Paragraph Counter
Count paragraphs and see how long each one really runs.
Find which lines repeat in a list, and where they are.
| Duplicated line | Times | On lines |
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The Duplicate Line Checker reports duplicates rather than removing them: every repeated line is listed with its occurrence count and the exact line numbers it appears on, which is what you need when you are diagnosing a data problem rather than tidying a file.
Removing duplicates is easy. Finding out which ones were duplicated, how many times, and on which lines is the part that actually matters when you are investigating a data problem rather than just cleaning it up.
This reports rather than removes. Every line that appears more than once is listed with its occurrence count and the line numbers it appears on, so a duplicated email address in an import file can be traced back to both rows. Comparison can ignore case, leading and trailing whitespace, and a chosen column of a delimited file — that last one being how you find rows sharing an ID even when the rest of the row differs.
You get the line numbers of every collision, which a de-duplicating tool throws away.
Compare only one field of a delimited row to find records sharing an ID even when the rest differs.
Catch the duplicates that differ only by capitalisation or a trailing space.
The entries that appear exactly once are listed separately, which is often the half you actually want.
Hash-based counting rather than nested comparison, so tens of thousands of lines stay fast.
An import file, an export, a mailing list or any set of lines.
Ignore case and surrounding whitespace, or compare only one column of a delimited file.
Each repeated line is shown with its count and the exact line numbers it appears on.
The duplicate list, the unique list and the line numbers can each be copied separately.
No, it reports them. That is the point — when you are diagnosing a data problem you need to know which rows collided and where, not just get a shorter file. Use the Duplicate Line Remover when you want them gone.
Yes. Set the delimiter and the column number and only that field is compared, which is how you find two rows sharing a customer ID even when their other fields differ.
For email addresses and usernames, yes — those are conventionally case-insensitive, so "Alex@example.com" and "alex@example.com" are the same person. For identifiers and codes, no, since case may be significant.
A line whose comparison key matches another line's. With trimming and case folding on, " Apple " and "apple" are duplicates. With both off, they are three different lines.
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