Building a Python-based airline solution using Amadeus API

Hi Guys,

Today, I’ll share a little different topic in Python compared to my last couple of posts, where I have demonstrated the use of Python in the field of machine learning & forecast modeling.

We’ll explore to create meaningful sample data points for Airlines & hotel reservations. At this moment, this industry is the hard-hit due to the pandemic. And I personally wish a speedy recovery to all employees who risked their lives to maintain the operation or might have lost their jobs due to this time.

I’ll be providing only major scripts & will show how you can extract critical data from their API.

However, to create the API, you need to register in Amadeus as a developer & follow specific steps to get the API details. You will need to register using the following link.

Step 1:

1. Generating API - Step 1

Once you provide the necessary details, you need to activate your account by clicking the email validation.

Step 2:

As part of the next step, you will be clicking the “Self-Service Workspace” option as marked in the green box shown above.

Now, you have to click My apps & under that, you need to click – Create new appshown below –

2. Generating API - Step 2

Step 3:

You need to provide the following details before creating the API. Note that once you create – it will take 30 minutes to activate the API-link.

3. Generating API - Step 3

Step 4:

You will come to the next page once you click the “Create” button in the previous step.

4. Generating API - Step 4

For production, you need to create a separate key shown above.

You need to install the following packages –

pip install amadeus

And, the installation process is shown as –

5. Installing Packages

pip install flatten_json

And, this installation process is shown as –

6. Installing Packages - Continuation

1. clsAmedeus (This is the API script, which will send the API requests & return JSON if successful.)

##############################################
#### Written By: SATYAKI DE               ####
#### Written On: 05-Jul-2020              ####
#### Modified On 05-Jul-2020              ####
####                                      ####
#### Objective: Main calling scripts.     ####
##############################################

from amadeus import Client, ResponseError
import json
from clsConfig import clsConfig as cf

class clsAmedeus:
    def __init__(self):
        self.client_id = cf.config['CLIENT_ID']
        self.client_secret = cf.config['CLIENT_SECRET']
        self.type = cf.config['API_TYPE']

    def flightOffers(self, origLocn, destLocn, departDate, noOfAdult):
        try:
            cnt = 0

            # Setting Clients
            amadeus = Client(
                                client_id=str(self.client_id),
                                client_secret=str(self.client_secret)
                            )

            # Flight Offers
            response = amadeus.shopping.flight_offers_search.get(
                originLocationCode=origLocn,
                destinationLocationCode=destLocn,
                departureDate=departDate,
                adults=noOfAdult)

            ResJson = response.data

            return ResJson
        except Exception as e:
            print(e)
            x = str(e)
            ResJson = {'errorDetails': x}

            return ResJson

    def cheapestDate(self, origLocn, destLocn):
        try:
            # Setting Clients
            amadeus = Client(
                client_id=self.client_id,
                client_secret=self.client_secret
            )

            # Flight Offers
            # Flight Cheapest Date Search
            response = amadeus.shopping.flight_dates.get(origin=origLocn, destination=destLocn)

            ResJson = response.data

            return ResJson
        except Exception as e:
            print(e)
            x = str(e)
            ResJson = {'errorDetails': x}

            return ResJson

    def listOfHotelsByCity(self, origLocn):
        try:
            # Setting Clients
            amadeus = Client(
                client_id=self.client_id,
                client_secret=self.client_secret
            )

            # Hotel Search
            # Get list of Hotels by city code
            response = amadeus.shopping.hotel_offers.get(cityCode=origLocn)

            ResJson = response.data

            return ResJson
        except Exception as e:
            print(e)
            x = str(e)
            ResJson = {'errorDetails': x}

            return ResJson

    def listOfOffersBySpecificHotels(self, hotelID):
        try:
            # Setting Clients
            amadeus = Client(
                client_id=self.client_id,
                client_secret=self.client_secret
            )

            # Get list of offers for a specific hotel
            response = amadeus.shopping.hotel_offers_by_hotel.get(hotelId=hotelID)

            ResJson = response.data

            return ResJson
        except Exception as e:
            print(e)
            x = str(e)
            ResJson = {'errorDetails': x}

            return ResJson

    def hotelReview(self, hotelID):
        try:
            # Setting Clients
            amadeus = Client(
                client_id=self.client_id,
                client_secret=self.client_secret
            )

            # Hotel Ratings
            # What travelers think about this hotel?
            response = amadeus.e_reputation.hotel_sentiments.get(hotelIds=hotelID)

            ResJson = response.data

            return ResJson
        except Exception as e:
            print(e)
            x = str(e)
            ResJson = {'errorDetails': x}

            return ResJson

    def process(self, choice, origLocn, destLocn, departDate, noOfAdult, hotelID):
        try:
            # Main Area to call apropriate choice
            if choice == 1:
                resJson = self.flightOffers(origLocn, destLocn, departDate, noOfAdult)
            elif choice == 2:
                resJson = self.cheapestDate(origLocn, destLocn)
            elif choice == 3:
                resJson = self.listOfHotelsByCity(origLocn)
            elif choice == 4:
                resJson = self.listOfOffersBySpecificHotels(hotelID)
            elif choice == 5:
                resJson = self.hotelReview(hotelID)
            else:
                resJson = {'errorDetails': 'Invalid Options!'}

            # Converting back to JSON
            jdata = json.dumps(resJson)

            # Checking the begining character
            # for the new package
            # As that requires dictionary array
            # Hence, We'll be adding '[' if this
            # is missing from the return payload
            SYM = jdata[:1]
            if SYM != '[':
                rdata = '[' + jdata + ']'
            else:
                rdata = jdata

            ResJson = json.loads(rdata)

            return ResJson

        except ResponseError as error:
            x = str(error)
            resJson = {'errorDetails': x}

            return resJson

Let’s explore the key lines –

Creating an instance of the client by providing the recently acquired API Key & API-Secret.

# Setting Clients
amadeus = Client(
                    client_id=str(self.client_id),
                    client_secret=str(self.client_secret)
                )

The following lines are used to fetch the API response for specific business cases. Different invocation of API retrieve different data –

# Flight Offers
# Flight Cheapest Date Search
response = amadeus.shopping.flight_dates.get(origin=origLocn, destination=destLocn)

The program will navigate to particular methods to invoke certain features –

# Main Area to call apropriate choice
if choice == 1:
    resJson = self.flightOffers(origLocn, destLocn, departDate, noOfAdult)
elif choice == 2:
    resJson = self.cheapestDate(origLocn, destLocn)
elif choice == 3:
    resJson = self.listOfHotelsByCity(origLocn)
elif choice == 4:
    resJson = self.listOfOffersBySpecificHotels(hotelID)
elif choice == 5:
    resJson = self.hotelReview(hotelID)
else:
    resJson = {'errorDetails': 'Invalid Options!'}

2. callAmedeusAPI (This is the main script, which will invoke the Amadeus API & return dataframe if successful.)

##############################################
#### Written By: SATYAKI DE               ####
#### Written On: 05-Jul-2020              ####
#### Modified On 05-Jul-2020              ####
####                                      ####
#### Objective: Main calling scripts.     ####
##############################################

from clsConfig import clsConfig as cf
import clsL as cl
import logging
import datetime
import clsAmedeus as cw
import pandas as p
import json

# Newly added package
from flatten_json import flatten

# Disbling Warning
def warn(*args, **kwargs):
    pass

import warnings
warnings.warn = warn

# Lookup functions from
# Azure cloud SQL DB

var = datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S")

def main():
    try:
        # Declared Variable
        ret_1 = 0
        textOrig = ''
        textDest = ''
        textDate = ''
        intAdult = 0
        textHotelID = ''
        debug_ind = 'Y'
        res_2 = ''

        # Defining Generic Log File
        general_log_path = str(cf.config['LOG_PATH'])

        # Enabling Logging Info
        logging.basicConfig(filename=general_log_path + 'AmadeusAPI.log', level=logging.INFO)

        # Initiating Log Class
        l = cl.clsL()

        # Moving previous day log files to archive directory
        log_dir = cf.config['LOG_PATH']
        curr_ver =datetime.datetime.now().strftime("%Y-%m-%d")

        tmpR0 = "*" * 157

        logging.info(tmpR0)
        tmpR9 = 'Start Time: ' + str(var)
        logging.info(tmpR9)
        logging.info(tmpR0)

        print("Log Directory::", log_dir)
        tmpR1 = 'Log Directory::' + log_dir
        logging.info(tmpR1)

        print('Welcome to Amadeus Calling Program: ')
        print('-' * 60)
        print('Please Press 1 for flight offers.')
        print('Please Press 2 for cheapest date.')
        print('Please Press 3 for list of hotels by city.')
        print('Please Press 4 for list of offers by specific hotel.')
        print('Please Press 5 for specific hotel review.')
        input_choice = int(input('Please provide your choice:'))

        # Create the instance of the Amadeus Class
        x2 = cw.clsAmedeus()

        # Let's pass this to our map section
        if input_choice == 1:
            textOrig = str(input('Please provide the Origin:'))
            textDest = str(input('Please provide the Destination:'))
            textDate = str(input('Please provide the Depart Date:'))
            intAdult = int(input('Please provide the No Of Adult:'))

            retJson = x2.process(input_choice, textOrig, textDest, textDate, intAdult, textHotelID)
        elif input_choice == 2:
            textOrig = str(input('Please provide the Origin:'))
            textDest = str(input('Please provide the Destination:'))

            retJson = x2.process(input_choice, textOrig, textDest, textDate, intAdult, textHotelID)
        elif input_choice == 3:
            textOrig = str(input('Please provide the Origin:'))

            retJson = x2.process(input_choice, textOrig, textDest, textDate, intAdult, textHotelID)
        elif input_choice == 4:
            textHotelID = str(input('Please provide the Hotel Id:'))

            retJson = x2.process(input_choice, textOrig, textDest, textDate, intAdult, textHotelID)
        elif input_choice == 5:
            textHotelID = str(input('Please provide the Hotel Id:'))

            retJson = x2.process(input_choice, textOrig, textDest, textDate, intAdult, textHotelID)
        else:
            print('Invalid options!')
            retJson = {'errorDetails': 'Invalid Options!'}

        #print('JSON::')
        #print(retJson)

        # Converting JSon to Pandas Dataframe for better readability
        # Capturing the JSON Payload
        res_1 = json.dumps(retJson)
        res = json.loads(res_1)

        # Newly added JSON Parse package
        dic_flattened = (flatten(d) for d in res)
        df_ret = p.DataFrame(dic_flattened)

        # Removing any duplicate columns
        df_ret = df_ret.loc[:, ~df_ret.columns.duplicated()]

        print('Publishing sample result: ')
        print(df_ret.head())

        # Logging Final Output
        l.logr('1.df_ret' + var + '.csv', debug_ind, df_ret, 'log')

        print("-" * 60)
        print()

        print('Finding Analysis points..')
        print("*" * 157)
        logging.info('Finding Analysis points..')
        logging.info(tmpR0)

        tmpR10 = 'End Time: ' + str(var)
        logging.info(tmpR10)
        logging.info(tmpR0)

    except ValueError as e:
        print(str(e))
        print("Invalid option!")
        logging.info("Invalid option!")

    except Exception as e:
        print("Top level Error: args:{0}, message{1}".format(e.args, e.message))

if __name__ == "__main__":
    main()

Key lines from the above script –

# Create the instance of the Amadeus Class
x2 = cw.clsAmedeus()

The above line will instantiate the newly written Amadeus class.

# Let's pass this to our map section
if input_choice == 1:
    textOrig = str(input('Please provide the Origin:'))
    textDest = str(input('Please provide the Destination:'))
    textDate = str(input('Please provide the Depart Date:'))
    intAdult = int(input('Please provide the No Of Adult:'))

    retJson = x2.process(input_choice, textOrig, textDest, textDate, intAdult, textHotelID)
elif input_choice == 2:
    textOrig = str(input('Please provide the Origin:'))
    textDest = str(input('Please provide the Destination:'))

    retJson = x2.process(input_choice, textOrig, textDest, textDate, intAdult, textHotelID)
elif input_choice == 3:
    textOrig = str(input('Please provide the Origin:'))

    retJson = x2.process(input_choice, textOrig, textDest, textDate, intAdult, textHotelID)
elif input_choice == 4:
    textHotelID = str(input('Please provide the Hotel Id:'))

    retJson = x2.process(input_choice, textOrig, textDest, textDate, intAdult, textHotelID)
elif input_choice == 5:
    textHotelID = str(input('Please provide the Hotel Id:'))

    retJson = x2.process(input_choice, textOrig, textDest, textDate, intAdult, textHotelID)
else:
    print('Invalid options!')
    retJson = {'errorDetails': 'Invalid Options!'}

The above lines will fetch the response based on the supplied inputs in the form of JSON.

# Converting JSon to Pandas Dataframe for better readability
# Capturing the JSON Payload
res_1 = json.dumps(retJson)
res = json.loads(res_1)

Now, the above line will convert the return payload to JSON.

Sample JSON should look something like this –

20. Sample_JASON_Option_4_1

Now, using this new package, our application will flatten the complex nested JSON.

# Newly added JSON Parse package
dic_flattened = (flatten(d) for d in res)
df_ret = p.DataFrame(dic_flattened)

The given lines will remove any duplicate column if it exists.

# Removing any duplicate columns
df_ret = df_ret.loc[:, ~df_ret.columns.duplicated()]

Let’s explore the directory structure –

13. Win_Dir

Let’s run our application –

We’ll invoke five different API’s (API related to different functionalities) & their business cases –

Run – Option 1:

7. Win_Run_Op_1

So, if we want to explore some of the key columns, below is the screenshot for a few sample data –

21. Key_Columns

Run – Option 2:

8. Win_Run_Op_2

Some of the vital sample data –

15. Option_2_Sample_Data

Run – Option 3:

9. Win_Run_Op_3

Sample relevant data for our analysis –

16. Option_3_Sample_Data

Run – Option 4:

10. Win_Run_Op_4

Few relevant essential information –

17. Option_4_Sample_Data

Run – Option 5:

11. Win_Run_Op_5

Finally, few sample records from the last option –

18. Option_5_Sample_Data

So, finally, we’ve done it. You will find that JSON package from this link.

During this challenging time, I would request you to follow strict health guidelines & stay healthy.

N.B.: All the data that are used here can be found in the public domain. We use this solely for educational purposes.

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