Interact with the Lean theorem prover language server
Project description
leanclient
Interact with the lean4 language server.
Key Features • Quickstart • Currently in Beta • Documentation • Testing • License
leanclient is a thin wrapper around the native Lean language server. It enables interaction with a Lean language server instance running in a subprocess.
Check out the documentation for more information.
Key Features
- Interact: Query and change lean files via the LSP.
- Thin wrapper: Directly expose the Lean Language Server.
- Synchronous: Requests block until a response is received.
- Fast: Typically more than 99% of time is spent waiting.
- Parallel: Easy batch processing of files using all your cores.
Quickstart
The best way to get started is to check out this minimal example in Google Colab:
Or try it locally:
-
Setup a new lean project or use an existing one. See the colab notebook for a basic Ubuntu setup.
-
Install the package:
pip install leanclient
- In your python code:
import leanclient as lc
# Start a new client, point it to your lean project root (where lakefile.toml is located).
PROJECT_PATH = "path/to/your/lean/project/root/"
client = lc.LeanLSPClient(PROJECT_PATH)
# Query a lean file in your project
file_path = "MyProject/Basic.lean"
result = client.get_goal(file_path, line=1, character=2)
print(result)
# Use a SingleFileClient for simplified interaction with a single file.
sfc = client.create_file_client(file_path)
result = sfc.get_term_goal(line=1, character=2)
print(result)
# Use a LeanClientPool for easy parallel processing multiple files.
files = ["MyProject/Basic.lean", "Main.lean"]
# Define a function that takes a SingleFileClient as its only parameter.
def count_tokens(client: lc.SingleFileClient):
return len(client.get_semantic_tokens())
with lc.LeanClientPool(PROJECT_PATH, num_workers=8) as pool:
results = pool.map(count_tokens, files)
# Or use pool.submit() for increased control.
futures = [pool.submit(count_tokens, path) for path in files]
res_fut = [f.get() for f in futures]
print(results)
Currently in Beta
- Missing features.
- Needs more testing with different setups.
- Any feedback is appreciated!
Next Features
- Documentation: Real examples
Potential Features
- Use document versions to handle evolving file states
- Automatic lean env setup for non Debian-based systems
- Parallel implementation (multiple requests in-flight) like multilspy
- Allow interaction before
waitForDiagnosticsreturns
Missing LSP Interactions
Might be implemented in the future:
workspace/symbol,workspace/didChangeWatchedFiles,workspace/applyEdit, ...textDocument/codeActiontextDocument/prepareRename,textDocument/rename
Internal Lean methods:
$/lean/ileanInfoUpdate,$/lean/ileanInfoFinal,$/lean/importClosure,$/lean/staleDependency$/lean/rpc/connect,$/lean/rpc/call,$/lean/rpc/release,$/lean/rpc/keepAlive
Documentation
Read the documentation at leanclient.readthedocs.io.
Run make docs to build the documentation locally.
Testing
# python3 -m venv venv # Or similar: Create environment
make install # Installs python package and dev dependencies
make test # Run all tests, also installs fresh lean env if not found
make test-profile # Run all tests with cProfile
License
MIT
Citing this repository is highly appreciated but not required by the license.
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