Many readers have asked whether there's Python GUI software for creating, managing, and analyzing MySQL databases. I have just released such software as completely open source. Source code is available on GitHub as follows:
1. Install Git on your machine from github.com 2. Initialize the target directory with "git init" 3. Download the software using "git pull git://github.com/dwbarne/PYLOTDB" 4. Read README_first.rtf file using Microsoft Word and follow directions. PYLOTDB consists of two codes, PylotDB and Co-PylotDB. The software allows users to access either local or remote MySQL servers and easily display table data in a GUI format. In PylotDB, data can be filtered, and table columns are indexed with radiobuttons and checkboxes so data can be easily selected for plotting or statistical analysis. Plotting capability includes X-Y, semi-log, log-log, Kiviat (radar charts), scatter, and scatter with polynomial curve fits of the data. Entire databases, selected databases, or selected tables in selected databases can be backed up and restored as desired. Interfaces are provided for individual entry edits and additions. PylotDB's companion software Co-PylotDB is used to send data files to a user-selected database table. If data files are in YAML format, PylotDB can automatically extract each entry in the file, expand the database table with new fields with names taken from the YAML entries, and insert the data in those fields for plotting and analysis. This is a tremendous time saver for analysts. This allows the cycle of "data capture to storage to analysis" to be completed in a matter of minutes. A powerful feature of PylotDB is the storage buffer where selected data from any table on any server can be stored and mathematically combined to generate new data not currently in any accessed table. The new data can then be plotted along with other data from the currently displayed table. This allows the user to generate desired data on the fly without the necessity of modifying any of the stored tables. PYLOTDB's dependencies include matplotlib, numpy, MySQLdb, Python MegaWidgets (Pmw), and YAML. All of these dependencies are included in the download for Windows machines only. They can easily be found on the web for Mac or Linux machines. Sample databases are also included to help users get up to speed quickly. We are using this software in my company for analyzing results from our computer performance modeling analysis, but it can be used for any type of analysis where database storage and analysis is desired. Hope this proves helpful for your readers.
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