DownloadWelcome to the project page for pyDaSSQLiteMan (Python Data and SQLite Manager). This application is a Python Tkinter application designed to enable easy SQLite database file manipulation, and an easy method to run SQL styled queries on CSV files.
If you're not downloading the pre-compiled executable you will need Python to run this app. You can download it from http://www.python.org/ . I'd recommend something after version 3. Testing has been Windows based.
SQLite is a free database format released into the public domain. See http://www.sqlite.org/
Please check out the Wiki Home page https://sourceforge.net/p/pycsvdb/wiki/Home/ and the General Help page (https://sourceforge.net/p/pycsvdb/wiki/General%20Help/) to find extra information and help.
Please check out the Wiki Home page for an introduction.
Features
- SQLite management with SQL
- Import and Export Delimited files (CSV, PSV etc)
- View simple Spatial objects in WKT, WKB, Spatialite, and Geopackage (all experimental)
- Query data using SQL
- Pre-built method for importing the Australian Georeferenced National Address File (G-NAF)
Project Samples
License
BSD LicenseFollow pyDaSSQLiteMan
User Reviews
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What does the program do in general? The program is generally incomprehensible. I used a lot of programs for working with SQLite, since I have a database in it. How to connect the database is not convenient at all, why by default press the "use memory" button? Who needs it, they will put it themselves. If you want someone to need the program, make it so that it is convenient for others, and not just you. Well, I indicated the base, I select the table on the left and click the "Run" button, but the program writes an error that I can not even copy. Do the processing of pressing CTRL + C or add the context menu and copy the item there. I switched to pyqt, there by default out of the box all the amenities familiar to users work out of the box.
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This has enabled me to query Geopackages and other SQL in amazingly flexible ways. I have even been able to analyse CSV files quickly and easily by importing them and running SQL queries over them.