markstore

Markdown as plain-text data storage

But Why?

Why use this when there are numerous alternatives for data storage and serialization?
Check if your use-case meets the following criteria:

1. Primarily human readable (not necessarily, writable) plain-text, especially for non-programmers
2. Easy consumption by version control
3. Easy export, or a desire to prevent vendor lock-in to your application

What this is

A simple, json-like interface to serialize basic objects to and from a markdown file.

What this isn't

• A generic markdown processing/generator tool
• A configuration language

It is a non-goal of this library to be tolerant of human error. The intended use case is machine-to-machine serialization and the occasional export to a human.

Example

To File

import markstore

# Serialize
myObject = {
    "myKey": "myData"
}

with open("out.md", mode='wb') as f:
    markstore.dump(myObject, f)

# Deserialize
with open("out.md", mode='rb') as f:
    myObject = markstore.load(f)

To String

import markstore

# Serialize
myObject = {
    "myKey": "myData"
}

myStr = markstore.dumps(myObject)

# Deserialize
myObject = markstore.loads(myStr)

Markdown Object Specification

Lists

["one", "two", "three", ["four", "five"], "six"]

Translates to

- one
- two
- three
- - four
  - five
- six

Dicts

{
    "key1": "data1",
    "key2": "data2",
    "key3": { 
        "subkey1": "subdata1",
        "subkey2": "subdata2"
        }
}

Translates to

# key1
data1
# key2
data2
# key3
## subkey1
subdata1
## subkey2
subdata2

Combinations

{
    "Key1":
    "My Data",
    "Data": [{
        "Subkey1": "Subdata1"
    }, {
        "Subkey2": {
            "Subkey2.1": "Subdata2.1",
            "Subkey2.2": "Subdata2.2"
        }
    }],
    "Key2":
    "Other data"
}

# Key1
My Data
# Data
- ## Subkey1
  Subdata1
- ## Subkey2
  ### Subkey2.1
  Subdata2.1
  ### Subkey2.2
  Subdata2.2
# Key2
Other data

Inner dictionary keys are always prefixed by an increasing number of #, even if the key is within a list