def test_get_category(mock_request_get, mock_datetime, category, datetime_str,
latest_value, country_name, country_code, province,
latest_country_value, coordinate_lat, coordinate_long):
#mock app.services.location.jhu.datetime.utcnow().isoformat()
mock_datetime.utcnow.return_value.isoformat.return_value = datetime_str
output = jhu.get_category(category)
#simple schema validation
assert output[
"source"] == "https://github.com/ExpDev07/coronavirus-tracker-api"
assert isinstance(output["latest"], int)
assert output["latest"] == latest_value #based on example data
#check for valid datestring
assert date.is_date(output["last_updated"]) is True
#ensure date formating
assert output["last_updated"] == datetime_str + "Z" #based on example data
#validate location schema
location_entry = output["locations"][0]
assert isinstance(location_entry["country"], str)
assert location_entry["country"] == country_name #based on example data
assert isinstance(location_entry["country_code"], str)
assert len(location_entry["country_code"]) == 2
assert location_entry[
"country_code"] == country_code #based on example data
assert isinstance(location_entry["province"], str)
assert location_entry["province"] == province #based on example data
assert isinstance(location_entry["latest"], int)
assert location_entry[
"latest"] == latest_country_value #based on example data
#validate coordinates in location
coordinates = location_entry["coordinates"]
assert isinstance(coordinates["lat"], str)
assert coordinates["lat"] == coordinate_lat
assert isinstance(coordinates["long"], str)
assert coordinates["long"] == coordinate_long
#validate history in location
history = location_entry["history"]
assert date.is_date(list(history.keys())[0]) is True
assert isinstance(list(history.values())[0], int)
def get_data_country_by_category_by_province(category, country_code):
"""
Get all the data of a country by category. There is three category (confirmed | death | recovered)
"""
data = request.get_data_time_series(category)
# The normalized locations.
locations = []
for item in data:
if country_code.upper() == countrycodes.country_code(
item['Country/Region']):
# Filter out all the dates.
history = dict(
filter(lambda element: date_util.is_date(element[0]),
item.items()))
# Sorted date history
history = sorted_history_date(formated_date(history))
# Country for this location.
country = item['Country/Region']
# Latest data insert value.
latest = list(history.values())[-1]
# Normalize the item and append to locations.
locations.append({
# General info.
'country': country,
'country_code': countrycodes.country_code(country),
'province': item['Province/State'],
# History.
'history': history,
# Latest statistic.
'total': int(latest or 0),
})
# Check if the country without province exist
data_country_all_province = []
# By country and province
for country in locations:
if country['country_code'] == country_code.upper(
) and country['province'] == '':
return {
'data': country['history'],
'country': country['country'],
'country_code': country['country_code'],
'province': country['province'],
'last_updated': ''
}
# Otherwise regrouped all provinces of the country
for country in locations:
if country['country_code'] == country_code.upper():
data_country_all_province.append(country['history'])
return {
'data': data_country_by_province(data_country_all_province),
'country': country['country'],
'country_code': country['country_code'],
'province': '',
'last_updated': ''
}
def get_data(category):
"""
Retrieves the data for the provided type. The data is cached for 1 hour.
"""
# Adhere to category naming standard.
category = category.lower().capitalize();
# Request the data
request = requests.get(base_url % category)
text = request.text
# Parse the CSV.
data = list(csv.DictReader(text.splitlines()))
# The normalized locations.
locations = []
for item in data:
# Filter out all the dates.
history = dict(filter(lambda element: date_util.is_date(element[0]), item.items()))
# Country for this location.
country = item['Country/Region']
# Latest data insert value.
latest = list(history.values())[-1];
# Normalize the item and append to locations.
locations.append({
# General info.
'country': country,
'country_code': countrycodes.country_code(country),
'province': item['Province/State'],
# Coordinates.
'coordinates': {
'lat': item['Lat'],
'long': item['Long'],
},
# History.
'history': history,
# Latest statistic.
'latest': int(latest or 0),
})
# Latest total.
latest = sum(map(lambda location: location['latest'], locations))
# Return the final data.
return {
'locations': locations,
'latest': latest,
'last_updated': datetime.utcnow().isoformat() + 'Z',
'source': 'https://github.com/ExpDev07/coronavirus-tracker-api',
}
def get_data(category):
"""
Retrieves the data for the provided type.
"""
# Adhere to category naming standard.
category = category.lower().capitalize();
# Request the data
request = requests.get(base_url % category)
text = request.text
# Parse the CSV.
data = list(csv.DictReader(text.splitlines()))
# The normalized locations.
locations = []
for item in data:
# Filter out all the dates.
history = dict(filter(lambda element: date_util.is_date(element[0]), item.items()))
# Normalize the item and append to locations.
locations.append({
# General info.
'country': item['Country/Region'],
'province': item['Province/State'],
# Coordinates.
'coordinates': {
'lat': item['Lat'],
'long': item['Long'],
},
# History.
'history': history,
# Latest statistic.
'latest': int(list(history.values())[-1]),
})
# Latest total.
latest = sum(map(lambda location: location['latest'], locations))
# Return the final data.
return {
'locations': locations,
'latest': latest
}
def get_data(category):
"""
Retrieves the data for the provided type. The data is cached for 1 hour.
"""
category = category.lower()
# URL to request data from.
url = base_url + "time_series_covid19_%s_global.csv" % category
request = requests.get(url)
text = request.text
# Parse the CSV.
data = list(csv.DictReader(text.splitlines()))
# The normalized locations.
locations = []
for item in data:
# Filter out all the dates.
history = dict(
filter(lambda element: date_util.is_date(element[0]),
item.items()))
# Sorted date history
history = sorted_history_date(formated_date(history))
# Country for this location.
country = item['Country/Region']
# Latest data insert value.
latest = list(history.values())[-1]
# Normalize the item and append to locations.
locations.append({
'country': country,
'country_code': countrycodes.country_code(country),
'province': item['Province/State'],
# History.
'history': history,
# Latest statistic.
'total': int(latest or 0),
})
# Latest total.
total = sum(map(lambda location: location['total'], locations))
# Return the final data.
return {
'locations': locations,
'total': total,
'last_updated': datetime.utcnow().isoformat() + 'Z'
}
def get_all_data_by_category(category):
"""
Get all the data of all the countries by category. There is three category (confirmed | death | recovered)
"""
data = request.get_data_time_series(category)
# The normalized locations.
locations = []
for item in data:
# Filter out all the dates.
history = dict(
filter(lambda element: date_util.is_date(element[0]),
item.items()))
# Sorted date history
history = sorted_history_date(formated_date(history))
# Country for this location.
country = item['Country/Region']
# Latest data insert value.
latest = list(history.values())[-1]
# Normalize the item and append to locations.
locations.append({
# General info.
'country': country,
'country_code': countrycodes.country_code(country),
'province': item['Province/State'],
# History.
'history': history,
# Latest statistic.
'total': int(latest or 0),
})
# Latest total.
total = sum(map(lambda location: location['total'], locations))
# Return the final data.
return {
'locations': locations,
'total': total,
'last_updated': datetime.utcnow().isoformat() + 'Z'
}
def test_is_date(str_date, fuzzy_bool, expected_value):
"""
Testdata from https://stackoverflow.com/a/25341965/7120095
"""
assert date.is_date(str_date, fuzzy=fuzzy_bool) is expected_value
def get_data(category):
"""
Retrieves the data for the provided type. The data is cached for 1 hour.
"""
# Adhere to category naming standard.
category = category.lower().capitalize()
print(">>>>>>", category)
print("Base_url: >>> ", base_url % category)
# Request the data
request = requests.get(base_url % category)
text = request.text
# Parse the CSV.
data = list(csv.DictReader(text.splitlines()))
# The normalized locations.
locations = {}
latest_count = 0 # latest count
for item in data:
# Filter out all the dates.
history = dict(
filter(lambda element: date_util.is_date(element[0]),
item.items()))
# Country for this location.
country = item['Country/Region']
# Latest data insert value.
latest = list(history.values())[-1]
# Normalize the item and append to locations.
if (country not in locations):
locations[country] = []
locations[country].append({
# General info.
'country':
country,
'country_code':
countrycodes.country_code(country),
'province':
item['Province/State'],
# Coordinates.
'coordinates': {
'lat': item['Lat'],
'long': item['Long'],
},
# History.
'history':
history,
# Latest statistic.
'latest':
int(latest or 0),
})
latest_count += int(latest or 0)
# Return the final data.
return {
'locations': locations,
'latest': latest_count,
'last_updated': datetime.utcnow().isoformat() + 'Z'
}