Querying data using qSQL with PyKX
This page explains how to query your data with PyKX using qSQL.
Querying tables using qSQL
Creating a sample table:
>>> import pykx as kx
>>> trades = kx.Table(data={
'sym': kx.random.random(100, ['AAPL', 'GOOG', 'MSFT']),
'date': kx.random.random(100, kx.q('2022.01.01') + [0,1,2]),
'price': kx.random.random(100, 1000.0)
})
>>> # Assign the table to a named object in q memory to allow name based query later
>>> kx.q['trades'] = tradesQuery a table, by name, using qSQL:
>>> kx.q('select from trades')
pykx.Table(pykx.q('
sym date price
------------------------
GOOG 2022.01.02 805.0147
AAPL 2022.01.03 847.6275
AAPL 2022.01.03 329.8159
GOOG 2022.01.02 982.5155
MSFT 2022.01.02 724.9456
..
'))Query a pykx.Table passing it as an argument:
>>> kx.q('{select from x}', trades)
pykx.Table(pykx.q('
sym date price
------------------------
GOOG 2022.01.02 805.0147
AAPL 2022.01.03 847.6275
AAPL 2022.01.03 329.8159
GOOG 2022.01.02 982.5155
MSFT 2022.01.02 724.9456
..
'))Passing multiple arguments:
>>> from datetime import date
>>> kx.q('{[x;y] select from trades where date = x, price < y}', date(2022, 1, 2), 500.0)
pykx.Table(pykx.q('
sym date price
------------------------
GOOG 2022.01.02 214.9847
AAPL 2022.01.02 126.2957
AAPL 2022.01.02 184.4151
AAPL 2022.01.02 217.0378
GOOG 2022.01.02 423.6121
..
'))Next Steps
Now that you have learnt how to query your data using the Pythonic API you may be interested in other methods for querying your data:
- If you want to query your data in a more Python-first way follow the guide here.
- If you wish to query your data using SQL, you can follow the introduction to this functionality here.
- To learn how to make your queries more performant following the tips and tricks here.
For some further reading, here are some related topics: