dariocorral / panoanda

Pandas framework for OANDA V1

Panoanda

Panoanda is a Pandas framework for OANDA API V1.

Installation

1. You can use this framework only if you have a "legacy" OANDA account (live or demo). (V20 not included)

2. You need to create a new environment with 3 environment variables :

   • "ACCOUNT" -> Your legacy OANDA account
   • "TOKEN" -> Your API token
   • "ENV" -> "practice" or "live"

   If you use Anaconda you can follow these steps : Managing environments

3. Activate your enviroment and use the following command in your terminal :

   $ pip install git+https://github.com/dariocorral/panoanda.git   --process-dependency-links
   

   It will install all required packages.

Usage and Examples

Panoanda includes these classes ready to use with Pandas dataframe:

• Candles (Historic Candles)
• Tickers (Info all instruments available)
• Indicators (Some basic trading indicators)
• Spreads (OANDA historic spreads)
• Units (Position size calculation)
• Financing (Financing charges calculation)
• Account (account info: NAV, balance, margin...)

Candles

from panoanda.candles import Candles

#You must create an instance
candles = Candles()

#Dataframe 50 periods,  daily timeframe, without Sunday candle and a list:
df =  candles.dataframe(50, 'D', False, *['GBP_USD', 'USD_JPY'])
print (df)

Tickers

import pandas as pd
from panoanda.tickers import Tickers

#Instance
tickers = Tickers()

#Set a dataframe with OANDA instruments like index
df = pd.DataFrame(index = ['EUR_USD', 'GBP_JPY', 'USD_CNH', 'AUD_USD'], data = [100, 100, 100, 100], columns = ['base'])

#This method add a new column with tick Value for all instruments of the dataframe index

df['tickValue'] = tickers.tick_value(df.index)

Indicators

from panoanda.indicators import Indicators

 #Instance
 indicators = Indicators()

 #A bollinger bands dataframe (sma, std bands) according index last dataframe (df)
 df1 = indicators.boll_bands(100, 'H4', 'close', 2, *df.index)

 #Adding a column with an exponential moving average
 df1['ema'] = indicators.ema(50, 'H4', 'close', *df1.index)

Spreads

from panoanda.spreads import Spreads

#Instance
spreads = Spreads()

#Call a dataframe with average spreads (min, avg, max) from last year
tickers = ['GBP_USD', 'USD_CAD', 'USD_JPY']
spreadsDf = spreads.dataframe('Y', *tickers)
print(spreadsDf)

Units

import pandas as pd
from panoanda.units import Units

#Instance
units = Units()

#Call a dataframe with pips and amounts to trade
tickers = ['GBP_USD', 'USD_CAD', 'USD_JPY']
pips = [100, 55, 39 ]
amounts = [120, 245, 520] #account currency amounts

#Dataframe
df = pd.DataFrame(data = [tickers, pips, amounts] )
df = df.transpose()
df.columns = ('ticker', 'pips', 'amount')
df.set_index('ticker', inplace = True)

#New units column calculated according dataframe index / columns 
df['units'] = units.dataframe(*(df.index, df['pips'], df['amount']))
print(df)

Financing

from panoanda.financing import Financing

#Instance
financing = Financing()

#List to use (index or columns dataframe are valid inputs too):
positions = ['long', 'short', 'long']
tickers = ['USD_CHF', 'EUR_USD', 'AUD_USD']
units = [120000, 250000, 40000] #You can use Units for this

#Interest charges for 120 hours holding position, 2 round decimals
df = financing.interest_dataframe(120, 2, *(positions, tickers, units))
print(df)

Account

from panoanda.account import Account

#Instance
account = Account()

#NAV (Net asset value)
nav = account.nav
print (nav)

Explore help documentation to know additional functions