How to Fetch Statistics From YouTube API Using Python

In this article you’ll learn how tо:

• get token for YouTube API
• get the full playlists of any channel (not only your own)
• and get all videos from a playlist

1. Make sure you’re logged into google.
2. Navigate to https://cloud.google.com/
3. Chose “Console” in the profile header

4. To create a new project: click “New Project”.  Otherwise, skip to step 7.

5. Enter your project name and click on the “create” button

6. Choose your new project

7.  Click to the API & Services

8. Click “ENABLE APIS AND SERVICES”

9. Click “YouTube Data API”

10. Click “Enable”

11. Click “Credentials” in the left column then click “CREATE CREDENTIALS” on the top row

12. To reveal your “API Key” Click“API key”

13. Your “API Key” will appear as follows (please, do not share your key):

Now that we have the “API key”, we need to get the “channel_id”. To get the channel_id, navigate to the video then click on the channel name, which is to the right of the avatar just above the number of subscribers.

Highlight and copy everything in the URL after “channel/” as follows:  https://www.youtube.com/channel/

Let’s import libraries:

import pandas as pd
import requests
import json

Now, let’s get the channel statistics.

api_key = 'YOUR_API_KEY'
channel_id = 'UCYvmuw-JtVrTZQ-7Y4kd63Q'

def get_channel_stat() -> dict:
    url = f'https://www.googleapis.com/youtube/v3/channels?part=statistics&id={channel_id}&key={api_key}'

    r = requests.get(url)
    data = r.json()
    return data['items'][0]['statistics']

stats = get_channel_stat()
pd.DataFrame([stats])

While page statistics have been collected, it is important to clarify that these results are approximations: API YouTube does not provide accurate statistics.

Even when updating one channel on YouTube in the browser,  sharp changes in the values will be noticeable: the number of subscribers, the number of views, and even the number of videos will change with the update.

If detailed statistics (e.g., the number of views for each video)how to get the full list of the “video_id” must first be decided. The best way that has been found so far is to get a stable video value on each request from “playlists”.

Collecting a list of videos is also possible via a

“GET request https://www.googleapis.com/youtube/v3/videos”

(To read more click the following: https://developers.google.com/youtube/v3/docs/videos/list)

But, for me, it didn't work for many reasons; one of which is that this query always returns a different number of IDs.

Let's take a look at how to get a list of playlists first.

(To read more click the following: https://developers.google.com/youtube/v3/docs/playlists/list)

In these requests, we will use pagination. Every request that contains the “nextPageToken” value in json has content on the next page, which we’ll request until the “nextPageToken” stops returning.

part=snippet,id, this parameter specifies which part of json that will be returned.

def get_pl_data_per_page(npt: str=None, limit: int=None) -> dict:

    url = f"https://www.googleapis.com/youtube/v3/playlists?key={api_key}&channelId={channel_id}&part=snippet,id&order=date"
    if limit is not None:
        url = f"{url}&maxResults={limit}"
    if npt is not None:
        url = f"{url}&&pageToken={npt}"

    r = requests.get(url)
    return r.json()

def get_playlists_data(limit: int=50):
    res = []
    nextPageToken = None
    while True:
        data = get_pl_data_per_page(nextPageToken)
        nextPageToken = data.get("nextPageToken", None)
        res.append(data)
        
        if nextPageToken is None: break
    return res

data = get_playlists_data()
df = pd.DataFrame(data)
p_ids = set(df.explode('items')["items"].apply(pd.Series)["id"].to_list())
p_ids

Now that we have the list of playlists, let's get all the videos from a playlist.

limit = 50
plid = 'PLz68cPKdtIOzuoKHzMcQoO7WaQHYm5J3Y'
url = f'https://www.googleapis.com/youtube/v3/playlistItems?part=snippet&maxResults={limit}\
        &playlistId={plid}&key={api_key}'
json_url = requests.get(url)
data = json.loads(json_url.text)

To collect the Data Frame, follow JSON as below:

to_append = []
for item in data['items']:
        playlistId = item['snippet']['playlistId']
        videoOwnerChannelTitle = item['snippet']['videoOwnerChannelTitle']
        position = item['snippet']['position']
        videoId = item['snippet']['resourceId']['videoId']
        to_append.append([playlistId, videoOwnerChannelTitle, position, videoId])

cols = ['playlist_id', 'videoOwnerChannelTitle', 'position', 'videoId']
pd.DataFrame(to_append, columns=cols)

In the next article, getting statistics for each video in a channel will be analyzed.