Sign up for a Bluemix account, learn how to obtain Personality Insights API credentials, interact with Personality Insights using Python, and analyze authored content from Twitter.

Using the Personality Insights API

Before we can send the content we retrieve from Twitter to Personality Insights to be analyzed, we need to setup the credentials for the Personality Insights.

We can do this by adding two variables that will store the username and password that are _unique to the Personality Insights instance_ you created in the previous exercise.

For example:

```py
text = "" 

for s in statuses:
    if (s.lang =='en'):
        text+=s.text.encode('utf-8')

#The IBM Bluemix credentials for Personality Insights!
pi_username = ''
pi_password = ''
```

Configuring Personality Insights Package

Personality Insights is a service that is part of the Watson Developer Cloud. The Watson Developer Cloud has a single software development kit (SDK) that allows users to access all of the available services. 

To use the SDK, you'll need an IBM Bluemix username and password. After creating a Bluemix account, you'll be able to use Personality Insights in the **Celebrity Match** application (and beyond Codecademy):

1. <a href="https://console.ng.bluemix.net/registration/?cm_mc_uid=41462758644914551453431&cm_mc_sid_50200000=1455145343" target="_blank">Login to Bluemix (or create an account)</a> (**Note:** Bluemix credentials are required to successfully complete the application we're building)
2. Create an instance of the Personality Insights service 
3. Click on “Service Credentials” in the navigation area to the left to access the username and password for Personality Insights service. 
 
For details on how to add a service instance to your account, follow the steps in the <a href="https://www.ng.bluemix.net/docs/services/reqnsi.html#add_service" target="_blank">IBM Bluemix documentation</a>.


IBM Bluemix

We'll use Personality Insights (PI) to analyze the data (tweets) that the **Celebrity Match** application retrieves from Twitter.

PI is just one of many services available in the Watson Developer Cloud and is part of the Bluemix Services Catalog. 

PI uses linguistic analytics to infer personality and social characteristics from unstructured text (like the Twitter data we retrieve). This service infers personality characteristics by using three models: 

* Big Five - the most generally used model which describes 5 dimensions of the personality (Agreeableness, Conscientiousness, Extraversion, Emotional Range, and Openness).
* Needs - describes what product attributes will resonate well with the person.
* Values - describes the factors that will motivate a user's decision making.
 
You can learn more about the models and their dimensions <a href="https://www.ibm.com/smarterplanet/us/en/ibmwatson/developercloud/doc/personality-insights/models.shtml" target="_blank">here</a>.

To get inspired and see use cases with Personality Insights and other Watson APIs, check out IBM's <a href="https://www.ibm.com/marketplace/learning-lab/use-cases/us/en-us" target="_blank">Learning Lab</a>

Overview: Personality Insights

Next, we'll make use of the `watson_developer_cloud` Python package we imported earlier.

Similar to how we interacted with the Twitter API, we'll create an instance, initialize it with a username and password, and set it equal to a variable called `personality_insights`, like so:

```py
personality_insights = PersonalityInsights(username=pi_username, password=pi_password) 
```

The variable `personality_insights` _represents_ the Personality Insights API that we'll interact with.