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Migration Guide

This guide is meant to help you migrate your Python code from influxdb-python to influxdb-client-python by providing code examples that cover common usages.

If there is something missing, please feel free to create a new request for a guide enhancement.

Before You Start

Please take a moment to review the following client docs:

Content

Initializing Client

influxdb-python

from influxdb import InfluxDBClient

client = InfluxDBClient(host='127.0.0.1', port=8086, username='root', password='root', database='dbname')

influxdb-client-python

from influxdb_client import InfluxDBClient

with InfluxDBClient(url='http://localhost:8086', token='my-token', org='my-org') as client:
    pass

Creating Database/Bucket

influxdb-python

from influxdb import InfluxDBClient

client = InfluxDBClient(host='127.0.0.1', port=8086, username='root', password='root', database='dbname')

dbname = 'example'
client.create_database(dbname)
client.create_retention_policy('awesome_policy', '60m', 3, database=dbname, default=True)

influxdb-client-python

from influxdb_client import InfluxDBClient, BucketRetentionRules

org = 'my-org'

with InfluxDBClient(url='http://localhost:8086', token='my-token', org=org) as client:
    buckets_api = client.buckets_api()

    # Create Bucket with retention policy set to 3600 seconds and name "bucket-by-python"
    retention_rules = BucketRetentionRules(type="expire", every_seconds=3600)
    created_bucket = buckets_api.create_bucket(bucket_name="bucket-by-python",
                                               retention_rules=retention_rules,
                                               org=org)

Dropping Database/Bucket

influxdb-python

from influxdb import InfluxDBClient

client = InfluxDBClient(host='127.0.0.1', port=8086, username='root', password='root', database='dbname')

dbname = 'example'
client.drop_database(dbname)

influxdb-client-python

from influxdb_client import InfluxDBClient

with InfluxDBClient(url='http://localhost:8086', token='my-token', org='my-org') as client:
    buckets_api = client.buckets_api()

    bucket = buckets_api.find_bucket_by_name("my-bucket")
    buckets_api.delete_bucket(bucket)

Writing LineProtocol

influxdb-python

from influxdb import InfluxDBClient

client = InfluxDBClient(host='127.0.0.1', port=8086, username='root', password='root', database='dbname')

client.write('h2o_feet,location=coyote_creek water_level=1.0 1', protocol='line')

influxdb-client-python

from influxdb_client import InfluxDBClient
from influxdb_client.client.write_api import SYNCHRONOUS

with InfluxDBClient(url='http://localhost:8086', token='my-token', org='my-org') as client:
    write_api = client.write_api(write_options=SYNCHRONOUS)

    write_api.write(bucket='my-bucket', record='h2o_feet,location=coyote_creek water_level=1.0 1')

Writing Dictionary-style object

influxdb-python

from influxdb import InfluxDBClient

record = [
        {
            "measurement": "cpu_load_short",
            "tags": {
                "host": "server01",
                "region": "us-west"
            },
            "time": "2009-11-10T23:00:00Z",
            "fields": {
                "Float_value": 0.64,
                "Int_value": 3,
                "String_value": "Text",
                "Bool_value": True
            }
        }
    ]

client = InfluxDBClient(host='127.0.0.1', port=8086, username='root', password='root', database='dbname')

client.write_points(record)

influxdb-client-python

from influxdb_client import InfluxDBClient
from influxdb_client.client.write_api import SYNCHRONOUS

with InfluxDBClient(url='http://localhost:8086', token='my-token', org='my-org') as client:
    write_api = client.write_api(write_options=SYNCHRONOUS)

    record = [
        {
            "measurement": "cpu_load_short",
            "tags": {
                "host": "server01",
                "region": "us-west"
            },
            "time": "2009-11-10T23:00:00Z",
            "fields": {
                "Float_value": 0.64,
                "Int_value": 3,
                "String_value": "Text",
                "Bool_value": True
            }
        }
    ]

    write_api.write(bucket='my-bucket', record=record)

Writing Structured Data

influxdb-python

from influxdb import InfluxDBClient
from influxdb import SeriesHelper

my_client = InfluxDBClient(host='127.0.0.1', port=8086, username='root', password='root', database='dbname')


class MySeriesHelper(SeriesHelper):
    class Meta:
        client = my_client
        series_name = 'events.stats.{server_name}'
        fields = ['some_stat', 'other_stat']
        tags = ['server_name']
        bulk_size = 5
        autocommit = True


MySeriesHelper(server_name='us.east-1', some_stat=159, other_stat=10)
MySeriesHelper(server_name='us.east-1', some_stat=158, other_stat=20)

MySeriesHelper.commit()

The influxdb-client-python doesn't have an equivalent implementation for MySeriesHelper, but there is an option to use Python Data Classes way:

influxdb-client-python

from dataclasses import dataclass

from influxdb_client import InfluxDBClient
from influxdb_client.client.write_api import SYNCHRONOUS


@dataclass
class Car:
    """
    DataClass structure - Car
    """
    engine: str
    type: str
    speed: float


with InfluxDBClient(url='http://localhost:8086', token='my-token', org='my-org') as client:
    write_api = client.write_api(write_options=SYNCHRONOUS)

    car = Car('12V-BT', 'sport-cars', 125.25)

    write_api.write(bucket="my-bucket",
                    record=car,
                    record_measurement_name="performance",
                    record_tag_keys=["engine", "type"],
                    record_field_keys=["speed"])

Writing Pandas DataFrame

influxdb-python

import pandas as pd

from influxdb import InfluxDBClient

df = pd.DataFrame(data=list(range(30)),
                  index=pd.date_range(start='2014-11-16', periods=30, freq='H'),
                  columns=['0'])

client = InfluxDBClient(host='127.0.0.1', port=8086, username='root', password='root', database='dbname')

client.write_points(df, 'demo', protocol='line')

influxdb-client-python

import pandas as pd

from influxdb_client import InfluxDBClient
from influxdb_client.client.write_api import SYNCHRONOUS

with InfluxDBClient(url='http://localhost:8086', token='my-token', org='my-org') as client:
    write_api = client.write_api(write_options=SYNCHRONOUS)

    df = pd.DataFrame(data=list(range(30)),
                      index=pd.date_range(start='2014-11-16', periods=30, freq='H'),
                      columns=['0'])

    write_api.write(bucket='my-bucket', record=df, data_frame_measurement_name='demo')

Querying

influxdb-python

from influxdb import InfluxDBClient

client = InfluxDBClient(host='127.0.0.1', port=8086, username='root', password='root', database='dbname')

points = client.query('SELECT * from cpu').get_points()
for point in points:
    print(point)

influxdb-client-python

from influxdb_client import InfluxDBClient

with InfluxDBClient(url='http://localhost:8086', token='my-token', org='my-org', debug=True) as client:
    query = '''from(bucket: "my-bucket")
  |> range(start: -10000d)
  |> filter(fn: (r) => r["_measurement"] == "cpu")
  |> pivot(rowKey:["_time"], columnKey: ["_field"], valueColumn: "_value")
'''

    tables = client.query_api().query(query)
    for record in [record for table in tables for record in table.records]:
        print(record.values)

If you would like to omit boilerplate columns such as _result, _table, _start, ... you can filter the record values by following expression:

print({k: v for k, v in record.values.items() if k not in ['result', 'table', '_start', '_stop', '_measurement']})

For more info see Flux Response Format.