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A Slack bot that understands the Emojirades game!

Project description

emojirades

Slack bot that understands the emojirades game and handles score keeping

Build Status PyPI version

Installation Guide

# Preferably run on a virtualenv

Install the dependencies

pip3 install --upgrade pip wheel

pip3 install -r requirements.txt --upgrade

# If you're developing locally
pip3 install -r test_requirements.txt --upgrade

Install the module ( For Dev )

cd emojirades
pip3 install -e .

Run the tests

black .
pytest

Set environment variables

If you're using the built in AWS functionality to persist your data, you'll need to set the appropriate AWS_ environment variables.

Run the daemon for a single workspace

This command uses locally stored files to keep the game state:

emojirades single --score-file scores.csv --state-file state.json --auth-file auth.json

This command uses S3 stored files to keep the game state:

`emojirades single --score-file s3://bucket/scores.csv --state-file s3://bucket/state.json --auth-file s3://bucket/auth.json

Run the daemon for multiple workspaces

Here we provide a local folder of workspaces and an optional set of workspace ids (will load all in folder by default):

emojirades mulitple --workspaces-dir path/to/workspaces [--workspace-id A1B2C3D4E]

Here we provide an S3 path of workspaces and an optional set of workspace ids (will load all in folder by default):

emojirades multiple --workspaces-dir s3://bucket/path/to/workspaces [--workspace-id A1B2C3D4E]

Here we provide an S3 path of workspaces and an AWS SQS queue to listen to for new workspaces:

emojirades multiple --workspaces-dir s3://bucket/path/to/workspaces --onboarding-queue workspace-onboarding-queue

The workspaces directory must be in the following format (local or s3):

./workspaces

./workspaces/shards
./workspaces/shards/0
./workspaces/shards/0/A1B2C3D4E.json
./workspaces/shards/0/Z9Y8X7W6V.json

./workspaces/directory
./workspaces/directory/A1B2C3D4E
./workspaces/directory/A1B2C3D4E/state.json
./workspaces/directory/A1B2C3D4E/scores.json
./workspaces/directory/A1B2C3D4E/auth.json
./workspaces/directory/Z9Y8X7W6V
./workspaces/directory/Z9Y8X7W6V/state.json
./workspaces/directory/Z9Y8X7W6V/scores.json
./workspaces/directory/Z9Y8X7W6V/auth.json

The concept above with the two different directories is shards to allow for the bot to scale out horizontally. As the bot(s) get busier, the operator can increase the shard (bot instance) count and new onboarded workspaces are allocated to the next available shard with capacity.

The emojirades bot will take care of running multiple games across different channels in a single workspace.

Service configuration

cp emojirades.service /etc/systemd/system/
sudo chmod 0664 /etc/systemd/system/emojirades.service

# Edit the /etc/systemd/system/emojirades.service file and update the user and group

cp emojirades.config /etc/emojirades
sudo chmod 0400 /etc/emojirades

# Edit the /etc/emojirades config file with your configuration for the bot

sudo systemctl daemon-reload
sudo systemctl enable emojirades
sudo systemctl start emojirades

Release process (for master branch)

  1. Create release branch containing new version in setup.py and Dockerfile
  2. Perform a PR into master
  3. Perform release in GitHub
  4. TravisCI will automatically build and deploy on a tagged commit into master (the release does this)
  5. Docker Hub will automatically build and deploy on a tagged commit into master (the release does this)

Building the Container Image

docker build --pull --no-cache -t emojirades/emojirades:X.Y.Z -t emojirades/emojirades:latest .

Running the Container

In this example we run the game with S3 hosted configuration for a single workspace.

docker run -d \
  --name emojirades \
  --restart=always \
  -v "/path/to/your/.aws/:/root/.aws/:ro" \
  -e "AWS_PROFILE=emojirades" \
  emojirades/emojirades:X.Y.Z \
    --score-file s3://bucket/path/to/scores.json \
    --state-file s3://bucket/path/to/state.json \
    --auth-file s3://bucket/path/to/auth.json \
    -vv

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