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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Lets Concept all the things!!!
First we need to import the goodies. Then we will start with Python...
Step1:  Now I am going to explode the and see what it does...
Step2:  The next operation explores the edges of the concept
Step3:  Expansion
The Concept Insights API returns its results in order of their relevance to the one at hand, but between the size of Wikipedia and the depth IBM Watson's own cognitive understanding this can result in unmanagably thousands of articles. To keep the information firehose at a managable level the Concept Insights service two parameters which are passed through by watsongraph graph-expansion methods
Step4:  Lets Start over with Python shall we? Yes we shall...
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Python Code:
py = ConceptModel(['Python'])
py.concepts()
Explanation: Lets Concept all the things!!!
First we need to import the goodies. Then we will start with Python...
End of explanation
py.explode()
len(py.concepts())
Explanation: Now I am going to explode the and see what it does...
End of explanation
py.edges()
Explanation: The next operation explores the edges of the concept
End of explanation
database = ConceptModel(['Database'])
database.explode(limit=2000, level=1)
len(database.concepts())
database.edges()[:20]
py.edges()[:20]
py.augment('Standard Library')
len(py.concepts())
py.neighborhood('Standard Library')
Explanation: Expansion
The Concept Insights API returns its results in order of their relevance to the one at hand, but between the size of Wikipedia and the depth IBM Watson's own cognitive understanding this can result in unmanagably thousands of articles. To keep the information firehose at a managable level the Concept Insights service two parameters which are passed through by watsongraph graph-expansion methods:
limit: The maximum number of concepts to be returned. Can be any int. Throttled to 50 by default.
level: The popularity threshold of the articles that will be returned, on a 0 (highest) to 5 (lowest) scale. Throttled to 0 by default.
The basic explode() command is a level-0 query. What happens when we play with the levels a bit?
End of explanation
py.abridge('Standard Library')
len(py.concepts())
py.abridge('Python')
len(py.concepts())
py.abridge('Database')
len(py.concepts())
py.remove()
Explanation: Lets Start over with Python shall we? Yes we shall...
End of explanation
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