Debugging Data Extraction Pipelines

From Text to Result

A data extraction pipeline turns formatted text into a useful result. Imagine a file containing lines such as New Revision: 39772. The task is not merely to find one number. It is to find every matching revision number, convert the extracted values into numbers, calculate their average, and verify that each stage produced the expected data.

Debugging becomes easier when you treat the process as a sequence of visible stages. Instead of looking only at the final average, inspect the extracted strings, the converted integers, the sum, and the final formatted result. The first stage whose output is wrong identifies where the problem begins.

Matching the Revision Pattern

The input follows a consistent structure: the literal text New Revision: followed by a number. A regular expression can describe that structure. The literal part identifies the correct lines, while a capturing group isolates the digits that should become the extracted value.

pattern = r"New Revision: (\d+)"

In this generated pattern, New Revision: matches the required label. The parentheses identify the capturing group, and the digit-matching part identifies the numerical portion. The capturing group is important because the task is to return the number rather than the entire line.

The findall() method applies the pattern across the available text and collects all matches. Because the pattern contains a capturing group, the collected results are the captured numerical strings. They look numeric, but they are still strings at this stage.

Tracing the Extracted Values

import re text = "New Revision: 39772\nNew Revision: 39726\n" pattern = r"New Revision: (\d+)" extracted = re.findall(pattern, text) values = [int(item) for item in extracted] total = sum(values) average = total / len(values) result = int(average) print(extracted) print(values) print(total) print(average) print(result)

["39772", "39726"]
[39772, 39726]
79498
39749.0
39749

The first printed list contains quoted values, showing that the extracted results are strings. The second list contains integer values without quotes. That distinction matters because arithmetic requires the values to be converted before the sum and average are calculated.

Calculating the Average

Once the extracted values are integers, calculate the average in two operations. First, add all the values. Then divide that sum by the number of values. The resulting average is then converted to an integer for the requested formatted result.

Finding the First Wrong Stage

A final result can be wrong for several different reasons. The pattern might match too few lines, findall() might return an unexpected collection, conversion might not happen, or the sum and division might be incorrect. Printing intermediate values separates these possibilities instead of treating the whole program as one opaque operation.

Common Pipeline Mistakes

• Treating the values returned by findall() as integers

  findall() returns strings. Values such as "39772" look numeric but have not yet been converted.

  Fix: Apply int() to each extracted value before calculating the sum or average.

• Checking only the final average

  The first error may have occurred during matching or conversion rather than during calculation.

  Fix: Print the intermediate collection after extraction, the integer collection, the sum, and the average.

• Extracting the whole formatted line instead of only the number

  The task requires the numerical values, not the label and the number together.

  Fix: Match the literal line structure and use a capturing group around the digits.

• Using the wrong number of values in the average

  The average requires the sum to be divided by the count of values actually being averaged.

  Fix: Check the extracted collection and use its count when calculating the average.

Practice the Trace

For a source-based verification target, the material reports an average of 38549 for mbox.txt and 39756 for mbox-short.txt. If your program produces a different result for either file, inspect the intermediate stages rather than assuming the final conversion is the problem.

Pipeline Checklist

1. Start with the consistent input format and write a regular expression that matches the required label while capturing only the digits. Use findall() to collect every captured value. Remember that the returned values are strings, so convert them to integers before arithmetic. Calculate the average from the integer values, then convert the average to an integer. Finally, print intermediate values so you can locate the first incorrect stage.