readBlocking multiple tags and DB insert

Ignition
1

The readBlocking example in the docs shows using a for loop.

If doing a multi-column DB insert of these values, what is the best method?

I can think of a crude one using if, elif statements. I bet someone has a nice one-liner.

I'm only working with a couple of tags for testing now and I will only be adding a few more. I don't mind manually adding extra ? into the Prep query at this stage. I know if it was many tags and subject to a lot of change, Phil etc have provided nice examples of dynamic building of ? based on the length of items.

8.1.25, Gateway Timer Script

2

This is entirely dependent on your table structure. Show more of what you are trying to achieve.

3

Wide table, index AI, multiple columns and a datetime with CURRENT_TIMESTAMP(). (MariaDB).

The multiple columns are all floats. 1-second granularity.

I've done similar in past with 79, looking for guidance on the most efficient 81 methods with readBlocking etc.

4

If you are just using the values, a one-liner would be something like:

tagList = ['[provider]path/to/tag1',
          '[provider]path/to/tag2',
          '[provider]path/to/tag3',
          ...
          '[provider]path/to/tagN'
         ]

values = [qValue.value for qValue in system.tag.readBlocking(tagList)]

However, if you also need to iterate over something else, (example: generate the column names from the last portion of the tag path), it becomes more efficient to use a for loop and zip:

tagList = ['[provider]path/to/tag1',
           '[provider]path/to/tag2',
           '[provider]path/to/tag3',
           ...
           '[provider]path/to/tagN'
          ]

colNames = values = []

for tag, qValue in zip(tagList, system.tag.readBlocking(tagList)):
	colNames.append(tag.split('/')[-1])
	values.append(qValue.value)
1 Like
5

you can also do like this ,

path = ["[provider]path/to/tag1",
"[provider]path/to/tag2"]
qualifiedValues = system.tag.readBlocking(path)
print qualifiedValues
print list(map(lambda x : x.value,qualifiedValues))