SocialMediaAnalytics

A python API wrapper for the Meta Graph API to pull social media post analytics over time for your connected Facebook and Instagram business accounts

fb_published_posts

published_posts endpoint field values to be used with the metrics param

Note that this is not a full list of fileds for the published_posts endpoint.

If you use likes.summary(total_count) note that "total_count represents the approximate number of nodes on the likes edge. The actual number of results returned might be different depending on privacy settings."

• actions
• admin_creator
• comments{}
  • message
  • name
  • username
• created_time
• from
• full_picture
• is_eligible_for_promotion
• instagram_eligibility
• id
• is_expired
• is_hidden
• is_inline_created
• is_instagram_eligible
• is_popular
• is_published
• likes.summary(total_count)
• message
• message_tags
• permalink_url
• reactions{}
  • username
  • type
• likes{}
  • name
  • username
• likes.summary(total_count)

fb.published_posts example

from SocialMediaAnalytics import SocialMedia


meta = SocialMedia.Meta(user_token='your_meta_access_token')
fb = meta.fb_published_post(metrics=['created_time', 'permalink_url',
                                     'message', 'likes.summary(total_count)'],
                            since='2023-03-01',
                            limit=10)

You can create a pandas.DataFrame from the above dict by doing something like:

fb_dfs = {list(data.keys())[0]: pd.json_normalize(data[list(data.keys())[0]]['published_posts']['data'])
          for data in fb}
# access each Facebook page's DataFrame by calling the name of the page
print(fb_dfs['Facebook Page Name'])

ig_media

Media endpoint field values to be used with the metrics param

Note that this is not a full list of fileds for the ig_media endpoint.

• caption
• comments{}
  • text
  • like_count
  • from
  • hidden
  • id
  • media
  • parent_id
  • timestamp
  • user
  • username
• comments_count
• id
• ig_id
• is_comment_enabled
• is_shared_to_feed
• like_count
• media_product_type
• media_type
• media_url
• owner
• permalink
• shortcode
• thumbnail_url
• timestamp
• username

ig_media example

from SocialMediaAnalytics import SocialMedia


meta = SocialMedia.Meta(user_token='your_meta_access_token')
ig = meta.ig_media(metrics=['timestamp', 'media_url', 'caption', 'like_count'],
                   since='2023-03-01',
                   limit=10)

You can create a pandas.DataFrame from the above dict by doing something like:

ig_dfs = {list(data.keys())[0]: pd.DataFrame(data[list(data.keys())[0]]['data']) for data in ig}
# access each Instagram page's DataFrame by calling the name of the page
print(ig_dfs['Instagram Page Name'])