Query Liberator for Time Range from a Dataset
query <— function(…)
The query function takes a list of arguments and streams data as a generator of Arrow Record Batches.
|
Argument |
Description |
Type |
Example |
|
symbols |
The security trading symbol(s) you wish to query |
string or list |
symbols="AAPL" |
|
name |
The name of the dataset |
string |
name=" daily_bars" |
|
as _of |
The date in time that you wish the data to be. as_of defaults to now. This value can be any past date so that you can see the data as it was known on the “as of” date. |
string Format YYYY-MM-DD HH:MM:SS (HH:MM:SS optional) |
as_of="2019-09-15" |
|
back_to |
The date where the return dataset should begin. This is reading all the data “back to” the specified date. |
string Format YYYY-MM-DD HH:MM:SS (HH:MM:SS optional) |
as_of=“2019-07-15” |
|
fields |
An optional filter of field names. Note: mandatory fields will always be included |
string |
fields= “volume” |
|
stats |
Set to 'total' to get count per symbol as Json result |
string |
stats= “total” |
|
crux_key |
if querying for a Crux data set |
string |
crux_key= “<Your Key>” |
|
compress |
The data compression method on the wire. CloudQuant uses compression. |
Boolean |
compress=FALSE |
|
json_xfer |
Json transfer. This is usually False |
Boolean. Always False |
json_xfer=FALSE |
|
debug_stream |
Send log info to this ostream ptr |
stderr() |
debug_stream= stderr() |
|
user |
The user identifier (as assigned by CloudQuant) |
string |
user=“Your Username” |
|
token |
The user’s assigned token |
string |
token=“Your Token” |
Example Query for Time Range
print(liberator::get_dataframe(liberator::query(symbols="APPL", name=" daily_bars", as_of="2019-09-15", back_to="2019-09-10")))
Query Liberator for Stats as JSON Result
Setting the “stats” argument to “total” will tell the query to return a json result containing the count per symbol.
Example Query for Stats
print(liberator::query(symblols="APPL", name="daily_bars", as_of="2019-09-15", back_to=“2019-09-10”, stats=“total”))