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‎.gitignore‎

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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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pip-wheel-metadata/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.nox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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*.py,cover
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.hypothesis/
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.pytest_cache/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3
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db.sqlite3-journal
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# Flask stuff:
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instance/
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.webassets-cache
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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docs/_build/
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# PyBuilder
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target/
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# Jupyter Notebook
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.ipynb_checkpoints
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# IPython
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profile_default/
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ipython_config.py
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# pyenv
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.python-version
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# pipenv
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# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
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# having no cross-platform support, pipenv may install dependencies that don't work, or not
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# install all needed dependencies.
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#Pipfile.lock
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow
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__pypackages__/
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# Celery stuff
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celerybeat-schedule
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celerybeat.pid
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# SageMath parsed files
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*.sage.py
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# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Spyder project settings
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.spyderproject
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.spyproject
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# Rope project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/
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.vscode/settings.json
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.vscode/launch.json
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subject_smiles_dictionary*
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*.pdf
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*.ipynb
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*.txt
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*.smi

‎LICENSE‎

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MIT License
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Copyright (c) 2022 Kevin Greenman
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.

‎README.md‎

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# PatentChem
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This code downloads the weekly bulk files from the [USPTO](https://developer.uspto.gov/product/patent-grant-dataxml), selects the patents relevant to chemistry, and queries the chemistry patent claims sections for given keywords to find molecule SMILES related to those keywords.
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## Installation
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```
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conda install -c conda-forge mamba
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mamba env create -f environment.yml
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```
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## Example Usage
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The scripts should be run in the following order. Steps 1 and 2 only need to be run once, then steps 3 and 4 can be run as many times as desired using different query terms.
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### 1. Download
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Download all USPTO patents for the given years:
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`python download.py --years 2021 --data_dir /data/patents_data/`
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Additional options:
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* `--remove_compressed`: remove the original .tar and .zip files for the weekly releases after decompressing them
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### 2. Select
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Select the patents related to chemistry based on the presence of CDX files:
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`python select_chem.py --years 2021 --data_dir /data/patents_data/`
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Additional options:
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* `--remove_compressed`: remove all original .zip files after unzipping those relevant to chemistry
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### 3. Search
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Provide a list of query terms to search for in the claims sections of the chemistry-related patents:
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`python search.py --years 2021 --data_dir /data/patents_data/ --naming opd --subject_list "organic electronic" "photodiode" "organic photovoltaic"`
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### 4. Clean
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Output a yaml file with the SMILES strings found related to the query terms and all of the patents related to each SMILES. Also output a text file with all unique SMILES strings from the query.
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`python clean.py --years 2021 --naming opd`
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Additional options:
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* `--output_dir`: parent directory of `--naming` if different from `.`
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* `--charged_only`: include only charged molecules in output
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* `--neutral_only`: include only neutral molecules in output
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* `--mw_min`: include only molecules with molecular weight greater than this
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* `--mw_max`: include only molecules with molecular weight less than this
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## Download File Sizes
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The following file sizes are taken from the [USPTO Bulk Data Storage System](https://bulkdata.uspto.gov) using the URLs `https://bulkdata.uspto.gov/data/patent/grant/redbook/<YEAR>/` and converting from bytes to GB. The 2023 file size is as of 10 March 2023. The download speed seems to be restricted to ~5-10MB/s, which means downloading the full set could require > 4 days if done in series. Alternatively, you can run multiple downloads in parallel. Either way, we recommend starting the downloads in a [tmux](https://github.com/tmux/tmux/wiki) session to run in the background. Note that these file sizes are for the *compressed* (zip or tar) files, so the total space required to store this data is larger than what is reported below. Use caution to avoid filling your hard drive to capacity.
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| **Year** | **File Size** | **Units** |
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|-------|-----------|-------|
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| 2001 | 37.07 | GB |
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| 2002 | 37.23 | GB |
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| 2003 | 39.20 | GB |
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| 2004 | 38.95 | GB |
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| 2005 | 30.67 | GB |
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| 2006 | 39.90 | GB |
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| 2007 | 39.98 | GB |
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| 2008 | 42.08 | GB |
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| 2009 | 43.82 | GB |
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| 2010 | 61.65 | GB |
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| 2011 | 68.24 | GB |
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| 2012 | 85.42 | GB |
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| 2013 | 96.55 | GB |
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| 2014 | 111.26 | GB |
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| 2015 | 119.98 | GB |
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| 2016 | 117.42 | GB |
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| 2017 | 124.10 | GB |
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| 2018 | 148.02 | GB |
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| 2019 | 182.28 | GB |
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| 2020 | 192.45 | GB |
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| 2021 | 184.41 | GB |
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| 2022 | 185 | GB |
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| 2023 | 39 | GB |
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| **Total** | **2.05** | **TB** |
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## Notes
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* Patent archives from 2001 - 2004 and 2009 follow a different format than other years; this code may not be able to process patents from these years properly.
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* For simplicity, `clean.py` replaces "*" and "Y" substituents from Markush structures with ethyl and O groups. This might not be appropriate for your applications.
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## Citation
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If you use this code, please cite the following [manuscript](): <!-- # TODO: fill in link and rest of bibtex citation -->
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```
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@article{patents-generative2023,
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title={Automated patent extraction powers generative modeling in focused chemical spaces},
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author={Subramanian, Akshay and Greenman, Kevin P. and Gervaix, Alexis and Yang, Tzuhsiung and G{\'{o}}mez-Bombarelli, Rafael},
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journal={TBD},
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doi={TBD},
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year={2023}
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}
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```

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