Fileson - JSON File database tools

Fileson is a set of Python scripts to create JSON file databases and use them to do various things, like compare differences between two databases. There are a few key files:

• fileson.py contains Fileson class to read, manipulate and write Fileson databases.
• fileson_util.py is a command-line toolkit to create Fileson databases and do useful things with them

API documentation (everything very much subject to change) available at https://fileson.readthedocs.io/en/latest/

Create a Fileson database

user@server:~$ python3 fileson_util.py scan files.fson ~/mydir

Fileson databases are essentially log files with JSON objects per row, containing directory and file information (name, modified date, size) for ~/mydir and some additional metadata for each scan (changes to entries are appended to the end).

To calculate an SHA1 checksum for the files as well:

user@server:~$ python3 fileson_util.py scan files.fson ~/mydir -c sha1

Calculating SHA1 checksums is somewhat slow, around 1 GB/s on modern m.2 SSD and 150 MB/s on a mechanical drive, so you can use -c sha1fast to only include the beginning of the file. It will differentiate most cases quite well.

Fileson databases are versioned. Once a database exists, repeated call to fileson_util.py scan will update the database, keeping track of the changes. You can then use this information to view changes between given runs, etc.

Normally SHA1 checksums are carried over if the previous version had a file with same name, size and modification time. For a stricter version, you can use -s or --strict to require full path match. Note that this means calculating new checksum for all moved files.

Duplicate detection

Once you have a Fileson database ready, you can do fun things like see if you have any duplicates in your folder (cryptic string before duplicates identifies the checksum collision, whether it is based on size or sha1):

user@server:~$ python3 fileson_util.py duplicates pics.fson

1afc8e06e081b772eadd6a981a83f67077e2ef10
2009/2009-03-07/DSC_3962-2.NEF
2009/2009-03-07/DSC_3962.NEF

Many folders tend to have a lot of small files common (including empty files), for example source code with git repositories, and that is OK so you can use for example -m 1M to only show duplicates that have a minimum size of 1 MB.

You can skip database creation and give a directory to the command as well:

user@server:~$ python3 fileson_util.py duplicates /mnt/d/SomeFolder -m 1M -c sha1fast

Change detection

Once you have a Fileson database or two, you can compare them with fileson_util.py diff. Like the duplicate command, one or both can be a directory. Note that two files with different checksum types will essentially differ on all files.

user@server:~$ python3 fileson_util.py diff myfiles-2010.fson myfiles-2020.fson \
  myfiles-2010-2020.delta

The myfiles-2010-2020.delta now contains a row per difference between the two databases/directories -- files that exist only in origin, only in target, or have changed.

Let's say you move some.zip around a bit (JSON formatted for clarity):

user@server:~$ python3 fileson_util.py scan files.fson ~/mydir -c sha1
user@server:~$ mv ~/mydir/some.zip ~/mydir/subdir/newName.zip
user@server:~$ python3 fileson_util.py diff files.fson ~/mydir -c sha1 -p
{"path": ".", "src": {"modified_gmt": "2021-02-28 19:42:05"},
    "dest": {"modified_gmt": "2021-02-28 19:42:26"}}
{"path": "some.zip", "src": {"size": 0, "modified_gmt": "2021-02-23 21:57:25"},
    "dest": null}
{"path": "subdir", "src": {"modified_gmt": "2021-02-28 19:42:05"},
    "dest": {"modified_gmt": "2021-02-28 19:42:26"}}
{"path": "subdir/newName.zip", "src": null,
    "dest": {"size": 0, "modified_gmt": "2021-02-23 21:57:25"}}

Doing an incremental backup would involve grabbing the deltas which have src set to null. With SHA1 checksums, you could also only upload the new file if the file blob has not been uploaded before (keeping a separate Fileson object log of backed up files).

Loading Fileson databases has special syntax similar to git where you can revert to previous versions with db.fson~1 to get the previous version or db.fson~3 to back down 3 steps. This makes printing out changes after a scan a breeze. Instead of the fileson_util.py diff invocation above, you could update the db and see what changed:

user@server:~$ python3 fileson_util.py scan files.fson
user@server:~$ python3 fileson_util.py diff files.fson~1 files.fson -p
[ same output as the above diff ]

Note that you did not have to specify checksum type or directory, as it is detected automatically from the Fileson DB.

Use Fileson for simple backups to local or cloud

Fileson contains a robust set of utilities to make backups locally or into S3, either unencrypted or with secure AES256 encryption. For S3 you need to have boto3 client configured first.

Encryption

Encryption is done with 256 bit key that you can generate easily:

user@server:~$ python3 fileson_backup.py keygen password salt > my.key

Now my.key contains a 64-hex key generated with given password and salt (with PBKDF2 using AES256 and 1 million iterations by default). You can use the key to encrypt and decrypt data.

user@server:~$ python3 fileson_backup.py encrypt some.txt some.enc my.key
user@server:~$ python3 fileson_backup.py decrypt some.enc some2.txt my.key
user@server:~$ diff some.txt some2.txt

Uploading to S3 and downloading

A simple upload/download client is also provided:

user@server:~$ python3 fileson_backup.py upload some.txt s3://mybucket/objpath
user@server:~$ python3 fileson_backup.py download s3://mybucket/objpath some2.txt
user@server:~$ diff some.txt some2.txt

Just add -k my.key to encrypt/decrypt files on the fly with upload and download.

Backup up a Fileson-scanned directory

Once you have a Fileson database at hand, you can do a backup run. Certain considerations:

1. Base path of files is taken from Fileson DB, so if you used a relative path when scanning, backup command needs to be run in the same directory.
2. To avoid backing up same files over and over, second command is a backup logfile, essentially recording SHA1 hashes and locations of files backed up.
3. You need to specify either a local directory or S3 path

Backup log is essentially a Fileson DB for your backup location, and it is written line-by-line as backup is progressing. So if the backup process gets interrupted, you can just rerun the backup command and it should resume with next item that was not yet backed up.

Here is an example of simple backup to a local folder:

user@server:~$ python3 fileson_scan.py scan db.fson ~/mydir -c sha1
user@server:~$ python3 fileson_backup.py backup db.fson db_backup.log /mnt/backup

That's it. Once files change, re-run scan to update changes and then backup to upload any added objects.

Note: Support for removing files that no longer exist in db.fson from backup location is not yet done.