tensor-grep
High-performance grep-compatible CLI with Rust, GPU, and AST/NLP routing
Decision gist · record as of 2026-08-14
Yes, with conditions. The package is actively maintained, has no known vulnerabilities, and offers genuine performance advantages via Rust and GPU support. However, verify the license terms before use—the metadata does not clarify licensing. Install friction is moderate due to compiled bindings, but wheels are available for common platforms. Best suited for developers who need faster search and can require Python 3.11+.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.11 or later.
- Precompiled wheels available for macOS ARM64, Linux x86_64, and Windows; other platforms may require building from source.
- Medium install friction due to compiled Rust bindings (wheels provided for macOS ARM64, Linux x86_64, and Windows).
License · maintenance · safety
(unclear) — License status is unclear—no SPDX identifier or raw license text is available in the package metadata. Verify the actual license terms before use in proprietary or restricted contexts.
last release 2026-08-13 (1 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 271,898 downloads/mo, #8,216 on PyPI
Alternatives
Verify before relying
pip install tensor-grep
from tensor_grep import search
results = search(pattern='example', path='.')- Whether GPU acceleration requires additional system libraries or CUDA/ROCm installation.
- What AST/NLP routing strategies are supported and how they affect search performance.
- Whether the tool maintains full grep command-line compatibility or implements a subset.
- How the package handles very large files or directory trees in practice.
What it is and what it does
tensor-grep is a command-line search utility that reimplements grep functionality with a Rust core for speed and optional GPU acceleration. It is designed to be grep-compatible while adding intelligent routing via AST and NLP analysis to optimize search strategies. The package exposes Rust bindings through pyo3 and depends on typer and rich for CLI presentation, plus cryptography and opentelemetry-api for security and observability.
The tool targets developers and system administrators who need faster text search than traditional grep, particularly when searching large codebases or when GPU acceleration is available. It is actively maintained and released frequently, though its license terms are not yet clarified in the package metadata.
Use it for
- Search large codebases faster than grep by leveraging Rust performance and GPU acceleration.
- Use AST-aware routing to optimize pattern matching in source code with semantic understanding.
- Integrate into CI/CD pipelines where search speed directly impacts build time.
- Perform NLP-guided searches when text content requires linguistic analysis beyond regex.
- Replace grep in shell scripts where performance is a bottleneck.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, with conditions.
The package is actively maintained, has no known vulnerabilities, and offers genuine performance advantages via Rust and GPU support. However, verify the license terms before use—the metadata does not clarify licensing. Install friction is moderate due to compiled bindings, but wheels are available for common platforms. Best suited for developers who need faster search and can require Python 3.11+.
Install
tensor-grep on PyPI
Before you install
Medium install friction due to compiled Rust bindings (wheels provided for macOS ARM64, Linux x86_64, and Windows). Active maintenance with a release 1 day old. Eight runtime dependencies including typer, rich, and cryptography add moderate complexity.
Requires Python 3.11 or later. Precompiled wheels available for macOS ARM64, Linux x86_64, and Windows; other platforms may require building from source.
License in practice
License status is unclear—no SPDX identifier or raw license text is available in the package metadata. Verify the actual license terms before use in proprietary or restricted contexts.
Quickstart
pip install tensor-grep
from tensor_grep import search
results = search(pattern='example', path='.')Verify before relying
- Whether GPU acceleration requires additional system libraries or CUDA/ROCm installation.
- What AST/NLP routing strategies are supported and how they affect search performance.
- Whether the tool maintains full grep command-line compatibility or implements a subset.
- How the package handles very large files or directory trees in practice.
Package facts
| License | Not declared unclear |
| Python support | Supports the current Python release >=3.11 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 8 packagestyperrichmcppathspecpyyamlopentelemetry-apiimportlib-metadatacryptography |
| Maintenance | Actively maintained 1 days since the last release |
| First released | |
| Downloads | 271,898 / month, #8,216 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: tensor_grep-1.110.16-cp311-abi3-macosx_11_0_arm64.whl; tensor_grep-1.110.16-cp311-abi3-manylinux_2_39_x86_64.whl; tensor_grep-1.110.16-cp311-abi3-win_amd64.whl
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