ipython-flux 0.0.2

InfluxDB access via IPython

Author:

Robert Hajek, Bonitoo.io

Introduces a %flux (or %%flux) magic.

Connect to a InfluxDB and run Flux commands within IPython or IPython Notebook.

Examples

In [1]: %load_ext flux

In [2]: %%flux http://localhost:9999 --token my-token --org my-org
   ...: from(bucket: "apm_metricset")
   ...:   |> range(start: v.timeRangeStart, stop: v.timeRangeStop)
   ...:   |> filter(fn: (r) => r["_measurement"] == "apm_metricset")
   ...:   |> filter(fn: (r) => r["_field"] == "samples_system.process.cpu.total.norm.pct")
   ...:
Out[2]: ...

After the first connection, connect info can be omitted:

In [3]: %flux
   ...: from(bucket: "apm_metricset")
   ...:   |> range(start: v.timeRangeStart, stop: v.timeRangeStop)
   ...:   |> filter(fn: (r) => r["_measurement"] == "apm_metricset")
   ...:   |> filter(fn: (r) => r["_field"] == "samples_system.process.cpu.total.norm.pct")

Out[8]: ...

If no connect string is supplied, %flux will use environment variables INFLUXDB_V2_URL, INFLUXDB_V2_ORG, INFLUXDB_V2_TOKEN to create connection into InfluxDB.

Assignment

Ordinary IPython assignment works for single-line %flux queries:

In [12]: result = %flux from(bucket: "apm_metricset")  |> range(start: 0)

The << operator captures query results in a local variable, and can be used in multi-line %%flux:

In [19]: %%flux works << %flux from(bucket: "apm_metricset")
    ...: |> range(start: 0)
    ...:

Pandas

result is automatically converted into pandas dataframe

In [3]: result =  %flux from(bucket: "apm_metricset")  |> range(start: 0)

The --persist argument, with the name of a DataFrame object in memory will create a measurement in the database from the named DataFrame.

In [1]: %flux --persist <data_frame_variable_name> --bucket my-bucket --measurement <new measurement name> --tags tag_column1,tag_column2

Options

-l / --connections

List all active connections

-t / --token

InfluxDB token

-o / --org

InfluxDB org

-f / --file <path>

Run Flux from file at this path

-x / --close <session-name>

Close named connection

Persist options

-p / --persist

Create a measurement in the database from the named DataFrame

-b / --bucket

target bucket name

-T / --tags

comma separated list of columns that will be stored as tags, rest of columns will be stored as fields

-m / --measurement

optional, target measurement name, if not specified measurement is taken from dataframe name

Installing

Install the lastest release with:

pip install ipython-flux

or download from https://github.com/bonitoo-io/ipython-flux and:

cd ipython-flux
sudo python setup.py install

Enable IPython flux magic extension in Jupyter notebook using

In [1]: %load_ext flux

Development

https://github.com/bonitoo-io/ipython-flux

News

0.0.2

Release date: 6-08-2020

• Fixed connection creation from os enviroment variables

• Added persist dataframe into InfluxDB

0.0.1

Release date: 21-07-2020

• Initial release