Gymnasium, Stable Baselines

.github/workflows/test.yml

@@ -2,22 +2,51 @@ name: test
 
 on:
   push:
-    branches: [main, dev]
-
+    branches: ["main"]
   pull_request:
-    branches: [main, dev]
+    branches: ["main"]
 
 jobs:
-  test-setup:
+  test-src:
     runs-on: ubuntu-latest
     steps:
-      - name: Checkout Source Code
-        uses: actions/checkout@v2
+      - uses: actions/checkout@v4
+      - name: python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.11'
+      - name: test
+        run: make test
 
-      - name: Setup Python
-        uses: actions/setup-python@v2
+  test-examples:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - name: python
+        uses: actions/setup-python@v5
         with:
-          python-version: 3.8.10
+          python-version: '3.11'
+      - name: test examples
+        run: make test-examples
 
-      - name: Run Tests
-        run: make test
+  check:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - name: python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.11'
+      - name: check
+        run: make check
+
+  static:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - name: python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.11'
+      - name: static checks
+        run: make static

Makefile

@@ -1,34 +1,31 @@
-.PHONY: test pushs3
-
 setup:
-	pip install -q -r requirements.txt
-	pip install .
-
-test: setup
-	pytest tests -m "not pybox2d" --tb=line --disable-pytest-warnings
+	curl -LsSf https://astral.sh/uv/0.6.3/install.sh | sh
+	uv venv
+	uv sync
 
-test-with-pybox2d:
-	pytest tests --tb=line --disable-pytest-warnings
-
-tensorboard:
-	tensorboard --logdir experiments
+clean:
+	rm -rf ./data/tensorboard/
 
+TB_DIR=./data/tensorboard/
 monitor:
-	jupyter lab
+	uv run tensorboard --logdir $(TB_DIR) --bind_all
+
+setup-test: setup
+	uv sync --group test
 
-pulls3:
-	make pulls3-dataset
-	make pulls3-nem
+test: setup-test
+	# TODO - test coverage up to 100 %
+	uv run pytest tests --tb=short -p no:warnings --disable-warnings --cov=src --cov-report=term-missing --cov-report=html:htmlcov --cov-fail-under=50
 
-pulls3-dataset:
-	aws --no-sign-request --region ap-southeast-2 s3 cp s3://energy-py/public/dataset.zip dataset.zip
-	unzip dataset.zip
+test-examples: setup-test
+	uv run examples/battery.py
+	uv run examples/battery_arbitrage_experiments.py
 
-pulls3-nem:
-	aws --no-sign-request --region ap-southeast-2 s3 cp s3://energy-py/public/nem.zip nem.zip
-	unzip nem.zip; mv nem-data ~
+# TODO - include the tests dir
+SRC_DIRS=src examples
+static: setup-test
+	uv run basedpyright $(SRC_DIRS) --level error
 
-setup-pybox2d-macos:
-	brew install swig
-	git clone https://github.com/pybox2d/pybox2d
-	cd pybox2d_dev; python setup.py build; python setup.py install
+RUFF_ARGS=
+check: setup-test
+	uv run ruff check $(SRC_DIRS) $(RUFF_ARGS)

README.md

@@ -1,72 +1,38 @@
-# energy-py
+# energypy
 
-[![Build Status](https://travis-ci.org/ADGEfficiency/energy-py.svg?branch=master)](https://travis-ci.org/ADGEfficiency/energy-py)
+![Tests](https://github.com/ADGEfficiency/energy-py/actions/workflows/test.yml/badge.svg?branch=main)
 
-energy-py is a framework for running reinforcement learning experiments on energy environments.
+A framework for running reinforcement learning experiments on energy environments - starting with electric battery storage.
 
-The library is focused on electric battery storage, and offers a implementation of a many batteries operating in parallel.
-
-energy-py includes an implementation of the Soft Actor-Critic reinforcement learning agent, implementated in Tensorflow 2:
-
-- test & train episodes based on historical Australian electricity price data,
-- checkpoints & restarts,
-- logging in Tensorboard.
-
-energy-py is built and maintained by Adam Green - adam.green@adgefficiency.com.
+## Features
 
+- Electric battery storage environment for energy arbitrage
+- Integration with [Gymnasium](https://gymnasium.farama.org/) as a custom Gymnasium environment
+- Integration with [Stable Baselines 3](https://stable-baselines3.readthedocs.io/) for reinforcement learning agents
+- Historical electricity price data for realistic training scenarios
+- Experiment framework for training and evaluation on separate datasets
+- Tensorboard logging for experiment tracking
 
 ## Setup
 
-```bash
+```shell-session
 $ make setup
 ```
 
+## Examples
 
-## Test
-
-```bash
-$ make test
-```
-
-
-## Running experiments
-
-`energypy` has a high level API to run a specific run of an experiment from a `JSON` config file.
-
-The most interesting experiment is to run battery storage for price arbitrage in the Australian electricity market.  This requires grabbing some data from S3.  The command below will download a pre-made dataset and unzip it to `./dataset`:
-
-```bash
-$ make pulls3-dataset
-```
-
-You can then run the experiment from a JSON file:
-
-```bash
-$ energypy benchmarks/nem-battery.json
+```shell-session
+$ uv run examples/battery.py
 ```
 
-Results are saved into `./experiments/{env_name}/{run_name}`:
+Or run a more extensive experiment with real electricity price data:
 
-```bash
-$ tree -L 3 experiments
-experiments/
-└── battery
-    ├── nine
-    │   ├── checkpoints
-    │   ├── hyperparameters.json
-    │   ├── logs
-    │   └── tensorboard
-    └── random.pkl
+```shell-session
+$ uv run examples/battery_arbitrage_experiments.py
 ```
 
-Also provide wrappers around two `gym` environments - Pendulum and Lunar Lander:
-
-```bash
-$ energypy benchmarks/pendulum.json
-```
-
-Running the Lunar Lander experiment has a dependency on Swig and pybox2d - which can require a bit of elbow-grease to setup depending on your environment.
+## Test
 
-```bash
-$ energypy benchmarks/lunar.json
+```shell-session
+$ make test
 ```