frutsel 0.17.19

A copy-pastable, human readable, scalable database with an easy API.

frutsel

A copy-pastable, human readable, scalable database with an easy API.

Quickstart

pip install frutsel

from frutsel import FrutselDB

with FrutselDB('/tmp/database.frutsel') as db:
    db.put('oh hai')
    for doc in db.get():
        print(doc)

Database file structure

The main reasons why you would use frutsel are:

• your data is stored in well-known data formats (JSON, xz, plain text)
• concurrent write access is supported without needing a database server process

These characteristics make frutsel attractive for use cases like:

• Concurrently working on creating/expanding a dataset
• Distributing your data to people who are cautious about propietary binary formats
• Long term software agnostic backup storage

In practice, a frutsel database looks like this:

database.frutsel
├── data
│   └── cc46fb1060004a261f1761a0cea1167ab14f6fd507fcedb17fd217a69221f37b
├── frutsel.py
└── meta
    ├── 0a0e7c970cf17e5bce4944757e926325eb874cd225770f52566cadf75164f80f.json
    ├── 18133ee431756a3421edad7c5cc63d6cdd73e1f332c63f447c57028679e443c2.json
    ├── 335af29a3d5d0ff75da889c59798586d4e4c7f14a283cf74eeba8a004507f18b.json
    ├── 6a9cff7bd332283f8a4b67c8f0e97d45a1d78450d461baad462c6878c26a5012.json
    └── 77316d966ff84dea85d2c4b0c10eea4da48e5bfde78274e61aad0e7d9ff5c653.json

In the top level directory, there are two subdirectories. The meta directory holds all relatively small data files. The filename extensions indicate the file format. You can read JSON files with your plain text editor, for instance meta/335af29a3d5d0ff75da889c59798586d4e4c7f14a283cf74eeba8a004507f18b.json in our example holds:

{"data":"oh hai"}

Large files are put in the data directory. For each of these files there is still a JSON file in the meta directory, but it only holds metadata. For the document contents, it refers to a data file. In our example, meta/18133ee431756a3421edad7c5cc63d6cdd73e1f332c63f447c57028679e443c2.json holds:

{"datafile":"cc46fb1060004a261f1761a0cea1167ab14f6fd507fcedb17fd217a69221f37b"}

By relying on widespread formats and preferring plain text (so you could search your database using grep), frutsel helps to keep your data accessible even without the context of your application(s). In addition, the database stores a copy of frutsel.py. This is a single-file Python script implementing the frutsel DBMS, including a command line interface for basic database interaction.

Data recovery

The main feature of frutsel is that your data will still be usable after all sorts of disaster scenarios. This section covers a few of those scenarios.

You have your application and your database, but you cannot get/update the frutsel library

There's always a copy of the frutsel library inside the database. You can use it as a library without even moving the Python file, by adding three lines to your Python application:

import sys
db_path = '/tmp/database.frutsel'
# Tell Python to look for modules in the database top-level directory.
sys.path.append(db_path)

# The frutsel library saved inside your database will be imported.
from frutsel import FrutselDB

with FrutselDB(db_path) as db:
    db.put('oh hai')
    for doc in db.get():
        print(doc)

Without changing any code, you can of course also copy frutsel.py to your application's file location to rely on a relative import while recovering your data.

Running frutsel.py as a script gives you a command line interface:

cd /tmp/database.frutsel
python3 ./frutsel.py --help

All else fails

In the worst case scenario, at least your files will be in common, broadly understood and supported formats.

To get you started with GNU find and jq:

find /tmp/database.frutsel/meta -type f -name '*.json' -exec sh -c "jq < {}" \;