Currency Tick History in Python

I am trying to obtain currency tick history, for example last 5 years of 1 minute Open, High,Low, Close for USDZAR. the documentaion seems to be fairly dated on how to set up the request (how do i obtain a token) and how do i structure the query to create a dataframe with DateTime Index, and the columns populated with values.

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Accepted answers

jolin.majmin

There was an error in the pdf. The code block with error line, in bold, corrected below.

timestamp = pd.Timestamp('now')
today = timestamp.tz_localize('UTC').tz_convert(pytz.timezone('Africa/Johannesburg'))
today_str = today.strftime('%Y-%m-%d')


yesterday = (today - pd.Timedelta(1, "d")).normalize()
yesterday_str = yesterday.strftime('%Y-%m-%d')


start_date = pd.to_datetime('2010-01-01', format='%Y-%m-%d')
start_date_str = start_date.strftime('%Y-%m-%d')


filedate = (timestamp - pd.Timedelta(1, "d")).strftime('%Y%m%d')


QueryStartDate = start_date.strftime("%Y-%m-%dT%H:%M:%S.000Z")
QueryEndDate = yesterday.strftime("%Y-%m-%dT%H:%M:%S.000Z")


print("QueryStartDate:", QueryStartDate)
print("QueryEndDate:", QueryEndDate)

All comments

jason.ramchandani01

@jolin.majmin Thanks for your question - have you tried downloading the python sample jupyter notebook and .py files here. We also have some articles about using Tick History with Python here and here. I hope these can help.

jolin.majmin

I did try some of those files, they were fairly dated. Been used to xbbg from bloomberg which is easier to access data, and a bit faster, but after some fiddling. I created the script attached that takes account of proxy servers....glued some old bits together.Refinitiv Tick Summary Extraction.pdf

jolin.majmin

There was an error in the pdf. The code block with error line, in bold, corrected below.

timestamp = pd.Timestamp('now')
today = timestamp.tz_localize('UTC').tz_convert(pytz.timezone('Africa/Johannesburg'))
today_str = today.strftime('%Y-%m-%d')


yesterday = (today - pd.Timedelta(1, "d")).normalize()
yesterday_str = yesterday.strftime('%Y-%m-%d')


start_date = pd.to_datetime('2010-01-01', format='%Y-%m-%d')
start_date_str = start_date.strftime('%Y-%m-%d')


filedate = (timestamp - pd.Timedelta(1, "d")).strftime('%Y%m%d')


QueryStartDate = start_date.strftime("%Y-%m-%dT%H:%M:%S.000Z")
QueryEndDate = yesterday.strftime("%Y-%m-%dT%H:%M:%S.000Z")


print("QueryStartDate:", QueryStartDate)
print("QueryEndDate:", QueryEndDate)

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