https://github.com/keenlycode/dictify

Dictify : Documents schema and data validation
https://github.com/keenlycode/dictify

Last synced: 3 months ago
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Dictify : Documents schema and data validation

• Host: GitHub
• URL: https://github.com/keenlycode/dictify
• Owner: keenlycode
• License: mit
• Created: 2018-08-18T09:47:13.000Z (almost 8 years ago)
• Default Branch: main
• Last Pushed: 2023-08-21T18:04:46.000Z (almost 3 years ago)
• Last Synced: 2025-04-15T19:53:58.969Z (about 1 year ago)
• Language: Python
• Homepage: https://keenlycode.github.io/dictify/
• Size: 7.56 MB
• Stars: 9
• Watchers: 2
• Forks: 1
• Open Issues: 3
• Metadata Files:
  • Readme: readme.md
  • License: LICENSE

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README

          
{ Dictify }


Documents schema and data validation




    

        

        Github

    



{ dictify } is a python library to define data schema and validation with simple and flexible syntax for documents data type such as **JSON** and **Python** `dict` object.



    ! New in V3.1.0

    strict mode

    post validation



## Get it

---

```shell

$ pip install dictify

```

## Schema definition

---

Let's start with an example note data:

```json

{

    "title": "Dictify",

    "content": "dictify is easy",

    "timestamp": "2021-06-13T05:13:45.326869"

}

```

The schema condition should be like:

**title**

1. Required field

2. Must be `str` instance

3. Length is <= 300

**content**

1. Must be `str` instance

**timestamp**

1. Required field

2. Default to datetime on creation in ISO format string

3. Must be a valid ISO datetime string

```python

from datetime import datetime

from dictify import Model, Field

class Note(Model):

    title = Field(required=True)\

        .instance(str)\

        .verify(lambda value: len(value) <= 300) # [1]

    content = Field().instance(str)

    timestamp = Field(

            required=True,

            default=lambda: datetime.utcnow().isoformat())\

        .verify(lambda value: datetime.fromisoformat(value))

```

> [1] Field validations can be chained.

## Data assignment and validation

---

After schema definition, now we can use it to create `Model` instance with required data.

```python

note = Note({'title': 'Dictify', 'content': 'dictify is easy'})

# `note` can be used like a dict object.

note.update({

    "content": "Updated content",

})

note["content"] = "Updated again"

# Code below will raise `Model.Error`.

note.update({'title': 0})

note['title'] = 0

```

> Note : Use `try..except` to catch errors if needed.

## Convert data to native 'dict' or 'JSON'

---

```python

import json

note_dict = dict(note) # Convert to python built-in `dict`

note_json = json.dumps(note)  # Convert to JSON string

```