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Library for fetching coin/token metrics data from the internet.

Project description PyPI PyPI - License PyPI - Downloads


Karpet is a tiny library with just a few dependencies for fetching coins/tokens metrics data the internet.

It can provide following data:

  • coin/token historical price data (no limits)
  • google trends for the given list of keywords (longer period than official API)
  • twitter scraping for the given keywords (no limits)
  • much more info about crypto coins/tokens (no rate limits)

What is upcoming?

  • Reddit metrics
  • Have a request? Open an issue ;)


Library uses a few nifty dependencies and is Python 3.6+ only. There is no need to install dependencies you don’t need. Therefore this library utilizes extras which install optional dependencies:

  • for Google trends - google
  • for Twitter scraping - twitter


  1. Install the library via pip.
pip install karpet  # Basics only
pip install karpet[twitter]  # For Twitter scraping
pip install karpet[google]  # For Google trends
pip install karpet[twitter,google]  # All features
  1. Import the library class first.
from karpet import Karpet


Symbol (ticker) -> URL slug conversion.

k = Karpet()
k.get_coin_slug("BTC")  # bitcoin


Retrieves historical data.

k = Karpet(date(2019, 1, 1), date(2019, 5, 1))
df = k.fetch_crypto_historical_data(symbol="btc")  # Dataframe with historical data.


Retrieves exchange list.

k = Karpet()
['DigiFinex', 'KuCoin', 'CryptoBridge', 'Bitbns', 'CoinExchange']


Retrieves twitter tweets.

k = Karpet(date(2019, 1, 1), date(2019, 5, 1))
df = k.fetch_tweets(kw_list=["bitcoin"], lang="en")  # Dataframe with tweets.


Retrieves crypto news.

k = Karpet()
news = k.fetch_news("btc")  # Gets 10 news.
   'url': ' ....',  # Truncated.
   'title': 'Shell Invests in Blockchain-Based Energy Startup',
   'description': 'The world’s fifth top oil and gas firm, Shell, has...',  # Truncated.
   'date': datetime.datetime(2019, 7, 28, 9, 24, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600)))
   'image': ''  # Truncated.
news = k.fetch_news("btc", limit=30)  # Gets 30 news.


Retrieves top crypto news in 2 categories:

  • Editor’s choices - articles picked by editors
  • Hot stories - articles with most views
k = Karpet()
editors_choices, top_stories = k.fetch_top_news()
   'url': '',  # Truncated.
   'title': 'Bank of China’s New Infographic Shows Why Bitcoin Price Is Going Up',
   'date': datetime.datetime(2019, 7, 27, 10, 7, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),
   'image': '', # Truncated.
   'description': 'The Chinese central bank released on its website an ...'  # Truncated.
   'url': '',  # Truncated.
   'title': 'Bitcoin Price Shuns Volatility as Analysts Warn of Potential Drop to $7,000',
   'date': datetime.datetime(2019, 7, 27, 10, 7, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),
   'image': ''  # Truncated.
   'description': 'Stability around $10,600 for Bitcoin price is ...'  # Truncated.



  • Added fetch_top_news() method for top crypto news separated in 2 categories.


  • fetch_news() adds new “description” item and renames “image_url” to “image”.
  • All fetch_news() item properties are now presented even if they are None.


  • Simplified import from from karpet.karpet import Karpet to from karpet import Karpet.


  • Added fetch_news() method for retrieving crypto news.


  • Added fetch_exchanges() method for retrieving symbol exchange list.
  • Removed obsolete library dependency.


  • Twitter scraping added.


  • Initial release.


This is my personal library I use in my long-term project. I can pretty much guarantee it will live for a long time then. I will add new features over time and I more than welcome any help or bug reports. Feel free to open an issue or merge request.

The code is is licensed under MIT license.

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