Metadata-Version: 1.1
Name: libcryptomarket
Version: 0.1.5
Summary: Library for cryptocurrency market information.
Home-page: https://github.com/gavincyi/libcryptomarket
Author: Gavin Chan
Author-email: gavincyi@gmail.com
License: GNU General Public License v3
Description-Content-Type: UNKNOWN
Description: # libcryptomarket: Powerful cryptocurrency market analysis toolkit
        
        ## Objective
        
        * Support API calls of top cryptocurrency exchanges
        
        * Support trading and analysis tools for cryptocurrency market
        
        The project aims to answer the following two questions:
        
        1. How to get historical data, especially a long period, in a single query?
        
        2. How to send exchange API query in an elegent fashion?
        
        ## Prerequisite
        
        Python 3.5+
        
        ## Installation
        
        You can install it via pip for static version
        
        ```
        pip install libcryptomarket
        ```
        
        or development version
        
        ```
        pip install git+https://github.com/libcryptomarket/libcryptomarket.git
        ```
        
        ## Exchanges supported
        
        | Exchange | Public API | Private API |
        |---|---|---|
        | [Bitfinex](https://docs.bitfinex.com/v2/docs/ws-general) | v | x |
        | [BitMEX](https://www.bitmex.com/api/explorer/) | v | x |
        | [CoinMarketCap](https://coinmarketcap.com/api/) | v | x |
        | [GDAX](https://docs.gdax.com/#api) | v | x |
        | [Poloniex](https://poloniex.com/support/api/) | v | v |
        
        ## Basic Usage
        
        ### Generic API
        
        You can just make a simple call to query the same function from different
        exchanges. For example, if you want to get the historical data from GDAX and
        Bitfinex in a 5 minute timeframe, just call
        
        ```
        In [1]: from libcryptomarket.api import GdaxApi, BitfinexApi
        
        In [2]: from libcryptomarket.core import historical_ticker
        
        In [3]: from datetime import datetime
        
        In [4]: ticker1 = historical_ticker(source=GdaxApi(), symbol="BTC-USD", period=300, start_time=datetime(2017, 12, 30, 12, 0, 0), end_time=datetime(2017, 12, 31, 12, 0, 0))
        
        In [5]: ticker2 = historical_ticker(source=BitfinexApi(), symbol="tBTCUSD", period="5m", start_time=datetime(2017, 12, 30, 12, 0, 0), end_time=datetime(2017, 12, 31, 12, 0, 0))
        ```
        
        The historical data query automatically rolls over if the exchange response 
        chunk a long period data. It can guarantee that you do not need to write your
        own logic to get a long period of data.
        
        
        ### Exchange API
        
        You can easily initialize an exchange API client and call any method stated
        in the exchange API official documentation. The return value is always
        the native response from library `requests`.
        
        
        For example, to get GDAX order book information,
        
        ```
        In [1]: from libcryptomarket.api import GdaxApi
        
        In [2]: exchange = GdaxApi()
        
        In [3]: exchange.products_book(product_id="BTC-USD").json()
        Out[3]:
        {'asks': [['14903.01', '22.60310282', 18]],
         'bids': [['14903', '3.4933731', 2]],
         'sequence': 4757644393}
        ```
        
        Also, to buy order in Poloniex,
        
        ```
        In [1]: from libcryptomarket.api import PoloniexApi
        
        In [2]: exchange = PoloniexApi(public_key="<your public key>", private_key="<your private key>")
        
        In [3]: exchange.buy(currencyPair="BTC_LTC", rate=0.001, amount=0.1, postOnly=1)
        ```
        
        The exchange API methods are always delimited by underscore.
        
        | Exchange | Method | libcryptomarket | URL |
        |---|---|---|---|
        | [Bitfinex](https://docs.bitfinex.com/v2/docs/ws-general) | [candles](https://docs.bitfinex.com/v2/reference#rest-public-candles) | `BitfinexApi().candles(timeframe="1m", symbol="tBTCUSD", session="hist")` | https://api.bitfinex.com/v2/candles/trade:1m:tBTCUSD/hist |
        | [BitMEX](https://www.bitmex.com/api/explorer/) | [trades/bucketed](https://www.bitmex.com/api/explorer/#!/Trade/Trade_getBucketed) | `BitmexApi().trade_bucketed(binSize="1m", symbol="XBTUSD")` | https://www.bitmex.com/api/v1/trade/bucketed?binSize=1m&symbol=XBTUSD |
        | [CoinMarketCap](https://coinmarketcap.com/api/) | [ticket/<id>/](https://coinmarketcap.com/api/) | `CoinMarketCapApi().ticker(id="bitcoin", convert="EUR")` | https://api.coinmarketcap.com/v1/ticker/bitcoin/?convert=EUR |
        | [GDAX](https://docs.gdax.com/#api) | [/products/<product-id>/candles](https://docs.gdax.com/#get-historic-rates) | `GdaxApi().products_candles(product_id="BTC-USD")` | https://api.gdax.com/products/BTC-USD/candles |
        | [Poloniex](https://poloniex.com/support/api/) | [returnOrderBook](https://poloniex.com/support/api/#returnOrderBook) | `PoloniexApi().return_order_book(currencyPair="BTC_NXT", depth=10)` | https://poloniex.com/public?command=returnOrderBook&currencyPair=BTC_NXT&depth=10 |
        
        ## Contribution
        
        The project is targeting as a core but generic toolkit to query cryptocurrency
        market, so we are happy if you join to contribute and make it better. Please
        do not hesitate to contact us (gavincyi at gmail dot com).
        
        =======
        History
        =======
        
        0.1.0 (2017-11-07)
        ------------------
        
        * First release on PyPI.
        
Keywords: libcryptomarket
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
