I am struggling to implement the following function:

def list_weather_violations(directory):

"""

Returns the (annotated) list of flight reservations that violate weather minimums.

This function reads the data files in the given directory (the data files are all

identified by the constants defined above in this module). It loops through the

list of flight lessons (in lessons.csv), identifying those takeoffs for which

get_weather_violation() is not the empty string.

This function returns a list that contains a copy of each violating lesson, together

with the violation appended to the lesson.

Example: Suppose that the lessons

S00687 548QR I061 2017-01-08T14:00:00-05:00 2017-01-08T16:00:00-05:00 VFR Pattern

S00758 548QR I072 2017-01-08T09:00:00-05:00 2017-01-08T11:00:00-05:00 VFR Pattern

S00971 426JQ I072 2017-01-12T13:00:00-05:00 2017-01-12T15:00:00-05:00 VFR Pattern

violate for reasons of 'Winds', 'Visibility', and 'Ceiling', respectively (and are the

only violations). Then this function will return the 2d list

[[S00687, 548QR, I061, 2017-01-08T14:00:00-05:00, 2017-01-08T16:00:00-05:00, VFR, Pattern, Winds],

[S00758, 548QR, I072, 2017-01-08T09:00:00-05:00, 2017-01-08T11:00:00-05:00, VFR, Pattern, Visibility],

[S00971, 426JQ, I072, 2017-01-12T13:00:00-05:00, 2017-01-12T15:00:00-05:00, VFR, Pattern, Ceiling]]

REMEMBER: VFR flights are subject to minimums with VMC in the row while IFR flights

are subject to minimums with IMC in the row. The examples above are all VFR flights.

If we changed the second lesson to

S00758, 548QR, I072, 2017-01-08T09:00:00-05:00, 2017-01-08T11:00:00-05:00, IFR, Pattern

then it is possible it is no longer a visibility violation because it is subject to

a different set of minimums.

Parameter directory: The directory of files to audit

Precondition: directory is the name of a directory containing the files 'daycycle.json',

'weather.json', 'minimums.csv', 'students.csv', and 'lessons.csv'

""" def list_weather_violations(directory):

"""

Returns the (annotated) list of flight reservations that violate weather minimums.

This function reads the data files in the given directory (the data files are all

identified by the constants defined above in this module). It loops through the

list of flight lessons (in lessons.csv), identifying those takeoffs for which

get_weather_violation() is not the empty string.

This function returns a list that contains a copy of each violating lesson, together

with the violation appended to the lesson.

Example: Suppose that the lessons

S00687 548QR I061 2017-01-08T14:00:00-05:00 2017-01-08T16:00:00-05:00 VFR Pattern

S00758 548QR I072 2017-01-08T09:00:00-05:00 2017-01-08T11:00:00-05:00 VFR Pattern

S00971 426JQ I072 2017-01-12T13:00:00-05:00 2017-01-12T15:00:00-05:00 VFR Pattern

violate for reasons of 'Winds', 'Visibility', and 'Ceiling', respectively (and are the

only violations). Then this function will return the 2d list

[[S00687, 548QR, I061, 2017-01-08T14:00:00-05:00, 2017-01-08T16:00:00-05:00, VFR, Pattern, Winds],

[S00758, 548QR, I072, 2017-01-08T09:00:00-05:00, 2017-01-08T11:00:00-05:00, VFR, Pattern, Visibility],

[S00971, 426JQ, I072, 2017-01-12T13:00:00-05:00, 2017-01-12T15:00:00-05:00, VFR, Pattern, Ceiling]]

REMEMBER: VFR flights are subject to minimums with VMC in the row while IFR flights

are subject to minimums with IMC in the row. The examples above are all VFR flights.

If we changed the second lesson to

S00758, 548QR, I072, 2017-01-08T09:00:00-05:00, 2017-01-08T11:00:00-05:00, IFR, Pattern

then it is possible it is no longer a visibility violation because it is subject to

a different set of minimums.

Parameter directory: The directory of files to audit

Precondition: directory is the name of a directory containing the files 'daycycle.json',

'weather.json', 'minimums.csv', 'students.csv', and 'lessons.csv'

"""

I am trying to call this helper function: def get_weather_report(takeoff,weather):

"""

Returns the most recent weather report at or before take-off.

The weather is a dictionary whose keys are ISO formatted timestamps and whose values

are weather reports. For example, here is an example of a (small portion of) a

weather dictionary:

{

"2017-04-21T08:00:00-04:00": {

"visibility": {

"prevailing": 10.0,

"units": "SM"

},

"wind": {

"speed": 13.0,

"crosswind": 2.0,

"units": "KT"

},

"temperature": {

"value": 13.9,

"units": "C"

},

"sky": [

{

"cover": "clouds",

"type": "broken",

"height": 700.0,

"units": "FT"

}

],

"code": "201704211056Z"

},

"2017-04-21T07:00:00-04:00": {

"visibility": {

"prevailing": 10.0,

"units": "SM"

},

"wind": {

"speed": 13.0,

"crosswind": 2.0,

"units": "KT"

},

"temperature": {

"value": 13.9,

"units": "C"

},

"sky": [

{

"type": "overcast",

"height": 700.0,

"units": "FT"

}

],

"code": "201704210956Z"

}

...

},

If there is a report whose timestamp matches the ISO representation of takeoff,

this function uses that report. Otherwise it searches the dictionary for the most

recent report before (but not equal to) takeoff. If there is no such report, it

returns None.

Example: If takeoff was as 8 am on April 21, 2017 (Eastern), this function returns

the value for key '2017-04-21T08:00:00-04:00'. If there is no additional report at

9 am, a 9 am takeoff would use this value as well.

Parameter takeoff: The takeoff time

Precondition: takeoff is a datetime object

Paramater weather: The weather report dictionary

Precondition: weather is a dictionary formatted as described above

"""

# HINT: Looping through the dictionary is VERY slow because it is so large

# You should convert the takeoff time to an ISO string and search for that first.

# Only loop through the dictionary as a back-up if that fails.

# Search for time in dictionary

# As fall back, find the closest time before takeoff

takeoff_iso = takeoff.isoformat()

if takeoff_iso in weather:

return weather[takeoff_iso]

for time in weather.keys():

if time < takeoff_iso:

return weather[time]

return None and receiving the error i've posted in the picture

Collapse 4. The Weather Violations Functions 31. Implement list_weather_vio... is not friendly to flying). Check the Function You may run this test multiple times (but run the test script first). This will take a while! Check It! LAST RUN on 4/10/2023, 7:33:41 PM The call list_weather_violations ('/home/codio/workspace/.guides/tests/1 crashed. Traceback (most recent call last): File "/home/codio/workspace/.guides/tests/step3/verifier.py", line 753, in grade_func6 results = func(tdir) File "/home/codio/workspace/auditor/violations.py", line 493, in list_weather_violations weather_cond = get_weather_report(takeoff, weather) "/home/codio/workspace/auditor/violations.py", File line 317, in get_weather_report takeoff_iso = takeoff.isoformat() AttributeError: 'str' object has no attribute 'isoformat' 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 # For each of the lessons pilot_min= {} for row in students: pilot_min[row [0]] = row [2:] min_cond = {"VMC": [], "IMC": []} for row in minimums: if row [0] == "VMC": min_cond ["VMC"] = row [1:] min_cond ["IMC"] = row [1:] else: violations = [] upp.py for i in lessons: # Get the takeoff time takeoff=i[3] # Get the pilot credentials student_id = i[1] # Get the weather conditions weather_cond = get_weather_report (takeoff, weather) # Get the pilot minimums pilot_min_id = pilot_min[student_id] weather_min = min_cond [weather_cond] # Check for a violation and add to result if so violation = get_weather_violation (pilot_min_id, weather_min) if violation: violations.append(i + [violation]) return violations