chematic
GitHub

Beginner · 5–15 min

Tutorials

Learn chematic by building small, useful chemistry tools. Each tutorial has a clear starting point, runnable code, and a next step.

Browser

Analyze your first molecule

Parse a SMILES string and inspect its 2D structure and basic properties without a backend.

What you will makeA local molecule analysis pageNext stepTry the browser demo
Steps
  1. Open the browser demo.
  2. Enter CCO, the SMILES for ethanol, then run the analysis.
  3. Compare the structure drawing with the molecular formula and molecular weight.

CheckYou should see a 2D structure and descriptor values for ethanol.

If it does not workIf the structure is blank, check that the input is valid SMILES and try CCO again.

CCO
Open guide

Python

Use chematic from Python

Install the package, parse a molecule, and use the same core in a notebook.

What you will makeA first notebook cellNext stepRead the Python guide
Steps
  1. Create a virtual environment and install chematic.
  2. Import the package and parse CCO.
  3. Print the molecule or one descriptor to confirm the call completed.

CheckThe notebook returns a molecule object without sending the structure to a server.

If it does not workActivate the environment before installing, and check the package name if the import is not found.

mol = chematic.parse_smiles("CCO")
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Python

Find similar molecules

Create fingerprints and compare molecules with Tanimoto similarity.

What you will makeA small similarity searchNext stepRead the API cookbook
Steps
  1. Parse a query molecule and two candidates.
  2. Generate the same fingerprint type for each molecule.
  3. Calculate Tanimoto similarity and sort the candidates.

CheckThe identical molecule scores 1.0; less similar structures score lower.

If it does not workUse the same fingerprint settings for every molecule before comparing scores.

mol.ecfp4()
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Python

Process a structure file

Move from one molecule to a CSV or SDF batch workflow with local, repeatable output.

What you will makeA batch analysis scriptNext stepRead the batch guide
Steps
  1. Prepare a file with one SMILES value per row.
  2. Parse each row and calculate the selected properties.
  3. Write results together with the original input and any parse error.

CheckThe output has one traceable result per input row, including invalid rows.

If it does not workDo not discard the original string; it makes failed rows easy to inspect and retry.

for smiles in rows:
Open guide

Rust

Build a native Rust tool

Add chematic to a Rust project and keep parsing and chemistry logic in one process.

What you will makeA Rust CLI or service foundationNext stepRead the Rust guide
Steps
  1. Create a small binary crate and add the required features.
  2. Parse one known SMILES in main.
  3. Return a clear error for invalid input before adding batch behavior.

CheckThe binary builds locally and produces a deterministic result for the same input.

If it does not workStart with only the features you need if compile time or binary size matters.

cargo add chematic --features "smiles,perception,chem,3d,fp"
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AI agents

Connect a local AI agent

Run the local stdio MCP server and expose structured chemistry operations to an AI client.

What you will makeA local chemistry tool connectionNext stepRead the MCP guide
Steps
  1. Build or install the MCP server locally.
  2. Register the stdio command in your AI client.
  3. Ask the client to parse a test SMILES and inspect the returned structured data.

CheckThe client can call a chemistry tool and receive a structured response without a network service.

If it does not workCheck the executable path and keep the server command free of interactive prompts.

cargo run -p chematic-mcp --release
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Check feature maturity

Validation / 検証