Metadata-Version: 2.1
Name: ipython-flux
Version: 0.0.5
Summary: InfluxDB access via IPython
Home-page: https://pypi.python.org/pypi/ipython-flux
Author: Robert Hajek
Author-email: robert.hajek@gmail.com
License: MIT
Keywords: ipython magic influxdb
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Database
Classifier: Topic :: Database :: Front-Ends
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 2
Description-Content-Type: text/x-rst
License-File: LICENSE

============
ipython-flux
============
.. image:: https://circleci.com/gh/bonitoo-io/ipython-flux.svg?style=svg
    :target: https://circleci.com/gh/bonitoo-io/ipython-flux

:Author: Robert Hajek, Bonitoo.io

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

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

.. image:: https://raw.github.com/bonitoo-io/ipython-flux/master/examples/example.png
   :width: 600px
   :alt: screenshot of ipython-flux in the Notebook

Examples
--------

.. code-block:: python

    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.

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

.. code-block:: python

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

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

.. code-block:: python

    In [19]: %%flux my_dataset <<
        ...: from(bucket: "my-bucket")
        ...: |> range(start: -30m)
        ...: |> filter(fn: (r) => r["_measurement"] == "cpu")
        ...: |> filter(fn: (r) => r["_field"] == "usage_idle" or r["_field"] == "usage_system" or r["_field"] == "usage_user")
        ...: |> filter(fn: (r) => r["cpu"] == "cpu-total")
        ...: |> drop(columns: ["_start", "_stop", "_result", "_measurement", "table", "_result"])
        ...: |> pivot(rowKey:["_time"], columnKey: ["_field"], valueColumn: "_value")


The result of the Flux command is automatically converted into Pandas dataframe. It is often useful to use Flux
functions ``fieldsAsCol()`` or ``pivot()`` to convert data containing multiple timeseries into one dataset.

Persist dataframe
-----------------

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

.. code-block:: python

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

.. _Pandas: http://pandas.pydata.org/

Options
-------

``-l`` / ``--connections``
    List all active connections

``-t`` / ``--token``
    InfluxDB token


``-o`` / ``--org``
    InfluxDB org

``--timeout``
    InfluxDB query timeout in milliseconds (default timeout is 10_000 ms)

``-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

.. code-block:: python

    In [1]: %load_ext flux

Development
-----------

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


News
----

0.0.5
~~~~~
*Release date: 25-03-2022*

- `#2 <https://github.com/bonitoo-io/ipython-flux/issues/2>`_ - Add connection timeout
- `#3 <https://github.com/bonitoo-io/ipython-flux/pull/3>`_ - Change default InfluxDB port from 9999 to 8086, update dependencies

0.0.4
~~~~~

*Release date: 18-08-2020*

- `#1 <https://github.com/bonitoo-io/ipython-flux/pull/1>`_: Fixed token argument starts with "-"


0.0.3
~~~~~

*Release date: 12-08-2020*

* Updated tox.ini and requirement dependencies

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


