Script Development / InfluxDB

The InfluxDB connector operates as a wrapper for the Python third-party 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 connects via HTTP protocol

DFF.CONN(...) parameters are as follows:

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

`.query(...)`

Execute an InfluxQL statement. Parameters are as follows:

Parameter	Type	Required / Default	Description
`sql`	str	Required	InfluxQL statement, which can contain binding parameter placeholders in the form `$var_name`
`bind_params`	dict	`None`	Binding parameters
`database`	str	`None`	Specify database for this query
`dict_output`	dict	`False`	Automatically convert returned data to {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 is also used to execute InfluxQL statements, but uses a different parameter placeholder, using the question mark ? as the parameter placeholder. Parameters are as follows:

Parameter	Type	Required / Default	Description
`sql`	str	Required	InfluxQL statement, which can contain parameter placeholders. `?` indicates a parameter that needs escaping; `??` indicates a parameter that does not need escaping
`sql_params`	list	`None`	InfluxQL parameters
`database`	str	`None`	Specify database for this query
`dict_output`	dict	`False`	Automatically convert returned data to `{"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 Statements

query2(...) internally uses DFF.SQL(...) to construct SQL statements and supports constructing complex dynamic SQL statements.

Such as WHERE IN (...) with an uncertain number of values, or INSERT INTO ... VALUES ... for batch data writing, etc.

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

`.write_point(...)`

Added in version 1.1.13

Write a single data point. Parameters are as follows:

Parameter	Type	Required / Default	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 Both key names and key values must be str
`timestamp`	str/int	`None`	Time ISO format, e.g., `2020-01-01T01:02:03Z` UNIX timestamp, e.g., `1577840523`
`database`	str	`None`	Specify database for this write operation

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 write data points. Parameters are as follows:

Parameter	Type	Required / Default	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 Both key names and key values must 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`	Specify database for this write operation

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