hardback 0.10.0
📓 Hardcopy backups of digital data 📓
Requires Python: >=3.10

# hardback: hard-copy backup of digital data

Newest updates are
[here](https://github.com/rec/hardback/blob/master/UPDATES.rst).

## In one sentence

Archive a digital document as a hardcopy book that can then be turned
back into the original document.

## High level picture

There are only two parts to this project:

-   Writing the original document or book from a digital document
-   Reading the book back in

Writing is non-trivial, but there is a clear path to a good solution for
that.

But I really don\'t have any solid solution yet to reading, short of
someone scanning each QR code individually.

Of course, that is a reasonable solution if you care about the data and
don\'t mind paying someone to take the time.

## The book format is EPUB

The output format will be EPUB, <https://en.wikipedia.org/wiki/EPUB>
-the only choice for an open-source book format, full-featured and
universally accepted.

I\'m using a Python library called EBookLib for this - I haven\'t looked
into it thoroughly yet, but it seems well-received and there is no other
candidate in Python.

Update: EBookLib is fairly gnarly, but the underlying format is just
XHTML, so I\'m having reasonable success getting output.

## The data format within the book is QR code

QR codes will be used to store the data in 1k blocks - again, QR is the
only reasonable choice for solving the problem of printable data.

A Python library called segno can write each one as a tiny PNG file
about 2K in size. This is quite reasonable - it means that we can aim to
create a book document that\'s less than three times the size of the
original digital document. (Interestingly enough, SVG files were an
order of magnitude larger -in some cases over one hundred times larger!)

We\'ll be using QR code format 36, which holds up to 1,051 bytes at the
highest error correction code level, \'H\'.

The official list of all the QR code formats,
<https://www.qrcode.com/en/about/version.html> is poorly organized -
click on 31-40 and then scroll down.

I\'m going to use that to hold 1024 bytes of target data with an index
and a hash of the original document, totalling 1,048 bytes. (The extra 3
bytes aren\'t entirely wasted - we get a tiny bit better error
correction.)

## Data layout

The binary data is divided into 1K *chunks*. A chunk is written to a QR
code as part of a *block*, which also contains an index and a hash of
the original documet.

The layout in bytes within the block is by default like this:

``` text
| index [8] | document[8] | chunk [up to 1024] |
```

but you can customize all these sizes.

There\'s no checksum or error correction for this block itself, as the
QR code is already taking care of that for us.

`hash` is the first 16 bytes of the 32-byte SHA256 hash of the entire
document. `data` is one kilobyte from your target file.

`index` is an 8-byte signed integer - a number that can be positive,
negative or zero, and that fits into 8 bytes (or equivalently 16 hex
digits).

If the index is zero or negative, then it is a metadata block.

The block with index zero always contains a JSON description of the
original file with the fields `filename`, `timestamp`, `size` and
`sha256`. If the original filename is too long (which would be about 900
characters or so!), it is truncated from the left.

Blocks with negative indexs are currently unspecified and reserved for
future expansion or individuals to use. The first version of the
software will only produce output with non-negative indexs.

If `index` is positive, it\'s the index of a data block. This means that
the first data block has `index` 1.

Eight bytes allows us to generate 2 to the power of 63 blocks of 1K
each, or about 9 zetabytes (which is 9,000,000,000,000 gigabytes) -
roughly the entire size of all the world\'s data in 2019.

Within a block, `index` is is represented in
[big-endian](https://en.wikipedia.org/wiki/Endianness) (or intuitive or
network order) -which means the *most* significant digits occur first.

Intel processors are little-ended, where the *least* significant digits
come first, so we use the [struct
library](https://docs.python.org/3/library/struct.html#byte-order-size-and-alignment)
to make sure that the output is system-independent.

Remembering that one byte is equal to two hex digits, if the hash of a
full document is
`56484fd9aad8e87540609ca6c938f98fab60296b3bec808ea8b3e24da2035ce9` then
the resulting sequence of QR codes would look like:

``` text
0000000000000000 56484fd9aad8e87540609ca6c938f98f {"filename": "me.jpg", ...
0000000000000001 56484fd9aad8e87540609ca6c938f98f ... 1024 bytes ...
0000000000000002 56484fd9aad8e87540609ca6c938f98f ... more data  ...
... etc
```

This means that each QR code identifies itself as to what part of the
whole document it is.

It also means that the metadata block is key to understanding how the
whole system works! If you have a metadata block, then you can
reconstruct at least part of the data even if a lot of it is lost.
Otherwise, you really have to guess.

So we\'re going to have to intersperse the metadata block within all the
other blocks periodically if we really want something that can be
partially reconstructed!

Update - this is done: the metadata blocks appear in varying locations
on each page so even a hole were punched through the book, some copy of
the metadata would probably survive.

Also, \"raw\" formats like RAW and AIFF are much preferable for this
sort of archival activity because compressed formats dramatically
magnify the effect of any errors or gaps. If you had a book containing
the digital data for an AIFF or RAW, you could still reconstruct pieces
of it even if you only have a limited number of pages, whereas you might
get nothing at all if you were using mp3 or jpg files.