucket – the bucket that will be queried. Must exist.
Returns:: a list of available measurements in bucket.

query_dataframe(query: FluxQuery) → DataFrame#

Submit a Flux query, and return the result as a DataFrame.

Parameters:: query (FluxQuery) – the query which will be submitted
Returns:: the resulting data as a DataFrame

query_series(start: datetime, stop: datetime, field: str, bucket: str = 'CAN_log', car: str = 'Brightside', measurement: str = None)#

Query the database for a specific field, over a certain time range. The data will be returned as a DataFrame.

Parameters:

start – the start time of the query as an ISO 8601-compliant string, such as “2024-06-30T23:00:00Z”.
stop – the end time of the query as an ISO 8601-compliant string, such as “2024-06-30T23:00:00Z”.
field – the field which is to be queried.
bucket (str) – the bucket which will be queried
car – the car which data is being queried for, default is “Brightside”.

Returns:

a TimeSeries of the resulting time-series data

query_time_series(start: datetime, stop: datetime, field: str | CanonicalName, bucket: str = 'CAN_log', car: str = 'Brightside', granularity: float = 0.1, units: str = '', measurement: str = None) → TimeSeries#

Query the database for a specific field, over a certain time range. The data will be processed into a TimeSeries, which has homogenous and evenly-spaced (temporally) elements. Data will be re-interpolated to have temporal granularity of granularity.

Parameters:

start – the start time of the query as an ISO 8601-compliant string, such as “2024-06-30T23:00:00Z”.
stop – the end time of the query as an ISO 8601-compliant string, such as “2024-06-30T23:00:00Z”.
field – the field which is to be queried.
bucket (str) – the bucket which will be queried
car – the car which data is being queried for, default is “Brightside”.
granularity – the temporal granularity of the resulting TimeSeries in seconds, default is 0.1s.
units – the units of the returned data, optional.

Returns:

a TimeSeries of the resulting time-series data