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Python/MongoDB Information Platform - Server

Project Description

.. image:: metrique/server/static/img/metrique_logo.png


Python/MongoDB Information Platform and Data Warehouse

*Metrique help bring data into an intuitive, indexable
data object collection that supports quick snapshotting,
advanced ad-hoc querying, including (mongodb) aggregations
and mapreduce, along with python, ipython, pandas,
numpy, matplotlib, and so on, is fully integrated
with the scientific python computing stack. I hope
so anyway. :)*

**Author:** "Chris Ward" <>



You must first install MongoDB. Then, to continue,
make sure it's started.

(suggested) Install virtualenv and create a new virtual
environment for metrique. Activate it.

Install metrique::

python-pip install metrique -r requirements.txt

.. note::
Make sure you have gcc and python-devel libraries installed

.. note::
If you see 'Connection reset by peer' error, try option: --use-mirrors

.. note::
If you see any other error, Google.

You should now be ready to go.

Run if you changed any defaults.

To start metrique, run::

$[/metrique/server/bin] metrique-server start [2|1|0] [1|0]

Where argv are debug on+/on/off and async on/off respectively.

It's suggested to run :mod:metrique-server-setup after install
as well, especially if you changed any default values of your
mongo or metrique servers, they're hosted on a different
ip than `localhost`.

If the metrique server is running on anything other than
``, run `metrique-client-setup`.

Then, launch a python shell. We suggest ipython notebook.

As of this time, :mod:cubes can be found in global
metrique namespace or local to the running user.

Default: `~/.metrique/cubes`

To quickly make those cubes available in sys.path::

IN [] from metrique.client.cubes import set_cube_path
IN [] set_cube_path() # defaults to '~/.metrique/cubes'

Then, to load a cube for extraction, query or administration,

IN [] from git_repo.gitrepo import Commit
IN [] g = Commit(config_file=None, uri=None)

Ping the server to ensure your connected. If all
is well, metriqe server should pong your ping!::

IN []
OUT [] pong!

Try running an example ::mod:git_commit etl job, for example::

IN [4] g.extract("git_commit")

Then, analyse away::

IN [5] q = c.query.fetch('git_commit', 'author, committer_ts')
IN [6] q.groupby(['author']).size().plot(kind='barh')
OUT [6] <matplotlib.axes.AxesSubplot at 0x6f77ad0>

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