metrique provides a simple python API to support ETL workloads for extracting data from disperate sources, iteratively, rapidly and reproducibly, with transparent, historical object persistence and tight clientside integration with popular python scientific computing libraries to faciliate creation and publication of a wide variety of analysis and reports, large and small.
- Backends currently supported are as follows:
- PostgreSQL (sqlalchemy)
- SQLite (sqlalchemy)
Author: "Chris Ward" <[email protected]> Sources: https://github.com/kejbaly2/metrique
The instructions given below assume fedora rpm package names:
# prerequisite *os* packages sudo yum install python python-devel python-setuptools python-pip sudo yum install openssl git gcc gcc-c++ gcc-gfortran sudo yum install freetype-devel libpng-devel # matplotlib deps # optional PostgreSQL sudo yum install postgresql postgresql-devel postgresql-server # make sure our core package managers are up2date sudo pip install -U distribute setuptools # our installation directory should always be a py virtualenv sudo pip install virtualenv # get metrique sources git clone https://github.com/kejbaly2/metrique.git cd metrique # deploy metrique master branch into a virtual environment, # including dependencies. # NOTE this can take ~5-10 minutes to compile everything from source! ./metrique.py -V ~/metrique.master deploy --all --develop # activate the virtual environment source ~/metrique.master/bin/activate ./metrique.py firstboot metrique # optional: setup default postgresql environment and start ./metrique.py firstboot postgresql # optional: edit ~/.metrique/postgresql_db/*.conf ./metrique.py postgresql start # launch ipython and start mining!
