Create a Program to Create API Queries in Python Assignment Solution.

import json

import requests

from datetime import datetime

def displayMenu():

print("1) Find the overall dataset count")

print("2) Find the files count for each dataset")

print("3) Find the total no. of files available")

print("4) Show the datasets between a date range")

print("5) Select a variable and show the associated dataset")

print("6) Show the download links for a selected dataset")

print("7) Show statistics for all datasets")

print("8) Export to JSON")

print("9) Exit")

def getOption(message, lb, ub):

while True:

try:

option = int(input(message))

if option in range(lb, ub+1):

return option

else:

print(f"Enter a number between {lb} and {ub}")

except ValueError:

print("Enter a valid option.")

link = "https://ghrc.nsstc.nasa.gov/hydro/es_proxy.php?esurl=_sql?sql=SELECT%20*%20from%20ghrc_inv"

text = requests.get(link).json()

# Variable to count the number of datasets

datasets = list() # Store the datasets here

datasets_clean = list() # this will store the same datasets but with dates as strings and not datetimes.

variables = ['ds_short_name', 'platform', 'authors', 'start_date', 'stop_date', 'format', 'coll_name', 'proj_name', 'dataset_name', 'project_home_page',

'format', 'granule_name', 'data_access', 'checksum', 'file_size']

for data in text['hits']['hits']:

dt = dict()

dt_clean = dict()

for var in variables:

if var in data['_source']:

if var not in ['start_date', 'stop_date']:

dt[var] = data['_source'][var]

dt_clean[var] = dt[var]

else:

dt[var] = datetime.strptime(data['_source'][var], "%Y-%m-%d %H:%M:%S")

dt_clean[var] = data['_source'][var]

datasets.append(dt)

datasets_clean.append(dt_clean)

# Begin with program

while True:

# Display menu

displayMenu()

option = getOption("Enter an option:", 1, 9)

if option == 1: # Display count

print(f"There are {len(datasets)} datasets")

elif option == 2:

print("The file count for each dataset is: ")

for data in datasets:

print("{}: {}".format(data['dataset_name'], data['file_size']))

elif option == 3:

all_files = 0

for data in datasets:

all_files += data['file_size']

print(f"There are {all_files} files between all datasets.")

elif option == 4:

start_date = input("Enter start date in the format year-month-day (i.e: 2015-10-21): ")

end_date = input("Enter start date in the format year-month-day (i.e: 2015-10-21): ")

start_date = datetime.strptime(start_date, '%Y-%m-%d')

stop_date = datetime.strptime(end_date, '%Y-%m-%d')

for data in datasets:

if data['start_date'] >=start_date and data['stop_date'] <= stop_date:

print("Dataset Name:", data['dataset_name'])

elif option == 5:

var = input("Enter variable: ")

value = input("Enter value: ")

for data in datasets:

if var in data and data[var] == value:

print("Dataset Name:", data['dataset_name'])

elif option == 6:

name = input("Enter the name of the dataset: ")

for data in datasets:

if data['dataset_name'] == name:

print("The download links are: ")

print(data['data_access'])

elif option == 7:

# Compute mean of file size

file_size_mean = 0.0

for data in datasets:

file_size_mean += data['file_size']

file_size_mean = file_size_mean / len(datasets)

print(f"There are {len(datasets)} datasets")

print("The average file size is: {:.2f}".format(file_size_mean))

elif option == 8:

with open('output.json', 'w', encoding='utf-8') as f:

for data in datasets_clean:

json.dump(data, f, ensure_ascii=False, indent=4)

print("Data saved to file output.json")

elif option == 9:

print("Good Bye!")

break

print()