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A Python SDK for GLPI REST Api.

Project description

GLPI REST API Python SDK v0.1.2

This Python library provides a wrapper for the GLPI REST API. It offers a collection of resources representing various GLPI items built upon generic classes. Install using:

pip install py_glpi

--------- or ---------

pip install py_glpi==[version]

Supported Items

  • Tickets:
    • CRUD operations
    • User assignment
    • Document attachment
  • Ticket Categories:
    • CRUD operations
  • Ticket SLAs:
    • CRUD operations
  • Request Origin:
    • CRUD operations
  • Ticket Users:
    • CRUD operations
  • Users:
    • CRUD operations
    • Related ticket querying
  • User Emails:
    • CRUD operations
  • Documents:
    • CRUD operations
    • Downloading
  • Document Items:
    • CRUD operations

How it Works

  1. Connection: The library establishes a connection to the GLPI server using the specified authentication method (basic or user token).
  2. Item Modeling: GLPI items are modeled using dataclasses and generic parent classes to provide global and specific functionalities for each item.
  3. Resource Creation: Resources are created for the modeled GLPI items. These resources handle querying, filtering, updating and creating.

Item Hierarchy:

Items can have subitems, which will be represented as subitem resources, or parent items, represented as read-only properties (only updatable from the glpi item update method). Here's an example of this hierarchy:

Ticket Categories -> Tickets -> Document Items
from py_glpi.resources.tickets import Tickets

ticket = Tickets(connection).get(11)
category = ticket.category                  # Get's the ticket category object throught property getter.
documents = ticket.linked_documents.all()   # Get's all the ticket related Document Items using the Subitem resource.
User -> Ticket Users <- Tickets
from py_glpi.resources.auth import Users

user = Users(connection).get(27)
tickets = user.tickets.all()           # Get's all the user Ticket User items using the Subitem resource.
tickets = user.get_requested_tickets() # Directly get the tickets where this user has the "applicant" role, directly returning the Ticket objects, instead of the relation registries (Ticket Users) 
  

This hierarchy attributes may be simplified using certain class methods for easier usage, for example, the ticket item has a method called "attach_document", which directly handles the creation of a related subitem.

Either way, all models are extendable inheriting them with dataclasses:

from py_glpi.resources.auth import Users, User
from dataclasses import dataclass

# Generally, Resources classes are called with a plural of the item they represent e.g User -> Modeled Item, Users -> User Resource.

@dataclass(repr=False)  # Set repr to false to avoid overriding the original method, unless you want to make your own
class User(User):       # The modeled item classes need to match the name of the GLPI itemtype they represent.

    other_attribute: str

    def post_initialization(self):     # Need to be cautious when modifying this method, since it migth lead to unexpected behaviour.
        super().post_initialization()  # Make sure to always call the original class post_initialization first
        my_attr = self.my_method()

    def my_method(self):
        ...

    @property
    def etc(self): ...   # Properties are a great way for adding calculated/extended attributes, i recommend this rather than modifying post_initialization method.

Resource Methods

Every resource has at least the following methods:

  • get(id): Retrieves an item with the specified ID.
  • all(): Retrieves all items.
  • get_multiple(*ids): Retrieves multiple items with the provided IDs.
  • search(filters[]): Filters items using GLPI's search engine.
  • instance(**kwargs): Instantiates a GLPI item based on API responses and modeled dataclasses.
  • create(**kwargs): Create's a resource with the specified data.

Item Methods

Every GLPI item has at least the following methods:

  • post_initialization(): Executes after an item is initialized, allowing for adding new attributes.
  • as_dict(): Represents the item as a dictionary.
  • get_api_object(): Provides access to all attributes returned by the GLPI API.
  • get_subitems_resource(): Creates a resource for a subitem related to this item (e.g., a Ticket with its Document Items).
  • get_related_parent(): Fetches a parent item using the parent's resource and the related field (e.g., accessing the parent Ticket of a Ticket User item using the tickets_id field).
  • update(): Updates the item.
  • delete(): Deletes the item.

Usage

1. Create a GLPI Connection:

from py_glpi.connection import GLPISession

connection = GLPISession(
    api_url = getenv("GLPI_REST_API_URL"),
    app_token = getenv("GLPI_APP_TOKEN"),
    auth_type = getenv("GLPI_AUTH_HEADER_METHOD"),
    user = getenv("GLPI_USER"),
    password = getenv("GLPI_PASSWORD"),
    user_token = getenv("GLPI_USER_TOKEN")
)

2. Create a Resource Instance:

from py_glpi.resources.tickets import Tickets

resource = Tickets(connection)

3. Perform Operations:

  • Retrieve all tickets:
resource.all()
  • Get a specific ticket:
resource.get(11)
resource.create(
    name="Test",
    content="Test ticket created with REST Api",
    itilcategories_id=12
)

4. Using the GLPI Search Engine:

By default, GLPI requires complex filtering criteria. This library simplifies it using the FilterCriteria class:

from py_glpi.models import FilterCriteria

filter = FilterCriteria(
    field_uid="Ticket.name",  # Searchable field UUID
    operator="Equals",        # Comparison operator
    value="Test"              # Matching value
)

resource.search(filter)

# Specifying a non-existent field_uid will raise an exception that includes a reference of all the searchable field_uids for the sepcified Resource.

Filters can be related using logical operators (AND, OR, XOR) defined as follows:

filter1 = filter
filter2 = FilterCriteria(
    field_uid="Ticket.content",
    operator="Contains",
    value="API"
)

filter = filter1 & filter2  # AND operation
filter = filter1 | filter2  # OR operation
filter = filter1 & filter2 | filter3 # Mixed operation

result = resource.search(filter)  # Logical operations between filter criteria will produce a list related by thus operation.

5. ItemList Methods:

Methods that return multiple items (all, search, get_multiple) use an extended list class named ItemList. This class provides the following methods:

  • filter(**kwargs): Offline Filters the results using the leopards library (refer to https://github.com/mkalioby/leopards for usage).
  • exclude(**kwargs): Reverse Offline Filters the results using the leopards.
  • to_representation(): Returns a list with the result of executing to_dict() method of each contained item.
result = resource.filter(priority__gt=2)  # Offline filters the search result, returns only the tickets with a priority higher than 2.
result = result.exclude(urgency__lt=4)  # Returns only the tickets with a urgency higher than 3.

For more usage examples, refer to tests in the github repository.

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