https://towardsdatascience.com/dockerize-your-dash-app-1e155dd1cea3
docker compose -f docker-compose-dev.yml build
docker compose -f docker-compose-dev.yml up
You must use this method. Do not try to directly by setting up a virtualenv with the requirements.txt
This uses components of the e-mission-server core, so it must have the e-mission-server modules in the PYTHONPATH
The easiest method to accomplish this is to use the docker container, which is built on top of the e-mission-server base docker container.
docker-compose -f docker-compose-prod-nginx.yml build
docker-compose -f docker-compose-prod-nginx.yml up -dThe dash component assumes that it is running from the host root, and will barf if you try to run it behind a reverse proxy with a different file prefix. This setting tests that configuration using an embedded reverse proxy in the docker container.
The CONFIG_PATH environment variable is used to specify the location of the configuration files that are required for
a Docker container to run properly. This means that the Docker container will attempt to download the configuration
files from the specified URL. The current path to the raw format of nrel configs is:
https://raw.githubusercontent.com/e-mission/nrel-openpath-deploy-configs/main/configs/
The STUDY_CONFIG environment variable is used to specify the name of the study or program that is being run inside the
Docker container. This variable is typically used by the application running inside the container to differentiate
between different studies or programs.
Note that the STUDY_CONFIG variable can be set to any string value, and should be set to a unique value for each
separate study or program.
The following document outlines the permissions that a user can have within the dashboard application. The permission
is specified as a key-value pair, where the key is the name of the permission and the value is either true or false.
If the value is true, the user has access to the corresponding feature or data, and if the value is false, the user
does not have access. You need to place these key-value pairs within the admin_dashboard key in one of the configs of
the emission.
These are all the permissions that you can specify:
overview_users: User can see the total number of users in the Overview page.overview_active_users: User can see the number of active users in the Overview page.overview_trips: User can see the number of trips in the Overview page.overview_signup_trends: User can view the signup trend graph in the Overview page.overview_trips_trend: User can view the trip trend graph in the Overview page.data_uuids: User can view the UUIDs data in the Data page.data_trips: User can view the trips data in the Data page.data_demographics: User can view the demographics data in the Data page.data_trajectories: User can view the trajectories data in the Data page.data_trips_columns_exclude: It used to specify a list of column names that should be excluded from the trips data
that is displayed on the Data page. It includes valid columns from the Stage_analysis_timeseries collection. Valid
columns are specified in the following sections.data_uuids_columns_exclude: It used to specify a list of column names that should be excluded from the uuids data
that is displayed on the Data page. It includes valid columns from the Stage_uuids collection. Valid columns are
specified in the following sections.data_demographics_columns_exclude: It used to specify a list of column names that should be excluded from the demographics data
that is displayed on the Data page. data_trajectories_columns_exclude: It used to specify a list of column names that should be excluded from the trajectories data
that is displayed on the Data page.token_generate: User can generate new tokens in the Token page.token_prefix: The prefix that will be added to all tokens when creating new tokens.map_heatmap: User can view the heatmap in the Map page.map_bubble: User can view the bubble map in the Map page.map_trip_lines: User can view the trip lines map in the Map page.segment_trip_time: User can view this page. (default true)segment_trip_time_full_trips: User can see the table containing non-aggregated data (default true)segment_trip_time_min_users: Minimal number of distinct users in data required to display anything (value is a number, default 0).push_send: User can send push notifications in the Push Notification page.options_uuids: User can see the UUIDs of users in dropdowns and choose between them.options_emails: User can see the emails of users in dropdowns and choose between them.
This document represents a single row in a MongoDB collection. The document contains a single object of a uuid with the
following fields that you can provide in data_uuids_columns_exlude:
valid_uuids_columns = [
'user_token',
'user_id',
'update_ts',
]It contains information about a segmentation trip. It has the following fields that you can provide in
data_trips_columns_exclude.
valid_trip_columns = [
"data.source",
"data.start_ts",
"data.start_local_dt",
"data.start_fmt_tm",
"data.start_place",
"data.start_loc",
"data.end_ts",
"data.end_local_dt",
"data.end_fmt_time",
"data.end_place",
"data.end_loc",
"data.duration",
"data.distance",
"metadata.key",
"metadata.platform",
"metadata.write_ts",
"metadata.time_zone",
"metadata.write_local_dt",
"metadata.write_fmt_time",
"user_id",
]The AUTH_TYPE environment variable is used to specify the authentication type for the dashboard, and it is defined in the Docker Compose file. It has two possible values: "basic" and "cognito". The "basic" option refers to basic authentication, which is a simple way to authenticate users using a username and password. The "cognito" option refers to Amazon Cognito, which is a user authentication service that can be used with AWS services.
config.pyThe config.py file is a Python module that contains configuration settings for an application that uses
authentication. To use this file, first make a copy of the provided config-fake.py file and rename it to config.py.
Then, fill in the necessary variables with your own valid data.
The CognitoConfig class contains variables used for authentication when using AWS Cognito. To use this authentication
method, fill in the following variables with your credential data from your AWS Cognito panel in config.py:
CLIENT_ID: This is a string that represents the client ID of the app that is registered with the user pool. When an
app wants to authenticate with a user pool, it must provide its client_id to the user pool's authentication server.CLIENT_SECRET: This is a string that represents the client secret of the app that is registered with the user pool.
The client_secret is a secret key that is used to authenticate the app with the user pool's authentication server. It
must be kept secure and not shared with anyone who should not have access to it.REDIRECT_URL: This is a string that represents the URL that users should be redirected to after they have
authenticated with the user pool's authentication server.TOKEN_ENDPOINT: This is a string that represents the endpoint for retrieving access tokens from the user pool's
authentication server. Access tokens are used by the app to access protected resources on behalf of the authenticated
user. It is your user pool's domain plus /oauth2/token.USER_POOL_ID: This is a string that represents the ID of the user pool that the app is registered with. The user
pool is a collection of users who can authenticate with the app.REGION: This is a string that represents the AWS region where the user pool is located. For example, "us-east-1" or
"eu-west-2".AUTH_URL: This is a string that represents the URL for initiating authentication requests with the user pool's
authentication server. It is the Hosted UI of your user pool.The VALID_USERNAME_PASSWORD_PAIRS dictionary contains all the valid usernames and passwords that users can
authenticate with when using basic authentication. To use this authentication method, fill in the dictionary with your
own valid usernames and passwords in config.py.
To use the configuration settings defined in config.py, import the module at the beginning of your Python script, and
access the variables using dot notation. For example:
from config import CognitoConfig, VALID_USERNAME_PASSWORD_PAIRS
# Access the CLIENT_ID variable in CognitoConfig
client_id = CognitoConfig.CLIENT_ID
# Access the valid username and password pairs
valid_pairs = VALID_USERNAME_PASSWORD_PAIRS