Overview

Symbolica documentation for getting started, symbolic expressions, numerical evaluation, pattern matching, and APIs in Python and Rust.

`Spenso`

A comprehensive Python tensor library for symbolic and numerical tensor computations, with a focus on physics applications.

The Spenso Python API provides powerful tools for:

Tensor Algebra: Dense and sparse tensors with flexible data types
Symbolic Computation: Integration with Symbolica for tensors with symbolic expressions
Network Operations: Tensor networks for optimized computation graphs
Physics Applications: Built-in support for HEP tensors (gamma matrices, color structures, etc.)
Performance: Compiled evaluators for high-speed numerical computation

`CompiledTensorEvaluator`	A compiled and optimized evaluator for maximum performance tensor evaluation
`ExecutionMode`	Execution modes for tensor network evaluation
`LibraryTensor`	A library tensor class optimized for use in tensor libraries and networks.
`Representation`	A representation in the sense of group representation theory for tensor indices.
`Slot`	A tensor index slot combining a representation with an abstract index
`SymbolicParallelism`	Policy for Rayon operations that manipulate Symbolica expressions.
`Tensor`	A tensor class that can be either dense or sparse with flexible data types
`TensorEvaluator`	An optimized evaluator for symbolic tensor expressions
`TensorFunctionLibrary`
`TensorIndices`	A tensor structure with abstract indices for symbolic tensor operations
`TensorLibrary`	A library for registering and managing tensor templates and structures.
`TensorName`	A symbolic name for tensor functions and structures
`TensorNamespace`	Enumeration for different tensor namespaces in physics
`TensorNetwork`	A tensor network representing computational graphs of tensor operations
`TensorStructure`	A tensor structure without abstract indices, defined purely by representations

set_symbolica_rayon_enabled Configure whether Spenso may use Rayon for Symbolica operations

set_symbolica_rayon_enabled(policy: SymbolicParallelism) -> builtins.bool

Configure whether Spenso may use Rayon for Symbolica operations.

Auto checks the Symbolica license once during this call. Tensor operations subsequently use the cached result without querying the license again.