2.2. Download, install and configure OnTask

  1. Download or clone a copy of OnTask .

  2. Using a command interpreter, go to the OnTask folder and locate a folder inside it with name requirements . Verify that it contains the files base.txt , production.txt and development.txt . The first file contains a list of python modules that are required by OnTask. The second is a set of additional modules to run a production instance, and the third is the same list if you intend to run a development instance.

  3. If you plan to run a production instance of OnTask execute the command:

    python3 -m pip install -r requirements/production.txt
    

    You may need administrative privileges to execute this command.

    If you plan to run a development instance of OnTask, execute the command:

    python3 -m pip install -r requirements/development.txt
    

    This command downloads a set of libraries and modules and installs them as part of the python libraries in the system.

2.2.1. OnTask Configuration

The variables used to execute OnTask are divided into two groups:

Environment variables

These variables need to be defined in the execution environment that starts OnTask.

DJANGO_SETTINGS_MODULE

Python expression pointing to the configuration script or initial module (python file) to execute on start up. Two of these modules are provided in the folder settings . The file development.py provides definitions recommended for a development environment. The file production.py provides the suggested definitions for a production deployment. Both scripts load the definitions in the module base.py .

Default: settings.production

ENV_FILENAME

Path and filename for the file with the configuration variables.

Default: settings/local.env

Configuration variables

These are variables that can be defined either in the execution environment (like the previous ones) or in the file with name specified in the variable ENV_FILENAME . The value of the configuration variables is obtaineed with the following rules:

  1. Take the value from the executing environment.

  1. If no value is found in the previous step, read the value from the definitions in the file with name ENV_FILENAME (if not empty).

  1. If no value is found in the previous step, take the default value.

The execution begins by running a python file read by Django during its start-up procedure. The first step is to read the environment and configuration variables followed by the definition of additional variables. The values of these additional variables can be any python expression and may have arbitrarily complex expressions and operations (even function calls).

2.2.1.1. Configuration variables

The following variables (in alphabetical order) can be defined outside the OnTask code for its configuration. All of them have deault values, some of them require a value, and the value of some of them can be changed without stopping the application.

ALLOWED_HOSTS

Comma-separated list of host names used to validate the HTTP requests received by the platform. It helps to avoid processing requests that fake their Host headers. If OnTask is going to be hosted in www.yoursite.com , then you may want to define it as www.yoursite.com,yoursite.com . By default the platform allows request with any Host header.

Default: [*] (any connection from any host)

AWS_ACCESS_KEY_ID

Amazon Web Services access key id. This value is used to access static files when served from a S3 bucket.

Default: ''

AWS_LOCATION

Path within the AWS S3 Bucket where the static files are located

Default: static

AWS_SECRET_ACCESS_KEY

Amazon Web Services secret attached to the given Access Key.

Default: ''

AWS_STORAGE_BUCKET_NAME

Name of the S3 Bucket used to serve the static content

Default: ''

BASE_URL

Suffix that follows the host name when accessing OnTask once deployed. This is to allow OnTask to be deployed as part of a larger web server when the application is accessed as, for example, hostname.com/suffix/ontask .

Default: ''

CANVAS_INFO_DICT

A dictionary with elements pairs containing the identifier for a Canvas instance that will be shown to the user and a dictionary with the following configuration parameters:

  • domain_port : A string containing the domain and port (if needed) of the Canvas host.

  • client_id : This value is provided by the administrator of the Canvas instance once permission to use the API has been granted.

  • client_secret : This value is provided together with the client_id once the permission to use the API is granted. It is typically a large random sequence of characters.

  • authorize_url : URL template to access the first step of the authorization. This is usually https://{0}/login/oauth2/auth . The string {0} is replaced internally with the value of domain_port .

  • access_token_url : URL template to access the token. This is usually https://{0}/login/oauth2/token . The string {0} is replaced internally with the value of domain_port .

  • conversation_URL : Similar to the previous two values, it is the entry point in the API to create a conversation (equivalent to send an email). This is usually https://{0}/api/v1/conversations . The string {0} is replaced internally with the value of domain_port .

  • aux_params : A dictionary with additional parameters. The dictionary may include a value for the key burst to limit the number of consecutive API invocations (to prevent throttling) and a value for the key pause with the number of seconds to separate bursts. Here is an example of the definition of this variable in the local.env file:

    CANVAS_INFO_DICT = {
        "Server one":
            {"domain_port": "yourcanvasdomain.edu",
             "client_id": "10000000000001",
             "client_secret": "YZnGjbkopt9MpSq2fujUO",
             "authorize_url": "http://{0}/login/oauth2/auth",
             "access_token_url": "http://{0}/login/oauth2/token",
             "conversation_url": "http://{0}/api/v1/conversations",
             "aux_params": {"burst": 10, "pause": 5}}
     }
    

Make sure you include this informtion all in a single line in the configuration file .

Default: {} (Empty dictionary)

CANVAS_TOKEN_EXPIRY_SLACK

The number of seconds to renew a token before it expires. For example, if the variable is 300, any API call performed with a token five minutes before it expires will prompt a token refresh.

Default: 600

DATABASE_URL Required

URL encoding the connection to the database. String of the format postgres://username:password@host:port/database

DATAOPS_CONTENT_TYPES

Content types allowed to be uploaded

Default: ["text/csv", "application/json", "application/gzip", "application/x-gzip", "application/vnd.ms-excel"]

DATAOPS_MAX_UPLOAD_SIZE Change does not require reset

Maximum file size for uploads

Default: 209715200 (200 Mb)

DATAOPS_PLUGIN_DIRECTORY Change does not require reset

Folder in the local file system containing the OnTask plugins.

Default: lib/plugins

DEBUG

Flag to control if the execution is in DEBUG mode.

Default: False

EMAIL_ACTION_NOTIFICATION_SENDER Required, Change does not require reset

Value to use in the sender field for emails notifying the execution of an action

EMAIL_ACTION_NOTIFICATION_SUBJECT Change does not require reset

Value to use in the subject field for emails notifying the execution of an action

Default: OnTask: Action executed

EMAIL_ACTION_NOTIFICATION_TEMPLATE Change does not require reset

Email template used to notify the execution of an action.

Default:

<html><head/><body>
<p>Dear {{ user.name }}</p>

<p>This message is to inform you that on {{ email_sent_datetime }}
{{ num_messages }} email{% if num_messages > 1 %}s{% endif %} were sent
resulting from the execution of the action with name "{{ action.name }}".</p>

{% if filter_present %}
<p>The action had a filter that reduced the number of messages from
{{ num_rows }} to {{ num_selected }}.</p>
{% else %}
<p>All the data rows stored in the workflow table were used.</p>
{% endif %}

Regards.
The OnTask Support Team
</body></html>``
EMAIL_BURST

Number of consecutive emails to send before pausing (to adapt to potential throttling of the SMTP server)

Default: 0

EMAIL_BURST_PAUSE

Number of seconds to wait between bursts.

Default: 0

EMAIL_HOST

Host providing the SMTP service.

Default: ''

EMAIL_HOST_USER

User account to log into the email host

Default: ''

EMAIL_HOST_PASSWORD

Password for the account to log into the email host

Default: ''

EMAIL_HTML_ONLY

Send HTML text only, or alternatively, send text and HTML as an attachment

Default: True (send HTML only)

EMAIL_OVERRIDE_FROM Change does not require reset

Send messages using this address in the From field

Default: '' (Use the user email)

EMAIL_PORT

Port to communicate with the host

Default: ''

EMAIL_USE_SSL

Boolean stating if the communication should use SSL

Default: False

EMAIL_USE_TLS

Boolean stating if the communication should use TLS

Default: False

EXECUTE_ACTION_JSON_TRANSFER

Boolean stating if the JSON transfers should be executed when sending personalized text.

Default: False

LANGUAGE_CODE

Official ISO 639-1 language code to use in the platform. Check the available languages in the file base.py.

Default: en-us

LDAP_AUTH_SERVER_URI

URI pointing to the LDAP server (only if LDAP is configured)

Default: ''

LDAP_AUTH_BIND_PASSWORD

Password to connect to the LDAP server (only if LDAP is configured)

Default: ''

LOG_FOLDER

Folder where to store the logs produced by the tool

Default: logs folder at the root of the project

LOGS_MAX_LIST_SIZE

Maximum number of logs shown to the user

Default: 200

LTI_OAUTH_CREDENTIALS

Dictionary with credentials required for LTI authentication (if configured)

Default: {}

LTI_INSTRUCTOR_GROUP_ROLES

List with the roles used to identify instructors

Default: ['Instructor']

MEDIA_LOCATION

URL suffix to be used by OnTask to access the media files in folder media .

Default: /media/

ONTASK_HELP_URL Change does not require reset

Relative URL suffix for the documentation (with respect to the static URL)

Default: html/index.html

REDIS_URL Required

List of URLs to access the cache service for OnTask. If there are several of these services, they can be specified as a comma-separated list such as 'rediscache://master:6379,slave1:6379,slave2:6379/1' (see Django Environ )

Default: rediscache:://localhost:6379??client_class=django_redis.client.DefaultClient&timeout=1000&key_prefix=ontask

SECRET_KEY Required

Random string of characters used to generate internal hashes. It should be kept secret. If not defined the platform will raise an error upon start.

SESSION_CLEANUP_CRONTAB

Crontab string specifying the frequency to run the cleansessions command.

Default ‘05 5 6 * *’

SHOW_HOME_FOOTER_IMAGE

Boolean to control the appearance of a footer image in the home page. If true, the file footer_image.gif is shown from the media folder.

Default: False

STATIC_URL_SUFFIX

URL suffix to be used by OnTask to access the static files. This definition is ignored if AWS_ACCESS_KEY_ID is defined as it is assumed that the static content is served through AWS. Make sure this value is not terminated by a slash.

Default: static

TIME_ZONE

String provided by the package pytz to identify the time zone in which the server is running. If you want to know the name of the time zone used by your platform execute the following command:

python3 -c 'import tzlocal; print(tzlocal.get_localzone().zone)'

Default: UTC

USE_SSL

Boolean to control if the server should use SSL for communication. There are several security features that are enabled with using SSL.

Default: False

2.2.1.2. Configuration file

Using a plain text editor create a file with name local.env in folder settings (or a file with the name assigned to the environment variable ENV_FILENAME as described in Configuration variables ). Include in this file the assignment of a variable from those described in Configuration variables .

Here is an example of a minimalistic configuration file (note there is no space between variable names and the equal signs):

ALLOWED_HOSTS=HOSTNAME1,HOSTNAME2
BASE_URL=''
# syntax: DATABASE_URL=postgres://username:password@127.0.0.1:5432/database
DATABASE_URL=postgres://[PSQLUSERNAME]:[PSQLPWD]@127.0.0.1:5432/ontask
DEBUG=False
EXECUTE_ACTION_JSON_TRANSFER=True
REDIS_URL=[YOUR REDIS URL]
TIME_ZONE=[YOUR LOCAL PYTHON TIME ZONE]
USE_SSL=True
SECRET_KEY=[SEE BELOW]
  1. Replace HOSTNAME1 , HOSTNAME2 with a comma-separated list of hostnames of the platform hosting the tool.

  2. If OnTask is going to be served from a location different from the root of your server (for example myhost.com/ontask , then modify the value of the variable BASE_URL with the suffix that should follow the domain name (in the example, /ontask ).

  3. Modify the line starting with DATABASE_URL= and change the field [PSQLUSERNAME] with the name of the Postgresql user created in the previous step (the one that could access the ontask database and run queries). If you decided to use a different name for the database, adjust the last part of the line accordingly (replace ontask by the name of your database).

  4. Replace the string [YOUR REDIS URL] with the URL where Redis can be accessed. This is typically something similar to redis://127.0.0.1:6379/1 .

  5. Replace [YOUR LOCAL PYTHON TIME ZONE] with the description of your time zone (see the definition of the variable TIME_ZONE in Configuration variables .

  6. Open a command interpreter and execute the following python command:

    python3 -c 'import random; import string; print("".join([random.SystemRandom().choice(string.digits + string.ascii_letters + string.punctuation) for i in range(100)]))'
    

    Copy the long string produced as output and add it at the end of the last line of the file . It should look something like (with different content after the equal sign):

    SECRET_KEY=4o93jf0572094jv...
    

The configuration file may include additional variables to configure functionality such as IMS LTI , LDAP Authentication , Email configuration , or Canvas Email Configuration .

2.2.1.3. Configuration script

The are some additional configuration variables that directly defined in the modules base.py , development.py and production.py in the folder settings . Modify the python code to perform additional configuration considering:

  1. The script base.py is always executed first

  2. The choice between develoment.py or production.py is decided based on the environment variable DJANGO_SETTINGS_MODULE and the default value is production.py

2.2.1.4. Log directory

Create a new folder with name logs in the OnTask top folder, next to the requirements folder, or in the location defined in the variable LOG_FOLDER . This folder is different from the folder with the same name in the ontask folder.

2.2.2. OnTask Installation

Once you have OnTask installed and configured and the tools Redis and Postgresql running, the next steps create the documentation, initial database configuration, additional site files, and deploy. To generate the documentation go to the folder docs , make sure it contains the sub-folders with names _static and _templates and execute the command:

make clean html copy_to_docs

The documentation is created by the application sphinx-doc and stored in the directory _build which is then copied to the ../static folder. Once the documentation has been created, the next steps configure the database. If at some point during the following steps you want to reset the content of the database, run the commands dropdb and createdb explained in Install and Configure PostgreSQL . The following commands have to be execute from the project folder.

  1. Execute the following command to create/update the database structure:

    python3 manage.py migrate
    

    A few messages should appear on the screen related to the initialization of the database.

  2. Execute the following command to upload to the platform some initial data structures:

    python3 manage.py initialize_db
    

    The command should run without any error or exception. If you need to create additional users before deploying the platform, read the section Creating users in Bulk .

  3. Execute the command to create a superuser account in OnTask:

    python3 manage.py createsuperuser
    

    Remember the data that you enter in this step so that you use it when you enter OnTask with your browser.

  4. Execute the following command to collect and install the static content:

    python3 manage.py collectstatic
    

    The static files are collected from the folder in the main project older with the name stored in the variable STATIC_URL_SUFFIX and placed, together with the static content from the folder ontask/static in the folder <base_dir>/site/static . This last folder is the only one that contains all the required files to be served statically by the application. Following the suggestions given in the Django project, the content in this folder should be served directly by the web server and not through the WSGI interface. The typical approach for this is to synchronize the content of this folder with the location from where the server takes the files. Make sure you do not make any changes to the folders <base_dir>/static or <base_dir>/ontask/static as they only contain a subset of the files.

  5. If you are running a production instance, execute the following command to check the status of the platform:

    python3 manage.py check --deploy
    

    The command should print just one warning about the configuration variable X_FRAME_OPTIONS. If you are running a development instance, you will get various additional warning that are derived most of them from running the instance without HTTPS.

  6. Execute the following command to start the OnTask server:

    python3 manage.py runserver
    

    If there are no errors, the message on the screen should say that your server is running in the url 127.0.0.1:8000. However, if you open your browser in that URL, an error will be shown. This error is normal and it is because the production version requires the pages to be served through SSL with a valid certificate in a conventional server.

  7. If OnTask is going to be accessed through a web server like Apache or Nginx, stop the application and configure the web server accordingly.

  8. If you want to use the server in development mode through the URL 127.0.0.1:8000 you have to perform two more steps. First, edit the file manage.py and change these three lines to look like:

    os.environ.setdefault("DJANGO_SETTINGS_MODULE", "settings.development")
    

    Second, execute the following command from the project folder:

    python3 -m pip install -r requirements/development.txt
    

    Now, the command:

    python3 manage.py runserver
    

    will start the server in the URL 127.0.0.1:8000 and you should be able to access it normally with the browser.

    Warning

    The development version of OnTask is not suited to be used in production because it disables several security features. Make sure you only deploy a production version.

2.2.3. Configure the Distributed Task Queue

There are various tasks that need to be executed by OnTask outside the web server. The solution adopted is to use Celery , Supervisor (a process control system) and Redis . Redis has been configured in a previous step. This section explains how to set up the distributed task queue and make sure it is continuously executing in parallel with the web server.

  1. Install the application supervisor using pip :

    python3 -m pip install supervisor
    

    This application makes sure the task queue program Celery is continuously running in the background and in communication with the server.

  2. Check that the binaries supervisord , supervisorctl and celery are installed in your system.

  3. Go to the folder supervisor in the top of the project and edit the file supervisor.conf .

  4. The file configures supervisord to run in the background and prepare two sets of processes for OnTask. You have two options to use this file:

    1. Use environment variables.

      The file uses internally the value of two environment variables:

      • PROJECT_PATH : Full path to the root of the project (the top folder containing the file LICENSE .

      • CELERY_BIN : Full path to the executable celery in your system (typically /usr/local/bin/celery or similar).

      • Set these variables in your environment to the correct values and make sure they are properly exported and visible when running other commands. For example, in bash , this operation would be achieve by two commands similar to:

        $ export PROJECT_PATH=/full/path/to/OnTask/root/folder
        $ export CELERY_BIN=/full/path/to/celery/executable
        
    2. Change the file supervisor.conf .

      • replace any appearance of the string %(ENV_PROJECT_PATH)s by the full path to the project folder.

      • replace any appearance of the string %(ENV_CELERY_BIN)s by the full path to the celery binary program.

  1. Start the process control system with the command:

    $ supervisord -c supervisor.conf
    

    The command starts the process control application supervisord which executes a set of process in the background.

  2. Check that the process control system is working with the command (executed from the supervisor folder):

    $ supervisorctl -c supervisor.conf status
    

    The output of this command should show a message similar to:

    ontask-beat-celery               RUNNING   pid 28579, uptime 1 day, 0:07:36
    ontask-celery                    RUNNING   pid 28578, uptime 1 day, 0:07:36
    

    If the status of the two processes is STARTING wait a few seconds and execute the command again. The names ontask-beat-celery and ontask-celery are the names of the two processes that OnTask uses for asynchronous task execution.

    You may use this command to check if supervisord is still running. The application is configured to write its messages to the file celery.log in the logs folder at the top of the project.

  3. If you are upgrading OnTask from a previous version (less than 2.8), you need to edit the crontab entry and remove the command to execute the script scheduler_script.py .