Script Development / InfluxDB

The operation object of the InfluxDB connector is a wrapper for the third-party Python package influxdb (version 5.2.3), primarily providing methods for querying InfluxDB. This connector is compatible with the following databases:

Alibaba Cloud Time Series Database InfluxDB Edition

This connector is based on HTTP protocol connection

Parameters for DFF.CONN(...) are as follows:

Parameter	Type	Required / Default Value	Description
`connector_id`	str	Required	Connector ID
`database`	str	`None`	Specify database

`.query(...)`

Executes an InfluxQL statement, parameters are as follows:

Parameter	Type	Required / Default Value	Description
`sql`	str	Required	InfluxQL statement, may include bound parameter placeholders in the form `$var_name`
`bind_params`	dict	`None`	Bound parameters
`database`	str	`None`	Specifies the database for this query
`dict_output`	dict	`False`	Automatically converts returned data into `{column name: value}` format

Example
sql = 'SELECT * FROM demo WHERE city = $city LIMIT 5'
bind_params = {'city': 'hangzhou'}
result = db.query(sql, bind_params=bind_params, database='demo')

Output Example
# {'series': [{'columns': ['time', 'city', 'hostname', 'status', 'value'], 'name': 'demo', 'values': [['2018-12-31T16:00:10Z', 'hangzhou', 'webserver', 'UNKNOW', 90], ['2018-12-31T16:00:20Z', 'hangzhou', 'jira', 'running', 40], ['2018-12-31T16:00:50Z', 'hangzhou', 'database', 'running', 50], ['2018-12-31T16:01:00Z', 'hangzhou', 'jira', 'stopped', 40], ['2018-12-31T16:02:00Z', 'hangzhou', 'rancher', 'UNKNOW', 90]]}]}

Example 2 (Specify return result as dictionary format)
sql = 'SELECT * FROM demo WHERE city = $city LIMIT 5'
bind_params = {'city': 'hangzhou'}
result = db.query(sql, bind_params=bind_params, database='demo', dict_output=True)

Output Example
# {'series': [[{'city': 'hangzhou', 'hostname': 'webserver', 'status': 'UNKNOW', 'time': '2018-12-31T16:00:10Z', 'value': 90}, {'city': 'hangzhou', 'hostname': 'jira', 'status': 'running', 'time': '2018-12-31T16:00:20Z', 'value': 40}, {'city': 'hangzhou', 'hostname': 'database', 'status': 'running', 'time': '2018-12-31T16:00:50Z', 'value': 50}, {'city': 'hangzhou', 'hostname': 'jira', 'status': 'stopped', 'time': '2018-12-31T16:01:00Z', 'value': 40}, {'city': 'hangzhou', 'hostname': 'rancher', 'status': 'UNKNOW', 'time': '2018-12-31T16:02:00Z', 'value': 90}]]}

`.query2(...)`

The query2(...) method also executes InfluxQL statements but uses different parameter placeholders, using ? as a parameter placeholder. Parameters are as follows:

Parameter	Type	Required / Default Value	Description
`sql`	str	Required	InfluxQL statement, may include parameter placeholders. `?` represents escaped parameters; `??` represents unescaped parameters
`sql_params`	list	`None`	InfluxQL parameters
`database`	str	`None`	Specifies the database for this query
`dict_output`	dict	`False`	Automatically converts returned data into `{"column name": "value"}` format

Example
sql = 'SELECT * FROM ?? WHERE city = ? LIMIT 5'
sql_params = ['demo', 'hangzhou']
result = db.query2(sql, sql_params=sql_params, dict_output=True)

Dynamic SQL Statement

Internally, query2(...) uses DFF.SQL(...) to construct SQL statements and supports building complex dynamic SQL statements.

For example, WHERE IN (...) with an uncertain number of values, or INSERT INTO ... VALUES ... for batch inserting data.

For more details, please refer to Script Development / SQL Construction DFF.SQL

`.write_point(...)`

Added in version 1.1.13

Writes a single data point. Parameters are as follows:

Parameter	Type	Required / Default Value	Description
`measurement`	str	Required	Measurement
`fields`	dict{str: str/int/float/bool}	Required	Fields Key names must be str Key values can be str/int/float/bool
`tags`	dict{str: str}	`None`	Tags Key names and key values must both be str
`timestamp`	str/int	`None`	Time ISO format, e.g., `2020-01-01T01:02:03Z` UNIX timestamp, e.g., `1577840523`
`database`	str	`None`	Specifies the database for this write

Example
fields = { 'cpu': 100, 'mem': 0.5 }
tags   = { 'host': 'web001' }
result = db.write_point(measurement='host_monitor', fields=fields, tags=tags)

`.write_points(...)`

Added in version 1.1.13

Batch writes multiple data points. Parameters are as follows:

Parameter	Type	Required / Default Value	Description
`points`	list	Required	Array of data points
`points[#]['measurement']`	str	Required	Measurement
`points[#]['fields']`	dict{str: str/int/float/bool}	Required	Fields Key names must be str Key values can be str/int/float/bool
`points[#]['tags']`	dict{str: str}	`None`	Tags Key names and key values must both be str
`points[#]['time']`	str/int	`None`	Time ISO format, e.g., `2020-01-01T01:02:03Z` UNIX timestamp, e.g., `1577840523`
`database`	str	`None`	Specifies the database for this write

Example
points = [
    {
        'measurement': 'host_monitor',
        'fields'     : { 'cpu': 100, 'mem': 0.5 },
        'tags'       : { 'host': 'web001' },
    }
]
result = db.write_points(points)