File manifest tools: Damage and FCheck


Damage logo

Damage (either DAtaMAnifestGEnerator or a wizard, your choice) is a simple multi-platform utility which creates file manifests in a variety of formats. It was created to deal primarily with statistical data, but it also functions as a generalized file manifest tool. A created manifest includes, for all file types:

  • The file name
  • Checksum in your choice of hash for the file. Current flavours of hashes are: sha1, sha224, sha256, sha384, sha512, blake2b, blake2s, md5
  • Encoding, if available (ie, utf-8, windows-1252, etc.)

For plain text files, often used for microdata, the utility also produces information on:

  • Minimum line length
  • Maximum line length
  • Number of records
  • Constant records flag (ie, all lines are of the same length)
  • Row and column of non-ASCII characters
  • Flag for DOS/Windows formatting (ie, carriage return + line feed as opposed to just a line feed).

For files in SAS, SPSS and Stata formats (ie, .sas7bdat, .sav and .dta) the utility will provide information on:

  • Number of cases (reported as rows)
  • Number of variables (reported as columns)

Note that statistical package files will always be reported as rectangular due to the limitations of parsing them.

Output formats are:

  • Plain text
  • Comma Separated Value (ie, a spreadsheet)
  • JSON. This JSON doesn’t conform to any particular standard, but is valid JSON object — one object for all the files. The command line program will produce output in the format of:
{"files":[{file1medata}, {file2metadata}, ...{fileNmetadata}]}

But that’s not all!

The fcheck module

While damage is the standalone piece of software that most people will use, the underlying checking mechanism is available as a Python module called fcheck which you can use in your own software.

Why would I need this?

More than ever, the world today revolves around data sharing. Knowing the data that you’ve downloaded is correct is key.

For data distributors

  • damage output can be included as a text file with your data so that you and end users can verify and identify what they’ve downloaded
  • Create detailed version notes with one command
  • Manage changes in file structure using digests which are unique to a particular version of a file, instead of relying on easily changeable file names
  • Easily find duplicate files

For researchers

  • damage and fcheck can help with creating descriptive documentation which is required for your research data deposit
  • damage output ensures the integrity of your data set when used by others

Obtaining the software/installation

Binary files

Console binaries are available for Windows and Mac (Intel) at If you don’t already have Python 3 installed (and potentially other python libraries) or you just don’t want to use Python this is the easiest way to proceed.

These files don’t need installation and can be run directly from the command line. For ease of use, you might consider adding the files to your PATH.

Windows users

The download should be in a directory that is listed in the %PATH% environment variable.

The easiest way to do this is to use the Start menu and type “Environment”, then select “Edit Environment variables for your account”. Either place the binary file into a directory listed in Path, or add a new directory to your path using the GUI.

Mac users

The easiest way to make this available system wide is simply to copy the Mac executable to the /usr/local/bin directory, which is normally found on the primary drive. In the finder, press CMD-SHIFT-G, then type /usr/local/bin in the box to easily find it.

Installing with pip

The software is written in Python (>= 3.6), and the source is available as a single file in If you have Python 3 installed you can either just download that single file to a place of convenience, or you can install it as a Python library by running the following commands in a terminal:

pip install git+

This second method installs the damage command line utility and will also allow you to use the fcheck.Checker class in your own projects, in the traditional import fcheck sort of way. If you don’t care about that, just download a binary or use the Python file directly. It will also automatically install the dependencies for you.

Documentation on the module is available via the API reference documentation.

Source code

As you may have surmised frotm the example above, source code is available at, along with all of the documentation and binary files.