Converting TPS files to SQL
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Published on Dec 13, 2017
Many people are still converting their Clarion for Windows applications from using the old Topspeed file format (.TPS) to various versions of SQL. We first undertook this process with a client in the year 2001! We had a lot on our plates back then with 'Year 2000' concerns about the world coming to an end when all dates in the format dd/mm/yy would suddenly become 01/01/00 – fortunately the fix for Clarion programs was very simple and life continued. Then, in Australia, we had the introduction of the Goods and Services Tax (GST). We were on a roll, so why not convert our Clarion applications to use SQL at the same time!
As usual, there is an easy way and the not-so-easy way and, as usual with Clarion, the easy way was to write a template that would handle most of the conversion processes for us. Thus, the GWBSQL template was born to convert Clarion dictionaries and data to use SQL. We were working with MSSQL, Interbase/Firefox and PervasiveSQL databases back then, so the template handles all of these versions of SQL.
This template is useful for converting small and large databases, and can handle small and large Clarion Dictionaries. The dictionary we were converting was largish, but our conversion was complicated by the fact that our TPS files were becoming corrupted due to a bad batch of NICs that were around at that time – although we didn't discover that until shortly afterwards. So our conversion needed to be a rushed job on a live database handling over 1000 order a day in a busy shop.
To help minimize disruption to the business we agreed to do a file-by-file conversion of the data – something we'd still consider doing today, and is easy enough to do with Clarion for Windows which can easily cope with multiple file formats. It's important though to consider which files to convert first, and pay particular attention to files in parent-child relationships. The GWBSQL template was designed to help with this process.
If you're undertaking a conversion of data from TPS to SQL you might find the templates useful as a tool to handle the whole job, or as a learning tool to prepare you for some of the issues you'll face in making the conversion.
If you're uncomfortable, or completely at sea when attempting the conversion, our services are available to help you. We can generate your database and data conversion scripts for you as a good means to get you started. We can also investigate your application and advise you of the best strategy for taking full advantage of the extra power SQL databases can offer you.
In this section, you will get SQL Server 2017 on Docker. After that you will install the necessary dependencies to create .NET Core apps with SQL Server.
Step 1.1 Install SQL Server
- In order to run SQL Server on your Mac, we are going to use the SQL Server on Linux Docker Image. For this, you need to install Docker for Mac.
- Configure at least 4GB of memory for your Docker environment, also consider adding multiple cores if you want to evaluate performance. You can do this in the Preferences - Advanced option on the menu bar.
- Next, start a new Terminal prompt and use the following commands to download and start the SQL Server on Linux Docker image. Make sure to use a strong password with special characters.
You now have SQL Server running locally in Docker! Check out the next section to continue installing prerequisites.
Step 1.2 Install Homebrew and .NET Core
Free Tps To Sql Conversion For Mac Windows 7
If you already have .NET Core installed on your machine, skip this step.
Sql Conversion Functions
Install .NET Core by downloading the official installer. This installer will install the tools and put them on your PATH so you can run dotnet from the Console.
You have successfully installed .NET Core on your Mac. You now have everything you need to start writing your C# apps with SQL Server!
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Have Questions?
Free Tps To Sql Conversion For Mac 64-bit
Happy to help! You can find us on GitHub, MSDN Forums, and StackOverflow. We also monitor the #SQLServerDev hashtag on Twitter.