# TACO CLI interface for Tensora
This Python package provides a Python wrapper around the CLI tool of the [Tensor Algebra Compiler](http://tensor-compiler.org/) (TACO). This package exists to support the `tensora[taco]` extra of [Tensora](https://tensora.drhagen.com). The main [`tensora`](https://github.com/drhagen/tensora) package is pure Python, and including TACO by default would complicate its distribution.
The `tensora-taco` Python package contains one function `taco_cli` that takes the `taco` CLI arguments of as a list of strings, and returns a [`Result`](https://returns.readthedocs.io/en/latest/pages/result.html).
```python
from tensora_taco import taco_cli
result = taco_cli(["y(i) = A(i,j) * x(j)", "-print-nocolor", "-print-compute"])
kernel = result.unwrap()
# // Generated by the Tensor Algebra Compiler (tensor-compiler.org)
#
# int compute(taco_tensor_t *y, taco_tensor_t *A, taco_tensor_t *x) {
# int y1_dimension = (int)(y->dimensions[0]);
# double* restrict y_vals = (double*)(y->vals);
# int A1_dimension = (int)(A->dimensions[0]);
# int A2_dimension = (int)(A->dimensions[1]);
# double* restrict A_vals = (double*)(A->vals);
# int x1_dimension = (int)(x->dimensions[0]);
# double* restrict x_vals = (double*)(x->vals);
#
# #pragma omp parallel for schedule(runtime)
# for (int32_t i = 0; i < A1_dimension; i++) {
# double tjy_val = 0.0;
# for (int32_t j = 0; j < x1_dimension; j++) {
# int32_t jA = i * A2_dimension + j;
# tjy_val += A_vals[jA] * x_vals[j];
# }
# y_vals[i] = tjy_val;
# }
# return 0;
# }
```
## Contributing
`tensora-taco` is a free and open source project developed under an MIT license. Development occurs at the [GitHub project](https://github.com/drhagen/tensora-taco).
### Cloning the repo
To make a local copy of `tensora-taco`, clone the repository with git. This project depends on TACO at build time as a submodule, so it must be cloned as well in order to build the project:
```shell
git clone --recurse-submodules https://github.com/drhagen/tabeline.git
```
### Installing from source
`tensora-taco` uses Poetry as its packaging and dependency manager. In whatever Python environment you prefer, [install Poetry](https://python-poetry.org/docs/) and then use Poetry to install this package and its dependencies:
```shell
pip install poetry
poetry install
```
### Testing
`tensora-taco` uses pytest to run the tests in the `tests/` directory. The test command is encapsulated with Nox:
```shell
poetry run nox -s test
```
This will try to test with all compatible Python versions that `nox` can find. To run the tests with only a particular version, run something like this:
```shell
poetry run nox -s test-3.11
```
It is good to run the tests locally before making a PR, but it is not necessary to have all Python versions run. It is rare for a failure to appear in a single version, and the CI will catch it anyway.
### Code quality
`tensora-taco` uses Ruff to ensure a minimum standard of code quality. The code quality commands are encapsulated with Nox:
```shell
poetry run nox -s ruff
```
### Making a release
1. Bump
1. Increment version in `pyproject.toml`
2. Commit with message "Bump version number to X.Y.Z"
3. Push commit to GitHub
4. Check [CI](https://github.com/drhagen/tensora-taco/actions/workflows/ci.yml) to ensure all tests pass
2. Tag
1. Tag commit with "vX.Y.Z"
2. Push tag to GitHub
3. Wait for [build](https://github.com/drhagen/tensora-taco/actions/workflows/release.yml) to finish
4. Check [PyPI](https://pypi.org/project/tensora-taco/) for good upload
3. Document
1. Create [GitHub release](https://github.com/drhagen/tensora-taco/releases) with name "Tensora TACO X.Y.Z" and major changes in body
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"description": "# TACO CLI interface for Tensora\n\nThis Python package provides a Python wrapper around the CLI tool of the [Tensor Algebra Compiler](http://tensor-compiler.org/) (TACO). This package exists to support the `tensora[taco]` extra of [Tensora](https://tensora.drhagen.com). The main [`tensora`](https://github.com/drhagen/tensora) package is pure Python, and including TACO by default would complicate its distribution.\n\nThe `tensora-taco` Python package contains one function `taco_cli` that takes the `taco` CLI arguments of as a list of strings, and returns a [`Result`](https://returns.readthedocs.io/en/latest/pages/result.html).\n\n```python\nfrom tensora_taco import taco_cli\n\nresult = taco_cli([\"y(i) = A(i,j) * x(j)\", \"-print-nocolor\", \"-print-compute\"])\n\nkernel = result.unwrap()\n# // Generated by the Tensor Algebra Compiler (tensor-compiler.org)\n#\n# int compute(taco_tensor_t *y, taco_tensor_t *A, taco_tensor_t *x) {\n# int y1_dimension = (int)(y->dimensions[0]);\n# double* restrict y_vals = (double*)(y->vals);\n# int A1_dimension = (int)(A->dimensions[0]);\n# int A2_dimension = (int)(A->dimensions[1]);\n# double* restrict A_vals = (double*)(A->vals);\n# int x1_dimension = (int)(x->dimensions[0]);\n# double* restrict x_vals = (double*)(x->vals);\n#\n# #pragma omp parallel for schedule(runtime)\n# for (int32_t i = 0; i < A1_dimension; i++) {\n# double tjy_val = 0.0;\n# for (int32_t j = 0; j < x1_dimension; j++) {\n# int32_t jA = i * A2_dimension + j;\n# tjy_val += A_vals[jA] * x_vals[j];\n# }\n# y_vals[i] = tjy_val;\n# }\n# return 0;\n# }\n```\n\n## Contributing\n\n`tensora-taco` is a free and open source project developed under an MIT license. Development occurs at the [GitHub project](https://github.com/drhagen/tensora-taco).\n\n### Cloning the repo\n\nTo make a local copy of `tensora-taco`, clone the repository with git. This project depends on TACO at build time as a submodule, so it must be cloned as well in order to build the project:\n\n```shell\ngit clone --recurse-submodules https://github.com/drhagen/tabeline.git\n```\n\n### Installing from source\n\n`tensora-taco` uses Poetry as its packaging and dependency manager. In whatever Python environment you prefer, [install Poetry](https://python-poetry.org/docs/) and then use Poetry to install this package and its dependencies:\n\n```shell\npip install poetry\npoetry install\n```\n\n### Testing\n\n`tensora-taco` uses pytest to run the tests in the `tests/` directory. The test command is encapsulated with Nox:\n\n```shell\npoetry run nox -s test\n```\n\nThis will try to test with all compatible Python versions that `nox` can find. To run the tests with only a particular version, run something like this:\n\n```shell\npoetry run nox -s test-3.11\n```\n\nIt is good to run the tests locally before making a PR, but it is not necessary to have all Python versions run. It is rare for a failure to appear in a single version, and the CI will catch it anyway.\n\n\n### Code quality\n\n`tensora-taco` uses Ruff to ensure a minimum standard of code quality. The code quality commands are encapsulated with Nox:\n\n```shell\npoetry run nox -s ruff\n```\n\n### Making a release\n\n1. Bump\n 1. Increment version in `pyproject.toml`\n 2. Commit with message \"Bump version number to X.Y.Z\"\n 3. Push commit to GitHub\n 4. Check [CI](https://github.com/drhagen/tensora-taco/actions/workflows/ci.yml) to ensure all tests pass\n2. Tag\n 1. Tag commit with \"vX.Y.Z\"\n 2. Push tag to GitHub\n 3. Wait for [build](https://github.com/drhagen/tensora-taco/actions/workflows/release.yml) to finish\n 4. Check [PyPI](https://pypi.org/project/tensora-taco/) for good upload\n3. Document\n 1. Create [GitHub release](https://github.com/drhagen/tensora-taco/releases) with name \"Tensora TACO X.Y.Z\" and major changes in body\n\n",
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