[SUBMISSION] ChemInformant – Python client for PubChem

[HzaCode]

Submitting Author: Zhiang He (@HzaCode)
All current maintainers: Zhiang He (@HzaCode)
Package Name: ChemInformant
One-Line Description of Package: A robust, high-throughput Python client for retrieving chemical information from the PubChem API; it returns analysis-ready Pandas/SQL outputs, handles caching, rate-limiting and retries, and includes convenient CLI tools.
Repository Link: https://github.com/HzaCode/ChemInformant
Version submitted: 2.4.0 (released 2025-07-30)
EiC: TBD
Editor: TBD
Reviewer 1: TBD
Reviewer 2: TBD
Archive: TBD
JOSS DOI: TBD
Version accepted: TBD
Date accepted (month/day/year): TBD

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• I agree to abide by pyOpenSci's Code of Conduct during the review process and in future interactions in spaces supported by pyOpenSci should it be accepted.
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Description

ChemInformant is a workflow-centric Python client for the PubChem REST API.
It transforms raw API responses into clean Pandas DataFrames or direct SQL tables, supports mixed identifiers (CIDs, names, SMILES), provides persistent on-disk caching, automatic rate-limiting and retries, and exposes both an object-oriented API and terminal-ready CLI tools (chemfetch, chemdraw).
The library leverages Pydantic v2 for runtime data validation and integrates seamlessly into machine-learning or QSAR pipelines that require large-scale descriptor retrieval.

Scope

• Data retrieval
• Data extraction
• Data processing/munging
• Data deposition
• Data validation and testing
• Data visualization[^1]
• Workflow automation
• Citation management and bibliometrics
• Scientific software wrappers
• Database interoperability

Domain Specific

• Geospatial
• Education

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Scope Explanation

• Target audience & applications: Computational chemists, cheminformatics researchers, drug-discovery scientists and data-science practitioners who require reliable, programmatic access to PubChem for large-scale descriptor retrieval and downstream ML/QSAR workflows.
• Comparison to similar packages: Existing clients such as PubChemPy or ChemSpiPy lack built-in caching, mixed-identifier handling and robust fault-tolerance; in benchmarks, ChemInformant achieves up to a 48× speed-up versus PubChemPy through batched queries and cache reuse.
• Pre-submission enquiry: None.

Technical checks

This package:

• does not violate the Terms of Service of any service it interacts with.
• uses an OSI approved license (MIT).
• contains a README with instructions for installing the development version.
• includes documentation with examples for all functions.
• contains a tutorial with examples of its essential functions and uses.
• has a test suite (pytest) located in tests/.
• has continuous integration setup via GitHub Actions.

Publication Options

• Do you wish to automatically submit to the [Journal of Open Source Software][JournalOfOpenSourceSoftware]?

  ChemInformant has been accepted by JOSS
  ([REVIEW]: ChemInformant: A Modern, Lightweight Python Client for PubChem with Robust Caching and Validation openjournals/joss-reviews#8341).

  I would be grateful if pyOpenSci could adopt the JOSS → pyOpenSci fast-track pathway so that a second full technical review is not required.

  Please let me know if any additional information or metadata would be helpful—thank you very much for your time and consideration.

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• I expect to maintain this package for at least 2 years and can help find a replacement for the maintainer (team) if needed.

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[eliotwrobson]

@HzaCode thanks for your submission! I'm the current EiC, just giving a heads up that we've seen this and will be giving a heads up on next steps soon 👍🏽

[HzaCode]

Thanks for letting me know! I'm really looking forward to the process and hope to contribute to the pyOpenSci community. 💪

[HzaCode]

Hi @eliotwrobson,

Just a quick update — my JOSS paper on this project has now been accepted. I’m looking forward to the pyOpenSci process as well — are there any next steps or timelines you could share? Thanks!