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Kill duplicate files, finding partial files as well

Project description

https://badge.fury.io/py/killdupes.png https://travis-ci.org/numerodix/killdupes.png?branch=master https://pypip.in/wheel/killdupes/badge.png https://pypip.in/license/killdupes/badge.png

Python version support: CPython 2.6, 2.7, 3.2, 3.3, 3.4 and PyPy.

How it works

killdupes scans your filesystem to find duplicate files, partial files and empty files.

It performs n:n comparison of files through md5 hashing and heavy use of dictionaries. Execute with wildcard, or input file containing file names to check.

The method:

  1. Scan all files, find the smallest.

  2. Read read size amount of bytes (equal to the remaining size of the smallest file, or at most CHUNK size) from all files into records.

  3. Hash all records, use hashes as keys into offsets[current_offset] dict.

  4. Files in the same bucket are known to be equal up to this offset.

  5. Continue until at least two files remain that are still equal at all offsets.

  6. Equal files are either a duplicate case (if they are the same size), or one is partial relative to the other (if not the same size).

Memory consumption should not exceed files_in_bucket * read_size.

The algorithm adapts to file changes; it will read all files until eof regardless of the filesize as recorded at startup.

Installation

$ pip install killdupes

Usage

$ killdupes.py 'tests/samples/*'
Empty files:
X    0.0  B  14.03.14 17:39:48  tests/samples/empty
Incompletes:
=    2.0  B  14.03.14 18:17:43  tests/samples/full
X    1.0  B  14.03.14 18:17:26  tests/samples/partial
Duplicates:
=    2.0  B  14.03.14 18:17:43  tests/samples/full
X    2.0  B  14.03.14 18:17:37  tests/samples/full2
Kill files? (all/empty/incompletes/duplicates) [a/e/i/d/N]

If there are many files to scan it will display a progress dashboard while working:

176.1 KB | Offs   0.0  B | Buck 1/1 | File 193868/600084 | Rs   1.0  B

The dashboard fields:

  1. Total bytes read

  2. Current offset of reading

  3. Current number of buckets

  4. File/files in this bucket

  5. Readsize at this offset

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