ScriptSmith / Socialreaper
Licence: mit
Social media scraping / data collection library for Facebook, Twitter, Reddit, YouTube, Pinterest, and Tumblr APIs
Stars: ✭ 338
Programming Languages
python
139335 projects - #7 most used programming language
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socialreaper
socialreaper
is a Python 3.6+ library that scrapes Facebook, Twitter, Reddit, Youtube, Pinterest, and Tumblr.
Not a programmer? Try the GUI
Install
pip3 install socialreaper
Examples
For version 0.3.0 only
pip3 install socialreaper==0.3.0
Get the comments from McDonalds' 1000 most recent posts
from socialreaper import Facebook
fbk = Facebook("api_key")
comments = fbk.page_posts_comments("mcdonalds", post_count=1000,
comment_count=100000)
for comment in comments:
print(comment['message'])
Save the 500 most recent tweets from the user @realDonaldTrump
to a csv file
from socialreaper import Twitter
from socialreaper.tools import to_csv
twt = Twitter(app_key="xxx", app_secret="xxx", oauth_token="xxx",
oauth_token_secret="xxx")
tweets = twt.user("realDonaldTrump", count=500, exclude_replies=True,
include_retweets=False)
to_csv(list(tweets), filename='trump.csv')
Get the top 10 comments from the top 50 threads of all time on reddit
from socialreaper import Reddit
from socialreaper.tools import flatten
rdt = Reddit("xxx", "xxx")
comments = rdt.subreddit_thread_comments("all", thread_count=50,
comment_count=500, thread_order="top", comment_order="top",
search_time_period="all")
# Convert nested dictionary into flat dictionary
comments = [flatten(comment) for comment in comments]
# Sort by comment score
comments = sorted(comments, key=lambda k: k['data.score'], reverse=True)
# Print the top 10
for comment in comments[:9]:
print("###\nUser: {}\nScore: {}\nComment: {}\n".format(comment['data.author'], comment['data.score'], comment['data.body']))
Youtube
Get the comments containing the strings prize
, giveaway
from
youtube channel mkbhd
's videos
from socialreaper import Youtube
ytb = Youtube("api_key")
channel_id = ytb.api.guess_channel_id("mkbhd")[0]['id']
comments = ytb.channel_video_comments(channel_id, video_count=500,
comment_count=100000, comment_text=["prize", "giveaway"],
comment_format="plainText")
for comment in comments:
print(comment)
CSV export
You can export a list of dictionaries using socialreaper's CSV
class
from socialreaper import Facebook
from socialreaper.tools import CSV
fbk = Facebook("api_key")
posts = list(fbk.page_posts("mcdonalds"))
CSV(posts, file_name='mcdonalds.csv')
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