Skip to main content

human readable and writable data interchange format

Project description

https://img.shields.io/travis/KenKundert/nestedtext/master.svg https://img.shields.io/coveralls/KenKundert/nestedtext.svg https://img.shields.io/pypi/v/nestedtext.svg https://img.shields.io/pypi/pyversions/nestedtext.svg
Authors: Ken & Kale Kundert
Version: 0.6.0
Released: 2020-09-26
Please post all questions, suggestions, and bug reports to NestedText Github.

NestedText is a file format for holding data that is to be entered, edited, or viewed by people. It allows data to be organized into a nested collection of dictionaries, lists, and strings. In this way it is similar to JSON and YAML, but without the complexity and risk of YAML and without the syntatic clutter of JSON. NestedText is both simple and natural. Only a small number of concepts and rules must be kept in mind when creating it. It is easily created, modified, or viewed with a text editor and easily understood and used by both programmers and non-programmers.

NestedText is convenient for configuration files, address books, account information and the like. Here is an example of a file that contains a few addresses:

# Contact information for our officers

president:
    name: Katheryn McDaniel
    address:
        > 138 Almond Street
        > Topika, Kansas 20697
    phone:
        cell: 1-210-555-5297
        home: 1-210-555-8470
            # Katheryn prefers that we always call her on her cell phone.
    email: KateMcD@aol.com
    kids:
        - Joanie
        - Terrance

vice president:
    name: Margaret Hodge
    address:
        > 2586 Marigold Lane
        > Topika, Kansas 20682
    phone: 1-470-555-0398
    email: margaret.hodge@uk.edu
    kids:
        - Arnie
        - Zach
        - Maggie

treasurer:
    name: Fumiko Purvis
    address:
        > 3636 Buffalo Ave
        > Topika, Kansas 20692
    phone: 1-268-555-0280
    email: fumiko.purvis@hotmail.com
    kids:
        - Lue

The format holds dictionaries (ordered collections of name/value pairs), lists (ordered collections of values) and strings (text) organized hierarchically to any depth. Indentation is used to indicate the hierarchy of the data, and a simple natural syntax is used to distinguish the types of data in such a manner that it is not easily confused. Specifically, lines that begin with a word or words followed by a colon are dictionary items; a dash introduces list items, and a leading greater-than symbol signifies a line in a multiline string. Dictionaries and lists are used for nesting, the leaf values are always strings.

Alternatives

There are no shortage of well established alternatives to NestedText for storing data in a human-readable text file. Probably the most obvious are json and YAML. Both have serious short comings.

JSON is a subset of JavaScript suitable for holding data. Like NestedText, it consists of a hierarchical collection of dictionaries, lists, and strings, but also allows integers, floats, Booleans and nulls. The problem with JSON for this application is that it is awkward. With all those data types it must syntactically distinguish between them. For example, in JSON 32 is an integer, 32.0 is the real version of 32, and “32” is the string version. These distinctions are not meaningful and can be confusing to non-programmers. In addition, in most datasets a majority of leaf values are strings and the required quotes adds substantial visual clutter. NestedText avoids these issues by treating all leaf values as strings with no need for quoting or escaping. It is up to the application that employs NestedText as an input format to sort things out later.

JSON does not provide for multiline strings and any special characters like newlines or unicode are encoded with escape codes, which can make strings quite difficult to interpret. Finally, dictionary and list items must be separated with commas, but a comma must not follow last item. All of this results in JSON being a frustrating format for humans to read, enter or edit.

NestedText has the following clear advantages over JSON as human readable and writable data file format:

  • text does not require quotes

  • data type does not change based on seemingly insignificant details (32, 32.0, “32”)

  • comments

  • multiline strings

  • special characters without escaping them

  • Unicode characters without encoding them

  • commas are not used to separate dictionary and list items

YAML was to be the human friendly alternative to JSON, but the authors were too ambitious and tried to support too many data types and too many formats. To distinguish between all the various types and formats, a complicated and non-intuitive set of rules developed. For example, 2 is interpreted as an integer, 2.0 as a real number, and both 2.0.0 and “2” are strings. YAML at first appears very appealing when used with simple examples, but things can quickly become complicated or provide unexpected results. A reaction to this is the use of YAML subsets, such as StrictYAML. However, the subsets still try to maintain compatibility with YAML and so inherit much of its complexity.

YAML recognized the problems that result from JSON needing to unambiguously distinguish between many data types and instead uses implicit typing, which creates its own problems. For example, consider the following YAML fragment:

Enrolled: NO
Country Code: NO

Presumably Enrolled is meant to be a Boolean value whereas Country Code is meant to be a string (NO is the country code for Norway). Reading this fragment with YAML results in {‘Enrolled’: False, ‘Country Code’: False}. When read by NestedText both values are retained in their original form as strings. With NestedText any decisions about how to interpret the leaf values are passed to the end application, which is the only place where they can be made knowledgeably. The assumption is that the end application knows that Enrolled should be a Boolean and knows how to convert ‘NO’ to False. The same is not possible with YAML because the Country Code value has been transformed and because there are many possible strings that map to False (n, no, false, off; etc.).

This is one example of the many possible problems that stem from implicit typing. In fact, many people make it a habit to add quotes to all values simply to avoid the ambiguities, which makes YAML more like JSON.

NestedText was inspired by YAML, but eschews its complexity. It has the following clear advantages over YAML as human readable and writable data file format:

  • simple

  • unambiguous (no implicit typing)

  • data type does not change based on seemingly insignificant details (2, 2.0, 2.0.0, “2”)

  • syntax is insensitive to special characters within text

  • safe, no risk of malicious code execution

Issues

Please ask questions or report problems on Github.

Contributing

This package contains a Python reference implementation of NestedText. Implementation in many languages is required for NestedText to catch on widely. If you like the format, please consider contributing additional implementations.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

nestedtext-0.6.0.tar.gz (14.9 kB view hashes)

Uploaded source

Built Distribution

nestedtext-0.6.0-py3-none-any.whl (14.9 kB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page