Comments (2)
It seems you have some overhead somewhere else since the total elapsed time is way less than 4s.
What is your pipeline and how do you call Parsr's API?
from parsr.
In order to time the full operation I am using the python client in a jupyter notebook:
%%timeit -n1 -r1
parsr.send_document(
file_path=pdf_file,
config_path='/tmp/parsr_config.json',
document_name='Test',
save_request_id=True)
while 'progress-percentage' in parsr.get_status()['server_response']:
time.sleep(0.1)
The client is instantiated with
from parsr_client import ParsrClient
parsr = ParsrClient('localhost:3001')
and the API is running via its docker image.
from parsr.
Related Issues (20)
- Webhook or some notification system for when parsing is finished HOT 1
- parsr-jupyter-demo doesn't work HOT 1
- Cannot detect table
- Deployment guide HOT 1
- Support detecting text in vertical direction HOT 1
- Jupyter-Demo Notebook Third Cell Keep on Running without Showing any output HOT 1
- UI in docker fails with io_setup() failed
- Followed Instructions, but ended up with Connection Error HOT 2
- After running parsr.get_text(), where are the text files saved?
- Blank GUI when behind nginx
- How to browse the entire queue?
- Estimated Remaining Time and Progress are 0
- Failing @ npm run test
- Cancelling jobs from the Python Client
- Parsr-Client on PyPI is outdated
- TypeScript Compilation Fails HOT 3
- Parsr AutoScaling on Kubernetes
- Version without Docker?
- TableDetection2 Fails - Can't Find Java
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from parsr.