Ever wanted to run a Levenshtein Distance algorithm inside Zoho Deluge? No? Me neither, but I did it anyway.
I built a fully functional fuzzy matching system inside Zoho, brute-forcing a dynamic programming solution using Maps and recursive list generation.
- Does it scale? Not really.
- Does it work? Absolutely.
- Did I need to do this? Not at all, but it was fun.
I don’t even use this anymore because I found a better way around fuzzy matching for my needs, but hey, if you ever need a low volume Levenshtein calculator inside Zoho, now you have one. 🤷♂️
How It Works
The function computes Levenshtein Distance, a metric for fuzzy string similarity, by calculating the number of insertions, deletions, and substitutions needed to convert one string into another.
This method is commonly used in spell-checking, DNA sequencing, and fuzzy search algorithms—so obviously, I decided to implement it inside Zoho, because why not?
🔹 The Challenge: Zoho doesn’t support 2D arrays natively.
🔹 The Solution: I brute-forced it using Map-of-Maps as a manual matrix.
🔹 Bonus: I even used recursion to generate number sequences (which is completely unnecessary but kinda cool).
Code & Example Usage
Main Function: standalone.levenshteinDistance
📌 Input: {"s": "kitten", "t": "sitting"}
📌 Output: "3"
Code:
string standalone.levenshteinDistance(Map args)
{
// Retrieve input strings.
s = args.get("s");
t = args.get("t");
m = s.length();
n = t.length();
// If one string is empty, return the length of the other.
if(m == 0)
{
return n.toString();
}
if(n == 0)
{
return m.toString();
}
//info "Length of s: " + m.toString() + ", Length of t: " + n.toString();
// ------------------------------
// Get index lists via the helper function.
// The helper function standalone.UtilitygetListOfLength returns a comma-separated string.
// For example, if (m+1) is 5, it returns "0,1,2,3,4".
// ------------------------------
indices_m_str = standalone.UtilitygetListOfLength({"myLength":m + 1});
indices_n_str = standalone.UtilitygetListOfLength({"myLength":n + 1});
//info "indices_m_str: " + indices_m_str;
//info "indices_n_str: " + indices_n_str;
// Convert these comma-separated strings into lists of long values.
indices_m = list();
numList_m = indices_m_str.toList(",");
for each numStr in numList_m
{
if(numStr.trim() != "")
{
indices_m.add(numStr.trim().toLong());
}
}
indices_n = list();
numList_n = indices_n_str.toList(",");
for each numStr in numList_n
{
if(numStr.trim() != "")
{
indices_n.add(numStr.trim().toLong());
}
}
//info "indices_m list: " + indices_m.toString();
//info "indices_n list: " + indices_n.toString();
// ------------------------------
// Initialize matrix as a map-of-maps.
// Each row is a map keyed by the column index.
// ------------------------------
matrix = Map();
for each i in indices_m
{
rowMap = Map();
for each j in indices_n
{
rowMap.put(j,0);
}
matrix.put(i,rowMap);
}
// Set up the first column: matrix[i][0] = i.
for each i in indices_m
{
rowMap = matrix.get(i);
rowMap.put(0,i);
}
// Set up the first row: matrix[0][j] = j.
firstRow = matrix.get(0);
for each j in indices_n
{
firstRow.put(j,j);
}
// ------------------------------
// Compute Levenshtein distances.
// ------------------------------
for each i in indices_m
{
if(i == 0)
{
continue;
}
for each j in indices_n
{
if(j == 0)
{
continue;
}
// Determine cost: 0 if characters are the same, otherwise 1.
if(s.subString(i - 1,i) == t.subString(j - 1,j))
{
cost = 0;
}
else
{
cost = 1;
}
deletion = matrix.get(i - 1).get(j) + 1;
insertion = matrix.get(i).get(j - 1) + 1;
substitution = matrix.get(i - 1).get(j - 1) + cost;
minValue = deletion;
if(insertion < minValue)
{
minValue = insertion;
}
if(substitution < minValue)
{
minValue = substitution;
}
rowMap = matrix.get(i);
rowMap.put(j,minValue);
}
}
result = matrix.get(m).get(n);
//info "Levenshtein distance: " + result.toString();
return result.toString();
}
Recursive Helper Function: standalone.UtilitygetListOfLength
📌 Input: {"myLength": 6}
📌 Output: "0,1,2,3,4,5"
Code:
string standalone.UtilitygetListOfLength(Map args)
{
myLength = args.get("myLength");
//info "Input myLength: " + myLength;
if(myLength == null || myLength <= 0)
{
//info "Base case reached (myLength <= 0). Returning empty string.";
return "";
}
else
{
// Recursively get the string for (myLength - 1)
prevStr = standalone.UtilitygetListOfLength({"myLength":myLength - 1});
//info "Previous string returned for myLength " + (myLength - 1).toString() + ": " + prevStr;
if(prevStr.equals(""))
{
result = "0";
}
else
{
result = prevStr + "," + (myLength - 1).toString();
}
//info "Returning result for myLength " + myLength.toString() + ": " + result;
return result;
}
}
This helper function is completely unnecessary, but I made it anyway. Instead of just looping, it recursively builds a CSV string of numbers—which is both inefficient and hilarious. 😆
Why Did I Do This?
Because it wasn't supposed to work—but it does.
- Zoho doesn’t support Levenshtein distance? I built it anyway.
- Zoho doesn’t have fuzzy matching? Now it does.
- Zoho doesn’t support 2D arrays? I brute-forced a matrix using Maps.
- Does this scale for massive data? Nope, but it’s perfect for low-volume cases.
Thoughts? Ideas? Have you ever done something in Zoho just because you wanted to see if it was possible? Let me know. 😆
TL;DR:
📌 I brute-forced Levenshtein Distance into Zoho
📌 Zoho wasn’t built for this, but I made it work anyway
📌 Does it scale? No. Does it work? Yes.
📌 Do I use it? Nope. Was it fun? Absolutely.
Let me know what you think! 🚀
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