# importing libraries
import requests
import pandas as pd
import numpy as np
import datetime

# For Booster Version
def gBV(data):
    for x in data['rocket']:
       if x:
        response = requests.get("https://api.spacexdata.com/v4/rockets/"+str(x)).json()
        BoosterVersion.append(response['name'])

# For Launch Site, Longitude, Latitude
def gLS(data):
    for x in data ['launchpad']:
        if x:
            response = requests.get("https://api.spacexdata.com/v4/launchpads/"+str(x)).json()
            Longitude.append(response['longitude'])
            Latitude.append(response['latitude'])
            LaunchSite.append(response['name'])

# For Payload mass_kg, orbit
def gpd(data):
    for load in data['payloads']:
       if load:
        response = requests.get("https://api.spacexdata.com/v4/payloads/"+load).json()
        PayloadMass.append(response['mass_kg'])
        Orbit.append(response['orbit'])

# For the cores column of the dataset
def gcd(data):
    for core in data['cores']:
            if core['core'] != None:
                response = requests.get("https://api.spacexdata.com/v4/cores/"+core['core']).json()
                Block.append(response['block'])
                ReusedCount.append(response['reuse_count'])
                Serial.append(response['serial'])
            else:
                Block.append(None)
                ReusedCount.append(None)
                Serial.append(None)
            Outcome.append(str(core['landing_success'])+' '+str(core['landing_type']))
            Flights.append(core['flight'])
            GridFins.append(core['gridfins'])
            Reused.append(core['reused'])
            Legs.append(core['legs'])
            LandingPad.append(core['landpad'])

# Requesting data from SpaceX API

spacex_url="https://api.spacexdata.com/v4/launches/past"
response = requests.get(spacex_url)

pd.set_option('display.max_columns', None)
pd.set_option('display.max_colwidth', None)
data=pd.json_normalize(response.json())
data.head()

# Using the API to get information on launches using the ID's for each launch
data = data[['rocket','payloads','launchpad','cores','flight_number','date_utc']]

#Filtering out rows with multiple cores - indicating Falcon2 rockets 
data = data[data['cores'].map(len)==1]
data = data[data['payloads'].map(len)==1]

# Both payload and cores are lists of size 1 we take the single value and replace the current feature with the result
data['cores'] = data['cores'].map(lambda x : x[0])
data['payloads'] = data['payloads'].map(lambda x : x[0])

# Converting the date_utc to datetime, then restricting our launches by the new date
data['date'] = pd.to_datetime(data['date_utc']).dt.date
data = data[data['date'] <= datetime.date(2020, 11, 13)]

# Creating lists to store the data from our requests

BoosterVersion = []
PayloadMass = []
Orbit = []
LaunchSite = []
Outcome = []
Flights = []
GridFins = []
Reused = []
Legs = []
LandingPad = []
Block = []
ReusedCount = []
Serial = []
Longitude = []
Latitude = []

# Calling our defined functions to fill the lists with data 
gBV(data)
gLS(data)
gpd(data)
gcd(data)

# Constructing a dictionary from our lists that now have the our requested data

launch_dct = {'FlightNumber': list(data['flight_number']),
'Date': list(data['date']),
'BoosterVersion':BoosterVersion,
'PayloadMass':PayloadMass,
'Orbit':Orbit,
'LaunchSite':LaunchSite,
'Outcome':Outcome,
'Flights':Flights,
'GridFins':GridFins,
'Reused':Reused,
'Legs':Legs,
'LandingPad':LandingPad,
'Block':Block,
'ReusedCount':ReusedCount,
'Serial':Serial,
'Longitude': Longitude,
'Latitude': Latitude}

# Creating a pandas df from our newly created dictionary
df=pd.DataFrame(launch_dct)
df.head()

# Filtering out Falcon 1 Launches by making a new dataframe
f9df = df[df['BoosterVersion']!= 'Falcon 1']
f9df.loc[:,'FlightNumber'] = list(range(1, f9df.shape[0]+1))
f9df.head()

# Downloading our dataframe to a CSV file

f9df.to_csv('dataset_p1_API.csv', index=False)