Support Instantiation, Linting and GitHub CI (#1)

* Instantiate backends

* Add tox and CI

* Update CI and README

.github/workflows/python-tox.yml

@@ -0,0 +1,52 @@
+name: tox
+
+on: [
+  push,
+  pull_request,
+]
+
+jobs:
+  build:
+
+    runs-on: ${{ matrix.os }}
+    strategy:
+      matrix:
+        os: [
+          ubuntu-latest,
+          macos-latest,
+          windows-latest,
+        ]
+
+    steps:
+      - uses: actions/checkout@v4
+      - name: Setup Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.12"
+          cache: "pip"
+      - name: Install dependencies
+        run: pip install -r requirements.txt
+      - name: Install package
+        run: pip install -e .
+
+  test:
+
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python: [
+          "3.10",
+          "3.12",
+        ]
+
+    steps:
+      - uses: actions/checkout@v4
+      - name: Setup Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python }}
+          cache: "pip"
+      - name: Install tox
+        run: pip install tox
+      - name: Run tox
+        run: tox

CHANGELOG.md

@@ -1,6 +1,17 @@
 # Changelog
 
-## 2027/08/09 - 00 - v0.0.7 - Update Callback
+## 2024/10/14 - 00 - v0.0.8 - Instantiation and GitHub CI
+* Instantiated backends and solvers with different numerical libraries:
+    * Added `context_manager` modules to `quantrl.backends` and `quantrl.solvers` packages.
+    * Added support for JIT-compilation in `quantrl.backends` package.
+    * Changed naming convention for GPU-based options as `gpu` from `cuda`.
+* Added `tox`-based testing and continuous integration with GitHub workflows.
+* Updated all modules with PEP-based code styling and added `pylintrc`.
+* Updated `requirements.txt` and added version to `quantrl.__init__`.
+* Replaced `setup.py` with `pyproject.toml`.
+* Updated `docs` and `README`.
+
+## 2024/08/09 - 00 - v0.0.7 - Update Callback
 * Fixed issue with cache indexing in `quantrl.envs.base` module.
 * Updated best reward callback in `quantrl.utils` module.
 * Added `seaborn` to `requirements` and `setup`.

README.md

@@ -1,6 +1,6 @@
 # QuantRL: Quantum Control using Reinforcement Learning
 
-![Latest Version](https://img.shields.io/badge/version-0.0.7-red?style=for-the-badge)
+![Latest Version](https://img.shields.io/badge/version-0.0.8-red?style=for-the-badge)
 
 > A library of modules to interface deterministic and stochastic quantum models for reinforcement learning.
 
@@ -30,7 +30,7 @@ The toolbox primarily relies on `gymnasium` (for single environments) and `stabl
 All of its dependencies can be installed using:
 
 ```bash
-conda install "numpy<2.0.0" scipy matplotlib tqdm gymnasium stable-baselines3
+conda install "numpy<2.0.0" scipy matplotlib tqdm pillow pandas gymnasium stable-baselines3
 ```
 
 Additionally, to avail the PyTorch or JAX backends, the latest version of these framework (for both CPU and GPU) should be installed (preferably in different `conda` environments) using in their official documentations: [PyTorch docs](https://pytorch.org/get-started/locally/) and [JAX docs](https://jax.readthedocs.io/en/latest/installation.html).
@@ -43,14 +43,16 @@ pip install torchdiffeq
 or,
 
 ```bash
+pip install jax
 pip install diffrax
 ```
 
+To install JAX with GPU support, use `jax[cuda12]`.
+
 ***Note: JAX-GPU support for Windows and MacOS is still limited but it runs well in WSL2.***
 
-Finally, to install the latest version of `quantrl` locally, download the repository as `.zip` and extract the contents, or clone the repository.
-Now, execute the following from *outside* the top-level directory, `ROOT_DIR`, inside which `setup.py` is located as:
+Finally, to install the latest version of `quantrl`, execute:
 
 ```bash
-pip install -e ROOT_DIR
-```
+pip install git+https://github.com/sampreet/quantrl.git
+```

docs/source/quantrl.backends.rst

@@ -10,6 +10,15 @@ quantrl.backends.base module
    :undoc-members:
    :show-inheritance:
 
+quantrl.backends.context_manager module
+---------------------------------------
+
+.. automodule:: quantrl.backends.context_manager
+   :members:
+   :private-members:
+   :undoc-members:
+   :show-inheritance:
+
 quantrl.backends.jax module
 ---------------------------
 

docs/source/quantrl.solvers.rst

@@ -10,6 +10,15 @@ quantrl.solvers.base module
    :undoc-members:
    :show-inheritance:
 
+quantrl.backends.context_manager module
+---------------------------------------
+
+.. automodule:: quantrl.backends.context_manager
+   :members:
+   :private-members:
+   :undoc-members:
+   :show-inheritance:
+
 quantrl.solvers.jax module
 --------------------------
 

pylintrc

@@ -0,0 +1,26 @@
+[MESSAGES CONTROL]
+disable=too-many-lines,
+        too-many-locals,
+        too-many-arguments,
+        too-many-statements,
+        too-few-public-methods,
+        too-many-public-methods,
+        too-many-instance-attributes,
+        too-many-positional-arguments,
+        line-too-long,                  # no bounded lines
+        redefined-builtin,              # catches __name__
+        duplicate-code,                 # catches __init__
+        unused-argument,                # catches Gym.Env methods
+        import-outside-toplevel,        # for numerical libraries
+        not-callable,                   # catches JAX JIT functions
+        fixme
+
+[BASIC]
+attr-naming-style=any
+variable-naming-style=any
+argument-naming-style=any
+const-naming-style=UPPER_CASE
+method-naming-style=any
+function-naming-style=any
+class-naming-style=PascalCase
+class-attribute-naming-style=snake_case

pyproject.toml

@@ -0,0 +1,87 @@
+[build-system]
+requires = ["cython", "setuptools>=61", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+dynamic = ["version"]
+name = "quantrl"
+authors = [
+    {name = "Sampreet Kalita", email = "9553215+Sampreet@users.noreply.github.com"},
+]
+maintainers = [
+    {name = "Sampreet Kalita", email = "9553215+Sampreet@users.noreply.github.com"},
+]
+description = "Quantum Control with Reinforcement Learning"
+keywords = [
+    "quantum",
+    "toolbox",
+    "reinforcement learning",
+    "python3",
+]
+readme = "README.md"
+license = {file = "LICENSE"}
+requires-python = ">=3.10"
+dependencies = [
+    "numpy<2.0.0",
+    "scipy",
+    "matplotlib",
+    "tqdm",
+    "pillow",
+    "pandas",
+    "gymnasium",
+    "stable-baselines3",
+]
+classifiers = [
+    "Programming Language :: Python :: 3",
+    "Development Status :: 2 - Pre-Alpha",
+    "Intended Audience :: Science/Research",
+    "License :: OSI Approved :: BSD License",
+    "Operating System :: OS Independent",
+    "Topic :: Scientific/Engineering",
+]
+
+[project.optional-dependencies]
+jax-cpu = [
+    "jax",
+    "diffrax",
+]
+jax-gpu = [
+    "jax[cuda12]",
+    "diffrax",
+]
+torch = [
+    "torch",
+    "torchvision",
+    "torchaudio",
+    "torchdiffeq",
+]
+
+[project.urls]
+Homepage = "https://github.com/sampreet/quantrl"
+Repository = "https://github.com/sampreet/quantrl"
+Issues = "https://github.com/sampreet/quantrl/issues"
+Changelog = "https://github.com/sampreet/quantrl/blob/master/CHANGELOG.md"
+
+[tool.setuptools.packages.find]
+include = ["quantrl"]
+namespaces = false
+
+[tool.setuptools.dynamic]
+version = {attr = "quantrl.__version__"}
+
+[tool.tox]
+legacy_tox_ini = """
+[tox]
+requires =
+    tox>=4
+    virtualenv>=20
+env_list =
+    lint
+
+[testenv:lint]
+description = run pylint under {base_python}
+deps =
+    -r requirements_tox.txt
+commands =
+    pylint quantrl
+"""

quantrl/__init__.py

@@ -0,0 +1,2 @@
+"""Module to initialize QuantRL."""
+__version__ = "0.0.8"