Replace colint with ruff and dprint

.github/workflows/lint.yaml

@@ -1,60 +1,18 @@
 name: Lint Checks
-
 on: [pull_request, push]
-
 jobs:
-  sort_libraries:
-    runs-on: ubuntu-latest
-
-    steps:
-      - name: Checkout Code
-        uses: actions/checkout@v3
-
-      - name: Install Colint
-        uses: ./.github/actions/install-colint
-
-      - name: Run Sort Libraries Check
-        run: |
-          colint sort-libraries . --check --config-file ./lint
-
-  code_format:
+  lint:
     runs-on: ubuntu-latest
-
     steps:
       - name: Checkout Code
         uses: actions/checkout@v3
-
-      - name: Install Colint
-        uses: ./.github/actions/install-colint
 
-      - name: Run Code Format Check
-        run: |
-          colint code-format . --check --config-file ./lint
-
-  grammar_check:
-    runs-on: ubuntu-latest
-
-    steps:
-      - name: Checkout Code
-        uses: actions/checkout@v3
-
-      - name: Install Colint
-        uses: ./.github/actions/install-colint
-
-      - name: Run Grammar Check
-        run: |
-          colint grammar-check . --check --config-file ./lint
-
-  newline_fix:
-    runs-on: ubuntu-latest
-
-    steps:
-      - name: Checkout Code
-        uses: actions/checkout@v3
-
-      - name: Install Colint
-        uses: ./.github/actions/install-colint
+      - name: Set up Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: "3.10.12"
 
-      - name: Run Newline Fix Check
+      - name: Run linting
         run: |
-          colint newline-fix . --check --config-file ./lint
+          make setup-env
+          make lint CHECK=1

.github/workflows/push-to-registry.yaml

@@ -16,7 +16,7 @@ jobs:
       - name: Set up Python
         uses: actions/setup-python@v4
         with:
-          python-version: '3.10.12'
+          python-version: "3.10.12"
 
       - name: Install Build Dependencies
         run: |

.gitignore

@@ -5,6 +5,7 @@ build
 *.jpg
 .DS_Store
 .venv/
+.venv-lint/
 .vscode
 *.eim
 .act-secrets

Makefile

@@ -0,0 +1,62 @@
+VENV_DIR := $(abspath .venv-lint)
+PIP := $(VENV_DIR)/bin/pip
+PYTHON := $(VENV_DIR)/bin/python
+RUFF := $(VENV_DIR)/bin/ruff
+DPRINT := $(VENV_DIR)/bin/dprint
+TARGET_DIRS ?= .
+CHECK ?= 0
+
+.PHONY: clean
+clean:
+	git clean -Xdf --exclude "!.env"
+
+.PHONY: setup-venv
+setup-venv:
+	@if [ ! -d "$(VENV_DIR)" ]; then \
+		echo "Creating virtual environment for linters..."; \
+		python3 -m venv $(VENV_DIR); \
+		$(PIP) install --upgrade pip; \
+		$(PIP) install ruff; \
+	fi
+
+.PHONY: setup-dprint
+setup-dprint: setup-venv
+	@if [ ! -f "$(DPRINT)" ]; then \
+		echo "Installing dprint to $(VENV_DIR)/bin..."; \
+		mkdir -p $(VENV_DIR)/bin; \
+		curl -fsSL https://dprint.dev/install.sh | DPRINT_INSTALL=$(VENV_DIR) sh; \
+	fi
+
+.PHONY: setup-env
+setup-env: setup-venv setup-dprint
+
+.PHONY: ruff
+ruff: setup-venv
+	@if [ "$(CHECK)" = "1" ]; then \
+		echo "Running Ruff in check mode..."; \
+		$(RUFF) check $(TARGET_DIRS); \
+		LINT_STATUS=$$?; \
+		$(RUFF) format $(TARGET_DIRS) --check; \
+		FMT_STATUS=$$?; \
+		if [ $$LINT_STATUS -ne 0 ] || [ $$FMT_STATUS -ne 0 ]; then exit 1; fi; \
+	else \
+		echo "Running Ruff and fixing issues..."; \
+		$(RUFF) check $(TARGET_DIRS) --fix; \
+		LINT_STATUS=$$?; \
+		$(RUFF) format $(TARGET_DIRS); \
+		FMT_STATUS=$$?; \
+		if [ $$LINT_STATUS -ne 0 ] || [ $$FMT_STATUS -ne 0 ]; then exit 1; fi; \
+	fi
+
+.PHONY: dprint
+dprint: setup-dprint
+	@if [ "$(CHECK)" = "1" ]; then \
+		echo "Running dprint in check mode..."; \
+		$(DPRINT) check $(TARGET_DIRS); \
+	else \
+		echo "Running dprint and formatting..."; \
+		$(DPRINT) fmt $(TARGET_DIRS); \
+	fi
+
+.PHONY: lint
+lint: ruff dprint

README.md

@@ -20,34 +20,34 @@ This library lets you run machine learning models and collect sensor data on Lin
 1. Install a recent version of [Python 3](https://www.python.org/downloads/) and `pip` tools.
 1. Install the SDK:
 
-    **Raspberry Pi**
+   **Raspberry Pi**
 
-    ```
-    $ sudo apt-get install libatlas-base-dev libportaudio0 libportaudio2 libportaudiocpp0 portaudio19-dev libopenjp2-7 libgtk-3-0 libswscale-dev libavformat58 libavcodec58
-    $ pip3 install edge_impulse_linux -i https://pypi.python.org/simple
-    ```
+   ```
+   $ sudo apt-get install libatlas-base-dev libportaudio0 libportaudio2 libportaudiocpp0 portaudio19-dev libopenjp2-7 libgtk-3-0 libswscale-dev libavformat58 libavcodec58
+   $ pip3 install edge_impulse_linux -i https://pypi.python.org/simple
+   ```
 
-    **Other platforms**
+   **Other platforms**
 
-    ```
-    $ pip3 install edge_impulse_linux
-    ```
+   ```
+   $ pip3 install edge_impulse_linux
+   ```
 
 1. Clone this repository to get the examples:
 
-    ```
-    $ git clone https://github.com/edgeimpulse/linux-sdk-python
-    ```
+   ```
+   $ git clone https://github.com/edgeimpulse/linux-sdk-python
+   ```
 
-4. Install pip dependencies:
+1. Install pip dependencies:
 
-    ```
-    $ pip3 install -r requirements.txt
-    ```
+   ```
+   $ pip3 install -r requirements.txt
+   ```
 
-    For the computer vision examples you'll want `opencv-python>=4.5.1.48,<5`
-    Note on macOS on apple silicon, you will need to use a later version,
-    4.10.0.84 tested and installs cleanly
+   For the computer vision examples you'll want `opencv-python>=4.5.1.48,<5`
+   Note on macOS on apple silicon, you will need to use a later version,
+   4.10.0.84 tested and installs cleanly
 
 ## Collecting data
 
@@ -69,31 +69,32 @@ To classify data (whether this is from the camera, the microphone, or a custom s
 1. Install the [Edge Impulse for Linux CLI](https://docs.edgeimpulse.com/docs/edge-impulse-for-linux).
 1. Download the model file via:
 
-    ```
-    $ edge-impulse-linux-runner --download modelfile.eim
-    ```
+   ```
+   $ edge-impulse-linux-runner --download modelfile.eim
+   ```
 
-    This downloads the file into `modelfile.eim`. (Want to switch projects? Add `--clean`)
+   This downloads the file into `modelfile.eim`. (Want to switch projects? Add `--clean`)
 
 Then you can start classifying realtime sensor data. We have examples for:
 
-* [Audio](https://github.com/edgeimpulse/linux-sdk-python/blob/master/examples/audio/classify.py) - grabs data from the microphone and classifies it in realtime.
-* [Camera](https://github.com/edgeimpulse/linux-sdk-python/blob/master/examples/image/classify.py) - grabs data from a webcam and classifies it in realtime.
-* [Camera (full frame)](https://github.com/edgeimpulse/linux-sdk-python/blob/master/examples/image/classify-full-frame.py) - grabs data from a webcam and classifies it twice (once cut from the left, once cut from the right). This is useful if you have a wide-angle lense and don't want to miss any events.
-* [Still image](https://github.com/edgeimpulse/linux-sdk-python/blob/master/examples/image/classify-image.py) - classifies a still image from your hard drive.
-* [Video](https://github.com/edgeimpulse/linux-sdk-python/blob/master/examples/image/classify-video.py) - grabs frames from a video source from your hard drive and classifies it.
-* [Custom data](https://github.com/edgeimpulse/linux-sdk-python/blob/master/examples/custom/classify.py) - classifies custom sensor data.
+- [Audio](https://github.com/edgeimpulse/linux-sdk-python/blob/master/examples/audio/classify.py) - grabs data from the microphone and classifies it in realtime.
+- [Camera](https://github.com/edgeimpulse/linux-sdk-python/blob/master/examples/image/classify.py) - grabs data from a webcam and classifies it in realtime.
+- [Camera (full frame)](https://github.com/edgeimpulse/linux-sdk-python/blob/master/examples/image/classify-full-frame.py) - grabs data from a webcam and classifies it twice (once cut from the left, once cut from the right). This is useful if you have a wide-angle lense and don't want to miss any events.
+- [Still image](https://github.com/edgeimpulse/linux-sdk-python/blob/master/examples/image/classify-image.py) - classifies a still image from your hard drive.
+- [Video](https://github.com/edgeimpulse/linux-sdk-python/blob/master/examples/image/classify-video.py) - grabs frames from a video source from your hard drive and classifies it.
+- [Custom data](https://github.com/edgeimpulse/linux-sdk-python/blob/master/examples/custom/classify.py) - classifies custom sensor data.
 
 ## Troubleshooting
 
 ### Collecting print out from the model
 
 To display the logging messages (ie, you may be used to in other deployments), init the runner like so
+
 ```
 # model_info = runner.init(debug=True) # to get debug print out
 ```
-This will pipe stdout and stderr into the same of your own process
 
+This will pipe stdout and stderr into the same of your own process
 
 ### [Errno -9986] Internal PortAudio error (macOS)
 

dprint.json

@@ -0,0 +1,33 @@
+{
+  "yaml": {
+    "formatComments": true,
+    "braceSpacing": false,
+    "preferSingleLine": true
+  },
+  "json": {
+    "lineWidth": 80
+  },
+  "toml": {
+    "lineWidth": 80
+  },
+  "markdown": {
+    "emphasisKind": "asterisks"
+  },
+  "markup": {
+    "formatComments": true
+  },
+  "includes": [
+    "**/*.{yaml,yml}",
+    "**/*.json",
+    "**/*.toml",
+    "**/*.md",
+    "**/*.html"
+  ],
+  "plugins": [
+    "https://plugins.dprint.dev/g-plane/pretty_yaml-v0.6.0.wasm",
+    "https://plugins.dprint.dev/toml-0.7.0.wasm",
+    "https://plugins.dprint.dev/json-0.21.3.wasm",
+    "https://plugins.dprint.dev/markdown-0.22.1.wasm",
+    "https://plugins.dprint.dev/g-plane/markup_fmt-v0.27.3.wasm"
+  ]
+}

examples/custom/collect.py

@@ -31,13 +31,11 @@
 freq = 1000 / INTERVAL_MS
 values_list = []
 for i in range(2 * int(round(freq, 0))):
-    values_list.append(
-        [
-            math.sin(i * 0.1) * 10,
-            math.cos(i * 0.1) * 10,
-            (math.sin(i * 0.1) + math.cos(i * 0.1)) * 10,
-        ]
-    )
+    values_list.append([
+        math.sin(i * 0.1) * 10,
+        math.cos(i * 0.1) * 10,
+        (math.sin(i * 0.1) + math.cos(i * 0.1)) * 10,
+    ])
 
 data = {
     "protected": {

examples/image/classify-video.py

@@ -76,7 +76,6 @@ def getFrame(sec):
             img = getFrame(sec)
 
             while img.size != 0:
-
                 # imread returns images in BGR format, so we need to convert to RGB
                 img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
 

examples/image/set-thresholds.py

@@ -108,12 +108,10 @@ def main(argv):
                     print("Invalid input, please enter a number")
 
             # dynamically override the thresold from 0.2 -> 0.8
-            runner.set_threshold(
-                {
-                    "id": threshold_id,
-                    "min_score": new_threshold,
-                }
-            )
+            runner.set_threshold({
+                "id": threshold_id,
+                "min_score": new_threshold,
+            })
 
             res = runner.classify(features)
             print("classify response", json.dumps(res, indent=4))