Python Liberator.query() Example Queries

 Last Known Value 

A query that does not provide any date parameters will return the last known value.

import liberator

liberator.url='https://api.cloudquant.ai'
res = liberator.query(name='daily_bars')
df = liberator.get_dataframe(res)
df[['symbol','timestamp','open','high','low','close','volume']]

💡: Note Rather than printing the whole dataframe, we choose the columns we want to print. Alternatively, you can pass a fields parameter to the query containing a list of the columns you require (note there will always be some key fields returned by default).

Time Series Queries – Providing Date Parameters

There are two date parameters that you can pass.

💡: Note if as_of and back_to are the same date time, then you will not receive a time series result.

💡: Note how you can roll the query and the dataframe conversion into one line.

import liberator

liberator.url='https://api.cloudquant.ai'

df = liberator.get_dataframe(liberator.query( name = 'daily_bars', as_of = '2020-11-15', symbols = ['FB', 'AAPL', 'NFLX', 'GOOG', 'MSFT', 'IBM']))

df

Query All Symbols in a Dataset

To query all the symbols in a dataset, simply drop the symbols= parameter from the above queries.

import liberator

liberator.url='https://api.cloudquant.ai'

df = liberator.get_dataframe(liberator.query( name = 'daily_bars', as_of = '2020-11-15'))

df

Query a Live Dataset

To query a live dataset, set the as_of= parameter to 'live'.

import liberator

liberator.url='https://api.cloudquant.ai'

res=liberator.query(name=‘ice_live_nasdaq_composite_564_b', as_of='live')

for batch in res:

       df=batch.to_pandas()

       print(df)