The sensor_template repository provides a robust framework for implementing a custom bicycle sensor. The framework handles file system operations, including the creation and management of data files, and automates the upload of sensor measurements to a remote server. This allows developers to focus on their custom sensor logic by extending the provided BicycleSensor class and implementing the necessary methods.

• File System Management: Automatically creates directories and manages data files for storing sensor measurements.
• Automated Data Upload: Periodically uploads sensor data to a configured remote server, with customizable upload intervals.
• Customizable Sensor Logic: Developers can create custom sensors by extending the BicycleSensor class and implementing specific methods for data handling.
• Logging: Configurable logging with options for file-based logging, rotating logs, and console output.

• Python 3.x: Ensure you have Python 3 installed on your system.
• Dependencies: The framework uses the requests module for handling HTTP requests. You can install it using:

pip install requests

Clone the repository to your local machine:

git clone https://github.com/bicycledata/sensor_template.git
cd sensor_template

To create a custom bicycle sensor, extend the BicycleSensor class and implement the abstract methods: write_header() and write_measurement(). The provided SensorTemplate class serves as an example implementation that records the current time as a sensor measurement.

Example:

class MyCustomSensor(BicycleSensor):
    def write_header(self):
        self.write_to_file('time, speed')

    def write_measurement(self):
        speed = get_speed_data()  # Replace with actual sensor logic
        self.write_to_file(f"{time.time()}, {speed}")

You can run the provided SensorTemplate class with the following command:

./sensor.py --hash <device_hash> --name <sensor_name> [options]

• --hash (required): The unique hash of the device, used for identifying the sensor during uploads.
• --name (required): The name of the sensor.
• --loglevel (optional): Set the logging level (DEBUG, INFO, WARNING). Default is INFO.
• --measurement-frequency (optional): Frequency of sensor measurements in Hertz (measurements per second). Default is 1.0 Hz.
• --stdout (optional): Enable logging output to the console (stdout).
• --upload-interval (optional): Interval between data uploads in seconds. Default is 300 seconds (5 minutes).

The framework handles the following operations:

• File Management: Data is written to CSV files stored in the pending directory. Upon successful upload, files are moved to the uploaded directory.
• Data Upload: Data is uploaded to a remote server (configured in the _upload_data method) using HTTP POST requests. The upload logic is executed in a separate thread to ensure that the main sensor loop runs without interruptions.
• Signal Handling: The framework gracefully handles shutdown signals (SIGTERM, SIGINT) and ensures that any pending data is uploaded before exiting.

Logging is configured through the configure() function. The framework supports:

• File-based logging: Logs are stored in the log/sensor_template.log file.
• Rotating logs: By enabling the rotating option, logs are rotated when they reach 5MB in size, with a backup count of 2.
• Console output: Enable logging to the console using the --stdout flag.

The framework's automated upload feature sends sensor data to the server at regular intervals. The upload process is managed by a separate thread, ensuring it does not interfere with data collection. The upload endpoint and payload are defined in the _upload_data() method.

Note: If the upload fails, the data remains in the pending directory and the framework retries in the next cycle.

Contributions are welcome! If you have suggestions for improvements or find any bugs, feel free to open an issue or submit a pull request.

This repository is licensed under the MIT License. See the LICENSE file for more details.