Python RESTful webservices with Python: Flask and Django solutions

RESTful webservices with
Python
For lazy developers
or
developers with deadlines

source: http://s3-ec.buzzfed.
com/static/enhanced/webdr01/2012/12/2/13/e
nhanced-buzz-wide-18383-1354473319-2.jpg

Who am I?

Justyna Żarna
Woman in Django / Python World
JavaScript freak

@Ustinez

http://solution4future.com

Content

1. REST software architecture.

2. Benchmarks - problem analysis.

3. Flask + SQLAlchemy.

4. Django & class-based views.
} case study

API

XML/RPC SOAP REST

based on HTTP based on HTTP
protocol protocol or other
protocols
many restriction
on data types synchronous ???
synchronous based on XML
and all xml
defects

What is so cool?

REpresentational State Transfer
}
Resource
http://a.com/resources/

http://a.com/resources/item1/ http://a.com/resources/item2/ http://a.com/resources/item3/

Representation Representation Representation

GET PUT POST DELETE

THE VERBS

What is so cool?

REpresentational State Transfer

1. Scalability 6. In HTTP context but not
limited to this protocol.
2. Generalization of interface 7. Good designed interface.

3. Independence

4. Security

5. Simplicity

http://www.2010theyearinbooks.com/2012/12/december-beach-reads-for-australian.html

make your API RESTful and go to rest...

Benchmark JSON
response for frameworks
and languages.

Python frameworks:

* Django-stripped 13 269
per second

* Flask - 11 506 per sec

* Django - 7122 per sec

http://www.techempower.com/blog/2013/04/05/frameworks-round-
2/

The source code and problems

https://github.com/TechEmpower/FrameworkBenchmarks/
http://www.techempower.com/blog/2013/04/05/frameworks-round-2/

In this souce code for flask and django isn't used
connection pool - cache of database connection.

connection
connection database
connection database
connection

connection for each request is connection are maintained for
open and closed. future

Solutions?

1. Database optimalization for PostgreSQL:
● pgBouncer
● pgPool

http://www.askthepony.com/blog/2011/07/django-and-postgresql-improving-the-performance-with-no-effort-and-no-code/

Solutions?
code profiler can tell us more...

2. JSON standard serialization in Python STD
library is slow, so we can improve performance by
using module ujson - ultra json.

Solutions?

3. Rendering template can be faster with template
engine jinja (inspired by Django templates)

Flask

● "micro" does not means micro possibilities,
● core is light, simple and extensible,
● support many extensions in each layer (for
example your database layer can by relational
database or non-relational data persistence).

Case study - micro framework Flask

from sqlalchemy import Column, Integer, String
from newsletter.database import Base

class Member(Base):
__tablename__ = 'newsletter_members'
id = Column(Integer, primary_key=True)
last_name = Column(String(50))
first_name = Column(String(120))
email = Column(String(120), unique=True)

def __init__(self, last_name=None, first_name=None, email=None):
self.last_name = last_name
self.first_name = first_name
self.email = email

def __repr__(self):
return '<Member %r>' % (self.last_name)


class API(MethodView):

def get(self, member_id):
if member_id is None:
return Member.query.all()
else:
return Member.query.filter_by(id = member_id).first()
def post(self, data ):
member = Member(first_name = data['first_name'], email=data['email'])
db.session.add(member)
db.session.commit()
return 'OK'

app.add_url_rule('/users/<int:user_id>', view_func=API.as_view('user_api'),
methods=['GET', 'POST'])

#class flask.views.MethodView and recognizing each REST methods are based on generic
dispatch_request()


It was simple and quick to code?

improve simplicity and spent time with...
Flask RESTless

Flask RESTless - full script
import flask
import flask.ext.sqlalchemy
import flask.ext.restless
app = flask.Flask(__name__)
app.config['DEBUG'] = True
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:////tmp/test.db'
db = flask.ext.sqlalchemy.SQLAlchemy(app)

class Member(db/Model):
__tablename__ = 'newsletter_members' Too simple for real project.. ?
id = db.Column(Integer, primary_key=True)
last_name = db.Column(String(50))
first_name = db.Column(String(120))
email = db.Column(String(120), unique=True)

db.create_all()

manager = flask.ext.restless.APIManager(app, flask_sqlalchemy_db=db)

manager.create_api(Member, methods=['GET', 'POST'])

app.run()

Flask RESTless - more sugar

● versioning:

GET /api/member
GET /api/member/(int: id)
GET /api/member?q=<json>
POST /api/member

apimanager.create_api(Member, url_prefix='/api/v2')
GET /api/v2/member

● validation:
manager.create_api(Member, methods=['GET', 'POST'], validation_exceptions=
[ValidationError])

{ "validation_errors":
{
"email": "Email is not valid..",
}
}

Flask RESTless - more sugar

● specify columns (include or exclude):

apimanager.create_api(Member, include_columns = ['last_name', 'email'])

● pagination:
manager.create_api(Member, methods=['GET', 'POST'], results_per_page=2)

{ "validation_errors":
{
"age": "Must be an integer",
}
{
"num_results": 6,
"total_pages": 3,
"page": 1,
"objects": [
{"last_name": "Kovalsky", "email": "kovalsky@gmail.com", "id": 1},
{"last_name": "Novak", "email": "novak@gmail.com", "id": 2}
]
}

Flask RESTless - more and more..
● pre/post-processors:
def pre_get_single(instid):
# do something
pass

def pre_get_many(params):
# do something
pass

# Create an API for the Member model.
manager.create_api(Person, methods=['GET', 'POST'],
# A list of preprocessors for each method.
preprocessors={'GET_SINGLE': [pre_get_single], 'GET_MANY': [pre_get_many],})

● Authentication:
def auth_func(params):
if not current_user.is_authenticated():
raise ProcessingException(message='Not authenticated!')
return NO_CHANGE
manager.create_api(Person, preprocessors={'GET_SINGLE': [auth_func]})

Flask RESTless - more and more..
● filtering:

import requests
import json

url = 'http://127.0.0.1:5000/api/member'
headers = {'Content-Type': 'application/json'}

filters = [dict(email='email', op='like', val='%y%')]
params = dict(q=json.dumps(dict(filters=filters)))
response = requests.get(url, params=params, headers=headers)

GET /api/member?q={"filters":[{"name":"email", "op":"like", "val": "kovalsky"}]}

OPERATORS examples:
○ ==, eq, !=, neq,
○ >, gte, <, lte FOR RELATIONS:
○ in, not_in ● column__column example:
member__group
○ is_null
○ like
○ has
○ any

What about Django?

● Define your model:

from django.db import models

class Member(models.Model):
last_name = models.CharField(max_length = 100, verbose_name = "Last name")
first_name = models.CharField(max_length = 100, verbose_name = "First name")
email = models.EmailField(max_length = 100, verbose_name = "Email")

def __unicode__(self):
return self.email

class Meta:
verbose_name = "Newsletter member"
verbose_name_plural = "Newsletter members"

What about Django?
● Define your model serializer:
class MemberSerializer(serializers.ModelSerializer):
class Meta:
model = Member
fields = ('last_name', 'first_name', 'email')

● Working with serializers:
from newsletter.models import Member
from newsletter.serializers import MemberSerializer
from rest_framework.renderers import JSONRenderer
from rest_framework.parsers import JSONParser

member = Member(last_name='Kovalsky', first_name= 'Johny', 'email' = 'kovalsky@gmail.
com')
member.save()

serializer = MemberSerializer(member)
content = JSONRenderer().render(serializer.data)
# content: {"pk": 2, "last_name": "Kovalsky", "first_name="Johny", email =
"kovalsky@gmail.com"}, more object in format [{'foo': 'bar'}, {'foo': 'bar'}]

What about Django?
● Define your class-based views:
class MemberDetail(APIView):
"""
Retrieve, update or delete a member instance.
"""
def get_object(self, pk):
try:
return Member.objects.get(pk=pk)
except Member.DoesNotExist:
raise Http404

def get(self, request, pk, format=None):
member = self.get_object(pk)
serializer = MemberSerializer(member)
return Response(member.data)

What about Django?
● Define your class-based views:

def put(self, request, pk, format=None):
serializer = MemberSerializer(member, data=request.DATA)
if serializer.is_valid():
serializer.save()
return Response(serializer.data)
return Response(serializer.errors, status=status.
HTTP_400_BAD_REQUEST)

def delete(self, request, pk, format=None):
member.delete()
return Response(status=status.HTTP_204_NO_CONTENT)

What about Django?
● Or generic views:
from newsletter.models import Member
from newsletter.serializers import MemberSerializer
from rest_framework import generics

class MemberList(generics.ListCreateAPIView):
model = Member
serializer_class = MemberSerializer

class MemberDetail(generics.RetrieveUpdateDestroyAPIView):
model = Member
serializer_class = MemberSerializer

● URLs patterns:

urlpatterns = patterns('',
url(r'^members/$', views.MeberList.as_view()),
url(r'^members/(?P<pk>[0-9]+)/$', views.MemberDetail.as_view()),
)

RESTful API - done

http://sarahwmackey.files.wordpress.com/

Thank you for your
attention

http://solution4future.com/

Python RESTful webservices with Python: Flask and Django solutions

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