pyharmonics detects harmonic patterns in OHLC candle data for any stock or crypto asset. See http://www.harmonictrader.com for more information on harmonic patterns and follow author Scott Carney.
From git
$ git clone git@github.com:niall-oc/pyharmonics.git
$ cd pyharmonics
$ pip install .
$ cd src
$ python
>>> from pyharmonics.marketdata import BinanceCandleData
...
From pypi
$ pip install pyharmonics
$ python
>>> from pyharmonics.marketdata import BinanceCandleData
https://pyharmonics.readthedocs.io/en/latest/
Use the market data features or generate your own market data matching the dataframe schema below. close_time, dts can be omitted
>>> from pyharmonics.marketdata import BinanceCandleData
>>> b = BinanceCandleData()
>>> b.get_candles('BTCUSDT', b.MIN_15, 1000)
>>> b.df
>>> b.df
open high low close volume close_time dts
index
2023-07-09 07:44:59+01:00 30249.04 30267.04 30233.79 30262.33 79.71611 1688885099 2023-07-09 07:44:59+01:00
2023-07-09 07:59:59+01:00 30262.32 30267.87 30235.00 30254.79 136.31718 1688885999 2023-07-09 07:59:59+01:00
2023-07-09 08:14:59+01:00 30254.80 30283.50 30233.33 30283.50 185.04086 1688886899 2023-07-09 08:14:59+01:00
2023-07-09 08:29:59+01:00 30283.50 30283.50 30263.37 30263.37 74.17937 1688887799 2023-07-09 08:29:59+01:00
2023-07-09 08:44:59+01:00 30263.37 30270.09 30243.10 30257.30 121.15791 1688888699 2023-07-09 08:44:59+01:00
... ... ... ... ... ... ... ...
2023-07-19 16:29:59+01:00 29841.37 29902.00 29841.36 29878.00 267.42077 1689780599 2023-07-19 16:29:59+01:00
2023-07-19 16:44:59+01:00 29878.00 29933.00 29866.15 29890.01 245.03318 1689781499 2023-07-19 16:44:59+01:00
2023-07-19 16:59:59+01:00 29890.01 29995.16 29890.00 29956.46 611.16786 1689782399 2023-07-19 16:59:59+01:00
2023-07-19 17:14:59+01:00 29956.46 29979.00 29901.70 29930.57 365.35485 1689783299 2023-07-19 17:14:59+01:00
2023-07-19 17:29:59+01:00 29930.57 29930.57 29870.00 29901.40 244.14513 1689784199 2023-07-19 17:29:59+01:00
[1000 rows x 7 columns]
Create a technicals object for further analysis.
>>> from pyharmonics.technicals import Technicals
>>> t = Technicals(b.df, b.symbol, b.interval)
Search for a harmonic pattern.
>>> from pyharmonics.search import MatrixSearch
>>> m = MatrixSearch(t)
>>> m.search()
Plot the findings.
>>> from pyharmonics.plotter import Plotter
>>> p = Plotter(t, 'BTCUSDT', b.MIN_15)
>>> p.add_matrix_plots(m.get_patterns(family=m.XABCD))
>>> p.show()
You will see something like this.
See all harmonic patterns.
>>> p = Plotter(t, 'BTCUSDT', b.HOUR_1)
>>> p.add_matrix_plots(m.get_patterns())
>>> p.show()
You will see something like this.
See all forming patterns.
>>> m = MatrixSearch(t)
>>> m.forming()
>>> p = Plotter(t, 'BTCUSDT', b.HOUR_1)
>>> p.add_matrix_plots(m.get_patterns(formed=False))
>>> p.show()
etc.