# Tips
## Change logging level

You can change the logging level by setting the `LOG_LEVEL` environment variable. For example,

```bash
export LOG_LEVEL=DEBUG 
ai2-kit ...
```

## Use custom tags to simplify YAML configuration

`ai2-kit` implement some customized tags for YAML parser to simplify the configuration. 

### `!load_text`
`!load_text` can be used to read a file and use its content as the value of the tag. It accepts a string value or a list of strings as the argument. The strings will be joined together to form the path of the file to be read. For example,

```yaml
data: !load_text /path/to/data/data.csv
# or
data: !load_text [/path/to/data, data.csv]
```

### `!load_yaml`
`!load_yaml` is same as `!load_text` except that it will parse content of the file as a YAML document. For example,

```yaml 
data: !load_yaml /path/to/data/data.yml
data: !load_yaml /path/to/data/data.json
# or
data: !load_yaml [/path/to/data, data.yml]
data: !load_yaml [/path/to/data, data.json]
```

> Note: it also support JSON format as it is a subset of YAML.

### `!join`
`!join` can be used to join elements in a list into a single string. This is useful when you have to use a lot of absolution paths that shares the same based directory in your configuration. For example,

> Note: this is string join not path join, so you need to add `/` manually when you want to join paths.

```yaml
.data_dir: &data_dir /data/in/a/very/long/path/
data1: !join [*data_dir, data1.csv]
data2: !join [*data_dir, data2.csv]
```
which is equivalent to

```yaml
data1: /data/in/a/very/long/path/data1.csv
data2: /data/in/a/very/long/path/data2.csv
```

## Use `nglview` to visualize atoms structures in Jupyter Notebook

You can use the `ase.visualize.view` function to view atoms structures in Jupyter Notebook. If you would like to use `nglview` as your viewer, you need to take some extra steps to make it work.

```bash
# Install nglview
pip install nglview

# Enable Jupyter Notebook extension
jupyter nbextension enable --py widgetsnbextension
```