Python and InfluxDB

Build IoT, analytics, and cloud applications using the Python client library with InfluxDB.

Why use the InfluxDB Python Client Library?

InfluxDB is an API-first time series database for your Python applications. Use the InfluxDB open-source Python API client to write and query data into your applications and even manage your InfluxDB instance from within your app.

Key features

• Provides API access to all InfluxDB Write and Read functionality, settings, and advanced features
• Write data in InfluxDB line protocol, point data structure, or as a pandas dataframe
• Easily configure timeouts, delays, and request retries
• Batch data to InfluxDB to gain greater efficiency
• Return InfluxDB data as a Flux Table Structure, string, csv, stream, or dataframe
• Panda dataframe integration

Get started

from influxdb_client import InfluxDBClient

url = 'https://us-west-2-1.aws.cloud2.influxdata.com'
token = 'my-token'
org = 'my-org'
bucket = 'my-bucket'

with InfluxDBClient(url=url, token=token, org=org) as client:
    query_api = client.query_api()

    tables = query_api.query('from(bucket: "my-bucket") |> range(start: -1d)')

    for table in tables:
        for record in table.records:
            print(str(record["_time"]) + " - " + record.get_measurement()
                  + " " + record.get_field() + "=" + str(record.get_value()))

from datetime import datetime

from influxdb_client import WritePrecision, InfluxDBClient, Point
from influxdb_client.client.write_api import SYNCHRONOUS

url = 'https://us-west-2-1.aws.cloud2.influxdata.com'
token = 'my-token'
org = 'my-org'
bucket = 'my-bucket'

with InfluxDBClient(url=url, token=token, org=org) as client:
    p = Point("weatherstation") \
        .tag("location", "San Francisco") \
        .field("temperature", 25.9) \
        .time(datetime.utcnow(), WritePrecision.MS)

    with client.write_api(write_options=SYNCHRONOUS) as write_api:
        write_api.write(bucket=bucket, record=p)

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