Python Programming
I came to Python fairly
late, but I like its power - there is a module to do almost anything.
In the last few years, I have used Python, both at home and at
work to do tasks such as:
- Copy an Access database to an SQLite database
- Merge a set of Excel spreadsheets into one gigantic Excel spreadsheet
- Copy a set of Excel spreadsheets into an SQLite database
- Test a proprietary ODBC driver
- Compare a configuration file with database and report inconsistencies
- Locate
a set of Team Foundation Change sets, find the matching incidents in a
Bugzilla (MySQL) database and generate a release note as an HTML file (optionally converted to PDF).
- A
platform independent GUI database browser, with a tree control to
display the list of tables and a string grid to display a selected
table.
- Regularly monitor a MySQL database and generate emails when changes are noticed
- Construct a set of Makefiles from a set of Visual Studio 2015 project files (XML).
- Scan an ini file and construct a summary in an easy-to-read PDF file.
- Scan
a set of log files looking for process exits, and try and find the
causes of the exits, summarizing the results in an Excel spreadsheet.
- Scan
40,000 folders for XML files and Photos, parse the XML files and
construct an SQLite database of the XML contents and the matching photos
- Construct
a Web page of selected columns from an Excel spreadsheet.
After some editing by Logan Kleinwaks, this became http://www.jewishgen.org/danzig/findingaidcivil.php
- Construct SQL to build a database schema from a database dictionary
- Construct an XML representation of a database schema from the above SQL script
- Monitor Solar Power Generation as reported by the web server in the communications gateway and store the current figure in an SQLite database every five minutes (using a Raspberry Pi)
- Graph the daily Solar Power production as stored in an SQLite database.
- Convert an obsolete Atari ST database to an Excel Spreadsheet
- merge two address lists, one with email addresses, the other without, one an .xls file and the other an .xlsx file.
To achieve all these I've used the following modules (amongst others):