ChEMBL Downloader

Reproducibly download, open, parse, and query ChEMBL.

Don't worry about downloading/extracting ChEMBL or versioning - just use chembl_downloader to write code that knows how to download it and use it automatically.

💪 Getting Started

Download an extract the SQLite dump using the following:

```python import chembl_downloader

path = chembldownloader.downloadextract_sqlite(version='28') ```

After it's been downloaded and extracted once, it's smart and does not need to download again. It gets stored using pystow automatically in the ~/.data/chembl directory.

Full technical documentation can be found on ReadTheDocs. Tutorials can be found in Jupyter notebooks in the notebooks/ directory of the repository.

Download the Latest Version

You can modify the previous code slightly by omitting the version keyword argument to automatically find the latest version of ChEMBL:

```python import chembl_downloader

path = chembldownloader.downloadextract_sqlite() ```

The version keyword argument is available for all functions in this package (e.g., including connect(), cursor(), and query()), but will be omitted below for brevity.

Automatically Connect to SQLite

Inside the archive is a single SQLite database file. Normally, people manually untar this folder then do something with the resulting file. Don't do this, it's not reproducible! Instead, the file can be downloaded and a connection can be opened automatically with:

```python import chembl_downloader

with chembl_downloader.connect() as conn: with conn.cursor() as cursor: cursor.execute(...) # run your query string rows = cursor.fetchall() # get your results ```

The cursor() function provides a convenient wrapper around this operation:

```python import chembl_downloader

with chembl_downloader.cursor() as cursor: cursor.execute(...) # run your query string rows = cursor.fetchall() # get your results ```

Run a Query and Get a Pandas DataFrame

The most powerful function is query() which builds on the previous connect() function in combination with pandas.read_sql to make a query and load the results into a pandas DataFrame for any downstream use.

```python import chembl_downloader

sql = """ SELECT MOLECULEDICTIONARY.chemblid, MOLECULEDICTIONARY.prefname FROM MOLECULEDICTIONARY JOIN COMPOUNDSTRUCTURES ON MOLECULEDICTIONARY.molregno == COMPOUNDSTRUCTURES.molregno WHERE moleculedictionary.prefname IS NOT NULL LIMIT 5 """

df = chembldownloader.query(sql) df.tocsv(..., sep='\t', index=False) ```

Suggestion 1: use pystow to make a reproducible file path that's portable to other people's machines (e.g., it doesn't have your username in the path).

Suggestion 2: RDKit is now pip-installable with pip install rdkit-pypi, which means most users don't have to muck around with complicated conda environments and configurations. One of the powerful but understated tools in RDKit is the rdkit.Chem.PandasTools module.

SDF Usage

Access an RDKit supplier over entries in the SDF dump

This example is a bit more fit-for-purpose than the last two. The supplier() function makes sure that the latest SDF dump is downloaded and loads it from the gzip file into a rdkit.Chem.ForwardSDMolSupplier using a context manager to make sure the file doesn't get closed until after parsing is done. Like the previous examples, it can also explicitly take a version.

```python from rdkit import Chem

import chembl_downloader

with chembl_downloader.supplier() as suppl: data = [] for i, mol in enumerate(suppl): if mol is None or mol.GetNumAtoms() > 50: continue fp = Chem.PatternFingerprint(mol, fpSize=1024, tautomerFingerprints=True) smi = Chem.MolToSmiles(mol) data.append((smi, fp)) ```

This example was adapted from Greg Landrum's RDKit blog post on generalized substructure search.

Iterate over SMILES

This example uses the supplier() method and RDKit to get SMILES strings from molecules in ChEMBL's SDF file. If you want direct access to the RDKit molecule objects, use supplier().

```python import chembl_downloader

for smiles in chembldownloader.iteratesmiles(): print(smiles) ```

Get an RDKit substructure library

Building on the supplier() function, the get_substructure_library() makes the preparation of a substructure library automated and reproducible. Additionally, it caches the results of the build, which takes on the order of tens of minutes, only has to be done once and future loading from a pickle object takes on the order of seconds.

The implementation was inspired by Greg Landrum's RDKit blog post, Some new features in the SubstructLibrary. The following example shows how it can be used to accomplish some of the first tasks presented in the post:

```python from rdkit import Chem

import chembl_downloader

library = chembldownloader.getsubstructure_library() query = Chem.MolFromSmarts('[O,N]=C-c:1:c:c:n:c:c:1') matches = library.GetMatches(query) ```

Morgan Fingerprints Usage

Get the Morgan Fingerprint file

ChEMBL makes a file containing pre-computed 2048 bit radius 2 morgan fingerprints for each molecule available. It can be downloaded using:

```python import chembl_downloader

path = chembldownloader.downloadfps() ```

The version and other keyword arguments are also valid for this function.

Load fingerprints with chemfp

The following wraps the download_fps function with chemfp's fingerprint loader:

```python import chembl_downloader

arena = chembldownloader.chemfpload_fps() ```

The version and other keyword arguments are also valid for this function. More information on working with the arena object can be found here.

Command Line Interface

After installing, run the following CLI command to ensure it and send the path to stdout:

console $ chembl_downloader download

Use the test subcommand to show two example queries:

console $ chembl_downloader test

Configuration

If you want to store the data elsewhere using pystow (e.g., in pyobo I also keep a copy of this file), you can use the prefix argument.

```python import chembl_downloader

It gets downloaded/extracted to

~/.data/pyobo/raw/chembl/29/chembl29/chembl29sqlite/chembl29.db

path = chembldownloader.downloadextract_sqlite(prefix=['pyobo', 'raw', 'chembl']) ```

See the pystow documentation on configuring the storage location further.

The prefix keyword argument is available for all functions in this package (e.g., including connect(), cursor(), and query()).

🚀 Installation

The most recent release can be installed from PyPI with uv:

console $ uv pip install chembl_downloader

or with pip:

console $ python3 -m pip install chembl_downloader

The most recent code and data can be installed directly from GitHub with uv:

console $ uv pip install git+https://github.com/cthoyt/chembl-downloader.git

or with pip:

console $ python3 -m pip install git+https://github.com/cthoyt/chembl-downloader.git

Users

See who's using chembl-downloader.

Statistics and Compatibility

chembl-downloader is compatible with all versions of ChEMBL (with a few caveats in the SQLite dumps of the first few versions, see discussion here). The following table can be generated with chembl_downloader history && chembl_downloader history-draw. These data can be found as a TSV in docs/_data/summary.tsv.

| Version | Date | Compounds | Named Compounds | Assays | Activities | Documents | Targets | Cells | Tissues | Drug Warnings | Drug Indications | Drug Mechanisms | | ------: | ---------- | --------: | --------------: | --------: | ---------: | --------: | ------: | ----: | ------: | ------------: | ---------------: | --------------: | | 35 | 2024-12-01 | 2,496,335 | 42,231 | 1,740,546 | 21,123,501 | 92,121 | 16,003 | 2,129 | 782 | 1,676 | 55,442 | 7,330 | | 34 | 2024-03-28 | 2,431,025 | 42,387 | 1,644,390 | 20,772,701 | 89,892 | 15,598 | 2,023 | 782 | 1,676 | 55,442 | 7,330 | | 33 | 2023-05-31 | 2,399,743 | 41,923 | 1,610,596 | 20,334,684 | 88,630 | 15,398 | 2,021 | 782 | 1,636 | 51,582 | 7,098 | | 32 | 2023-01-26 | 2,354,965 | 41,923 | 1,536,903 | 20,038,828 | 86,361 | 15,139 | 2,015 | 759 | 1,636 | 51,582 | 7,098 | | 31 | 2022-07-12 | 2,331,700 | 41,585 | 1,498,681 | 19,780,369 | 85,431 | 15,072 | 2,000 | 757 | 1,293 | 48,816 | 6,656 | | 30 | 2022-02-22 | 2,157,379 | 41,549 | 1,458,215 | 19,286,751 | 84,092 | 14,855 | 1,991 | 752 | 1,293 | 48,816 | 6,656 | | 29 | 2021-07-01 | 2,105,464 | 41,383 | 1,383,553 | 18,635,916 | 81,544 | 14,554 | 1,978 | 743 | 1,262 | 45,902 | 6,202 | | 28 | 2021-01-15 | 2,086,898 | 41,049 | 1,358,549 | 17,276,334 | 80,480 | 14,347 | 1,950 | 739 | 1,256 | 42,988 | 5,347 | | 27 | 2020-05-18 | 1,961,462 | 40,834 | 1,221,361 | 16,066,124 | 76,086 | 13,382 | 1,831 | 707 | 0 | 37,259 | 5,134 | | 26 | 2020-02-14 | 1,950,765 | 40,822 | 1,221,311 | 15,996,368 | 76,076 | 13,377 | 1,830 | 707 | 0 | 37,259 | 5,070 | | 25 | 2019-02-01 | 1,879,206 | 39,885 | 1,125,387 | 15,504,603 | 72,271 | 12,482 | 1,670 | 655 | 0 | 29,457 | 4,992 | | 24.1 | 2018-05-01 | 1,828,820 | 39,877 | 1,060,283 | 15,207,914 | 69,861 | 12,091 | 1,667 | 655 | 0 | 29,163 | 4,992 | | 24 | 2018-05-01 | 1,828,820 | 39,877 | 1,060,283 | 15,207,914 | 69,861 | 12,091 | 1,667 | 655 | 0 | 29,163 | 4,992 | | 23 | 2017-05-18 | 1,735,442 | 39,584 | 1,302,147 | 14,675,320 | 67,722 | 11,538 | 1,624 | 125 | 0 | 13,504 | 4,305 | | 22.1 | 2016-11-17 | 1,686,695 | 39,422 | 1,246,683 | 14,371,197 | 65,213 | 11,224 | 1,619 | 111 | 0 | 12,573 | 3,834 | | 22 | 2016-09-28 | 1,686,695 | 39,422 | 1,246,132 | 14,371,219 | 65,213 | 11,224 | 1,619 | 111 | 0 | 12,573 | 3,834 | | 21 | 2015-02-12 | 1,592,191 | 39,347 | 1,212,831 | 13,968,617 | 62,502 | 11,019 | 1,612 | 0 | 0 | 5,951 | 3,799 | | 20 | 2015-02-03 | 1,463,270 | 39,016 | 1,148,942 | 13,520,737 | 59,610 | 10,774 | 1,647 | 0 | 0 | 0 | 2,266 | | 19 | 2014-07-23 | 1,411,786 | 38,910 | 1,106,285 | 12,843,338 | 57,156 | 10,579 | 1,653 | 0 | 0 | 0 | 2,239 | | 18 | 2014-04-02 | 1,359,508 | 35,817 | 1,042,374 | 12,419,715 | 53,298 | 9,414 | 1,655 | 0 | 0 | 0 | 2,233 | | 17 | 2013-09-16 | 1,324,941 | 32,692 | 734,201 | 12,077,491 | 51,277 | 9,356 | 1,746 | 0 | 0 | 0 | 2,213 | | 16 | 2013-05-15 | 1,295,510 | 23,532 | 712,836 | 11,420,351 | 50,095 | 9,844 | 1,432 | 0 | 0 | 0 | 0 | | 15 | 2013-01-30 | 1,254,575 | 23,528 | 679,259 | 10,509,572 | 48,735 | 9,570 | 1,432 | 0 | 0 | 0 | 0 | | 14 | 2012-07-18 | 1,213,242 | 16,573 | 644,734 | 10,129,256 | 46,133 | 9,003 | 0 | 0 | 0 | 0 | 0 | | 13 | 2012-02-29 | 1,143,682 | 16,397 | 617,681 | 6,933,068 | 44,682 | 8,845 | 0 | 0 | 0 | 0 | 0 | | 12 | 2011-11-30 | 1,077,189 | 16,658 | 596,122 | 5,654,847 | 43,418 | 8,703 | 0 | 0 | 0 | 0 | 0 | | 11 | 2011-06-07 | 1,060,258 | 16,264 | 582,982 | 5,479,146 | 42,516 | 8,603 | 0 | 0 | 0 | 0 | 0 | | 10 | 2011-06-07 | 1,000,468 | 16,159 | 534,391 | 4,668,202 | 40,624 | 8,372 | 0 | 0 | 0 | 0 | 0 | | 9 | 2011-01-04 | 658,075 | 3,746 | 499,867 | 3,030,317 | 39,094 | 8,091 | 0 | 0 | 0 | 0 | 0 | | 8 | 2010-11-05 | 636,269 | 0 | 488,898 | 2,973,034 | 38,462 | 8,088 | 0 | 0 | 0 | 0 | 0 | | 7 | 2010-09-03 | 602,500 | 0 | 485,095 | 2,948,069 | 38,204 | 8,078 | 0 | 0 | 0 | 0 | 0 | | 6 | 2010-09-03 | 600,625 | 0 | 481,752 | 2,925,588 | 38,029 | 8,054 | 0 | 0 | 0 | 0 | 0 | | 5 | 2010-06-07 | 578,715 | 0 | 459,823 | 2,787,240 | 36,624 | 7,493 | 0 | 0 | 0 | 0 | 0 | | 4 | 2010-05-26 | 565,245 | 0 | 446,645 | 2,705,136 | 35,821 | 7,330 | 0 | 0 | 0 | 0 | 0 | | 3 | 2010-04-30 | 547,133 | 0 | 432,022 | 2,490,742 | 34,982 | 7,330 | 0 | 0 | 0 | 0 | 0 | | 2 | 2009-12-07 | 517,261 | 0 | 416,284 | 2,404,622 | 33,956 | 7,192 | 0 | 0 | 0 | 0 | 0 | | 1 | 2009-10-28 | 440,055 | 0 | 329,250 | 1,936,969 | 26,299 | 5,694 | 0 | 0 | 0 | 0 | 0 |

Or, as a chart:

👐 Contributing

Contributions, whether filing an issue, making a pull request, or forking, are appreciated. See CONTRIBUTING.md for more information on getting involved.

👋 Attribution

⚖️ License

The code in this package is licensed under the MIT License.

📖 Citation

Improving reproducibility of cheminformatics workflows with chembl-downloader Hoyt, C.T. (2025) arXiv, 2507.17783

bibtex @article{hoyt2025chembl, title={Improving reproducibility of cheminformatics workflows with chembl-downloader}, author={Charles Tapley Hoyt}, year={2025}, eprint={2507.17783}, archivePrefix={arXiv}, primaryClass={q-bio.QM}, doi={https://doi.org/10.48550/arXiv.2507.17783} url={https://arxiv.org/abs/2507.17783}, }

🍪 Cookiecutter

This package was created with @audreyfeldroy's cookiecutter package using @cthoyt's cookiecutter-snekpack template.

🛠️ For Developers

See developer instructions

The final section of the README is for if you want to get involved by making a code contribution. ### Development Installation To install in development mode, use the following: ```console $ git clone git+https://github.com/cthoyt/chembl-downloader.git $ cd chembl-downloader $ uv pip install -e . ``` Alternatively, install using pip: ```console $ python3 -m pip install -e . ``` ### Updating Package Boilerplate This project uses `cruft` to keep boilerplate (i.e., configuration, contribution guidelines, documentation configuration) up-to-date with the upstream cookiecutter package. Install cruft with either `uv tool install cruft` or `python3 -m pip install cruft` then run: ```console $ cruft update ``` More info on Cruft's update command is available [here](https://github.com/cruft/cruft?tab=readme-ov-file#updating-a-project). ### 🥼 Testing After cloning the repository and installing `tox` with `uv tool install tox --with tox-uv` or `python3 -m pip install tox tox-uv`, the unit tests in the `tests/` folder can be run reproducibly with: ```console $ tox -e py ``` Additionally, these tests are automatically re-run with each commit in a [GitHub Action](https://github.com/cthoyt/chembl-downloader/actions?query=workflow%3ATests). ### 📖 Building the Documentation The documentation can be built locally using the following: ```console $ git clone git+https://github.com/cthoyt/chembl-downloader.git $ cd chembl-downloader $ tox -e docs $ open docs/build/html/index.html ``` The documentation automatically installs the package as well as the `docs` extra specified in the [`pyproject.toml`](pyproject.toml). `sphinx` plugins like `texext` can be added there. Additionally, they need to be added to the `extensions` list in [`docs/source/conf.py`](docs/source/conf.py). The documentation can be deployed to [ReadTheDocs](https://readthedocs.io) using [this guide](https://docs.readthedocs.io/en/stable/intro/import-guide.html). The [`.readthedocs.yml`](.readthedocs.yml) YAML file contains all the configuration you'll need. You can also set up continuous integration on GitHub to check not only that Sphinx can build the documentation in an isolated environment (i.e., with `tox -e docs-test`) but also that [ReadTheDocs can build it too](https://docs.readthedocs.io/en/stable/pull-requests.html). #### Configuring ReadTheDocs 1. Log in to ReadTheDocs with your GitHub account to install the integration at https://readthedocs.org/accounts/login/?next=/dashboard/ 2. Import your project by navigating to https://readthedocs.org/dashboard/import then clicking the plus icon next to your repository 3. You can rename the repository on the next screen using a more stylized name (i.e., with spaces and capital letters) 4. Click next, and you're good to go! ### 📦 Making a Release #### Configuring Zenodo [Zenodo](https://zenodo.org) is a long-term archival system that assigns a DOI to each release of your package. 1. Log in to Zenodo via GitHub with this link: https://zenodo.org/oauth/login/github/?next=%2F. This brings you to a page that lists all of your organizations and asks you to approve installing the Zenodo app on GitHub. Click "grant" next to any organizations you want to enable the integration for, then click the big green "approve" button. This step only needs to be done once. 2. Navigate to https://zenodo.org/account/settings/github/, which lists all of your GitHub repositories (both in your username and any organizations you enabled). Click the on/off toggle for any relevant repositories. When you make a new repository, you'll have to come back to this After these steps, you're ready to go! After you make "release" on GitHub (steps for this are below), you can navigate to https://zenodo.org/account/settings/github/repository/cthoyt/chembl-downloader to see the DOI for the release and link to the Zenodo record for it. #### Registering with the Python Package Index (PyPI) You only have to do the following steps once. 1. Register for an account on the [Python Package Index (PyPI)](https://pypi.org/account/register) 2. Navigate to https://pypi.org/manage/account and make sure you have verified your email address. A verification email might not have been sent by default, so you might have to click the "options" dropdown next to your address to get to the "re-send verification email" button 3. 2-Factor authentication is required for PyPI since the end of 2023 (see this [blog post from PyPI](https://blog.pypi.org/posts/2023-05-25-securing-pypi-with-2fa/)). This means you have to first issue account recovery codes, then set up 2-factor authentication 4. Issue an API token from https://pypi.org/manage/account/token #### Configuring your machine's connection to PyPI You have to do the following steps once per machine. ```console $ uv tool install keyring $ keyring set https://upload.pypi.org/legacy/ __token__ $ keyring set https://test.pypi.org/legacy/ __token__ ``` Note that this deprecates previous workflows using `.pypirc`. #### Uploading to PyPI After installing the package in development mode and installing `tox` with `uv tool install tox --with tox-uv` or `python3 -m pip install tox tox-uv`, run the following from the console: ```console $ tox -e finish ``` This script does the following: 1. Uses [bump-my-version](https://github.com/callowayproject/bump-my-version) to switch the version number in the `pyproject.toml`, `CITATION.cff`, `src/chembl_downloader/version.py`, and [`docs/source/conf.py`](docs/source/conf.py) to not have the `-dev` suffix 2. Packages the code in both a tar archive and a wheel using [`uv build`](https://docs.astral.sh/uv/guides/publish/#building-your-package) 3. Uploads to PyPI using [`uv publish`](https://docs.astral.sh/uv/guides/publish/#publishing-your-package). 4. Push to GitHub. You'll need to make a release going with the commit where the version was bumped. 5. Bump the version to the next patch. If you made big changes and want to bump the version by minor, you can use `tox -e bumpversion -- minor` after. #### Releasing on GitHub 1. Navigate to https://github.com/cthoyt/chembl-downloader/releases/new to draft a new release 2. Click the "Choose a Tag" dropdown and select the tag corresponding to the release you just made 3. Click the "Generate Release Notes" button to get a quick outline of recent changes. Modify the title and description as you see fit 4. Click the big green "Publish Release" button This will trigger Zenodo to assign a DOI to your release as well.