Metadata-Version: 2.1
Name: py-dactyl
Version: 2.0.4
Summary: An easy to use Python wrapper for the Pterodactyl Panel API.
Home-page: https://github.com/iamkubi/pydactyl
Author: Ryan Kubiak
Author-email: iamkubi@gmail.com
License: UNKNOWN
Project-URL: Documentation, https://pydactyl.readthedocs.io/
Project-URL: Source, https://github.com/iamkubi/pydactyl
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Requires-Python: >=3.4
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: requests (>=2.21.0)

# pydactyl

![lint-and-test]
[![Latest docs][docs-img]][docs]
[![Coverage][codecov-img]][codecov]
[![Latest version][pypi-img]][pypi]
[![Discord][discord-img]][discord-join]

An easy to use Python wrapper for the Pterodactyl Panel API.

## State of the project

Support for the Pterodactyl 1.x API is complete.
The 2.0 Pydactyl release was created to standardize how includes and params 
are passed.  As a result some endpoints (namely nests) **will break** when 
upgrading from Pydactyl 1.x to 2.0.

Pull Requests are being accepted and new endpoints will continue to be added.

If you encounter problems, find APIs that haven't been implemented, or have a
feature request please file a [Github issue][issues].

## Documentation

Generated documentation can be found at [https://pydactyl.readthedocs.io/][docs]
.

## Installing

To install with pip:

```shell
pip install py-dactyl
```

**If you get an error saying `ImportError: cannot import name 
'PterodactylClient' from 'pydactyl'` this probably means you installed the 
wrong package from pip.**

## Getting Started

**Pterodactyl has two different types of API keys: Client (also known as 
Account) and Application.**  Any user can generate an Account API key to 
control their own servers.  The Account API key for an Administrator user will
be able to access any server's Client API.

Application API keys can only be generated by administrators.  These keys can be used to create, modify, and delete servers, among other things.  They have access to any server on the panel and can be destructive, so use with care.

### Exploring the API
In addition to the documentation you can explore the interface in an 
interactive Python interpreter using built-ins like `dir()` and the
`__doc__` attribute as shown below.

```python
from pydactyl import PterodactylClient
api = PterodactylClient('debug', 'anything')

[i for i in dir(api.client.servers) if not i.startswith('_')]
# ['account', 'backups', 'databases', 'files', 'get_server', 'get_server_utilization', 'list_permissions', 'list_servers', 'network', 'schedules', 'send_console_command', 'send_power_action', 'servers', 'settings', 'startup', 'users']
[i for i in dir(api.client.servers.settings) if not i.startswith('_')]
# ['reinstall_server', 'rename_server']
print(api.client.servers.settings.rename_server.__doc__)
#Renames the server.
#        Args:
#            server_id(str): Server identifier (abbreviated UUID)
#            name(str): New name for the server
```

### Client API
The Client API or Account API is accessed by users of the Pterodactyl panel. 
Below is the layout of the Client API namespace.

```python
api.client.account
api.client.servers
api.client.servers.backups
api.client.servers.databases
api.client.servers.files
api.client.servers.network
api.client.servers.schedules
api.client.servers.settings
api.client.servers.startup
api.client.servers.users
```

A full list of methods available can be found in the [documentation][docs]. 


Below are examples of how you might get information about your servers.

```python
from pydactyl import PterodactylClient

# Create a client to connect to the panel and authenticate with your API key.
api = PterodactylClient('https://panel.mydomain.com', 'MySuperSecretApiKey')

# Get a list of all servers the user has access to
my_servers = api.client.servers.list_servers()
# Get the unique identifier for the first server.
srv_id = my_servers[0]['attributes']['identifier']

# Check the utilization of the server
srv_utilization = api.client.servers.get_server_utilization(srv_id)
print(srv_utilization)

# Turn the server on.
api.client.servers.send_power_action(srv_id, 'start')
```

### Application API
**As of Pterodactyl 1.8.0 Application API keys are deprecated and client API keys should now be used exclusively.**  

The Application API is the administrative API of the Pterodactyl panel. 
Below is the layout of the Application API namespace.

```python
api.locations
api.nests
api.nodes
api.servers
api.user
```

Below are examples of how you might use this API.

```python
from pydactyl import PterodactylClient

# Create a client to connect to the panel and authenticate with your API key.
api = PterodactylClient('https://panel.mydomain.com', 'MySuperSecretApiKey')

# Create a server.  Customize the Nest and Egg IDs to match the IDs in your panel.
# This server is created with a limit of 8000 MB of memory, no access to swap, unlimited disk space, in location_id 1.
api.servers.create_server(name='My Paper Server', user_id=1, nest_id=1,
                          egg_id=3, memory_limit=8000, swap_limit=0,
                          backup_limit=0, disk_limit=0, location_ids=[1])
< Response[201] >
```

A 201 response indicates success, however if there is a problem with the request
Pydactyl will raise an exception with additional details. When updating the
location_ids field to an invalid location it displays an error:

 ```python
api.servers.create_server(name='My Paper Server', user_id=1, nest_id=1,
                          egg_id=3, memory_limit=8000, swap_limit=0,
                          disk_limit=0, location_ids=[199])
Traceback (most recent call last):
 File "<input>", line 6, in <module>
 File "D:\code\pydactyl\pydactyl\api\servers.py", line 268, in create_server
   mode='POST', data=data, json=False)
 File "D:\code\pydactyl\pydactyl\api\base.py", line 98, in _api_request
   'code'], errors['detail'])
pydactyl.exceptions.PterodactylApiError: Bad API Request(400) - NoViableNodeException - No nodes satisfying the requirements specified for automatic deployment could be found.
```

You can use the User class to add, modify, and delete panel users.

```python
# Create a new user
result = api.user.create_user('test_user', 'test@gmail.com', 'Test', 'Name')
# Get the ID of the created user
user_id = result['attributes']['id']
# Get the user info, also returned by create_user()
api.user.get_user_info(user_id)
{'object': 'user', 'attributes': {'id': 14, 'external_id': None, .... }}
# Delete the user
api.user.delete_user(user_id=14)
```

### Includes

Pterodactyl API endpoints have different sets of includes you can pass to alter 
the response.  Using includes will cause additional information to show up 
in the relationships field of the response data.  Some endpoints have no 
includes and some have many.

Pydactyl docstrings include examples of 
valid includes for each endpoint, but they are **not an exhaustive list**.

```
server_includes = [
    'allocations', 'user', 'subusers', 'pack', 'nest', 'egg', 'variables',
    'location', 'node', 'databases']
```

As an example the application server details endpoint has 10 potential 
includes according to the API docs.  Note that the API docs are not always 
accurate either!

Most endpoints that generate lists will have optional includes that can be 
passed as lists or tuples.

```python
api.nodes.list_nodes(includes=('allocations', 'location'))
api.servers.get_server_info(
    server_id=53,
    includes=['user', 'subusers', 'location'])
```

### Params

Most endpoints with includes will also have a `params` parameter.  This can 
be used to pass additional parameters.  Many endpoint specific `params` are 
already supported by Pydactyl, however some additional params apply 
universally like `per_page`.

```python
api.nodes.list_nodes(params={'per_page': 9001})
api.servers.list_servers(params={'per_page': 9001})
api.users.list_users(params={'per_page': 9001})
```

## PterodactylClient

Each of the classes in pydactyl could be imported independently, but the 
PterodactylClient class [pydactyl/api_client.py](pydactyl/api_client.py) 
provides a simplified interface that imports libraries for you and provides 
some convenience features like retries and debug logging.

### Retries

Instances of [PterodactylClient](pydactyl/api_client.py) will automatically
retry calls that fail with a 429 status code indicating that the request was
rate-limited by Pterodactyl.

By default it uses a backoff_factor of 1 with 3 retries. You can configure the
number of retries and backoff_factor when instantiating a client.

```python
PterodactylClient('panel', 'key', backoff_factor=2, retries=10)
```

Details on backoff_factor and retires can be found in the
[urllib3.util.Retry documentation](https://urllib3.readthedocs.io/en/stable/reference/urllib3.util.html#urllib3.util.Retry)
.

If your server is overloaded or intermittently unavailable you may want to retry
on other status codes as well. To do this you can pass in a list of integer HTTP
status codes.

```python
PterodactylClient('foo', 'bar', extra_retry_codes=[502, 504])
```

### Debug logging

Most errors from pydactyl will present as exceptions and there is no logging 
by default, however sometimes additional logging is helpful.  You can get 
request logging by passing `debug=True` to PterodactylClient.

```python
app_api = PterodactylClient('https://why', 'broken', debug=True)
app_api.servers.list_servers(includes=('egg', 'nest'))
DEBUG:urllib3.connectionpool:Starting new HTTPS connection (1): why:443
DEBUG:urllib3.connectionpool:https://why:443 "GET /api/application/servers?include=egg%2Cnest HTTP/1.1" 200 None
```

## Paginated Responses

Pydactyl API responses return
a [PaginatedResponse object](pydactyl/responses.py#L4) that can be iterated over
to automatically fetch additional pages as required. This is currently 
implemented on many endpoints which frequently return multi-page responses, 
but not all.

```python
# Create a list of all ports
allocs = api.nodes.list_node_allocations(node_id)
ports = []
for page in allocs:
    for item in page:
        ports.append(item['attributes']['port'])
len(ports)
151
```

#### collect()

The `collect()` method will fetch the data from all pages of a
PaginatedResponse. This allows you to easily fetch all results when you want all
the data without having to iterate over the pages.

The above example to get a list of ports now looks like:

```python
# Create a list of all ports
allocs = api.nodes.list_node_allocations(node_id)
ports = allocs.collect()
len(ports)
151
```

[docs]: https://pydactyl.readthedocs.io/

[docs-img]: https://readthedocs.org/projects/pydactyl/badge/?version=latest (Latest docs)

[pulls]: https://github.com/iamkubi/pydactyl/pulls

[issues]: https://github.com/iamkubi/pydactyl/issues

[pypi]: https://pypi.python.org/pypi/py-dactyl/

[pypi-img]: https://img.shields.io/pypi/v/py-dactyl.svg

[codecov]: https://codecov.io/gh/iamkubi/pydactyl

[codecov-img]: https://codecov.io/gh/iamkubi/pydactyl/branch/main/graph/badge.svg

[discord-img]: https://img.shields.io/badge/discord-join-7289DA.svg?logo=discord&longCache=true&style=flat

[discord-join]: https://discord.gg/TgZDHPB

[lint-and-test]: https://github.com/iamkubi/pydactyl/actions/workflows/lint-and-test.yml/badge.svg?branch=main (https://github.com/iamkubi/pydactyl/actions/workflows/lint-and-test.yml)