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Building a RESTful API with Pyramid - Resource and Traversal

2013-11-13 · 9 min read

In the previous post we built a basic Pyramid application: a foundation for a RESTful API. For simplicity, I left out many details. Today, we will transform that application into something more close a real API. At the end of this article, we will have developed Pyramid API that handles single resource persisted with MongoDB database and managed by Pyramid’s traversal routing mechanism.


Let’s start with the view layer. A RESTful API should provide up to four operations to interact with each resource: Create, Retrieve, Update and Delete (CRUD). According to REST guidelines, URLs identify resources while HTTP verbs are used to specify actions on these resources. As a result we end up with unified and consisted naming approach.

A RESTful API needs to provide only two URLs per resource: one for a collection and one for a specific resource. Collections will be referred by plural names while resources by identifiers (ObjectId in case of MongoDB).

/cities          # HTTP verbs allowed: GET, POST
/cities/:id      # HTTP verbs allowed: GET, PUT, DELETE

Operations update, retrieve (single result) and delete are bound to a single resource i.e. City (specified as context).

@view_config(request_method=‘PATCH', context=City, renderer='json')
def update_city(context, request):
    r = context.update(request.json_body, True)

    return Response(
        status='202 Accepted',
        content_type='application/json; charset=UTF-8')

@view_config(request_method='GET', context=City, renderer='json')
def get_city(context, request):
    r = context.retrieve()

    if r is None:
        raise HTTPNotFound()
        return r

@view_config(request_method=‘DELETE', context=City, renderer='json')
def delete_city(context, request):

    return Response(
        status='202 Accepted',
        content_type='application/json; charset=UTF-8’)

For operations create and retrieve (listing) we define context as a resource collection, i.e. Cities.

@view_config(request_method=‘PUT', context=Cities, renderer='json')
def create_city(context, request):
    r = context.create(request.json_body)

    return Response(
        status='201 Created',
        content_type='application/json; charset=UTF-8')

@view_config(request_method='GET', context=Cities, renderer='json')
def list_cities(context, request):
    return context.retrieve()

Error handling is still very basic. Pyramid allows us to redefine most common errors in the view with a custom handler. We will use that feature to redefine notfound handler so it returns data in JSON format.

def notfound(request):
    return Response(
        body=json.dumps({'message': 'Custom `Not Found` message'}),
        status='404 Not Found’,

Finally, we can optionally add a view for the root of our API; it will be called home.

@view_config(renderer='json', context=Root)
def home(context, request):
    return {'info': 'City API’}

Persistance Layer

We will be using PyMongo to talk to our database; it’s a lightweight Python driver supported by 10gen. You can install it into current virtual environment using pip.

pip install pymongo

We need to also add pymongo to the list of requires inside setup.py.

requires = [

Within development.ini, under [app:main], we specify our database connection string.

mongo_uri = mongodb://

Now, we are ready to write the code that connects to the database. It will be stored in db.py.

def includeme(config):
    settings = config.registry.settings

    # Store DB connection in registry
    db_url = urlparse(settings['mongo_uri'])
    conn = pymongo.Connection(host=db_url.hostname, port=db_url.port)
    settings['db_conn'] = conn

    # Make DB connection accessible as a request property
    def _get_db(request):
        settings = request.registry.settings
        db = settings['db_conn'][db_url.path[1:]]
        if db_url.username and db_url.password:
            db.authenticate(db_url.username, db_url.password)
        return db

    config.set_request_property(_get_db, 'db', reify=True)

This code parses the configuration file and adds MongoDB connection as a request property. Lastly, we include that file in __init__.py using config.include(‘.db’).


The second major change will be transforming our routing mechanism: traditional URL dispatch approach will be replaced by traversal, Pyramid’s unique feature.

In a nutshell, the idea behind traversal is to build a tree structure out of possible paths which the application can respond to; e.g. /country/us/cities/sf, /country/france/cities/paris, /country/france/cities/nancy form a tree with three nodes. When a request reaches the application, its path is being compared with each branch from that tree (in other words, the tree is being traversed to find a matching branch). If a branch matches the requested path, the associated logic is applied.

Such approach goes well with document-oriented approach of MongoDB database; it allows to map application’s routes hierarchy directly into a hierarchy of the underlaying data store. For the previous example, /country segment can be mapped to countries collection in a MongoDB database while /city segment could be associated with embedded cities collection. Obviously, this only makes sense if it’s the natural way to present the data, i.e. a city cannot belong to the same country at the same time.

When using traversal, we don't need the code that dispatches requests (let’s remove that from __init__.py). The dispatch process is being handled by Pyramid’s resource layer - each Pyramid’s resource represent a node in a virtual tree that maps to the structure of a route.

Let’s start with the resource abstraction that is built around dict. It knows what is its parent and how to bind another resource node to it via add_child method.

class Resource(dict):

    def __init__(self, ref, parent):
        self.__name__ = ref
        self.__parent__ = parent

    def __repr__(self):
        # use standard object representation (not dict's)
        return object.__repr__(self)

    def add_child(self, ref, klass):
        resource = klass(ref=ref, parent=self)
        self[ref] = resource

In the next step, we are going to focus on a persistence abstraction and separate MongoDB collection from MongoDB document representation. A collection should only know how to fetch its all elements (its retrieve method) and how to add a new element to that collection (its create method).

class MongoCollection(Resource):

    def collection(self):
        root = find_root(self)
        request = root.request
        return request.db[self.collection_name]

    def retrieve(self):
      return [elem for elem in self.collection.find()]

    def create(self, document):
        object_id = self.collection.insert(document)
        return self.resource_name(ref=str(object_id), parent=self)

A single document abstraction operates on « itself » and should be able (1) to return an element for a particular identifier, (2) to update an element with a particular identifier or (3) to delete an element with a particular identifier; this identifier is stored inside ref for a given resource.

class MongoDocument(Resource):

    def __init__(self, ref, parent):
        Resource.__init__(self, ref, parent)

        self.collection = parent.collection
        self.spec = {'_id': ObjectId(ref)}

    def retrieve(self):
        return self.collection.find_one(self.spec)

    def update(self, data, patch=False):
        if patch:
            data = {'$set': data}

        self.collection.update(self.spec, data)

    def delete(self):

update method is able to different between a partial update (when patch is True) and full update (a resource is fully replaced).

With those persistence abstraction, we can now construct resources that will correspond to our City resource, i.e. its collection (named Cities) and its single document (named City).

class City(MongoDocument):

    def __init__(self, ref, parent):
        MongoDocument.__init__(self, ref, parent)

class Cities(MongoCollection):

     collection_name = 'cities'
     resource_name = City

     def __getitem__(self, ref):
          return City(ref, self)

Cities collection delegates the task to City document when an identifier is provided.

Now, we are ready to assemble it all together using Root resource.

class Root(Resource):

    def __init__(self, request):
        Resource.__init__(self, ref='', parent=None)

        self.request = request
        self.add_child('cities', Cities)

Test it

With everything put in place, we are ready to run our application and see how it behaves. First, let’s create several cities

curl -XPOST -d ‘{ “name”: “Poznan”, “population”: “550,742" }' localhost:6543/cities
curl -XPOST -d ‘{ “name”: “Paris”, “population”: “2,234,105" }' localhost:6543/cities
curl -XPOST -d ‘{ “name”: “San Francisco”, “population”: “825,865" }' localhost:6543/cities

Let’s verify if were persisted and are available from the API.

curl localhost:6543/cities
[{"_id": {"$oid": "5292826fa0022dde6b80ebf0"}, "name": "Paris", "population": "2,234,105"}, {"_id": {"$oid": "52928283a0022dde6b80ebf1"}, "name": "San Francisco", "population": "825,865"}, {"_id": {"$oid": "5292abce643a0851b949db22"}, "name": "Poznan", "population": "550,742"}]%

There is a small mistake in the name of Poznań city. The last letter is a special character. Let’s amend it by updating that particular city.

curl -XPUT -d '{"name": "Poznań"}' localhost:6543/cities/5292abce643a0851b949db22

Let’s see if that changed has been taken into account by retrieving that particular city.

curl localhost:6543/cities/5292abce643a0851b949db22
{"_id": {"$oid": "5292abce643a0851b949db22"}, "name": "Pozna\u0144", "population": "550,742"}%

Lastly, we should be able to remove any city.

curl -XDELETE localhost:6543/cities/5292826fa0022dde6b80ebf0
curl localhost:6543/cities
[{"_id": {"$oid": "52928283a0022dde6b80ebf1"}, "name": "San Francisco", "population": "825,865"}, {"_id": {"$oid": "5292abce643a0851b949db22"}, "name": "Poznan", "population": "550,742"}]%


Our application looks now much more like a real RESTful API. We have implemented all CRUD operations backed with a MongoDB database. We have also switched the routing mechanism into traversal. The application, however, is not very generic: there are many code repetitions, error handling is rudimentary and we haven’t written a single test. In the next article, I will show you how to solve these problems.

The code of this tutorial is available on Github under persist-part2 tag.

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