In an R&D company fast prototyping is vital to develop new projects or proofs of concept quickly and inexpensively. In this talk we will demonstrate how real fast and agile development can be achieved with MongoDB and dynamic languages, with examples and best practices. All the code shown is already uploaded to a public Git repository - https://github.com/pablito56/py-eshop

1. FAST REST APIS DEVELOPMENT
WITH MONGODB
Pablo Enfedaque Vidal
@pablitoev56

2. WHO?
• Pablo Enfedaque
• Computers Engineer
• Tech Lead and R&D software engineer at Telefonica Digital
• Working with MongoDB for some years.

3. TELEFONICA DIGITAL. WHAT?
• Telefonica
• Fifth largest telecommunications company in the world
• Operations in Europe (7 countries), the United States and
Latin America (15 countries)
• Movistar, O2, Vivo, Terra, Tuenti, Jahjah, Tokbox,
everything.me, Open Web Device…

4. TELEFONICA DIGITAL. WHAT?
• Telefonica Digital
• Web and mobile digital contents and services division
• Product Development and Innovation unit
• Products & services development, research, technology
strategy, user experience, deployment & operations…
• Around 70 different on going projects

5. OUR PROJECTS
• Full product development, with life cycle and several deployments
• 20 people team, 1 year or more
• Pilot or small product to be deployed in a certain environment
• 6 people team, 6 months
• Seedbed or proof of concept to be run with reduced set of users
• 3 people team, 3 months
• Ten Fridays open exploratory project to work on your ideas
• 2 people team, 10 days (consecutive Fridays)

6. SO…
FAST DEVELOPMENT IS
REALLY CRUCIAL FOR US

7. HOW TO SPEED UP OUR DEVELOPMENTS?
• Agile methodologies
• Lean startup
• eXtreme Programming
• Continuous Integration
• …

8. HOW TO SPEED UP OUR DEVELOPMENTS?
CHOOSE THE
RIGHT TECHNOLOGY
(AT FIRST)

9. ¿ RIGHT TECHNOLOGY ?

10. THE RIGHT TECHNOLOGY
• Faster development with Dynamic Languages
• 3x
• 4x
• 10x

11. THE RIGHT TECHNOLOGY
THE SAME CAN BE STATED FOR
• 3x
MONGODB
• 4x
• 10x

12. THE RIGHT TECHNOLOGY
• Several times faster development with Dynamic Languages
• Several times faster development with MongoDB
AND BOTH TOGETHER IS A
WIN WIN

13. WHY? HOW?
LET’S SEE SOME EXAMPLES

14. ONLY DYNAMIC LANGUAGES?

15. JAVA VERSION
public int[] getDims() {
if (this.dims != null) {
return this.dims;
}
BasicDBObject query = new BasicDBObject();
query.put("_id", "ctxt_dimensions");
DBObject setup = setup_coll.findOne(query);
BasicDBList dbl = (BasicDBList)setup.get("dims");
this.dims = new int[dbl.size() + 2];
BasicDBObject users_counter_ref = new BasicDBObject("_id", users_coll_name);
BasicDBObject apps_counter_ref = new BasicDBObject("_id", apps_coll_name);
dims[0] = (Integer)counters_coll.findOne(users_counter_ref).get("value") + 1;
dims[1] = (Integer)counters_coll.findOne(apps_counter_ref).get("value") + 1;
for (int i=0; i<dbl.size(); i++) {
dims[i + 2] = (Integer)dbl.get(i);
}
return dims;
}

16. PYTHON VERSION
def get_dims(self):
ud = self.counters_coll.find_one({'_id': 'users'})['value']
ad = self.counters_coll.find_one({'_id': 'applications'})['value']
res = [ud, ad]
res.extend(self.setup_coll.find_one({}, {'dims': 1})['dims'])
return res
IT’S UP TO YOU…

17. THE RIGHT TECHNOLOGY

18. LET’S PLAY TO SPOT THE
DIFFERENCES

19. EXAMPLE: SPEAKER JSON
{
"name": "Pablo Enfedaque",
"company": "Telefonica Digital",
"accepted": true,
"registration_date": "2012-03-15T14:35:05",
"num_talks": 1,
”votes": 4,
"email": "pev@td.com"
}

20. EXAMPLE: DECODED JSON (PYTHON)
{
"name": "Pablo Enfedaque",
"company": "Telefonica Digital",
"accepted": True,
"registration_date": datetime(2012, 3, 15, 14, 35, 5),
"num_talks": 1,
”votes": 4,
"email": "pev@td.com"
}

21. EXAMPLE: MONGODB BSON
{
"name": "Pablo Enfedaque",
"company": "Telefonica Digital",
"accepted": true,
"registration_date": ISODate("2012-03-15T14:35:05Z"),
"num_talks": 1,
”votes": 4,
"email": "pev@td.com",
”_id": ObjectId("5142d08c5db1362abc2d208b”)
}

22. LOOKS PRETTY
STRAIGHT FORWARD,
RIGHT?

23. SPEAKER CREATION
decoded_input = json.loads(input_json)
decoded_input['registration_date'] =
datetime.strptime(decoded_input['registration_date'], "%Y-%m-%dT%H:%M:
%S”)
return dbconn['speakers'].insert(decoded_input)
> ObjectId('5142d2845db1362bb3155322')

24. SPEAKER RETRIEVAL
retrieved = dbconn['speakers'].find_one({'name': 'Pablo'}, {'_id': 0})
retrieved['registration_date'] =
retrieved['registration_date'].strftime("%Y-%m-%dT%H:%M:%S")
return retrieved

25. IT IS REALLY
STRAIGHT FORWARD!

26. WHAT IF WE WANT TO
CHANGE SPEAKERS DATA?

27. EXAMPLE: SPEAKER JSON
{
"name": "Pablo Enfedaque",
"company": "Telefonica Digital",
"position": "R&D SW Engineer",
"accepted": true,
"registration_date": "2012-03-15T14:35:05",
"num_talks": 1,
”votes": 4.3,  WAS AN INTEGER
"email": "pev@td.com"
}

28. SPEAKER CREATION
decoded_input = json.loads(input_json)
decoded_input['registration_date'] =
datetime.strptime(decoded_input['registration_date'], "%Y-%m-%dT%H:%M:
%S”)
return dbconn['speakers'].insert(decoded_input)
SPEAKER RETRIEVAL
retrieved = dbconn['speakers'].find_one({'name': 'Pablo'}, {'_id': 0})
retrieved['registration_date'] =
retrieved['registration_date'].strftime("%Y-%m-%dT%H:%M:%S")
0 LINES CHANGED
return retrieved

29. INPUT VALIDATION NEEDED?

30. SPEAKER VALIDATION
from rest_framework import serializers
class SpeakerSerializer(serializers.Serializer):
name = serializers.CharField(max_length=150)
company = serializers.CharField(max_length=150)
position = serializers.CharField(required=False)
accepted = serializers.BooleanField()
registration_date = serializers.DateTimeField()
num_talks = serializers.IntegerField()
votes = serializers.FloatField()
email = serializers.EmailField(max_length=150)
def restore_object(self, attrs, instance=None):
return attrs

31. SPEAKER CREATION
decoded_input = json.loads(input_json)
serializer = SpeakerSerializer(decoded_input)
print dbconn['speakers'].insert(serializer.object)
SPEAKER RETRIEVAL
retrieved = dbconn['speakers'].find_one({'name': 'Pablo'})
serializer = SpeakerSerializer(retrieved)
return serializer.object

32. DON’T LIKE TO WORK WITH
DICTIONARIES / HASHES?

33. CUSTOMISE ATTRIBUTES ACCESS
class AttrDict(dict):
def __getattr__(self, name):
try:
return super(AttrDict, self).__getitem__(name)
except KeyError, e:
raise AttributeError(e)
def __setattr__(self, name, value):
if name in self:
super(AttrDict, self).__setitem__(name, value)
else:
super(AttrDict, self).__setattr__(name, value)

34. USE DICTIONARIES AS OBJECTS
decoded_input = json.loads(input_json)
serializer = SpeakerSerializer(decoded_input)
speaker_obj = AttrDict(serializer.object)
print speaker_obj.company
print speaker_obj['position']
> Telefonica Digital
R&D SW Engineer

35. USE AN ORM?

36. NO

37. OBJECT-RELATIONAL MAPPER
NO RELATIONAL  NO ORM
NEEDED

38. CONCLUSIONS

39. CONCLUSIONS
• MongoDB + dynamic languages = fastest development speed
• 14 months project with Oracle à 3 months project with MongoDB
• REST API best practices
• Use JSON
• Use dictionaries / hashes
• Access dictionaries as objects
• No relational model à no ORM
• No other mappers
• Use decorators to handle AutoReconnect