Skip to main content

A client for extracting software mentions in scholar publications

Project description

Softcite software mention recognizer client

PyPI version License

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)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

software_mentions_client-0.1.9.tar.gz (25.6 kB view details)

Uploaded Source

File details

Details for the file software_mentions_client-0.1.9.tar.gz.

File metadata

File hashes

Hashes for software_mentions_client-0.1.9.tar.gz
Algorithm Hash digest
SHA256 817f592b4e7ce2a017ec3a27cc9aaddbb8b26e65aa4f57a09b983c8c43b80a02
MD5 ffe7d7c97734592fc6517170b8e0cf8f
BLAKE2b-256 99011b37b4f9dca980e67501ba651c14dd620cb47a85f5b1e77d9156bb4037c3

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page