ScienceBeam Parser, parse scientific documents.
Project description
ScienceBeam Parser Python Library
ScienceBeam Parser allows you to parse scientific documents. It provides a REST API Service, as well as a Python API.
Installation
pip install sciencebeam-parser
CLI
CLI: Start Server
python -m sciencebeam_parser.service.server --port=8080
The server will start to listen on port 8080
.
The default config.yml defines what models to load.
Python API
Python API: Start Server
from sciencebeam_parser.config.config import AppConfig
from sciencebeam_parser.resources.default_config import DEFAULT_CONFIG_FILE
from sciencebeam_parser.service.server import create_app
config = AppConfig.load_yaml(DEFAULT_CONFIG_FILE)
app = create_app(config)
app.run(port=8080, host='127.0.0.1', threaded=True)
The server will start to listen on port 8080
.
Python API: Parse Multiple Files
from sciencebeam_parser.resources.default_config import DEFAULT_CONFIG_FILE
from sciencebeam_parser.config.config import AppConfig
from sciencebeam_parser.utils.media_types import MediaTypes
from sciencebeam_parser.app.parser import ScienceBeamParser
config = AppConfig.load_yaml(DEFAULT_CONFIG_FILE)
# the parser contains all of the models
sciencebeam_parser = ScienceBeamParser.from_config(config)
# a session provides a scope and temporary directory for intermediate files
# it is recommended to create a separate session for every document
with sciencebeam_parser.get_new_session() as session:
session_source = session.get_source(
'test-data/minimal-example.pdf',
MediaTypes.PDF
)
converted_file = session_source.get_local_file_for_response_media_type(
MediaTypes.TEI_XML
)
# Note: the converted file will be in the temporary directory of the session
print('converted file:', converted_file)
More Usage Examples
For more usage examples see sciencebeam-usage-examples.
Project details
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