Skip to main content

Using BINDEVENT to ease FoxPro Grid issues

BINDEVENT is one of those great FoxPro commands that you never think of until you need it but when you do, you really appreciate it and you'll want to immediately refactor your code (hmmm- this sounds like a good Refactoring rule for the Code Analyst).

I was updating a client's older VFP system that used a lot of grids with RightClick methods. Lots of older programs do the same thing: putting code directly into the rightclick method of each columns' Text1 control. It's a real pain later on - especially if you ever reset the recordsource (which rebuilds the columns from scratch). In addition, if you use Page Up and Page Down to scroll through the various pieces of code, you get to see each individual column's method, which can get very tedious if you have a lot of grids.

Now, when you use BINDEVENT, it's a lot less code and a lot easier to manage. I put the actual rightclick code into a method either on the form or grid and then just do:

FOR EACH loColumn IN THIS.Grid.Columns
BINDEVENT(loColumn.text1,"Rightclick",;
THIS,"ColRightClick")
ENDFOR

When the user right-clicks in the grid, it calls the ColRightClick method.

Is this easier than putting THIS.ColRightClick() in each Text1 object? Maybe not if you only have two or three columns; but most of the grids I work with have lots of columns. Using this approach means I can keep my code OUT of the grid's columns and accomplish this in only three lines of code.

Comments

Garrett said…
Yup, BINDEVENT() is really useful in this situation.

The question is, is it more useful here than MemberClasses?
September 7, 2006 at 9:15 PM
Post a Comment

Popular posts from this blog

Elevating Project Specifications with Three Insightful ChatGPT Prompts

For developers and testers, ChatGPT, the freely accessible tool from OpenAI, is game-changing. If you want to learn a new programming language, ask for samples or have it convert your existing code. This can be done in Visual Studio Code (using GitHub CoPilot) or directly in the ChatGPT app or web site.  If you’re a tester, ChatGPT can write a test spec or actual test code (if you use Jest or Cypress) based on existing code, copied and pasted into the input area. But ChatGPT can be of huge value for analysts (whether system or business) who need to validate their needs. There’s often a disconnect between developers and analysts. Analysts complain that developers don’t build what they asked for or ask too many questions. Developers complain that analysts haven’t thought of obvious things. In these situations, ChatGPT can be a great intermediary. At its worst, it forces you to think about and then discount obvious issues. At best, it clarifies the needs into documented requirements. ...
Post a Comment
Read more

Respect

Respect is something humans give to each other through personal connection. It’s the bond that forms when we recognize something—or someone—as significant, relatable, or worthy of care. This connection doesn’t have to be limited to people. There was an  article  recently that described the differing attitudes towards AI tools such as ChatGPT and Google Gemini (formerly Bard). Some people treat them like a standard search while others form a sort of personal relationship — being courteous, saying “please” and “thank you”. Occasionally, people share extra details unrelated to their question, like, ‘I’m going to a wedding. What flower goes well with a tuxedo?’ Does an AI “care” how you respond to it? Of course not — it reflects the patterns it’s trained on. Yet our interaction shapes how these tools evolve, and that influence is something we should take seriously. Most of us have all expressed frustration when an AI “hallucinates”. Real or not, the larger issue is that we have hi...
Post a Comment
Read more

When A Machine Starts To Care

“Any sufficiently advanced technology is indistinguishable from magic.” Arthur C. Clarke (1962)  I first used that quote when I was starting out in the tech industry. Back then, it was a way to illustrate just how fast and powerful computers had become. Querying large datasets in seconds felt magical—at least to those who didn’t build them.  Today, we’re facing something even more extraordinary. Large Language Models (LLMs) can now carry on conversations that approach human-level fluency. Clarke’s quote applies again. And just as importantly, many researchers argue that LLMs meet—or at least brush up against—the criteria of the Turing Test.  We tend to criticize LLMs for their “hallucinations,” their sometimes-confident inaccuracies. But let’s be honest: we also complain when our friends misremember facts or recount things inaccurately. This doesn’t excuse LLMs—it simply highlights that the behavior isn’t entirely alien. In some ways, it mirrors our own cognitive limits....
Post a Comment
Read more