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@ -14,6 +14,10 @@ data: ## Create dataset
help: ## Show all available commands
@awk 'BEGIN {FS = ":.*##"; printf "Usage: make \033[36m<target>\033[0m\n"} /^[a-zA-Z_-]+:.*?##/ { printf " \033[36m%-36s\033[0m %s\n", $$1, $$2 } /^##@/ { printf "\n\033[1m%s\033[0m\n", substr($$0, 5) } ' $(MAKEFILE_LIST);
.PHONY: install
install: ## Install dependencies
@poetry install --no-interaction
.PHONY: run
run: ## Run the Docker image
@docker run --rm -it -p "8888:8888" ds-interview jupyter lab --collaborative --no-browser --allow-root --ip "0.0.0.0" --ServerApp.allow_remote_access true --config Xfrozen_modules=off

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@ -3,10 +3,13 @@
## Requirements
- Python 3.11 (you can change this in the `pyproject.toml` file)
- [Poetry](https://python-poetry.org/)
- [Docker](https://www.docker.com/)
- [Ngrok](https://ngrok.com/)
- [GNU Make](https://www.gnu.org/software/make/)
I recommend using [asdf](https://asdf-vm.com/) to manage your Python versions and Poetry installation.
## Usage
### Get Setup
@ -14,14 +17,14 @@
Create your local environment with
```shell
poetry install
make install
```
Ensure you have created and validated your account with [Ngrok](https://ngrok.com/).
### Make you Dataset
`src/interview/data.py` contains an example function to build the classic [Iris dataset](https://scikit-learn.org/stable/auto_examples/datasets/plot_iris_dataset.html). You can build this with
`src/interview/data.py` contains an example function to build the classic [Iris dataset](https://scikit-learn.org/stable/auto_examples/datasets/plot_iris_dataset.html). You can extend this as you see fit to create one or more custom datasets relevant to your business. There is a Poetry script to run the `make_data` function and build the dataset, which you can run with:
```shell
make data