def get_intraday_data_extended(
self,
symbol: str,
interval: TimeInterval,
n_months: int = 12,
) -> pd.DataFrame:
# Artificial restriction
# TODO: resconsider this later
assert (
n_months < 100
), "a maximum of 100 months worth of data can be fetched, Mostly for safety"
year, month = 1, 1
base_params = {
"apikey": self.api_key,
"symbol": symbol,
"interval": interval.value,
"function": AVFunctions.INTRADAY_EXTENDED.value,
}
final_df = pd.DataFrame()
throttle_count = 1
for month in range(1, n_months + 1):
if throttle_count == 5:
# "Note": "Thank you for using Alpha Vantage! Our standard API call frequency
# is 5 calls per minute and 500 calls per day.
# Please visit https://www.alphavantage.co/premium/
# if you would like to target a higher API call frequency."\n}'
time.sleep(60)
if month > 12:
month = 1
year += 1
query_params = QueryParams(
**base_params,
slice=f"year{year}month{month}",
)
response = requests.get(
API_BASE_URL,
params=query_params, # type: ignore
timeout=API_TIMEOUT,
)
response.raise_for_status()
result_df = pd.read_csv(io.StringIO(response.content.decode("utf-8")))
assert "time" in result_df.columns, f"{year}_{month}"
result_df = result_df.set_index("time")
result_df.index.name = None
final_df = final_df.append(result_df)
throttle_count += 1
return final_df.sort_index()
def get_company_overview(self, symbol: str):
assert symbol, "symbol cannot be null"
query_params = QueryParams(
apikey=self.api_key, symbol=symbol, function=AVFunctions.OVERVIEW.value
)
response = requests.get(API_BASE_URL, params=query_params, timeout=API_TIMEOUT)
response.raise_for_status()
response_json = response.json()
if not super().is_response_valid(response_json):
raise HTTPError(f"Invalid Request with params - {query_params}")
return pd.DataFrame.from_dict(response_json, orient="index").T
def get_cashflow_report(self, symbol: str):
assert symbol, "symbol cannot be null"
query_params = QueryParams(
apikey=self.api_key, symbol=symbol, function=AVFunctions.CASH_FLOW.value
)
response = requests.get(API_BASE_URL, params=query_params, timeout=API_TIMEOUT)
response.raise_for_status()
response_json = response.json()
if not super().is_response_valid(response_json):
raise HTTPError(f"Invalid Request with params - {query_params}")
return __class__.parse_fundamental_report(financial_report=response_json)
def get_daily_data(
self,
symbol: str,
outputsize: OutputSize = OutputSize.COMPACT,
adjusted: bool = True,
last_ten_years_only: bool = True,
) -> pd.DataFrame:
if adjusted:
av_function: str = AVFunctions.DAILY_ADJUSTED
else:
av_function = AVFunctions.DAILY
query_params = QueryParams(
apikey=self.api_key,
function=av_function.value,
symbol=symbol,
outputsize=outputsize.value,
)
response = requests.get(
API_BASE_URL,
params=query_params, # type: ignore
timeout=API_TIMEOUT,
)
response.raise_for_status()
response_json = response.json()
if not super().is_response_valid(response_json):
raise HTTPError(f"Invalid Request with params - {query_params}")
result = response_json[f"Time Series (Daily)"]
result_df = pd.DataFrame.from_dict(result, orient="index")
result_df.index = pd.to_datetime(result_df.index)
result_df.columns = list(map(clean_column_names, result_df.columns))
result_df = result_df.astype(float)
if last_ten_years_only:
result_df = result_df.loc[
result_df.index > datetime.now() - timedelta(weeks=520)
]
return result_df.sort_index()
def get_symbol_search_results(self, search_keyword: str) -> pd.DataFrame:
query_params = QueryParams(
apikey=self.api_key,
function=AVFunctions.SYMBOl_SEARCH.value,
keywords=search_keyword,
)
response = requests.get(API_BASE_URL, params=query_params, timeout=API_TIMEOUT)
response.raise_for_status()
response_json = response.json()
if not super().is_response_valid(response_json):
raise HTTPError(f"Invalid Request with params - {query_params}")
result = response_json.get("bestMatches")
result_df = pd.DataFrame(result)
result_df.columns = list(map(clean_column_names, result_df.columns))
return result_df
def get_intraday_data(
self,
symbol: str,
interval: TimeInterval,
outputsize: OutputSize = OutputSize.COMPACT,
) -> pd.DataFrame:
query_params = QueryParams(
apikey=self.api_key,
symbol=symbol,
interval=interval.value,
outputsize=outputsize.value,
function=AVFunctions.INTRADAY.value,
)
response = requests.get(
API_BASE_URL,
params=query_params, # type: ignore
timeout=API_TIMEOUT,
)
response.raise_for_status()
response_json = response.json()
if not AVTimeseries.is_response_valid(response_json):
raise HTTPError(f"Invalid Request with params - {query_params}")
result = response_json[f"Time Series ({interval.value})"]
result_df = pd.DataFrame.from_dict(result, orient="index")
result_df.index = pd.to_datetime(result_df.index)
result_df.columns = list(map(clean_column_names, result_df.columns))
result_df = result_df.astype(float)
return result_df.sort_index()