anaconda-cli-base 0.8.1
A base CLI entrypoint supporting Anaconda CLI plugins
License: BSD-3-Clause
Requires Python: >=3.10

# anaconda-cli-base

A base CLI entrypoint supporting Anaconda CLI plugins using [Typer](https://github.com/fastapi/typer).

## Registering plugins

To develop a subcommand in a third-party package, first create a `typer.Typer()` app with one or more commands.
See [this example](https://typer.tiangolo.com/#example-upgrade). The commands defined in your package will be prefixed
with the *subcommand* you define when you register the plugin.

In your `pyproject.toml` subcommands can be registered as follows:

```toml
# In pyproject.toml

[project.entry-points."anaconda_cli.subcommand"]
auth = "anaconda_auth.cli:app"
```

In the example above:

* `"anaconda_cli.subcommand"` is the required string to use for registration. The quotes are important.
* `auth` is the name of the new subcommand, i.e. `anaconda auth`
  * All `typer.Typer` commands you define in your package are accessible the registered subcommand
  * i.e. `anaconda auth <command>`.
* `anaconda_auth.cli:app` signifies the object named `app` in the `anaconda_auth.cli` module is the entry point for the subcommand.

### Error handling

By default any exception raised during CLI execution in your registered plugin will be caught and only a minimal
message will be displayed to the user.

You can define a custom callback for individual exceptions that may be thrown from your subcommand. You can
register handlers for standard library exceptions or custom defined exceptions. It may be best to use custom
exceptions to avoid unintended consequences for other plugins.

To register the callback decorate a function that takes an exception as input, and return an integer error code.
The error code will be sent back through the CLI and your subcommand will exit with that error code.

```python
from typing import Type
from anaconda_cli_base.exceptions import register_error_handler

@register_error_handler(MyCustomException)
def better_exception_handling(e: Type[Exception]) -> int:
    # do something or print useful information
    return 1

@register_error_handler(AnotherException)
def just_ignore_it(e: Type[Exception])
    # ignore the error and let the CLI exit successfully
    return 0


@register_error_handler(YetAnotherException)
def fix_the_error_and_try_again(e: Type[Exception]) -> int:
    # do something and retry the CLI command
    return -1
```

In the second example the handler returns `-1`. This means that the handler has attempted to correct the error
and the CLI subcommand should be re-tried. The handler could call another interactive command, like a login action,
before attempting the CLI subcommand again.

See the [anaconda-auth](https://github.com/anaconda/anaconda-auth/blob/main/src/anaconda_auth/cli.py) plugin for an example custom handler.

### Config file

If your plugin wants to utilize the Anaconda config file, default location `~/.anaconda/config.toml`, to read configuration
parameters you can derive from `anaconda_cli_base.config.AnacondaBaseSettings` to add a section in the config file for
your plugin.
 Each subclass of `AnacondaBaseSettings`
defines the section header. The base class is configured so that parameters defined in subclasses can be read in the
following priority from lowest to highest.

1. default value in the subclass of `AnacondaBaseSettings`
1. Global config file at ~/.anaconda/config.toml
1. `ANACONDA_<PLUGIN-NAME>_<FIELD>` variables defined in the .env file in your working directory
1. A file named `/run/secrets/anaconda_<plugin-name>_<field>`, usually populated by a mounted
   [Docker secret](https://docs.docker.com/engine/swarm/secrets/)
1. `ANACONDA_<PLUGIN-NAME>_<FIELD>` env variables set in your shell or on command invocation
1. value passed as kwarg when using the config subclass directly

Notes:

* `AnacondaBaseSettings` is a subclass of `BaseSettings` from [pydantic-settings](https://docs.pydantic.dev/latest/concepts/pydantic_settings/#usage).
* Nested pydantic models are also supported.
* Per pydantic defaults, both secret filenames and environment variables
  may be uppercase or lowercase.

Here's an example subclass:

```python
from anaconda_cli_base.config import AnacondaBaseSettings

class MyPluginConfig(AnacondaBaseSettings, plugin_name="my_plugin"):
    foo: str = "bar"
```

To read the config value in your plugin according to the above
priority:

```python
config = MyPluginConfig()
assert config.foo == "bar"
```

Since there is no value of `foo` in the config file it assumes the default value from the subclass definition.

The value of `foo` can now be written to the config file under the section `my_plugin`

```toml
# ~/.anaconda/config.toml
[plugin.my_plugin]
foo = "baz"
```

Now that the config file has been written, the value of `foo` is read from the
config.toml file:

```python
config = MyPluginConfig()
assert config.foo == "baz"
```

### Nested tables

The AnacondaBaseSettings supports nested Pydantic models.

```python
from anaconda_cli_base.config import AnacondaBaseSettings
from pydantic import BaseModel

class Nested(BaseModel):
    n1: int = 0
    n2: int = 0

class MyPluginConfig(AnacondaBaseSettings, plugin_name="my_plugin"):
    foo: str = "bar"
    nested: Nested = Nested()
```

In the `~/.anaconda/config.toml` you can set values of nested fields as an in-line table

```toml
# ~/.anaconda/config.toml
[plugin.my_plugin]
foo = "baz"
nested = { n1 = 1, n2 = 2}
```

Or as a separate table entry

```toml
# ~/.anaconda/config.toml
[plugin.my_plugin]
foo = "baz"

[plugin.my_plugin.nested]
n1 = 1
n2 = 2
```

To set environment variables use the `__` delimiter

```bash
ANACONDA_MY_PLUGIN_NESTED__N1=1
ANACONDA_MY_PLUGIN_NESTED__N2=2
```

### Nested plugins

You can pass a tuple to `plugin_name=` in subclasses of `AnacondaBaseSettings` to nest whole plugins,
which may be defined in separate packages.

```python
class Nested(BaseModel):
    n1: int = 0
    n2: int = 0
class MyPluginConfig(AnacondaBaseSettings, plugin_name="my_plugin"):
    foo: str = "bar"
    nested: Nested = Nested()
```

Then in another package you can nest a new config into `my_plugin`.

```python
class MyPluginExtrasConfig(AnacondaBaseSettings, plugin_name=("my_plugin", "extras")):
    field: str = "default"
```

The new config table is now nested in the config.toml

```toml
# ~/.anaconda/config.toml
[plugin.my_plugin]
foo = "baz"
nested = { n1 = 1, n2 = 2}
[plugin.my_plugin.extras]
field = "value"
```

And can be set by env variable using the concatenation of `plugin_name`

```bash
ANACONDA_MY_PLUGIN_EXTRAS_FIELD="value"
```

### Writing configuration

Plugin configurations can be written directly from subclasses of `AnacondaBaseSettings` with the
`.write_config()` member method. This method takes two arguments

* `preserve_existing_keys`:
  * If True (default) updates to existing keys in the
    config.toml file, will not remove the key if set to the default
    value. If False fields set to default value are removed from the file
* `dry_run`:
  * If True, displays a diff of proposed changes without writing
    to the file. If False (default), writes changes to config.toml.

Here are some key aspects of writing configuration

* `.write_config()` will only update changed lines in the config.toml preserving all existing configuration and comments
* toml does not support `None` or `null`, any field set to the value `None` will not be written to the config.toml
* fields set to their default value are not written to the config.toml
  * Except when an existing key in the config.toml is updated to its default value. The key will still be written
  * This is disabled with `preserve_existing_keys=False`

Let's start with the plugin defined earlier and an instance of the config object with all default values

```python
from anaconda_cli_base.config import AnacondaBaseSettings
from pydantic import BaseModel

class Nested(BaseModel):
    n1: int = 0
    n2: int = 0

class MyPluginConfig(AnacondaBaseSettings, plugin_name="my_plugin"):
    foo: str = "bar"
    nested: Nested = Nested()


config = MyPluginConfig()
```

If there is either no config.toml or the existing file does not have the `[plugin.my_plugin]` table attempting
to write the current state of the config will just add the table header since all values are default. Here is an
example of the `dry_run` output in the case where the config.toml file did not exist

```text
>>> config.write_config(dry_run=True)
--- ~/.anaconda/config.toml
+++ ~/.anaconda/config.toml 01-06-26 09:40
@@ -0,0 +1 @@
+[plugin.my_plugin]
```

You can change the configuration either by passing kwargs to the initialization or by directly updating attributes.

```python
config.foo = "baz"
config.nested.n1 = 1
config.nested.n2 = 2
```

this will now write the configuration equivalent to what you saw above

```text
>>> config.write_config(dry_run=True)
--- ~/.anaconda/config.toml
+++ ~/.anaconda/config.toml 01-06-26 09:44
@@ -0,0 +1,6 @@
+[plugin.my_plugin]
+foo = "baz"
+
+[plugin.my_plugin.nested]
+n1 = 1
+n2 = 2
```

Now with that configuration written to disk (using `dry_run=False`) we can re-read the configuration to confirm
the change.

```text
>>> config = MyPluginConfig()
>>> print(config)
foo='baz' nested=Nested(n1=1, n2=2)
```

Let's change `foo` back to its default value. We can do that either by setting the attribute `config.foo = "bar"` or
by passing a kwarg to override the config.toml.

The dry-run output now only changes the `foo` key in the config.toml leaving all other lines unchanged

```text
>>> config = MyPluginConfig(foo="bar")
>>> config.write_config(dry_run=True)
--- ~/.anaconda/config.toml 01-06-26 09:53
+++ ~/.anaconda/config.toml 01-06-26 09:56
@@ -1,5 +1,5 @@
 [plugin.my_plugin]
-foo = "baz"
+foo = "bar"

 [plugin.my_plugin.nested]
 n1 = 1
```

If instead we wish to remove keys when set to their default value pass the `preserve_existing_keys=False` argument

```text
>>> config.write_config(dry_run=True, preserve_existing_keys=False)
--- ~/.anaconda/config.toml 01-06-26 09:53
+++ ~/.anaconda/config.toml 01-06-26 09:57
@@ -1,5 +1,4 @@
 [plugin.my_plugin]
-foo = "baz"

 [plugin.my_plugin.nested]
 n1 = 1
```

See the [tests](https://github.com/anaconda/anaconda-cli-base/blob/main/tests/test_config.py) for more examples of reading and writing plugin configuration.

## Setup for development

Ensure you have `conda` installed.
Then run:

```shell
make setup
```

### Run the unit tests

```shell
make test
```

### Run the unit tests across isolated environments with tox

```shell
make tox
```