A client for extracting software mentions in scholar publications
Project description
Softcite software mention recognizer client
Python client for using the Softcite software mention recognition service. It can be applied to
-
individual PDF or XML fulltext file
-
recursively to a local directory, processing all the encountered PDF and XML fulltext files
-
to a collection of documents harvested by biblio-glutton-harvester and article-dataset-builder, with the benefit of re-using the collection manifest for injectng metadata and keeping track of progress. The collection can be stored locally or on a S3 storage.
Requirements
The client has been tested with Python 3.5-3.8.
The client requires a working Softcite software mention recognition service. Service host and port can be changed in the config.json
file of the client.
Install
> git clone https://github.com/softcite/software_mentions_client.git
> cd software_mentions_client/
It is advised to setup first a virtual environment to avoid falling into one of these gloomy python dependency marshlands:
> virtualenv --system-site-packages -p python3 env
> source env/bin/activate
Install the dependencies, use:
> python3 -m pip install -r requirements.txt
Finally install the project in editable state
> python3 -m pip install -e .
Usage and options
usage: python3 -m software_mentions_client.client [-h] [--repo-in REPO_IN] [--file-in FILE_IN] [--file-out FILE_OUT]
[--data-path DATA_PATH] [--config CONFIG] [--reprocess] [--reset] [--load]
[--diagnostic-mongo] [--diagnostic-files] [--scorched-earth]
Softcite software mention recognizer client
optional arguments:
-h, --help show this help message and exit
--repo-in REPO_IN path to a directory of PDF or XML fulltext files to be processed by the
Softcite software mention recognizer
--file-in FILE_IN a single PDF or XML input file to be processed by the Softcite software
mention recognizer
--file-out FILE_OUT path to a single output the software mentions in JSON format, extracted
from the PDF file-in
--data-path DATA_PATH
path to the resource files created/harvested by biblio-glutton-harvester
--config CONFIG path to the config file, default is ./config.json
--reprocess reprocessed failed PDF or XML fulltexts
--reset ignore previous processing states and re-init the annotation process
from the beginning
--load load json files into the MongoDB instance, the --repo-in or --data-path
parameter must indicate the path to the directory of resulting json
files to be loaded, --dump must indicate the path to the json dump file
of document metadata
--diagnostic-mongo perform a full count of annotations and diagnostic using MongoDB
regarding the harvesting and annotation process
--diagnostic-files perform a full count of annotations and diagnostic using repository
files regarding the harvesting and annotation process
--scorched-earth remove the PDF or XML fulltext files file after their sucessful
processing in order to save storage space, careful with this!
The logs are written by default in a file ./client.log
, but the location of the logs can be changed in the configuration file (default ./config.json
).
Processing local PDF files
For processing a single file., the resulting json being written as file at the indicated output path:
python3 -m software_mentions_client.client --file-in toto.pdf --file-out toto.json
For processing recursively a directory of PDF files, the results will be:
-
written to a mongodb server and database indicated in the config file
-
and in the directory of PDF files, as json files, together with each processed PDF
python3 -m software_mentions_client.client --repo-in /mnt/data/biblio/pmc_oa_dir/
The default config file is ./config.json
, but could also be specified via the parameter --config
:
python3 -m software_mentions_client.client --repo-in /mnt/data/biblio/pmc_oa_dir/ --config ./my_config.json
Processing a collection of PDF harvested by biblio-glutton-harvester or article-dataset-builder
biblio-glutton-harvester and article-dataset-builder creates a collection manifest as a LMDB database to keep track of the harvesting of large collection of files. Storage of the resource can be located on a local file system or on a AWS S3 storage. The software-mention
client will use the collection manifest to process these harvested documents.
- locally:
python3 -m software_mentions_client.client --data-path /mnt/data/biblio-glutton-harvester/data/
--data-path
indicates the path to the repository of data harvested by biblio-glutton-harvester.
The resulting JSON files will be enriched by the metadata records of the processed PDF and will be stored together with each processed PDF in the data repository.
- on a S3 storage:
If the harvested collection is located on a S3 storage, the access information must be indicated in the configuration file of the client config.json
. The extracted software mention will be written in a file with extension .software.json
, for example:
-rw-rw-r-- 1 lopez lopez 1.1M Aug 8 03:26 0100a44b-6f3f-4cf7-86f9-8ef5e8401567.pdf
-rw-rw-r-- 1 lopez lopez 485 Aug 8 03:41 0100a44b-6f3f-4cf7-86f9-8ef5e8401567.software.json
If a MongoDB server access information is indicated in the configuration file config.json
, the extracted information will additionally be written in MongoDB.
License and contact
Distributed under Apache 2.0 license. The dependencies used in the project are either themselves also distributed under Apache 2.0 license or distributed under a compatible license.
If you contribute to Softcite software mention recognizer client project, you agree to share your contribution following these licenses.
Main author and contact: Patrice Lopez (patrice.lopez@science-miner.com)
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