bpy_data_texts

disambiguation: If you're looking for Font / Text Object go here

Text DataBlock (text files inside Blender)

---

Text data-blocks are used for all kinds of things. Storing

• notes
• scripts
• data (coordinates, data structures, relationships, etc.,)
• Any string.

Creating a new text block with content is as simple as this:

some_str = "Hello\nMy name is\ngobbledigook"
f = bpy.data.texts.new('new_text.txt')
f.from_string(some_str)

You might find that it can be useful to indicate what kind of data the text block stores. Just like variables, it's useful to name the text blocks in a meaningful way. The addition of the file-type extension is not mandatory, but often it can describe quickly how the data is arranged.

reading and writing json or dict literal

Both methods below work only on dicts that can be stringified, so they can't contain Objects.

json

JSON can easily be constructed from a dictionary and written to bpy.data.texts as a string. Imagine you have some dict of information, call it my_dict. To write that dict as a JSON to the .blend file you do:

    import bpy
    import json
    
    my_dict = {
      'key1': 'some string storage',
      'key2': ['some', 'list', 'storage'],
      'key3': 5
    }
    
    # dump string
    m = json.dumps(my_dict, sort_keys=True, indent=2)
    text_block = bpy.data.texts.new('my_storage.json')
    text_block.from_string(m)

bpy.data.texts['my_storage.json'] would then contain:

    {
      "key1": "some string storage",
      "key2": [
        "some",
        "list",
        "storage"
      ],
      "key3": 5
    }

to read this back in at a later stage:

    import bpy
    import json
    
    text_obj = bpy.data.texts['my_storage.json']
    text_str = text_obj.as_string()
    
    my_json = json.loads(text_str)
    print(my_json['key1'])

---

dict and ast.literal_eval

    import bpy
    import ast
    
    mydict = dict(deb=["two", "three"], far="booo", foo=34)
    
    # write the string representation of the dict to a text datablock
    # this assumes you know how to create text datablocks, it is shown in the other method anyway.
    d = bpy.data.texts['dict_storage']
    d.from_string(str(mydict))
    
    # read from the datablock
    d = bpy.data.texts['dict_storage']
    stringified_dict = d.as_string()
    my_read_dict = ast.literal_eval(stringified_dict)
    
    for k, v in my_read_dict.items():
        print(k, v)