pano 2.1.0
Panoramic Command Line Tool
Requires Python: >=3.6

# Pano Data Tool

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This repository contains the Pano Data Tool. This tool allows you to create & maintain your Panoramic data models. It is built with Python 3.7+ and can be installed via PyPI or other similar tools.

## Installation

To install the CLI, use [`pip`](https://pip.pypa.io/en/stable/quickstart/) or [`pipenv`](https://docs.pipenv.org):

```console
$ pip install -U pano
```

## Usage

Once you install the tool, you can call it using `pano` on the command line. For more information, run `pano` with no commands to see the help information:

```
Usage: pano [OPTIONS] COMMAND [ARGS]...

Options:
  --debug     Enables debug mode
  --version   Show the version and exit.
  -h, --help  Show this message and exit.

Commands:
  detect-joins      Detect joins under a dataset
  field             Commands on local field files.
  init              Initialize metadata repository
  scan              Scan remote database and generates models for found objects
  validate          Validate local files
```

See docs folder for more extensive documentation.

## Release process

To release a new version of the library, follow these steps:

- In your PR, update version in [\_\_version\_\_.py](src/panoramic/cli/__version__.py) and add entry to [CHANGELOG.md](CHANGELOG.md)
- After merge, tag the commit with version number from setup.py. For example `git tag v0.1.1`.
- Once the tag is pushed, it will trigger a build with GitHub Actions, which will publish the new version on PyPI and create a release on GitHub.

## Development

### Virtual Environment Using venv

Add python virtual environment using python venv (adds `.venv` inside current directory):

```
> python3 -m venv .venv
```

Then, you can switch to it from command-line using following command:

```
> source .venv/bin/activate
```

### Virtual Environment Using pyenv

Alternatively if you use pyenv and pyenv-virtualenv, you can create virtual environment using:

```
> pyenv virtualenv pano-cli
```

And use the created virtual environment:

```
> pyenv local pano-cli
```

### Build and Run

Use following command to install dependencies (make sure you have correct python environment active):

```
> make install
```

Now you should have `pano` package available. First create config. You need to ask friendly SRE Team Member for OAuth credentials for yourself.

```
> pano configure
```

And finally you are ready to use `pano`. You can find all commands in help:

```
> pano -h
```

## Tests

Use following command to run all tests:

```
> make test
```

Use following command to run all other checks:

```
> make lint
```

Capture expectations for tests by setting environment variable `APP_WRITE_EXPECTATIONS=true`.

## Pre commit hooks

You can install pre-commit. It is useful to avoid commiting code that doesn't pass the linter. It installs git hooks that run pre-commit.

```
> make pre-commit-install
```

## Generate documentation about TEL functions

Documentation under docs folder can be generated by running

```
> make docs
```

## VSCode

You can use following debug config to run pano cli using VSCode debugger:

```
{
    "name": "Python: Pano CLI Scan",
    "type": "python",
    "request": "launch",
    "module": "panoramic.cli",
    "args": ["scan", "testsource"]
}
```