Скачать или смотреть How to Parse Repeating Headers with Data Groups in .NET Using Regex

Learn how to effectively parse and associate data fields with their corresponding headers in `.NET` using `Regex`. This guide provides a step-by-step approach for handling repeating headers and data connections.
---
This video is based on the question https://stackoverflow.com/q/122775/ asked by the user 'user13810' ( https://stackoverflow.com/u/13810/ ) and on the answer https://stackoverflow.com/a/123303/ provided by the user 'Jeffrey Knight' ( https://stackoverflow.com/u/83418/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, comments, revision history etc. For example, the original title of the Question was: Repeating Header in a group

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 3.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 2.5' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Understanding the Problem of Parsing Repeating Headers

When dealing with text that includes headers followed by associated data, it becomes crucial to ensure that each piece of data is correctly linked to its corresponding heading. This challenge is particularly evident in scenarios involving structured text where such headers may repeat throughout the data.

The Example Scenario

Imagine you have a list structured as follows:

[[See Video to Reveal this Text or Code Snippet]]

Your goal is to extract each group of data and associate it accurately with the relevant headings. The expected output should look like this:

[[See Video to Reveal this Text or Code Snippet]]

Devising a Solution Step-by-Step

To tackle this parsing problem, a well-structured approach is necessary. Here are the steps to follow to achieve your desired output:

Step 1: Read Input Line by Line

Instead of jumping directly into using regular expressions, start by processing the input text line by line. This will help you avoid complications that may arise from trying to match multiple patterns at once. In a programming context, you could use a loop to iterate through each line of your text file or string.

Step 2: Identify and Store Headers

As you parse each line, keep an eye out for lines that represent headers. When you find a header, save it temporarily as you will need to reference it later when you process the associated data.

Store headers in variables.

Use an array or a list to collect them as you go along.

Step 3: Extract Data Groups

When you encounter a line labeled as a group (e.g., (Group 1)), begin capturing the subsequent data lines that follow.

Continue reading until you reach a new header or the end of the data.

Store these data lines in an array or list, ensuring that they’re tied to the most recently found header.

Step 4: Assemble the Output

After you've assembled the data for each group alongside its headers, format the output in the desired structure.

Concatenate the group label, headers, and the associated data to form the complete result for each group.

Ensure to handle changes in headers whenever they occur, storing the new headers correctly before processing the new set of data.

Step 5: Confirmation and Adjustment

Review the final output, ensuring it meets expectations. You may need to tweak the process slightly if your inputs vary in structure.

Conclusion

By following a systematic approach to parsing text with repeating headers and associated data, you can effectively generate your desired output. This method emphasizes clarity and simplicity, allowing you to handle changes in headers easily without getting lost in complex regex operations.

If you find that your dataset changes frequently, consider creating a function to automate this parsing process, so you can reuse it across different datasets.

With these strategies in hand, you can confidently tackle any textual parsing challenge you face in the .NET environment.