Historical Data Request¶
Accern Historical Batch data request is available for user who has the permission to create a job(data request). The data can be downloaded when the job request is finished.
Create Historical Instance¶
Create an Historical instance
from accern import HistoricalClient
token = 'YOUR TOKEN'
Client = HistoricalClient(token)
Set up a job¶
name
, description
, filters
and select
are required field to
create a job schema. For more detail of how to work with filters
and
select
, please refer to the Schema.
schema = {
'name': 'test',
'description': 'request 2017 November data',
'filters': [
{
'harvested_at': [
['2017-11-01 00:00:00', '2017-11-30 23:59:59']
],
'entity_sentiment': [
[-100, 50]
]
}
],
'select': [
{'field': 'entity_sentiment'},
{'field': 'entity_ticker'},
{'field': 'event'},
{'field': 'harvested_at'}
]
}
Check your job history¶
resp = Client.get_jobs()
If you pass a job id to the get_jobs
function, you will get the information
of that job.
job_id = 'YOUR JOB ID'
resp = Client.get_jobs(job_id)
Select and Aggregations¶
You can add minute
, hour
, day
, week
, or month
aggregation function to the field harvested_at
. The alias
field should
match the function name you choose.
schema = {
'name': 'Month',
'description': 'Month Sentiment data',
'select': [
{
'field': 'harvested_at',
'alias': 'month',
'function': 'month'
}
]
}
The aggregation function will group signals based on the time interval you choose. If your data will contain other fields, an aggregation function should be given. Otherwise, an API error will occur.
schema = {
'name': 'Month',
'description': 'Month Sentiment data',
'filters': [
{
'harvested_at': [
['2012-08-01 00:00:00', '2017-11-30 00:00:00']
],
'entity_sentiment': [
[-100, 50]
],
'entity_ticker': [
'AAPL',
'AMZN'
]
}
],
'select': [
{
'field': 'entity_sentiment',
'function': 'sum'
},
{
'field': 'entity_ticker',
'function': 'group'
},
{
'field': 'harvested_at',
'alias': 'month',
'function': 'month'
}
]
}
A full list of the available aggregation functions can be found at Aggregation function