What’s new in this release? The most important changes are fixes to a number of issues identified by users of SQLPython. Gerald was appearing to take a long time to collect large schemas but was actually failing silently. I added test cases to show the problem and then fixed the code. This shouldn’t happen any more.

I applied a couple of patches supplied by Catherine Devlin to cope with columns without defined lengths and to not get DBA objects in Oracle schemas.

I slipped in some new features as well; I implemented the to_xml and compare methods on the CodeObject class, and Gerald now supports views in MySQL (as long as you are running 5.1 or above).

Finally, I changed the project documentation to use Sphinx.

Downloads are available at the PyPI page and the SourceForge project page.

If you find any problems or want to contribute any code just send me an email.

So I thought that as long as docutils is written in Python it would only take a moment or two to knock up a script to do what I needed. Well yes, and no. The script itself is fairly simple;

from docutils import core

def convert_files(name_pattern):
    for file_name in glob.glob(name_pattern):
        source = open(file_name, 'r')
        file_dest = file_name[:-4] + '.html'
        destination = open(file_dest, 'w')
        core.publish_file(source=source, destination=destination, writer_name='html')
        source.close()
        destination.close()

The most useful line being the one where I call core.publish_file. But it wasn’t immediately obvious from the docutils documentation what series of incantations would achieve my desired results. Luckily, after some time spent perusing the documents I came across this dissection of rst2html.py. This, in turn, lead me to the description of the Docutils Publisher, which lists the convenience functions available to work with the engine.

The end result isn’t particularly elegant but it does get the job done and I thought I would share it in case anyone else has a similar need in the future.

This release was at the request of the sqlpython project and contains only one change. A new convenience method connect has been added to the Schema class. This enables a schema to be initiated and then later have a database connection associated with it. Because this changes the public API of gerald I’ve released this under a new version number.

Development, bug and issue tracking and the project wiki are available on the project Trac site. Source code and distribution files are available at the sourceforge page.

The next release will be 0.4. Exactly what will make up that release is still evolving, although it is likely to feature SQL Server support as I have just started a new job and all of the systems there use it. To see what else is in the release and to track progress take a look at the version 0.4 roadmap.

Everything is fine on my Ubuntu virtual machine, but on my shiny new work laptop I have Python 2.6 and today I downloaded and installed setuptools version 06.c11. When I try and install Gerald I get an error complaining about a lack of a setup.py file;

(TEST) C:\Work\virtualenvs\TEST>easy_install gerald
Searching for gerald
Reading http://pypi.python.org/simple/gerald/
Reading http://halfcooked.com/code/gerald/
Reading http://sourceforge.net/project/showfiles.php?group_id=53184&package_id=109623
Reading http://sourceforge.net/projects/halfcooked/files
Best match: gerald 0.3.5
Downloading http://sourceforge.net/projects/halfcooked/files/gerald/0.3.5/gerald-0.3.5-py2.6.egg/download
Processing download
error: Couldn't find a setup script in c:\docume~1\andy~1.tod\locals~1\temp\easy_install-woqly0\download
(TEST) C:\Work\virtualenvs\TEST>

The only thing that I can find different is that my Ubuntu virtual machine is running version 0.6c9 of setuptools. Has the function changed between two release candidates?

Needless to say this means that Gerald won’t install under Windows using easy_install until I figure this out. All help and suggestions warmly received.

The major component of this release was to add a ‘User’ class to the oracle_schema module. This is similar to the ‘Schema’ class but whilst that shows all of the objects a database user owns the ‘User’ class contains details of all of the objects they can access, including those owned by other database users. This was requested by the sqlpython project to enable them to use gerald for database introspection.

The only other change was to ensure that the NotImplementedError exception is raised in all of the super type methods that are just stubs. This is mainly in the Schema.py module and thus meant that I had to add a set of tests for this module.

Development, bug and issue tracking and the project wiki are available on the project Trac site. Source code and distribution files are available at the sourceforge page.

The next release will be 0.4. Exactly what will make up that release is still evolving. To see what is in the release and to track progress take a look at the version 0.4 roadmap.

• Ticket 17 – Views have been converted to dictionaries from tuples
• Ticket 18 – Reading an Oracle sequence updates it’s current value
• Ticket 19 – Postgres primary keys were not represented properly when read from the database

Development, bug and issue tracking and the project wiki are available on the project Trac site. Source code and distribution files are available at the sourceforge page.

The next release will be 0.3.5 and will introduce the concept of a ‘User’. This is similar to a ‘Schema’ but will reference all of the objects a database user can see even if they don’t own them. You can track progress for the release using the version 0.3.5 roadmap.

Now the casual observer would think that these are the same as CSV files, but with a different delimiter. And you would almost be correct -as long as you aren’t relying on popular desktop productivity software to produce your files.

The reasons for this exact format are lost in the mists of time but these files are supposed to be easy to produce by anyone with a computer. The assumption was that most of the people producing these files would be running Microsoft Windows and Office.

This leads to the assumption that you can enter your tabulated data into Excel and save as a pipe delimited CSV right? Wrong. It is next to impossible to do this in Excel unless you change some system wide settings. To which my first response was WTF?

Luckily, Python came to my rescue and all I needed to do was this:

>>> import csv
>>> old_file = csv.reader(open('blah.csv'), dialect='excel')
>>> new_file = csv.writer(open('ANDY.csv', 'w'), delimiter='|')
>>> for record in old_file:
...     new_file.writerow(record)

Of course, this doesn’t help the average person in the street who doesn’t have my l33t Python skills. So I’ll be changing the interface format as soon as I get a chance.

Gerald is being considered for use in the SQLPython toolkit. For them to get full value I will need to make a number of changes to the code. Luckily for all of us these were on the development roadmap anyway, so I’ve just moved them up the priority list.

As other people have shown an interest in the tool I have also invested in a little infrastructure and have fired up Trac for the sourceforge project. Gerald now has a wiki and, more importantly, a ticketing system for bug reports and feature requests. I’ve put the changes coming for release 0.3 in a number of tickets and you can track progress for the release using the version 0.3 roadmap.

• Fixed a bug in some connections to PostgreSQL
• Removed references to database links without passwords in Oracle
• Converted the package to use setuptools and from this release onward it is installable using easy_install

The last change was at the request of the SQLPython project, if you haven’t taken a look at that wonderful utility yet, please do. To support them it is likely that the next release of Gerald will support SQLite.

Please download, install and enjoy. Bug reports. tumultuous praise or cash bribes to the usual address please.