Bayeslite is a BQL database built on SQLite3. BQL is an extension to SQL that supports queries about the probable implications of data.
Bayeslite is part of an ongoing research project. For more information, contact [email protected].
Bayeslite is written in Python 2.7, using the sqlite3 module with SQLite3 >=3.8.0.
Bayeslite depends on:
- Crosscat, a general-purpose nonparametric Bayesian population model which serves as a default in the absence of a domain-specific model.
- apsw, a sqlite3 wrapper for Python more articulated than the builtin sqlite3 module
- numpy, a library of vectorized numerical algorithms
- requests, an HTTP/HTTPS library, which we use to track users.
The bayeslite automatic tests depend on:
The bayeslite documentation depends on:
To check that everything will work, before installing:
$ ./check.sh
To install system-wide, or into the current virtual environment:
$ python setup.py build
$ python setup.py install
Import the bayeslite
module. See the documentation for details on
the Python API.
To build the documentation (requires sphinx):
$ make doc
The result will be placed in build/doc
, with one subdirectory per
output format.
To build only one output format, e.g. HTML because you don't want to install TeX:
$ make html