Is there a way to add records inline, like Postman does when adding params? This gif explains the desired result:
Related
I'm using datatables and yadcf to filter a table. Now I'd like to take all the table row id values, for example, and use those as arguments in a POST request. How can I "collect" the values of these ids from the result of the filters that have been applied? I've seen this example, which doesn't seem to apply to yadcf, but is similar to my use-case.
I was able to get the information I wanted using the answer found here. I didn't realize that jQuery will select only the visible elements, which is what I want. So, after applying the yadcf filter to my table it's simple to select all the tr.id values resulting from the filter.
Yes, the submit content is only the visible row with datatables.
If you have 5 rows and after filter 2 rows, if you click on submit button with the active filter only 2 rows will be submitted.
And if, conversely, you still wanted to submit all the elements of the table despite the filtering, on the onsubmit there is a yadcf function that you just have to execute which deactivates all active filtering to submit the entire table like this :
var table = $('#mytable').DataTable( {}) ;
document.onsubmit = function(){
yadcf.exResetAllFilters(table) ;
};
I am trying to insert data to big query using google cloud dataprep, I did create recipe and add first row as header row, but when I am trying to run on multiple files it insert the header row to my big query table also.
Anybody facing this problem ?
Welcome to StackOverflow, Andy!
I think I'm correctly understanding your problem, but I want to make sure since I'm making some assumptions:
You have multiple files imported in Dataprep
You created a recipe for the first file and convert row 1 to be a header
You apply a UNION step to merge the additional files
Your output contains the header rows for the additional files
If that's correct, the issue is that the header rows in the other files aren't being removed simply because Dataprep doesn't know what they are. In most cases, Dataprep will detect the file structure and you won't have to manually specify the header row. When that fails, however, UNION steps get a little funny like this—but you can definitely fix it in Dataprep.
Workarounds:
Apply a Recipe to Each Input File
Simply add a recipe to each file that converts the first row to a header—then instead of selecting your original file in the main recipe's UNION, select the other recipes (Dataprep will run them before merging the data).
While this takes some extra effort, it's doable for a small number of files. The advantage here is that you don't have to worry about whether your data may contain the header value—but I'd recommend using the other option if you're able to.
Use a Custom Filter Formula to Delete All Header Rows
The other option is a bit more dependent on your data, but lets you do everything in the main recipe. For example, after setting headers from the first file and applying your UNION you would add a "Filter rows using custom formula" step (or clicking Filter Rows > On column values > Custom Filter...), then match using a column that wouldn't contain the header string (e.g. CustomerID == "CustomerID")—integer columns work great since you don't have to worry if the value could contain the header string. The Resulting wrangle script should look something like this:
header sourcerownumber: 1
[union step goes here]
filter type: custom rowType: single row: CustomerID == 'CustomerID' action: Delete
Note: You may be tempted to do this by using $sourcerownumber, but that doesn't exist due to the union. I'm hoping that they'll eventually support it for this use case though.
These aren't the only ways you could eliminate the headers, but should provide two easy options for you.
As a pro-tip, you can copy a line of the wrangle script above and paste it after clicking "New Step" in your recipe and it'll set up the filter the same way that I did so you don't have to start from scratch. Just change the column name/value and you should be good to go.
Again, welcome to the site—and if any of the assumptions above are incorrect, update your original question with the additional details and let me know in a comment and I'll be happy help you out further.
I have to parse a Json file and show it into a Nattable.
Using this tutorial i am able to parse json and display in Nattable.
But as shown in screenshot for cat column its showing list values as it is .
Is there a way from which i can show list values as Dropdown.
A dropdown in NatTable is intended for editing. I suppose you don't want to support editing but only showing values right? For that you can try to use the TableCellPainter for that column. That painter tries to render the data as subcells in case the data structure is an array or a Collection.
Found many examples on simple API queries but nothing close to what i want.
I have my space key and page ID, this is my table
How can i append hyperlinks, and attach a file in cell 3 for each build using REST API.
get the page : add expand=body.storage as a query parameter to get the body.storage.value which holds the html tags. Then parse the get response to edit the specific value in the 's then when updating the page update the body.storage.value withing your json like in the example: https://docs.atlassian.com/atlassian-confluence/REST/latest-server/#content-update
I have a table created with DataTable of Google Chart, which has a column with a drop-down list. In this way the user can set the proper value of a row.
I am working in Python and Flask and I can retrieve the request data correctly. The problem is that the table, given the amount of data, is showed in pages, each one with 20 rows. When I retrieve the request I get only those 20 rows, so I have no way to know what the user set in the other pages.
How can I get the values of all pages?
Moreover, I noticed that when I change page and then I go back, the table forgets the user changes, so I think I should be careful also to this fact.
Finally, I solved the problem by using a dictionary containing all the changes made to the table and updating the html string inside the table to keep the content updated.