Greg Von Kuster 1a6daca3a4 Streamlined interface for supporting new data types - requires db change and note config change.
db change:
update dataset set extension = 'txt' where extension = 'text';

Adding support for a new data type is now as simple as adding the new type to the config file and optionally adding the
type into the new sniff_order section in the config file, and adding the new class for the data type to the appropriate
datatypes code.

The config file now has a new section [galaxy:sniff_order] which lists the order in which datatype class sniff functions will
be called (each datatype class can now optionally include its own sniff function, although not a requirement).

Support for the 'text' file extension has been eliminated as we will standardize on the 'txt' file extension for the Text data type.
2007-09-27 14:10:16 +00:00
2007-09-20 21:36:00 +00:00
2007-08-17 14:23:42 +00:00
2007-01-16 17:17:23 +00:00
2007-02-08 20:16:16 +00:00

INTRO
=====

This program requires python 2.4 or later. To check your python version type:

python -V.

To start a server you need to do run the server as:

python universe.py

This will start a server on localhost port 8080. 
In your browser go to: http://localhost:8080 and you should see the 
Galaxy environment with some default tools. To customize the tools that 
are loaded see tool.conf.sample To customize the way your server is ran edit 
universe.conf 

*Note* certain tools may require certain libraries to be present.
(See run.sh for more details)


RUNTIME ENVIRONMENT
===================

The default server home will be the directory where the program starts.
You can use the UNIVERSE_HOME environment variable to point to a different
server home. The path that the UNIVERSE_HOME variable points to must be 
a directory with the following subdirectories:

database
database/files
database/import
tools

OPTIMIZED LIBRARIES
===================

To allow python to load optimized libraries the path to these must be listed 
in the python path. See the previous section or run.sh for an example. Loading 
the optimized Cheetah templating libraries can lead to significant 
performance gains. 

At startup you the log message: 

Optimized  Namemapper: True|False

will tell you whether the optimized Cheetah template was loaded (or not).

The log message:

database type: dbhash|....

will tell you what kind of underlying database is the server using. Dbhash 
stands for the BerkleyDB. The server should work fine with other libraries 
as well but BerkleyDB is provides the most reliable and efficient storage.

TOOL DEVELOPMENT
================

See the wiki pages for more details:

http://g2.bx.psu.edu


CREATING A RELEASE
==================

type:

python setup.py sdist 
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