def generate_plot():
temp_num = rd_temp.dbsize(
) # Get the number of temperature dictionaries in database
''' Use the "random" module to randomly-generate a temp field to
develop a time-series line plot of from the list: "GALT", "GMAXLT",
and "GMINLT": '''
temp_field_list = [
"GALT (Celsius)", "GMAXLT (Celsius)", "GMINLT(Celsius)"
]
temp_field = temp_field_list[random.randint(0, 2)]
# Use matplolib to generate plot of time-series temperature data:
time_array = numpy.array([]) # Initialize array to store time data
temperature_array = numpy.array(
[]) # Initialize array to store temperature data
# Use for loop to append values to array storing time and temperature field values:
for i in range(0, temp_num):
temp_key = i # Assign keyname to temperature
time_array = numpy.append(time_array, i)
temperature_array = numpy.append(
temperature_array, float(rd_temp.hget(temp_key, temp_field)))
# Use "Matplotlib" to generate a line plot of the time-series dataset:
plt.plot(time_array, temperature_array)
plt.title("Plot of " + temp_field +
" vs. Time (Months) Starting from 01/01/1930 ")
plt.xlabel("Time (Months)")
plt.ylabel(temp_field)
plt.savefig('/Time-Series-Line-Plot.png')
# Open image and add to redis database containing job information:
with open('/Time-Series-Line-Plot.png', 'rb') as f:
img = f.read()
rd_jobs.hset(f'job.{jid}', "image",
img) # Set the image in redis database
return_status = "Plot Generated Successfully"
return return_status
def update_data_api():
temp_num = rd_temp.dbsize() # Get the number of temperature dictionaries in database
# Query the UUID for date with historical temperature value(s) to be updated:
UUID = request.args.get('UUID')
# Get the temp_key from the database using UUID:
for i in range(0, temp_num ):
UUID_rd = rd_temp.hget(i, "UUID")# Get the UUID from database
''' If UUID returned from database equals UUID query value, define
"temp_key" value and break '''
if (UUID_rd == UUID):
# Assign keyname to temperature:
temp_key = i
break
# Query the Global Average Land Temperature (GALT) in Celsius
GALT_str = request.args.get('Global_Average_Land_Temp')
# If "GALT_str" query value is defined update value in database:
if (GALT_str != None):
GALT = float(GALT_str)
rd_temp.hset(temp_key, "GALT (Celsius)", GALT)
# Query the Global Maximum Land Temperature (GMAXLT) in Celsius
GMAXLT_str = request.args.get('Global_Maximum_Land_Temp')
# If "GMAXLT_str" query value is defined update value in database:
if (GMAXLT_str != None):
GMAXLT = float(GMAXLT_str)
rd_temp.hset(temp_key, "GMAXLT (Celsius)", GMAXLT)
# Query the Global Minimum Land Temperature (GMINLT) in Celsius
GMINLT_str = request.args.get('Global_Minimum_Land_Temp')
# If "GMINLT_str" query value is defined update value in database:
if (GMINLT_str!= None):
GMINLT = float(GMINLT_str)
rd_temp.hset(temp_key, "GMINLT(Celsius)", GMINLT)
return_status = "Data Updated Successfully"
return return_status
def delete_data_api():
temp_num = rd_temp.dbsize() # Get the number of temperature dictionaries in database
# Query the date bounds for historical temperature value(s) to be deleted:
date_low = request.args.get('date_lower_bound')
date_up = request.args.get('date_upper_bound')
''' Extract date parameters from lower bound: '''
year_low = int(date_low[6:10])
month_low = int(date_low[0:2])
day_low = int(date_low[3:5])
''' Extract date parameters from upper bound: '''
year_up = int(date_up[6:10])
month_up = int(date_up[0:2])
day_up = int(date_up[3:5])
temp_store = [] # Initialize list to store data outside range of deletion:
# Use a for loop to return field values between start and end date:
for i in range(0, temp_num):
temp_key = i # Assign keyname to temperature
''' Extract the date parameters from the database: '''
date_db = rd_temp.hget(temp_key, "dt")
year_db = int(date_db[6:10])
month_db = int(date_db[0:2])
day_db = int(date_db[3:5])
sto_cond = True # Initialize storage condition to true
''' Use while loop with nested if statements to check if date from
database falls within range: '''
while (sto_cond == True):
if (year_db < year_up and year_db > year_low):
sto_cond = False
break
elif (year_db == year_up and month_db < month_up and month_db > month_low):
sto_cond = False
break
elif (year_db == year_low and month_db > month_low and month_db < month_up):
sto_cond = False
break
elif (year_db == year_up and month_db == month_up and day_db < day_up and day_db > day_low):
sto_cond = False
break
elif (year_db == year_low and month_db == month_low and day_db > day_low and day_db < day_up):
sto_cond = False
break
break
''' Append field values from database to data storage list if the condition
"sto_cond" is true: '''
if (sto_cond == True):
temp_store.append(rd_temp.hgetall(temp_key))
temp_store_num = len(temp_store)
rd_temp.flushall() # Clear all elements from the redis database
''' Store new data structure in redis database: '''
for i in range(0,temp_store_num):
temp_key = i # Assign keyname to temperature
''' Set data points that lie outside range of deletion to database: '''
rd_temp.hmset(temp_key, {"dt": temp_store[i]["dt"], "GALT (Celsius)": \
temp_store[i]["GALT (Celsius)"], "GMAXLT (Celsius)": \
temp_store[i]["GMAXLT (Celsius)"], "GMINLT(Celsius)": \
temp_store[i]["GMINLT(Celsius)"], "UUID": \
temp_store[i]["UUID"]})
return_status = "Temperature Data Deleted Successfully"
return return_status
def retrieve_data_api():
temp_num = rd_temp.dbsize() # Get the number of temperature dictionaries in database
# Query the dates for historical temperature value(s) to be created and stored:
date_low = request.args.get('date_lower_bound')
date_up = request.args.get('date_upper_bound')
''' Extract date parameters from lower bound: '''
year_low = int(date_low[6:10])
month_low = int(date_low[0:2])
day_low = int(date_low[3:5])
''' Extract date parameters from upper bound: '''
year_up = int(date_up[6:10])
month_up = int(date_up[0:2])
day_up = int(date_up[3:5])
temp_output = [] # Initialize list to store output data
# Use a for loop to return field values between start and end date:
for i in range(0, temp_num):
temp_key = i # Assign keyname to temperature
''' Extract the date parameters from the database: '''
date_db = rd_temp.hget(temp_key, "dt")
year_db = int(date_db[6:10])
month_db = int(date_db[0:2])
day_db = int(date_db[3:5])
out_cond = True # Initialize output condition to true
''' Use while loop with nested if statements to check if date from
database falls within range: '''
while (out_cond == True):
if (year_db > year_up or year_db < year_low):
out_cond = False
break
elif (year_db == year_up and month_db > month_up):
out_cond = False
break
elif (year_db == year_low and month_db < month_low):
out_cond = False
break
elif (year_db == year_up and month_db == month_up and day_db > day_up):
out_cond = False
break
elif (year_db == year_low and month_db == month_low and day_db < day_low):
out_cond = False
break
break
''' Append field values from database to output list if the condition
"out_cond" is true: '''
if (out_cond == True):
temp_output.append(rd_temp.hgetall(temp_key))
# Store data in json formatted dictionary:
temp_dict = {"Earth Surface Temperature Data": temp_output}
return temp_dict
def create_data_api():
temp_num = rd_temp.dbsize() # Get the number of temperature dictionaries in database
# Query the data for historical temperature value(s) to be created and stored:
date_in = request.args.get('date')
# Query the Global Average Land Temperature (GALT) in Celsius
GALT_str = request.args.get('Global_Average_Land_Temp')
GALT = float(GALT_str)
# Query the Global Maximum Land Temperature (GMAXLT) in Celsius
GMAXLT_str = request.args.get('Global_Maximum_Land_Temp')
GMAXLT = float(GMAXLT_str)
# Query the Global Minimum Land Temperature (GMINLT) in Celsius
GMINLT_str = request.args.get('Global_Minimum_Land_Temp')
GMINLT = float(GMINLT_str)
create_cond = True # Initialize data creation condition to true
for i in range(0,temp_num):
''' Return date parameters for "temp_key" from database: '''
temp_key = i # Assign keyname to temperature
date_db = rd_temp.hget(temp_key, "dt") # Return date for "temp_key"
''' Conditional to compare input date of creation to date in database: '''
if (date_in == date_db):
create_cond = False
break
if (create_cond == True):
temp_key = temp_num + 1
# Set value of date "date_in" in database:
rd_temp.hset(temp_key, "dt", date_in)
# Set value of GALT in database:
rd_temp.hset(temp_key, "GALT (Celsius)", GALT)
# Set value of GMAXLT in database:
rd_temp.hset(temp_key, "GMAXLT (Celsius)", GMAXLT)
# Set value of GMINLT in database:
rd_temp.hset(temp_key, "GMINLT(Celsius)", GMINLT)
# Invoke "uuid4()" method to assign random unique identifier to temperature
UUID = str(uuid.uuid4())
rd_temp.hset(temp_key, "UUID", UUID)
return_status = "Data Created and Stored Successfully"
return return_status