.. image:: src/metriqued/metriqued/static/img/metrique_logo.png
Metrique
========
Python/MongoDB Data Warehouse and Data Glue
*Metrique can help bring data into an intuitive, indexable
data object collection that supports transparent
historical version snapshotting, advanced ad-hoc
server-side querying, including (mongodb) aggregations
and (mongodb) mapreduce, along with python, ipython,
pandas, numpy, matplotlib, and so on, is well integrated
with the scientific python computing stack.
**Author:** "Chris Ward" <cward@redhat.com>
**Sources:** https://github.com/drpoovilleorg/metrique
Installation
------------
You must first install MongoDB. Then, make sure it's started.
**Metrique**
(suggested) Install virtualenv and create a new virtual
environment for metrique. Activate it.
Make sure you have the following *stuff* installed. The
examples given below are fedora rpm package names::
mongodb-server git python python-setuptools
gcc gcc-c++ python-devel libpng-devel freetype-devel
postgresql postgresql-devel kerberos-devel
mysql-devel
Install metrique and metriqued::
pip install metrique metriqued
If you see any error, Google.
Otherwise, you should now be ready to go.
Run metriqued-config if you changed any defaults.
To start metrique, run::
$> metriqued-server start [2|1|0] [1|0]
Where argv are debug on+/on/off and async on/off respectively.
**Client**
If the metrique server is running on anything other than
`http://127.0.0.1`, run `metrique-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`
If you have any of your own cubes to install, i suggest
copying them there now.
To start using them::
IN [] from metrique import pyclient
Then, to load a cube for extraction, query or administration,
import::
IN [] g = pyclient(cube="gitrepo_commit"")
Ping the server to ensure your connected. If all
is well, metriqe server should pong your ping!::
IN [] g.ping()
OUT [] pong!
Try running an example ::mod:git_commit etl job, for example::
IN [] g.extract(uri='https://github.com/drpoovilleorg/metrique.git')
Then, analyse away::
IN [] q = c.query.fetch('git_commit', 'author, committer_ts')
IN [] q.groupby(['author']).size().plot(kind='barh')
OUT [] <matplotlib.axes.AxesSubplot at 0x6f77ad0>
Metrique
========
Python/MongoDB Data Warehouse and Data Glue
*Metrique can help bring data into an intuitive, indexable
data object collection that supports transparent
historical version snapshotting, advanced ad-hoc
server-side querying, including (mongodb) aggregations
and (mongodb) mapreduce, along with python, ipython,
pandas, numpy, matplotlib, and so on, is well integrated
with the scientific python computing stack.
**Author:** "Chris Ward" <cward@redhat.com>
**Sources:** https://github.com/drpoovilleorg/metrique
Installation
------------
You must first install MongoDB. Then, make sure it's started.
**Metrique**
(suggested) Install virtualenv and create a new virtual
environment for metrique. Activate it.
Make sure you have the following *stuff* installed. The
examples given below are fedora rpm package names::
mongodb-server git python python-setuptools
gcc gcc-c++ python-devel libpng-devel freetype-devel
postgresql postgresql-devel kerberos-devel
mysql-devel
Install metrique and metriqued::
pip install metrique metriqued
If you see any error, Google.
Otherwise, you should now be ready to go.
Run metriqued-config if you changed any defaults.
To start metrique, run::
$> metriqued-server start [2|1|0] [1|0]
Where argv are debug on+/on/off and async on/off respectively.
**Client**
If the metrique server is running on anything other than
`http://127.0.0.1`, run `metrique-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`
If you have any of your own cubes to install, i suggest
copying them there now.
To start using them::
IN [] from metrique import pyclient
Then, to load a cube for extraction, query or administration,
import::
IN [] g = pyclient(cube="gitrepo_commit"")
Ping the server to ensure your connected. If all
is well, metriqe server should pong your ping!::
IN [] g.ping()
OUT [] pong!
Try running an example ::mod:git_commit etl job, for example::
IN [] g.extract(uri='https://github.com/drpoovilleorg/metrique.git')
Then, analyse away::
IN [] q = c.query.fetch('git_commit', 'author, committer_ts')
IN [] q.groupby(['author']).size().plot(kind='barh')
OUT [] <matplotlib.axes.AxesSubplot at 0x6f77ad0>
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