148 lines
4.7 KiB
Markdown
148 lines
4.7 KiB
Markdown
# Battlesnake Python Starter Project
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An official Battlesnake template written in Python. Get started at [play.battlesnake.com](https://play.battlesnake.com).
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This project is a great starting point for anyone wanting to program their first Battlesnake in Python. It can be run locally or easily deployed to a cloud provider of your choosing. See the [Battlesnake API Docs](https://docs.battlesnake.com/api) for more detail.
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## Technologies Used
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This project uses [Python 3](https://www.python.org/) and [Flask](https://flask.palletsprojects.com/). It also comes with an optional [Dockerfile](https://docs.docker.com/engine/reference/builder/) to help with deployment.
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## Run Your Battlesnake
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Install dependencies using pip
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```sh
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pip install -r requirements.txt
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```
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Start your Battlesnake
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```sh
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python main.py
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```
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You should see the following output once it is running
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```sh
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Running your Battlesnake at http://0.0.0.0:8000
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* Serving Flask app 'My Battlesnake'
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* Debug mode: off
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```
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Open [localhost:8000](http://localhost:8000) in your browser and you should see
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```json
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{"apiversion":"1","author":"","color":"#888888","head":"default","tail":"default"}
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```
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## Play a Game Locally
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Install the [Battlesnake CLI](https://github.com/BattlesnakeOfficial/rules/tree/main/cli)
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* You can [download compiled binaries here](https://github.com/BattlesnakeOfficial/rules/releases)
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* or [install as a go package](https://github.com/BattlesnakeOfficial/rules/tree/main/cli#installation) (requires Go 1.18 or higher)
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Command to run a local game
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```sh
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battlesnake play -W 11 -H 11 --name 'Python Starter Project' --url http://localhost:8000 -g solo --browser
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```
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## Next Steps
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Continue with the [Battlesnake Quickstart Guide](https://docs.battlesnake.com/quickstart) to customize and improve your Battlesnake's behavior.
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## Included Competitive Snake
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This repo now includes `snakes/BestBattleSnake.py`, a stronger default snake that combines:
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- collision and head-to-head risk checks
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- flood-fill space evaluation to avoid traps
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- food routing that gets more aggressive as health drops
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- tail access checks for better long-term survival
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Run it explicitly with:
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```sh
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SNAKE=BestBattleSnake python main.py
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```
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Optional duel tuning (when only 2 snakes are alive):
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```sh
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BATTLE_SNAKE_DUEL_STYLE=balanced python main.py
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```
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Allowed values: `safe`, `balanced`, `aggressive`.
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## Export Training Dataset
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Game saves now include a `dataset` section with labeled move samples.
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Export all stored samples to JSONL:
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```sh
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python -m server.DatasetExporter --input data --output data/dataset/good_moves.jsonl
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```
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Or with `just`:
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```sh
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just export-dataset
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```
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Curate a high-quality training subset (single file):
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```sh
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python -m server.DatasetCurator --input good_moves-2026-04-03.jsonl --output data/dataset/best_moves.jsonl
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```
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Curate from multiple JSONL sources (repeat `--input`):
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```sh
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python -m server.DatasetCurator \
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--input good_moves-2026-04-03.jsonl \
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--input good_moves-2026-04-04.jsonl \
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--output data/dataset/best_moves.jsonl
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```
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Curate from folder or glob:
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```sh
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python -m server.DatasetCurator --input data/dataset --output data/dataset/best_moves.jsonl
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python -m server.DatasetCurator --input "good_moves-*.jsonl" --output data/dataset/best_moves.jsonl
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```
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Append mode (keeps existing curated rows and deduplicates against them):
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```sh
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python -m server.DatasetCurator --input "good_moves-*.jsonl" --output data/dataset/best_moves.jsonl --append
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```
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Archive processed input files after curation:
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```sh
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python -m server.DatasetCurator --input "good_moves-*.jsonl" --output data/dataset/best_moves.jsonl --append --archive-input
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python -m server.DatasetCurator --input "good_moves-*.jsonl" --output data/dataset/best_moves.jsonl --append --archive-input --archive-dir data/dataset/archive
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```
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Or with `just`:
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```sh
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just curate-dataset
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just curate-dataset append=true
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just curate-dataset append=true archive=true archive_dir=data/dataset/archive
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```
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To store compact dataset-only records (JSONL) and skip full per-game JSON files:
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```sh
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STORE_DATASET_ONLY=true DATASET_JSONL_PATH=data/dataset/good_moves.jsonl python main.py
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```
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Optional compact storage tuning:
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- `DATASET_ROTATE_DAILY=true` creates one JSONL file per day (default: `true`)
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- `DATASET_JSONL_MAX_MB=50` rotates when file reaches max size in MB (default: `50`)
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- `DATASET_COMPRESS_ROTATED=true` gzip-compresses rotated/old JSONL files (default: `true`)
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**Note:** To play games on [play.battlesnake.com](https://play.battlesnake.com) you'll need to deploy your Battlesnake to a live web server OR use a port forwarding tool like [ngrok](https://ngrok.com/) to access your server locally.
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