Logic Apps – Remove Diacritics in a String: A Step-by-Step Guide

Are you tired of dealing with strings that contain diacritics, making it difficult to process and analyze data in your Logic Apps? Well, you’re in luck because today, we’re going to explore a simple yet effective way to remove diacritics from strings using Logic Apps. So, let’s dive right in!

What are Diacritics?

Before we dive into the solution, let’s take a step back and understand what diacritics are. Diacritics are special markings or symbols added to letters or characters to indicate a change in pronunciation or to distinguish between similar-looking characters. Examples of diacritics include accents, umlauts, and cedillas.

Here are a few examples of diacritics:

• é (e with an acute accent)
• ü (u with an umlaut)
• ç (c with a cedilla)

Why Remove Diacritics?

There are several reasons why you might want to remove diacritics from strings in your Logic Apps:

1. Data normalization**: Removing diacritics helps to normalize data, making it easier to process and analyze.
2. String comparison**: Diacritics can make string comparisons tricky. By removing them, you can ensure accurate matches.
3. Character limitations**: Some systems or APIs may have character limitations, and diacritics can take up valuable space.
4. Search and filtering**: Removing diacritics makes it easier to search and filter data, as users may not always include diacritics in their searches.

The Solution: Using the Replace Function

Now that we’ve covered the why, let’s get to the how. One way to remove diacritics from strings in Logic Apps is by using the Replace function. Here’s an example:

replace(variables('originalString'), '[\\u0300-\\u036F]', '')

In this example, we’re using the Replace function to remove diacritics from the `originalString` variable. The regular expression `[\\u0300-\\u036F]` matches most diacritics, and the `”` replaces them with nothing, effectively removing them.

How the Regular Expression Works

The regular expression `'[\\u0300-\\u036F]’` is the key to removing diacritics. Here’s a breakdown of how it works:

• `\\u` matches a Unicode character in the range of 0300 to 036F.
• The `u` is an escape character to indicate that the following characters are in Unicode format.
• The `0300-036F` range covers most diacritics, including accents, umlauts, and cedillas.

Using the Replace Function in a Logic App

Now that we’ve covered the basics, let’s see how to use the Replace function in a Logic App. Here’s an example:

Step	Action	Inputs
1	Initialize variable	originalString: “Héllô Wørld”
2	Replace function	replace(originalString, ‘[\\u0300-\\u036F]’, ”)
3	Set variable	newString: outputs of replace function
4	Log information	Log newString: “Hello World”

In this example, we’re initializing a variable `originalString` with the value “Héllô Wørld”. We then use the Replace function to remove diacritics, and set the output to a new variable `newString`. Finally, we log the output to see the resulting string without diacritics.

Using a Custom Function

If you need to remove diacritics from multiple strings or want a more reusable solution, you can create a custom function. Here’s an example:

func removeDiacritics	string: (originalString: string) => {
  return replace(originalString, '[\\u0300-\\u036F]', '');
}

In this example, we’re defining a custom function `removeDiacritics` that takes a string input `originalString` and returns a new string with diacritics removed. We can then call this function from anywhere in our Logic App:

newString: removeDiacritics(originalString)

Conclusion

Removing diacritics from strings in Logic Apps is a simple yet powerful technique to normalize data and ensure accurate string comparisons. By using the Replace function with a clever regular expression, you can easily remove diacritics and make your data more manageable. Whether you’re dealing with user input, data imports, or API responses, this technique is sure to come in handy.

So, the next time you encounter a string with diacritics, remember this guide and give your data the normalization it deserves. Happy coding!

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