def test_transform_response():
# function should read through JSON data to output dictionary of Daily Time Series data parsed by timestamp
parsed_response = {
"Meta Data": {
"1. Information":
"Daily Prices (open, high, low, close) and Volumes",
"2. Symbol": "MSFT",
"3. Last Refreshed": "2018-06-08",
"4. Output Size": "Full size",
"5. Time Zone": "US/Eastern"
},
"Time Series (Daily)": {
"2019-06-08": {
"1. open": "101.0924",
"2. high": "101.9500",
"3. low": "100.5400",
"4. close": "101.6300",
"5. volume": "22165128"
},
"2019-06-07": {
"1. open": "102.6500",
"2. high": "102.6900",
"3. low": "100.3800",
"4. close": "100.8800",
"5. volume": "28232197"
}
}
}
transformed_response = [{
"timestamp": "2019-06-08",
"open": 101.0924,
"high": 101.95,
"low": 100.54,
"close": 101.63,
"volume": 22165128
}, {
"timestamp": "2019-06-07",
"open": 102.65,
"high": 102.69,
"low": 100.38,
"close": 100.88,
"volume": 28232197
}]
assert transform_response(parsed_response) == transformed_response
def test_transform_response():
wsd = {
"2020-04-15": {
"1. open": "164.3500",
"2. high": "173.7500",
"3. low": "162.3000",
"4. close": "171.8800",
"5. volume": "135368325"
},
"2020-04-09": {
"1. open": "160.3200",
"2. high": "170.0000",
"3. low": "157.5800",
"4. close": "165.1400",
"5. volume": "229630744"
},
"2020-04-03": {
"1. open": "152.4400",
"2. high": "164.7800",
"3. low": "150.0100",
"4. close": "153.8300",
"5. volume": "290191457"
}
}
transformed_response = [[
"timestamp", "open", "high", "low", "close", "volume"
],
[
"2020-04-15", "164.3500", "173.7500",
"162.3000", "171.8800", "135368325"
],
[
"2020-04-09", "160.3200", "170.0000",
"157.5800", "165.1400", "229630744"
],
[
"2020-04-03", "152.4400", "164.7800",
"150.0100", "153.8300", "290191457"
]]
Dates = list(wsd.keys())
Headers = ['timestamp', 'open', 'high', 'low', 'close', 'volume']
Rows = [Headers]
assert transform_response(wsd, Dates, Rows) == transformed_response
def test_transform_response():
parsed_response = {
"Meta Data": {
"1. Information":
"Daily Prices (open, high, low, close) and Volumes",
"2. Symbol": "AAPL",
"3. Last Refreshed": "2019-05-02 16:00:01",
"4. Output Size": "Compact",
"5. Time Zone": "US/Eastern"
},
"Time Series (Daily)": {
"2019-05-02": {
"1. open": "209.8400",
"2. high": "212.6500",
"3. low": "208.1300",
"4. close": "209.1500",
"5. volume": "29368219"
},
"2019-05-01": {
"1. open": "209.8800",
"2. high": "215.3100",
"3. low": "209.2300",
"4. close": "210.5200",
"5. volume": "63420533"
}
}
}
transformed_response = transform_response(parsed_response)
expected_response = [{
'timestamp': '2019-05-02',
'open': '209.8400',
'high': '212.6500',
'low': '208.1300',
'close': '209.1500',
'volume': '29368219'
}, {
'timestamp': '2019-05-01',
'open': '209.8800',
'high': '215.3100',
'low': '209.2300',
'close': '210.5200',
'volume': '63420533'
}]
assert transformed_response == expected_response
def test_transform_response():
parsed_response = {
"Meta Data": {
"1. Information":
"Daily Prices (open, high, low, close) and Volumes",
"2. Symbol": "MSFT",
"3. Last Refreshed": "2018-06-08",
"4. Output Size": "Full size",
"5. Time Zone": "US/Eastern"
},
"Time Series (Daily)": {
"2019-06-08": {
"1. open": "101.0924",
"2. high": "101.9500",
"3. low": "100.5400",
"4. close": "101.6300",
"5. volume": "22165128"
},
"2019-06-07": {
"1. open": "102.6500",
"2. high": "102.6900",
"3. low": "100.3800",
"4. close": "100.8800",
"5. volume": "28232197"
},
"2019-06-06": {
"1. open": "102.4800",
"2. high": "102.6000",
"3. low": "101.9000",
"4. close": "102.4900",
"5. volume": "21122917"
}
}
}
transformed_response = [
{
"timestamp": "2019-06-08",
"open": 101.0924,
"high": 101.95,
"low": 100.54,
"close": 101.63,
"volume": 22165128
},
{
"timestamp": "2019-06-07",
"open": 102.65,
"high": 102.69,
"low": 100.38,
"close": 100.88,
"volume": 28232197
},
{
"timestamp": "2019-06-06",
"open": 102.48,
"high": 102.60,
"low": 101.90,
"close": 102.49,
"volume": 21122917
},
]
assert transform_response(parsed_response) == transformed_response
def test_transform_response():
parsed_response = {
"Meta Data": {
"1. Information":
"Daily Prices (open, high, low, close) and Volumes",
"2. Symbol": "MSFT",
"3. Last Refreshed": "2019-05-01",
"4. Output Size": "Full size",
"5. Time Zone": "US/Eastern"
},
"Time Series (Daily)": {
"2019-05-31": {
"1. open": "123.4500",
"2. high": "123.8900",
"3. low": "120.3400",
"4. close": "123.5600",
"5. volume": "12345678"
},
"2019-05-30": {
"1. open": "124.5600",
"2. high": "124.8900",
"3. low": "123.3400",
"4. close": "124.5600",
"5. volume": "22345678"
},
"2019-05-29": {
"1. open": "122.4500",
"2. high": "122.8900",
"3. low": "121.3400",
"4. close": "122.5600",
"5. volume": "32345678"
}
}
}
#Referenced Prof. Rossetti's solution
transformed_response = [
{
"timestamp": "2019-05-31",
"open": 123.4500,
"high": 123.8900,
"low": 120.3400,
"close": 123.5600,
"volume": 12345678
},
{
"timestamp": "2019-05-30",
"open": 124.5600,
"high": 124.8900,
"low": 123.3400,
"close": 124.5600,
"volume": 22345678
},
{
"timestamp": "2019-05-29",
"open": 122.4500,
"high": 122.8900,
"low": 121.3400,
"close": 122.5600,
"volume": 32345678
},
]
assert transform_response(parsed_response) == transformed_response