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scos-sensor is a work-in-progress reference implementation of the IEEE 802.15.22.3 Spectrum Characterization and Occupancy Sensing (SCOS) sensor developed by NTIA/ITS. scos-sensor defines a RESTful application programming interface (API), that allows authorized users to discover capabilities, schedule actions, and acquire resultant data.

Table of Contents


scos-sensor was designed by NTIA/ITS with the following goals in mind:

  • Easy-to-use sensor control and data retrieval via IP network
  • Low-cost, open-source development resources
  • Design flexibility to allow developers to evolve sensor technologies and metrics
  • Hardware agnostic
  • Discoverable sensor capabilities
  • Task scheduling using start/stop times, interval, and/or priority
  • Standardized metadata/data format that supports cooperative sensing and open data initiatives
  • Security controls that prevent unauthorized users from accessing internal sensor functionality
  • Easy-to-deploy with provisioned and configured OS
  • Quality assurance of software via automated testing prior to release

Sensor control is accomplished through a RESTful API. The API is designed to be rich enough that multiple heterogeneous sensors can be automated effectively while being simple enough to still be useful for single-sensor deployments. For example, by advertising capabilities and location, an owner of multiple sensors can easily filter by frequency range, available actions, or geographic location. Yet, since each sensor hosts its own Browsable API, controlling small deployments is as easy as clicking around a website.

Opening the URL to your sensor (localhost if you followed the Quickstart) in a browser, you will see a frontend to the API that allows you to do anything the JSON API allows. Relationships in the API are represented by URLs which you can click to navigate from endpoint to endpoint. The full API is discoverable simply by following these links:

Browsable API Root

Scheduling an action is as simple as filling out a short form on /schedule:

Browsable API Submission

Actions that have been scheduled show up in the schedule entry list:

Browsable API Schedule List

We have tried to remove the most common hurdles to remotely deploying a sensor while maintaining flexibility in two key areas. First, the API itself is hardware agnostic, and the implementation assumes different hardware will be used depending on sensing requirements. Second, we introduce the high-level concept of "actions" which gives the sensor owner control over what the sensor can be tasked to do. For more information see Actions and Hardware Support.


This section provides an overview of high-level concepts used by scos-sensor.

  • action: A function that the sensor owner implements and exposes to the API. Actions are the things that the sensor owner wants the sensor to be able to do. Since actions block the scheduler while they run, they have exclusive access to the sensor's resources (like the signal analyzer). Currently, there are several logical groupings of actions, such as those that create acquisitions, or admin-only actions that handle administrative tasks. However, actions can theoretically do anything a sensor owner can implement. Some less common (but perfectly acceptable) ideas for actions might be to rotate an antenna, or start streaming data over a socket and only return when the recipient closes the connection.

  • acquisition: The combination of data and metadata created by an action (though an action does not have to create an acquisition). Metadata is accessible directly though the API, while data is retrievable in an easy-to-use archive format with its associated metadata.

  • admin: A user account that has full control over the sensor and can create schedule entries and view, modify, or delete any other user's schedule entries or acquisitions.

  • capability: Available actions, installation specifications (e.g., mobile or stationary), and operational ranges of hardware components (e.g., frequency range of signal analyzer). These values are generally hard-coded by the sensor owner and rarely change.

  • plugin: A Python package with actions designed to be integrated into scos-sensor.

  • schedule: The collection of all schedule entries (active and inactive) on the sensor.

  • scheduler: A thread responsible for executing the schedule. The scheduler reads the schedule at most once a second and consumes all past and present times for each active schedule entry until the schedule is exhausted. The latest task per schedule entry is then added to a priority queue, and the scheduler executes the associated actions and stores/POSTs task results. The scheduler operates in a simple blocking fashion, which significantly simplifies resource deconfliction. When executing the task queue, the scheduler makes a best effort to run each task at its designated time, but the scheduler will not cancel a running task to start another task, even one of higher priority.

  • schedule entry: Describes a range of scheduler tasks. A schedule entry is at minimum a human readable name and an associated action. Combining different values of start, stop, interval, and priority allows for flexible task scheduling. If no start time is given, the first task is scheduled as soon as possible. If no stop time is given, tasks continue to be scheduled until the schedule entry is manually deactivated. Leaving the interval undefined results in a "one-shot" entry, where the scheduler deactivates the entry after a single task is scheduled. One-shot entries can be used with a future start time. If two tasks are scheduled to run at the same time, they will be run in order of priority. If two tasks are scheduled to run at the same time and have the same priority, execution order is implementation-dependent (undefined).

  • signals: Django event driven programming framework. Actions use signals to send results to scos-sensor. These signals are handled by scos-sensor so that the results can be processed (such as storing measurement data and metadata).

  • task: A representation of an action to be run at a specific time. When a task acquires data, that data is stored on disk, and a significant amount of metadata is stored in a local database. The full metadata can be read directly through the self-hosted website or retrieved in plain text via a single API call. Our metadata and data format is an extension of, and compatible with, the SigMF specification - see sigmf-ns-ntia.

  • task result: A record of the outcome of a task. A result is recorded for each task after the action function returns, and includes metadata such as when the task started, when it finished, its duration, the result (success or failure), and a freeform detail string. A TaskResult JSON object is also POSTed to a schedule entry's callback_url, if provided.


When deploying equipment remotely, the robustness and security of software is a prime concern. scos-sensor sits on top of a popular open-source framework, which provides out-of-the-box protection against cross site scripting (XSS), cross site request forgery (CSRF), SQL injection, and clickjacking attacks, and also enforces SSL/HTTPS (traffic encryption), host header validation, and user session security.

scos-sensor uses a open source software stack that should be comfortable for developers familiar with Python.

  • Persistent metadata is stored on disk in a relational database, and measurement data is stored in files on disk.
  • A scheduler thread running in a Gunicorn worker process periodically reads the schedule from the database and performs the associated actions.
  • A website and JSON RESTful API using Django REST framework is served over HTTPS via NGINX, a high-performance web server. These provide easy administration over the sensor.

SCOS Sensor Architecture Diagram

A functioning scos-sensor utilizes software from at least three different GitHub repositories. As shown below, the scos-sensor repository integrates everything together as a functioning scos-sensor and provides the code for the user interface, scheduling, and the storage and retrieval of schedules and acquisitions. The scos-actions repository provides the core actions API, defines the signal analyzer interface that provides an abstraction for all signal analyzers, and provides basic actions. Finally, using a real signal analyzer within scos-sensor requires a third scos-<signal analyzer> repository that provides the signal analyzer specific implementation of the signal analyzer interface where <signal analyzer> is replaced with the name of the signal analyzer, e.g. a USRP scos-sensor utilizes the scos-usrp repository. The signal analyzer specific implementation of the signal analyzer interface may expose additional properties of the signal analyzer to support signal analyzer specific capabilities and the repository may also provide additional signal analyzer specific actions.

SCOS Sensor Modules

Overview of scos-sensor Repo Structure

  • configs: This folder is used to store the sensor_definition.json file.
  • docker: Contains the docker files used by scos-sensor.
  • docs: Documentation including the documentation hosted on GitHub pages generated from the OpenAPI specification.
  • entrypoints: Docker entrypoint scripts which are executed when starting a container.
  • gunicorn: Gunicorn configuration file.
  • nginx: Nginx configuration template and SSL certificates.
  • scripts: Various utility scripts.
  • src: Contains the scos-sensor source code.
    • actions: Code to discover actions in plugins and to perform a simple logger action.
    • authentication: Code related to user authentication.
    • capabilities: Code used to generate capabilities endpoint.
    • handlers: Code to handle signals received from actions.
    • schedule: Schedule API endpoint for scheduling actions.
    • scheduler: Scheduler responsible for executing actions.
    • sensor: Core app which contains the settings, generates the API root endpoint.
    • static: Django will collect static files (JavaScript, CSS, …) from all apps to this location.
    • status: Status endpoint.
    • tasks: Tasks endpoint used to display upcoming and completed tasks.
    • templates: HTML templates used by the browsable API.
    • Used to configure pytest fixtures.
    • Django’s command line tool for administrative tasks.
    • requirements.txt and requirements-dev.txt: Python dependencies.
    • tox.ini: Used to configure tox.
  • docker-compose.yml: Used by Docker Compose to create services from containers. This is needed to run scos-sensor.
  • env.template: Template file for setting environment variables used to configure scos-sensor.


This section describes how to spin up a production-grade sensor in just a few commands.

We currently support Ettus USRP B2xx signal analyzers out of the box, and any Intel-based host computer should work.

  1. Install git, Docker, and Docker Compose.

  2. Clone the repository.

    git clone
    cd scos-sensor
  3. Copy the environment template file and modify the copy if necessary, then source it. The settings in this file are set for running in a development environment on your local system. For running in a production environment, many of the settings will need to be modified. Some of the values, including the ENCRYPTION_KEY, POSTGRES_PASSWORD, and the Django SECRET_KEY are randomly generated in this file. Therefore, if the source command is run a second time, the old values will be lost. Make sure to hardcode and backup these environment variables to enable scos-sensor to decrypt the data files stored in scos-sensor and access the database. See Configuration section. Also, you are strongly encouraged to change the default ADMIN_EMAIL and ADMIN_PASSWORD before running scos-sensor. Finally, source the file before running scos-sensor to load the settings into your environment.

    cp env.template env
    source ./env
  4. Create sensor certificate. Running the script in the below command will create a certificate authority and localhost SSL certificate for the sensor. The certificate authority and the sensor certificate will have dummy values for the subject and password. To create a certificate specific to your host and organization, see the security section. The sensor certificate created by '' should only be used for testing purposes when connecting to scos-sensor website from the same computer as where it is hosted.

    cd scripts/
  5. Run a Dockerized stack.

    docker-compose up -d --build  # start in background
    docker-compose logs --follow api  # reattach terminal


When running in a production environment or on a remote system, various settings will need to be configured.


  • shm_size: This setting is overriding the default setting of 64 mb. If using scos-sensor on a computer with lower memory, this may need to be decreased. This is currently only used by the NasctnSeaDataProduct action.

Environment File

As explained in the Quickstart section, before running scos-sensor, an environment (env) file is created from the env.template file. These settings can either be set in the environment file or set directly in docker-compose.yml. Here are the settings in the environment file:

  • ADMIN_EMAIL: Email used to generate admin user. Change in production.
  • ADMIN_PASSWORD: Password used to generate admin user. Change in production.
  • BASE_IMAGE: Base docker image used to build the API container.
  • CALLBACK_SSL_VERIFICATION: Set to “true” in production environment. If false, the SSL certificate validation will be ignored when posting results to the callback URL.
  • DEBUG: Django debug mode. Set to False in production.
  • DOCKER_TAG: Always set to “latest” to install newest version of docker containers.
  • DOMAINS: A space separated list of domain names. Used to generate ALLOWED_HOSTS.
  • ENCRYPT_DATA_FILES: If set to true, sigmf-data files will be encrypted when stored in the api container by scos-sensor.
  • ENCRYPTION_KEY: Encryption key to encrypt sigmf-data files if ENCRYPT_DATA_FILES is set to true. The env.template file sets to a randomly generated value.
  • GIT_BRANCH: Current branch of scos-sensor being used.
  • GUNICORN_LOG_LEVEL: Log level for Gunicorn log messages.
  • IPS: A space separated list of IP addresses. Used to generate ALLOWED_HOSTS.
  • FQDN: The server’s fully qualified domain name.
  • MAX_DISK_USAGE: The maximum disk usage percentage allowed before overwriting old results. Defaults to 85%. This disk usage detected by scos-sensor (using the Python shutil.disk_usage function) may not match the usage reported by the Linux df command.
  • POSTGRES_PASSWORD: Sets password for the Postgres database for the “postgres” user. Change in production. The env.template file sets to a randomly generated value.
  • REPO_ROOT: Root folder of the repository. Should be correctly set by default.
  • SECRET_KEY: Used by Django to provide cryptographic signing. Change to a unique, unpredictable value. See The env.template file sets to a randomly generated value.
  • SSL_CERT_PATH: Path to server SSL certificate. Replace the certificate in the scos-sensor repository with a valid certificate in production.
  • SSL_KEY_PATH: Path to server SSL private key. Use the private key for your valid certificate in production.

Sensor Definition File

This file contains information on the sensor and components being used. It is used in the SigMF metadata to identify the hardware used for the measurement. It should follow the sigmf-ns-ntia Sensor Object format. See an example below. Overwrite the example file in scos-sensor/configs with the information specific to the sensor you are using.

    "sensor_spec": {
        "id": "",
        "model": "greyhound"
    "antenna": {
        "antenna_spec": {
            "id": "",
            "model": "L-com HG3512UP-NF"
    "signal_analyzer": {
        "sigan_spec": {
            "id": "",
            "model": "Ettus USRP B210"
    "computer_spec": {
        "id": "",
        "model": "Intel NUC"


This section covers authentication, permissions, and certificates used to access the sensor, and the authentication available for the callback URL. Two different types of authentication are available for authenticating against the sensor and for authenticating when using a callback URL.

Sensor Authentication And Permissions

The sensor can be configured to authenticate using OAuth JWT access tokens from an external authorization server or using Django Rest Framework Token Authentication.

Django Rest Framework Token Authentication

This is the default authentication method. To enable Django Rest Framework Authentication, make sure AUTHENTICATION is set to TOKEN in the environment file (this will be enabled if AUTHENTICATION set to anything other than JWT).

A token is automatically created for each user. Django Rest Framework Token Authentication will check that the token in the Authorization header ("Token " + token) matches a user's token.

OAuth2 JWT Authentication

To enable OAuth 2 JWT Authentication, set AUTHENTICATION to JWT in the environment file. To authenticate, the client will need to send a JWT access token in the authorization header (using "Bearer " + access token). The token signature will be verified using the public key from the PATH_TO_JWT_PUBLIC_KEY setting. The expiration time will be checked. Only users who have an authority matching the REQUIRED_ROLE setting will be authorized.

The token is expected to come from an OAuth2 authorization server. For more information, see


Use this section to create self-signed certificates with customized organizational and host information. This section includes instructions for creating a self-signed root CA, SSL server certificates for the sensor, optional client certificates, and test JWT public/private key pair.

As described below, a self-signed CA can be created for testing. For production, make sure to use certificates from a trusted CA.

Below instructions adapted from here.

Sensor Certificate

This is the SSL certificate used for the scos-sensor web server and is always required.

To be able to sign server-side and client-side certificates, we need to create our own self-signed root CA certificate first. The command will prompt you to enter a password and the values for the CA subject.

openssl req -x509 -sha512 -days 365 -newkey rsa:4096 -keyout scostestca.key -out scostestca.pem

Generate a host certificate signing request. Replace the values in square brackets in the subject for the server certificate.

openssl req -new -newkey rsa:4096 -keyout sensor01.key -out sensor01.csr -subj "/C=[2 letter country code]/ST=[state or province]/L=[locality]/O=[organization]/OU=[organizational unit]/CN=[common name]"

Before we proceed with openssl, we need to create a configuration file -- sensor01.ext. It'll store some additional parameters needed when signing the certificate. Adjust the settings, especially DNS names and IP addresses, in the below example for your sensor:

subjectAltName = @alt_names
subjectKeyIdentifier = hash
keyUsage = critical, digitalSignature, keyEncipherment
extendedKeyUsage = serverAuth, clientAuth
DNS.1 = sensor01.domain
DNS.2 = localhost
IP.1 =
IP.2 =

Sign the host certificate.

openssl x509 -req -CA scostestca.pem -CAkey scostestca.key -in sensor01.csr -out sensor01.pem -days 365 -sha256 -CAcreateserial -extfile sensor01.ext

If the sensor private key is encrypted, decrypt it using the following command:

openssl rsa -in sensor01.key -out sensor01_decrypted.key

Combine the sensor certificate and private key into one file:

cat sensor01_decrypted.key sensor01.pem > sensor01_combined.pem
Client Certificate

This certificate is required for using the sensor with mutual TLS which is required if OAuth authentication is enabled.

Replace the brackets with the information specific to your user and organization.

openssl req -new -newkey rsa:4096 -keyout client.key -out client.csr -subj "/C=[2 letter country code]/ST=[state or province]/L=[locality]/O=[organization]/OU=[organizational unit]/CN=[common name]"

Create client.ext with the following:

basicConstraints = CA:FALSE
subjectKeyIdentifier = hash
authorityKeyIdentifier = keyid,issuer
keyUsage = digitalSignature
extendedKeyUsage = clientAuth

Sign the client certificate.

openssl x509 -req -CA scostestca.pem -CAkey scostestca.key -in client.csr -out client.pem -days 365 -sha256 -CAcreateserial -extfile client.ext

Convert pem to pkcs12:

openssl pkcs12 -export -out client.pfx -inkey client.key -in client.pem -certfile scostestca.pem

Import client.pfx into web browser for use with the browsable API or use the client.pem or client.pfx when communicating with the API programmatically.

Generating JWT Public/Private Key

The JWT public key must correspond to the private key of the JWT issuer (OAuth authorization server). For manual testing, the instructions below could be used to create a public/private key pair for creating JWTs without an authorization server.

Step 1: Create public/private key pair
openssl genrsa -out jwt.pem 4096
Step 2: Extract Public Key
openssl rsa -in jwt.pem -outform PEM -pubout -out jwt_public_key.pem
Step 3: Extract Private Key
openssl pkey -inform PEM -outform PEM -in jwt.pem -out jwt_private_key.pem
Configure scos-sensor

The Nginx web server can be set to require client certificates (mutual TLS). This can optionally be enabled. To require client certificates, uncomment ssl_verify_client on; in the Nginx configuration file. If you use OCSP, also uncomment ssl_ocsp on;. Additional configuration may be needed for Nginx to check certificate revocation lists (CRL).

Copy the server certificate and server private key (sensor01_combined.pem) to scos-sensor/configs/certs. Then set SSL_CERT_PATH and SSL_KEY_PATH (in the environment file) to the path of the sensor01_combined.pem relative to configs/certs (for file at scos-sensor/configs/certs/sensor01_combined.pem, set SSL_CERT_PATH=sensor01_combined.pem and SSL_KEY_PATH=sensor01_combined.pem). For mutual TLS, also copy the CA certificate to the same directory. Then, set SSL_CA_PATH to the path of the CA certificate relative to configs/certs.

If you are using JWT authentication, set PATH_TO_JWT_PUBLIC_KEY to the path of the JWT public key relative to configs/certs. This public key file should correspond to the private key used to sign the JWT. Alternatively, the JWT private key created above could be used to manually sign a JWT token for testing if PATH_TO_JWT_PUBLIC_KEY is set to the JWT public key created above.

If you are using client certificates, use client.pfx to connect to the browsable API by importing this certificate into your browser.

For callback functionality with an OAuth authorized callback URL, set PATH_TO_CLIENT_CERT and PATH_TO_VERIFY_CERT, both relative to configs/certs. Depending on the configuration of the callback URL server and the authorization server, the sensor server certificate could be used as a client certificate by setting PATH_TO_CLIENT_CERT to the path of sensor01_combined.pem relative to configs/certs. Also the CA used to verify the client certificate could potentially be used to verify the callback URL server certificate by setting PATH_TO_VERIFY_CERT to the same file as used for SSL_CA_PATH (scostestca.pem).

Permissions and Users

The API requires the user to either have an authority in the JWT token matching the the REQUIRED_ROLE setting or that the user be a superuser. New users created using the API initially do not have superuser access. However, an admin can mark a user as a superuser in the Sensor Configuration Portal. When using JWT tokens, the user does not have to be pre-created using the sensor's API. The API will accept any user using a JWT token if they have an authority matching the required role setting.

Callback URL Authentication

OAuth and Token authentication are supported for authenticating against the server pointed to by the callback URL. Callback SSL verification can be enabled or disabled using CALLBACK_SSL_VERIFICATION in the environment file.


A simple form of token authentication is supported for the callback URL. The sensor will send the user's (user who created the schedule) token in the authorization header ("Token " + token) when posting results to callback URL. The server can then verify the token against what it originally sent to the sensor when creating the schedule. This method of authentication for the callback URL is enabled by default. To verify it is enabled, set CALLBACK_AUTHENTICATION to TOKEN in the environment file (this will be enabled if CALLBACK_AUTHENTICATION set to anything other than OAUTH). PATH_TO_VERIFY_CERT, in the environment file, can used to set a CA certificate to verify the callback URL server SSL certificate. If this is unset and CALLBACK_SSL_VERIFICATION is set to true, standard trusted CAs will be used.


The OAuth 2 password flow is supported for callback URL authentication. The following settings in the environment file are used to configure the OAuth 2 password flow authentication.

  • CLIENT_ID - client ID used to authorize the client (the sensor) against the authorization server.
  • CLIENT_SECRET - client secret used to authorize the client (the sensor) against the authorization server.
  • OAUTH_TOKEN_URL - URL to get the access token.
  • PATH_TO_CLIENT_CERT - client certificate used to authenticate against the authorization server.
  • PATH_TO_VERIFY_CERT - CA certificate to verify the authorization server and callback URL server SSL certificate. If this is unset and CALLBACK_SSL_VERIFICATION is set to true, standard trusted CAs will be used.

In src/sensor/, the OAuth USER_NAME and PASSWORD are set to be the same as CLIENT_ID and CLIENT_SECRET. This may need to change depending on your authorization server.

Data File Encryption

The data files are encrypted on disk by default using Cryptography Fernet module. The Fernet encryption module may not be suitable for large data files. According to the Cryptography documentation for Fernet encryption, the entire message contents must fit in memory. Note that the SigMF metadata is currently not encrypted. The SCOS_TMP setting controls where data will be written when decrypting the file and creating the SigMF archive. Defaults to /scos_tmp docker tmpfs mount. Set the ENCRYPTION_KEY environment variable to control the encryption key used for encryption. The env.template file will generate a random encryption key for testing. When used in production, it is recommended to store the encryption key in a safe location to prevent data loss and to prevent data from being compromised. Use the ENCRYPT_DATA_FILES setting in the env.template file to disable encryption. The SCOS_TMP location is used to create the SigMF archive regardless of whether encryption is enabled.

Actions and Hardware Support

"Actions" are one of the main concepts used by scos-sensor. At a high level, they are the things that the sensor owner wants the sensor to be able to do. At a lower level, they are simply Python classes with a special method __call__. Actions are designed to be discovered programmatically in installed plugins. Plugins are Python packages that are designed to be integrated into scos-sensor. The reason for using plugins to install actions is that different actions can be offered depending on the hardware being used. Rather than requiring a modification to scos-sensor repository, plugins allow anyone to add additional hardware support to scos-sensor by offering new or existing actions that use the new hardware.

Common action classes can still be re-used by plugins through the scos-actions repository. The scos-actions repository is intended to be a dependency for every plugin as it contains the actions base class and signals needed to interface with scos-sensor. These actions use a common but flexible signal analyzer interface that can be implemented for new types of hardware. This allows for action re-use by passing the signal analyzer interface implementation and the required hardware and measurement parameters to the constructor of these actions. Alternatively, custom actions that support unique hardware functionality can be added to the plugin.

The scos-actions repository can also be installed as a plugin which uses a mock signal analyzer.

scos-sensor uses the following convention to discover actions offered by plugins: if any Python package begins with "scos_", and contains a dictionary of actions at the Python path, these actions will automatically be available for scheduling.

The scos-usrp plugin adds support for the Ettus B2xx line of signal analyzers. It can also be used as an example of a plugin which adds new hardware support and re-uses the common actions in scos-actions.

For more information on adding actions and hardware support, see scos-actions.

Preselector Support

Scos-sensor can be configured to support preselectors. By default, scos-sensor will look in the configs directory for a file named preselector_config.json. This location/name can be changed by setting PRESELECTOR_CONFIG in docker-compose.yaml. By default, scos-sensor will use a WebRelayPreselector. This can be changed by setting PRESELECTOR_MODULE in docker-compose.yaml to the python module that contains the preselector implementation you specify in PRESELECTOR_CLASS in docker-compose.yaml.

Relay Support

Scos-sensor can be configured with zero or more network controlled relays. The default relay configuration directory is configs/switches. Relay support is provided by the its_preselector package. Any relay configs placed in the relay configuration directory will be used to create an instance of a ControlByWebWebRelay and added into a switches dictionary in scos-actions.hardware. In addition, each relay is registered to provide status through the scos-sensor status endpoint as specified in the relay config file (see its_preselector for additional details).


Running the Sensor in Development

The following techniques can be used to make local modifications. Sections are in order, so "Running Tests" assumes you've done the setup steps in “Requirements and Configuration”.

Requirements and Configuration

It is highly recommended that you first initialize a virtual development environment using a tool such a conda or venv. The following commands create a virtual environment using venv and install the required dependencies for development and testing.

python3 -m venv ./venv
source venv/bin/activate
python3 -m pip install --upgrade pip # upgrade to pip>=18.1
python3 -m pip install -r src/requirements-dev.txt

Using pip-tools

It is recommended to keep direct dependencies in a separate file. The direct dependencies are in the and files. Then pip-tools can be used to generate files with all the dependencies and transitive dependencies (sub-dependencies). The files containing all the dependencies are in requirements.txt and requirements-dev.txt. Run the following in the virtual environment to install pip-tools.

python -m pip install pip-tools

To update requirements.txt after modifying


To update requirements-dev.txt after modifying or


Use pip-sync to match virtual environment to requirements-dev.txt:

pip-sync requirements.txt requirements-dev.txt

For more information about pip-tools, see

Running Tests

Ideally, you should add a test that covers any new feature that you add. If you've done that, then running the included test suite is the easiest way to check that everything is working. In any case, all tests should be run after making any local modifications to ensure that you haven't caused a regression.

scos-sensor uses pytest and pytest-django for testing. Tests are organized by application , so tests related to the scheduler are in ./src/scheduler/tests. tox is a tool that can run all available tests in a virtual environment against all supported versions of Python. Running pytest directly is faster, but running tox is a more thorough test.

The following commands install the sensor's development requirements. We highly recommend you initialize a virtual development environment using a tool such a conda or venv first.

cd src
pytest          # faster, but less thorough
tox             # tests code in clean virtualenv
tox --recreate  # if you change `requirements.txt`
tox -e coverage # check where test coverage lacks

Running Docker with Local Changes

The docker-compose file and application code look for information from the environment when run, so it's necessary to source the following file in each shell that you intend to launch the sensor from. (HINT: it can be useful to add the source command to a post-activate file in whatever virtual environment you're using).

cp env.template env     # modify if necessary, defaults are okay for testing
source ./env

Then, build the API docker image locally, which will satisfy the smsntia/scos-sensor and smsntia/autoheal images in the Docker compose file and bring up the sensor.

docker-compose down
docker-compose build
docker-compose up -d
docker-compose logs --follow api

Running Development Server (Not Recommended)

Running the sensor API outside of Docker is possible but not recommended, since Django is being asked to run without several security features it expects. See Common Issues for some hints when running the sensor in this way. The following steps assume you've already set up some kind of virtual environment and installed python dev requirements from Requirements and Configuration.

docker-compose up -d db
cd src
export MOCK_SIGAN=1 MOCK_SIGAN_RANDOM=1 # if running without signal analyzer attached
./ makemigrations
./ migrate
./ createsuperuser
./ runserver
Common Issues
  • The development server serves on localhost:8000, not :80
  • If you get a Forbidden (403) error, close any tabs and clear any cache and cookies related to SCOS Sensor and try again
  • If you're using a virtual environment and your signal analyzer driver is installed outside of it, you may need to allow access to system sitepackages. For example, if you're using a virtualenv called scos-sensor, you can remove the following text file: rm -f ~/.virtualenvs/scos-sensor/lib/python3.7/no-global-site-packages.txt, and thereafter use the ignore-installed flag to pip: pip install -I -r requirements.txt. This should let the devserver fall back to system sitepackages for the signal analyzer driver only.


Besides running the test suite and ensuring that all tests are passed, we also expect all Python code that's checked in to have been run through an auto-formatter.

This project uses a Python auto-formatter called Black. You probably won't like every decision it makes, but our continuous integration test-runner will reject your commit if it's not properly formatted.

Additionally, import statement sorting is handled by isort.

The continuous integration test-runner verifies the code is auto-formatted by checking that neither isort nor Black would recommend any changes to the code. Occasionally, this can fail if these two autoformatters disagree. The only time I've seen this happen is with a commented-out import statement, which isort parses, and Black treats as a comment. Solution: don't leave commented-out import statements in the code.

There are several ways to autoformat your code before committing. First, IDE integration with on-save hooks is very useful. Second, there is a script, scripts/, that will run both isort and Black over the codebase. Lastly, if you've already pip-installed the dev requirements from the section above, you already have a utility called pre-commit installed that will automate setting up this project's git pre-commit hooks. Simply type the following once, and each time you make a commit, it will be appropriately autoformatted.

pre-commit install

You can manually run the pre-commit hooks using the following command.

pre-commit run --all-files





For technical questions about scos-sensor, contact Justin Haze,