I want to get all recent episodes for the last week. I used this Python script that makes a request of the most recent 1000 episodes, takes the last one and passes it to a before param.
res_df = pd.DataFrame()
tmp_df = pd.DataFrame(get_episodes_batch(f'https://api.podcastindex.org/api/1.0/recent/episodes?max=1000')['items'])
res_df = pd.concat([res_df, tmp_df])
while True:
last_id = tmp_df['id'].values[-1]
print(last_id)
print(tmp_df['datePublishedPretty'].values[0])
print(tmp_df['datePublishedPretty'].values[-1])
tmp_df = pd.DataFrame(get_episodes_batch(f'https://api.podcastindex.org/api/1.0/recent/episodes?max=1000&before={last_id}')['items'])
res_df = pd.concat([res_df, tmp_df])
I expect tmp_df['datePublishedPretty'].values[0] and tmp_df['datePublishedPretty'].values[-1] to go back in time, but i got these results.
For some reason time windows overlap each other. The results become even stranger when the script goes through several iterations
it returns only 1000 episodes for March 09, 2023 3:00pm - April 07, 2025 10:31am time window. In the result I have about 35k episodes from random periods of time.
Maybe i'm using endpoint incorrectly?
I want to get all recent episodes for the last week. I used this Python script that makes a request of the most recent 1000 episodes, takes the last one and passes it to a before param.
I expect tmp_df['datePublishedPretty'].values[0] and tmp_df['datePublishedPretty'].values[-1] to go back in time, but i got these results.
For some reason time windows overlap each other. The results become even stranger when the script goes through several iterations
it returns only 1000 episodes for March 09, 2023 3:00pm - April 07, 2025 10:31am time window. In the result I have about 35k episodes from random periods of time.
Maybe i'm using endpoint incorrectly?