Learn Tessero
From your first array to optimisation and Markov decision processes, a path for every level, plus a NumPy/SciPy → Tessero cheatsheet.
Start here
- Install, pick a backend (FFI, native extension, or Laravel).
- Getting started, create your first
NDArrayand run it.
Coming from NumPy or SciPy?
Tessero mirrors the NumPy and SciPy APIs and matches them exactly: full, verified parity against SciPy and the NumPy core, generated from recorded test runs rather than self-reported. The coverage & translation reference maps the functions you already know to their Tessero equivalents, your cheatsheet for porting Python code to PHP. Porting is safe: one C kernel drives both backends so results never diverge, and an independent BCMath oracle cross-checks the core math.
The guided path
Work through the user guide, roughly beginner → advanced:
- Arrays
- Indexing and slicing
- Maths, reductions, sorting
- Universal functions
- Linear algebra
- FFT
- Random numbers
- Statistics and special functions
- Sparse matrices
- Optimisation
- Linear programming
- Markov decision processes
- Input and output
- Memory-mapped arrays
- Laravel
Learn by example
Every snippet shows its expected output: browse the examples and the Laravel examples.
Go deeper
- API reference, every class, method and signature.
- Performance, BLAS-class matmul benchmarks, measured and reproducible.
- Operations manual, deployment, performance tuning, memory & threads.
- Honest exclusions, the non-numeric and non-deterministic symbols transparently left out.
Community tutorials
Written a tutorial or recorded a video about Tessero? Add it to the showcase or get in touch, curated community learning resources will be featured here.