add historical_employee_count to company_valuation.py

fmpsdk-example.py

@@ -255,3 +255,11 @@
 # print(f"Available Forex Currency Pairs: {fmpsdk.available_cryptocurrencies(apikey=apikey)=}")
 # print(f"Historical Forex Prices: {fmpsdk.historical_chart(apikey=apikey, symbol=symbol, time_delta=time_delta_5min, from_date=from_date, to_date=to_date))=}")
 # print(f"Historical Daily Forex Prices: {fmpsdk.historical_price_full(apikey=apikey, symbol=symbol)=}")
+
+### Bulk Requests
+#bulkEods = fmpsdk.bulk_historical_eod(apikey=apikey, date="2021-05-18")
+#bulkEodsDf = pd.DataFrame(bulkEods)
+#print(bulkEodsDf)
+#bulkProfiles = fmpsdk.bulk_profiles(apikey=apikey)
+#bulkProfilesDf = pd.DataFrame(bulkProfiles)
+#print(bulkProfilesDf)

fmpsdk/__init__.py

@@ -53,6 +53,9 @@
     stock_news,
     stock_screener,
     symbols_list,
+
+    # mod
+    historical_employee_count,
 )
 from .cryptocurrencies import available_cryptocurrencies, cryptocurrencies_list
 from .etf import available_efts, available_etfs, etf_price_realtime
@@ -107,6 +110,12 @@
 from .technical_indicators import technical_indicators
 from .tsx import available_tsx, tsx_list
 
+
+from .bulk import (
+    bulk_historical_eod, 
+    bulk_profiles,
+)
+
 attribution: str = "Data provided by Financial Modeling Prep"
 logging.info(attribution)
 
@@ -144,6 +153,7 @@
     "market_capitalization",
     "historical_market_capitalization",
     "symbols_list",
+    "historical_employee_count",
     "etf_list",
     "available_traded_list",
     "stock_screener",
@@ -215,4 +225,8 @@
     "senate_disclosure_rss",
     "senate_disclosure_symbol",
     "shares_float",
+
+    #bulk apis
+    "bulk_historical_eod",
+    "bulk_profiles",
 ]

fmpsdk/bulk.py

@@ -0,0 +1,42 @@
+import logging
+import typing
+import requests
+
+from .general import __quotes
+from .settings import (
+    DEFAULT_LIMIT,
+    BASE_URL_v3,
+    BASE_URL_v4
+)
+from .url_methods import __return_json_v3, __return_json_v4
+
+
+def bulk_historical_eod(apikey: str, date: str) -> typing.Optional[typing.List[typing.Dict]]:
+    """
+    Batch request that contains all end of day prices for specific date
+
+    https://site.financialmodelingprep.com/developer/docs#batch-eod-prices
+
+    Endpoint:
+        https://financialmodelingprep.com/api/v4/batch-historical-eod?date=2021-05-18
+
+    :param apikey: Your API key.
+    :return: A list of dictionaries.
+    """
+    path = f"batch-historical-eod"
+    query_vars = {"apikey": apikey, "date": date}
+    return __return_json_v4(path=path, query_vars=query_vars)
+
+def bulk_profiles(apikey: str) -> typing.Optional[typing.List[typing.Dict]]:
+    """
+    It contains all profiles from our API in one CSV file
+
+    Endpoint:
+        https://financialmodelingprep.com/api/v4/profile/all
+
+    :param apikey: Your API key.
+    :return: A list of dictionaries.
+    """
+    path = f"profile/all"
+    query_vars = {"apikey": apikey}
+    return __return_json_v4(path=path, query_vars=query_vars)

fmpsdk/company_valuation.py

@@ -957,3 +957,14 @@ def analyst_estimates(
         "limit": limit,
     }
     return __return_json_v3(path=path, query_vars=query_vars)
+
+
+def historical_employee_count(
+    apikey: str, symbol: str
+) -> typing.Optional[typing.List[typing.Dict]]:
+    """
+      historical_employee_count  
+    """
+    path = f"historical/employee_count"
+    query_vars = {"apikey": apikey, "symbol": symbol}
+    return __return_json_v4(path=path, query_vars=query_vars)

fmpsdk/url_methods.py

@@ -1,5 +1,7 @@
 import logging
 import typing
+import csv
+import io
 
 import requests
 
@@ -85,7 +87,16 @@ def __return_json_v4(
             url, params=query_vars, timeout=(CONNECT_TIMEOUT, READ_TIMEOUT)
         )
         if len(response.content) > 0:
-            return_var = response.json()
+            try:
+                return response.json()
+            except Exception as e:
+                # check if response.content is csv, convert csv to json format
+                content = response.content.decode("utf-8")
+                try:
+                    reader = csv.DictReader(io.StringIO(content))
+                    return [row for row in reader]
+                except csv.Error:
+                    raise e
 
         if len(response.content) == 0 or (
             isinstance(return_var, dict) and len(return_var.keys()) == 0