API for News Headlines - date problem

ArdaCetinkaya

Hi,

I am trying to download headlines data with the ek.get_news_headlines function. Yet, I am running into the error: ValueError: Parser must be a string or character stream, not Timestamp when passing datetime values like below. Or running into "TypeError: datetime64 values must have a unit specified" when passing string values. Have you any idea how to resolve? Thanks!

 

import eikon as ek

import pandas as pd

print(ek.__version__)

ek.set_app_key('hidden')

 

range_of_dates = pd.to_datetime([d.strftime('%Y-%m-%dT%H:%M:%S') for d in pd.date_range(start='1/1/2024', end='11/1/2024')])

print(range_of_dates)

print(type((range_of_dates[0])))

stocks = ["AAPL.O", "NVDA.O", "MSFT.O", "GOOGL.O", "AMZN.O"]

 

df_list = []

for d in range(len(range_of_dates)-1):

    for s in stocks:

            headlines = ek.get_news_headlines(query=s,

                                count=100,

                                date_from=range_of_dates[d],

                                date_to=range_of_dates[d+1],)

            df.append(headlines)

           

df = pd.concat(df_list)

df.to_csv("df_test.csv")

 

Jirapongse

@ArdaCetinkaya

Thank you for reaching out to us.

Please use the LSEG Data Libaray for Python instead.

The news sample is on GitHub. The code looks like this:

import lseg.data as ld
import pandas as pd

APP_KEY = "<app key>"
ld.open_session(app_key = APP_KEY)

range_of_dates = pd.to_datetime([d.strftime('%Y-%m-%dT%H:%M:%S') for d in pd.date_range(start='1/1/2024', end='11/1/2024')])

print(range_of_dates)

print(type((range_of_dates[0])))

stocks = ["AAPL.O", "NVDA.O", "MSFT.O", "GOOGL.O", "AMZN.O"]
 
df_list = []

for d in range(len(range_of_dates)-1):

    for s in stocks:
            print(s, str(range_of_dates[d].strftime('%Y-%m-%dT%H:%M:%S')),str(range_of_dates[d+1].strftime('%Y-%m-%dT%H:%M:%S')))

            headlines = ld.news.get_headlines(s,
                                count=100,
                                start=range_of_dates[d],
                                end=range_of_dates[d+1],)            

            df_list.append(headlines)

           

df = pd.concat(df_list) 

df.to_csv("df_test.csv")