Direct Lake Mode in Power BI Fabric: Real-Time Speed Meets Enterprise Scale

Twitter is a good source for mining text. Because 330 million monthly active users are tweeting. For extracting the data from the Twitter we need to access the Twitter API.

Twitter API

Twitter API is REST API(Representational state transfer api)  and it outputs a json file which is faster than traditional xml data transfer method. By using Twitter API we can access some of the elements that tweet contains tweet,author name,tweeted time etc, all these things are encoded in json file.

In order to connect to twitter API you need to have a Twitter account and for developers you can register from right here https://apps.twitter.com/ and create a  new app

After that you will be provided 2 keys those are consumer key and access key. This authentication method is called OAuth authentication

Using of OAuth autentication provide following benifits

• Tweets can be customized to have a string which identifies the app which was used.
• It doesn’t reveal user password, making it more secure.
• It's easier to manage the permissions, for example a set of tokens and keys can be generated that only allows reading from the timelines, so in case someone obtains those credentials, he/she won’t be able to write or send direct messages, minimizing the risk.
• The application doesn't reply on a password, so even if the user changes it, the application will still work.

In the Keys and Access Tokens you can get the relevant consumer and access keys.

After using tweepy we can handle the authentication process as follows After that you can get the twitters from the api.
Representation of data
above shows a sample json file from the twitter API
after getting from the api we can simply get that from the tweepy cursor.
above code will store the cursor value in a python Dictionary.

References

http://www.tweepy.org/