Python, RapidAPI Terms

APIs and tooling like Jupyter docs allows many opportunities in fields like Data Science. As more and more developers use APIs, they build standards in how you setup a client, send requests and receive information...

Covid19 RapidAPI Example

To begin the API journey. You need to find an API provider.

  • RapidAPI is a great option. You must setup and account, but there are many free options.
  • Goto this page for starters, the Corona virus World and India data- Under Code Snippets pick Python - Requests

RapidAPI, you will select Python Requests type of code to work with you Notebook.

  • The url is the endpoint to which the API is directed
  • The headers is a dictionary data structure to send special messaging to the endpoint
  • The requests.request() python function is used to send a request and retrieve their responses
  • The response variable receives result of of the request in JSON text

Next step, is to format the response according to your data science needs

"""
Requests is a HTTP library for the Python programming language. 
The goal of the project is to make HTTP requests simpler and more human-friendly. 
"""
import requests

url = "https://cost-of-living-and-prices.p.rapidapi.com/cities"

headers = {
	"X-RapidAPI-Key": "hi",
	"X-RapidAPI-Host": "hi"
}

response = requests.request("GET", url, headers=headers)

print(response.text)

# # This code looks for "house types"
# print("House Type: ")
# names = response.json().get('homeType')  # turn response to json() so we can extract "homeType"
# for key in names.items():  # this finds key, value pairs in country
#     print(key)

# # print()

# This code looks for San Diego

result = response.json().get('cities')
for re in result:  
    if re["city_name"] == "San Diego":  
        for key, value in re.items(): 
            print(key, value)



# print("Condos: ")
# condos = response.json().get('homeType')
# for condo in condos:  
#     if condo["homeType"] == "CONDO":  
#         for key, value in condo.items():  
#             print(key, value)

Digital Coin Example

This example provides digital coin feedback (ie Bitcoin). It include popularity, price, symbols, etc.

  • A valid X-RapidAPI-Key is required. Look in code for link to RapidAPI page
  • Read all comments in code for further guidance
# RapidAPI page https://rapidapi.com/Coinranking/api/coinranking1/

# Begin Rapid API Code
import requests

url = "https://coinranking1.p.rapidapi.com/coins"
querystring = {"referenceCurrencyUuid":"yhjMzLPhuIDl","timePeriod":"24h","tiers[0]":"1","orderBy":"marketCap","orderDirection":"desc","limit":"50","offset":"0"}
headers = {
	"X-RapidAPI-Key": "jcmbea0fa2ff5msh7f14bf69be38ca6p175482jsn6c4988114560",  # place your key here
	"X-RapidAPI-Host": "coinranking1.p.rapidapi.com"
}

response = requests.request("GET", url, headers=headers, params=querystring)
print(response.text)
# End Rapid API Code
json = response.json()  # convert response to python json object

# Observe data from an API.  This is how data transports over the internet in a "JSON" text form
# - The JSON "text" is formed in dictionary {} and list [] divisions
# - To read the result, Data Scientist of  Developer converts JSON into human readable form
# - Review the first line, look for the keys --  "status" and "data"

Formatting Digital Coin example

JSON text transferred from the API in the previous cell was converted to a Python Dictionary called json. The "coins" in the dictionary contain a list of the most relevant data. Look at the code and comments to see how the original text is turned into something understandable. Additionally, there are error check to make sure we are starting the code with the expectation that the API was run correctly.

"""
This cell is dependent on valid run of API above.
- try and except code is making sure "json" was properly run above
- inside second try is code that is used to process Coin API data

Note.  Run this cell repeatedly to format data without re-activating API
"""

try:
    print("JSON data is Python type: " + str(type(json)))
    try:
        # Extracting Coins JSON status, if the API worked
        status = json.get('status')
        print("API status: " + status)
        print()
        
        # Extracting Coins JSON data, data about the coins
        data = json.get('data')
        
        # Procedural abstraction of Print code for coins
        def print_coin(c):
            print(c["symbol"], c["price"])
            print("Icon Url: " + c["iconUrl"])
            print("Rank Url: " + c["coinrankingUrl"])

        # Coins data was observed to be a list
        for coin in data['coins']:
            print_coin(coin)
            print()
            
    except:
        print("Did you insert a valid key in X-RapidAPI-Key of API cell above?")
        print(json)
except:
    print("This cell is dependent on running API call in cell above!")

JSON data is Python type: <class 'dict'>
Did you insert a valid key in X-RapidAPI-Key of API cell above?
{'message': 'You are not subscribed to this API.'}

menu =  {"burger": 3.99,
         "fries": 1.99,
         "drink": 0.99}
total = 0

#shows the user the menu and prompts them to select an item
print("Menu")
for k,v in menu.items():
    print(k + "  $" + str(v)) #why does v have "str" in front of it?

order = []
#ideally the code should prompt the user multiple times
item = input("Please select an item from the menu")

# total += menu.get(item)

#code should add the price of the menu items selected by the user 
print(total + menu.get(item))

Go deeper into APIs

Web Development vs Jupyter Notebook. A notebook is certainly a great place to start. But, for your end of Trimester project we want you to build the skill to reference and use APIs within your Project. Here are some resources to get you started with this journey.

Hacks

Find and use an API as part of your project. An API and a little coding logic will be a big step toward getting meaningful data for a project. There are many API providers, find one that might work for your project to complete this hack. When picking an API you are looking for something that will work with either JavaScript Fetch or Python Request. Here are some samples, these are not qualified in any way.

Show API and format results in either Web Page or Jupyter Notebook. Ultimately, I will expect that we do APIs in backend (Python/Flask). However, for this Hack you can pick your preference. We will discuss pros and cons in next API tech talk.