App Engine application for the Udacity training course.

Products

• App Engine

Language

• Python

APIs

• Google Cloud Endpoints

Setup Instructions

1. Update the value of application in app.yaml to the app ID you have registered in the App Engine admin console and would like to use to host your instance of this sample.
2. Update the values at the top of settings.py to reflect the respective client IDs you have registered in the Developer Console.
3. Update the value of CLIENT_ID in static/js/app.js to the Web client ID
4. (Optional) Mark the configuration files as unchanged as follows: $ git update-index --assume-unchanged app.yaml settings.py static/js/app.js
5. Run the app with the devserver using dev_appserver.py DIR, and ensure it's running by visiting your local server's address (by default localhost:8080.)
6. (Optional) Generate your client library(ies) with the endpoints tool.
7. Deploy your application.

APP:

Name: mozgul-udacity-fs-p4
Access: mozgul-udacity-fs-p4.appspot.com

Task 1:

Design Decisions:

#####Profile 1--* Conferences Profile has many (created/owned) conferences. Conference belongs to one profile (creator)

#####Conference 1--* Sessions Conference has many sessions. Session belongs to one conference

#####Speaker: Option 1) Implemented this option. Speaker is a (string) property of session.
If app business logic is not focusing on speakers (we are not keeping other information about the speaker other than name), faster implementation, faster read time for sessions and grabbing the speaker name. But duplicating speaker data (name).

Option 2) NOT Implemented this option. Speaker as a seperate entity. Use key (or keys) to associate with session. Can store more information about speakers. A single update to a speaker is reflected to every related session, for example no need to iterate through every session object to fix a name typo for speaker.

#####Wishlist: Wishlist is a repeated string property field, containing keys of sessions.

class Profile(ndb.Model):
    """Profile -- User profile object"""
    displayName = ndb.StringProperty()
    mainEmail = ndb.StringProperty()
    teeShirtSize = ndb.StringProperty(default='NOT_SPECIFIED')
    conferenceKeysToAttend = ndb.StringProperty(repeated=True)
    sessionKeysWishlisted = ndb.StringProperty(repeated=True)

class Session(ndb.Model):
    """Session -- Session object"""
    name = ndb.StringProperty(required=True)
    speaker = ndb.StringProperty()
    sessionType = ndb.StringProperty()
    startTime = ndb.StringProperty()
    duration = ndb.IntegerProperty()
    highlights = ndb.StringProperty()

class SessionForm(messages.Message):
    """SessionForm -- Session outbound form message"""
    name = messages.StringField(1)
    speaker = messages.StringField(2)
    sessionType = messages.StringField(3)
    startTime = messages.StringField(4)
    duration = messages.IntegerField(5)
    urlsafe_id = messages.StringField(6)
    highlights = messages.StringField(7)

Task 3:

Query Problem

Question:

Let’s say that you don't like workshops and you don't like sessions after 7 pm. How would you handle a query for all non-workshop sessions before 7 pm? What is the problem for implementing this query? What ways to solve it did you think of?

Answer:

From docs:

Inequality filters are limited to at most one property.  

To avoid having to scan the entire index, the query mechanism relies on all 
of a query's potential results being adjacent to one another in the index. 

To satisfy this constraint, a single query may not use inequality comparisons 
(LESS_THAN, LESS_THAN_OR_EQUAL, GREATER_THAN, GREATER_THAN_OR_EQUAL) on more 
than one property across all of its filters.

Workarounds:

Option 1) Apply one inequality filter, do the rest of the filtering by manually iterating
Option 2) Enumerate possible types (lecture, workshop, training, qa) and use equalities or IN operator for the types other than the undesired ones

Additional Queries:

1. getSessionsWithMissingData: Query for all the sessions that has missing properties. Used for quality user experience, these incomplete sessions can be fixed or deleted.
2. getLightningTalks: Query for all the sessions that are between 5-20 mins long.