karpet 0.4.9

Library for fetching coin/token historical data, trends and more.

Contents

• Karpet

  • Dependencies

  • Usage

    • fetch_crypto_historical_data()

    • fetch_crypto_exchanges()

    • fetch_google_trends()

    • fetch_news()

    • fetch_top_news()

    • get_coin_ids()

    • get_basic_data()

    • get_quick_search_data()

    • fetch_crypto_live_data()

  • Changelog

    • 0.4.9

    • 0.4.8

    • 0.4.7.

    • 0.4.6

    • 0.4.5

    • 0.4.4

    • 0.4.3

    • 0.4.2

    • 0.4.1

    • 0.4

    • 0.3.3

    • 0.3.2

    • 0.3.1

    • 0.3

    • 0.2.5

    • 0.2.4

    • 0.2.3

    • 0.2.2

    • 0.2.1

    • 0.2

    • 0.1

  • Credits

Karpet

Karpet is a tiny library with just a few dependencies for fetching coins/tokens metrics data from 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 ;)

Dependencies

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

Usage

1. Install the library via pip.

pip install karpet  # Basics only
pip install karpet[google]  # For Google trends

2. Import the library class first.

from karpet import Karpet

fetch_crypto_historical_data()

Retrieves historical data.

k = Karpet(date(2019, 1, 1), date(2019, 5, 1))
df = k.fetch_crypto_historical_data(id="ethereum")  # Dataframe with historical data.
df.head()

                 price   market_cap total_volume
2019-01-01  131.458725  1.36773e+10  1.36773e+10
2019-01-02  138.144802  1.43923e+10  1.43923e+10
2019-01-03  152.860453  1.59222e+10  1.59222e+10
2019-01-04  146.730599  1.52777e+10  1.52777e+10
2019-01-05  153.056567  1.59408e+10  1.59408e+10

fetch_crypto_exchanges()

Retrieves exchange list.

k = Karpet()
k.fetch_crypto_exchanges("nrg")
['DigiFinex', 'KuCoin', 'CryptoBridge', 'Bitbns', 'CoinExchange']

fetch_google_trends()

Retrieves Google Trends - in percents for the given date range.

k = Karpet(date(2019, 1, 1), date(2019, 5, 1))
df = k.fetch_google_trends(kw_list=["bitcoin"])  # Dataframe with trends.
df.head()

And with a few lines of code you can get a chart

df = df.set_index("date")
df.plot()

fetch_news()

Retrieves crypto news.

k = Karpet()
news = k.fetch_news("btc")  # Gets 10 news.
print(news[0])
{
   'url': 'https://cointelegraph.com/ ....',  # 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': 'https://images.cointelegraph.com/....jpg'  # Truncated.
}
news = k.fetch_news("btc", limit=30)  # Gets 30 news.

fetch_top_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()
print(len(editors_choices))
5
print(len(top_stories))
5
print(editors_choices[0])
{
   'url': 'https://cointelegraph.com/...',  # 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': 'https://images.cointelegraph.com/images/740_aHR...', # Truncated.
   'description': 'The Chinese central bank released on its website an ...'  # Truncated.
}
print(top_stories[0])
{
   'url': 'https://cointelegraph.com/...',  # 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': 'https://images.cointelegraph.com/images/740_aHR0c...'  # Truncated.
   'description': 'Stability around $10,600 for Bitcoin price is ...'  # Truncated.
}

get_coin_ids()

Resolves coin ID’s based on the given symbol (there are coins out there with identical symbol).

Use this to get distinctive coin ID which can be used as id param for method fetch_crypto_historical_data().

k = Karpet()
print(k.get_coin_ids("sta"))
['statera']

get_basic_data()

Fetches coin/token basic data like:

open_issues is only provided if total_issues and closed_issues are available.

k = Karpet()
print(k.get_basic_data(id="ethereum"))
{
    'closed_issues': 5530,
    'commit_count_4_weeks': 40,
    'current_price': 3167.67,
    'forks': 11635,
    'market_cap': 371964284548,
    'name': 'Ethereum',
    'open_issues': 230,
    'pull_request_contributors': 552,
    'rank': 2,
    'reddit_accounts_active_48h': 2881.0,
    'reddit_average_comments_48h': 417.083,
    'reddit_average_posts_48h': 417.083,
    'reddit_subscribers': 1057875,
    'stars': 31680,
    'total_issues': 5760,
    'year_high': 4182.790285752286,
    'year_low': 321.0774351739628,
    'yoy_change': 695.9225871929757,  # growth/drop in percents
    'price_change_24': 120.1,
    'price_change_24_percents': 1.23
}

get_quick_search_data()

Lists all coins/tokes with some basic info.

k = Karpet()
print(k.get_quick_search_data()[0])
{
    "name": "Bitcoin",
    "symbol": "BTC",
    "rank": 1,
    "slug": "bitcoin",
    "tokens": [
        "Bitcoin",
        "bitcoin",
        "BTC"
    ],
    "id": 1,
}

fetch_crypto_live_data()

Retrieves live market data.

k = Karpet()
df = k.fetch_crypto_live_data(id="ethereum")  # Dataframe with live data.
df.head()

                        open     high      low    close
2023-01-16 20:00:00  1593.01  1595.05  1593.01  1594.28
2023-01-16 20:30:00  1593.37  1593.37  1589.03  1589.35
2023-01-16 21:00:00  1592.68  1593.66  1584.71  1587.87
2023-01-16 21:30:00  1587.28  1587.28  1583.13  1583.13
2023-01-16 22:00:00  1573.99  1580.11  1573.99  1579.97

Changelog

0.4.9

• new retry policy

0.4.8

• new fetch_crypto_live_data()

0.4.7.

• dependencies updated

• news with non UTF-8 chars handled and dropped

• fixed code formatting

0.4.6

• new price_change_24 and price_change_24_percents properties for get_basic_data()

• new get_quick_search_data()

0.4.5

• fixed dependencies

0.4.4

• removed obsolete parts of the code and some dependencies

0.4.3

• fixed get_basic_data() method (different data source)

• new property in get_basic_data() return dict - rank

• tests enhanced

0.4.2

• fixed minor bugs

0.4.1

• new data in get_basic_data() method - year_low, year_high, yoy_change

0.4

• new method get_basic_data()

0.3.3

• removed twitter integration - twitterscraper library is not up to date

• fixed news fetching

0.3.2

• new method get_coin_ids()

• method fetch_crypto_historical_data() has id param now

0.3.1

• migrated to coingecko.com API (no API key needed anymore)

0.3

• migrated to cryptocompare.com API (you need an API key now)

• requirements are now managed by Poetry

0.2.5

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

0.2.4

• 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

0.2.3

• simplified import from from karpet.karpet import Karpet to from karpet import Karpet

0.2.2

• added fetch_news() method for retrieving crypto news

0.2.1

• added fetch_exchanges() method for retrieving symbol exchange list

• removed obsolete library dependency

0.2

• twitter scraping added

0.1

• initial release

Credits

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.