TextBuilder | Like a SwiftUI ViewBuilder , but for Text | Frontend Framework library

Your lambda is timing out after 3 seconds. From your error message:

Task timed out after 3.00 seconds

I think increasing the timeout should help. In CloudFormation you have Timeout parameter for that:

The amount of time that Lambda allows a function to run before stopping it. The default is 3 seconds. The maximum allowed value is 900 seconds.

Try like this

The contents of the console buffer can be retrieved with the PS script from PowerShell's team blog Capture console screen mentioned in a comment, now edited into OP's question.

The last line could also be changed to copy the contents to the clipboard instead of returning it.

EDIT: you can also try and use pdftotext library

pdf2image is a simple wrapper around pdftoppm and pdftocairo. It internally does nothing more but calls subprocess. This script should do what you want, but you need a wand library as well as pyocr (I think this is a matter of preference, so feel free to use any library for text extraction you want).

Not having enough detail for a specific answer, here's how you solve such problems in general:

1. Ensure you understand the Open XML specification and valid Open XML markup on an appropriate level of detail.

   • If you don't understand what w:document, w:body, w:p, w:r, w:t, w:tbl, etc. are and how they relate to each other, you have no chance.
   • You must look at actual Open XML markup, e.g., using the Open XML Productivity Tool or the Open XML Package Editor for Modern Visual Studios to get to an appropriate level of understanding and develop Open XML-based solutions.

2. Understand that most Open XML-related code transforms some source markup into some target markup. Therefore, you must:

   • understand the source and target markup first and then
   • define the transformation required to create the target from the source.

Depending on what you need to do, the Open XML Productivity Tool can help create the transforming code. If you have a source and target document, you can use the Productivity Tool to compare those documents. This shows the difference in the markup, so you see what markup is created, deleted, or changed. It even shows you the Open XML SDK-based code required to effect the change.

In my own use cases, I typically prefer to write recursive, pure functional transformations. While you need to wrap your head around the concept, this is an extremely powerful approach.

In your case, you should:

• take a few representative, manually-created samples of source (A.docx with "Vetaran" still to be replaced) and target (A.docx with "Veteran" replaced as desired) documents;
• look at the Open XML markup of the source and target documents; and
• write code that creates the target markup.

Once you have created code that at least tries to create valid target Open XML markup, you could come back with further questions in case you identify further issues.

You can read the selected value using the value property of the select tag. Try this:

As far as I understand, you want all new purchases to be positioned at the top. The rest to be lower than new purchases.

Before building the widget you can just sort the order of _purchase based on isRead. If isRead property is false give it a low sort order, making it show higher in an ascending order.

Here's a simple approach

• Convert image to grayscale
• Otsu's threshold
• Dilate to connect contours
• Find contours and extract ROI for each word
• Perform OCR and remove word

After converting to grayscale, we Otsu's threshold to obtain a binary image

Next we invert the image and dilate to form a single contour for each word

From here we find contours and extract the ROI for each word. Here's the detected ROIs

We throw each ROI into Pytesseract OCR. If the OCR result is a word we want to remove, we simply "delete" the word by filling in the ROI with white and replace it in the original image

With

For a question like this, you should supply a Minimum Reproducible Example as there is some code left out. Also, you should provide your test image. For this example, though, you cannot attach a multi-page TIFF, so a link to one would be good.

I was able to find this test image from this question. It's a 10 page TIFF.

Here's a solution using pyocr: