First Steps

lima tries to be lean, consistent, and easy to learn. Assuming you already have installed lima, this section should help you getting started.

Note

Throughout this documentation, the terms marshalling and serialization will be used synonymously.

A simple Example

Let’s say we want to expose our data to the world via a web API and we’ve chosen JSON as our preferred serialization format. We have defined a data model in the ORM of our choice. It might behave something like this:

class Person:
    def __init__(self, first_name, last_name, date_of_birth):
        self.first_name = first_name
        self.last_name = last_name
        self.date_of_birth = date_of_birth

Our person objects look like this:

import datetime
person = Person('Ernest', 'Hemingway', datetime.date(1899, 7, 21))

If we want to serialize such person objects, we can’t just feed them to Python’s json.dumps() function: per default it only knows how to deal with a very basic set of data types.

Here’s where lima comes in: Defining an appropriate Schema, we can convert person objects into data structures accepted by json.dumps().

from lima import fields, Schema

class PersonSchema(Schema):
    first_name = fields.String()
    last_name = fields.String()
    date_of_birth = fields.Date()

schema = PersonSchema()
serialized = schema.dump(person)
# {'date_of_birth': '1899-07-21',
#  'first_name': 'Ernest',
#  'last_name': 'Hemingway'}

... and to conclude our example:

import json
json.dumps(serialized)
# '{"last_name": "Hemingway", "date_of_birth": "1899-07-21", ...

First Steps Recap

• You now know how to do basic marshalling (Create a schema class with appropriate fields. Create a schema object. Pass the object(s) to marshal to the schema object’s dump() method.
• You now know how to get JSON for arbitrary objects (pass the result of a schema object’s dump() method to json.dumps()).