odata1c-client 0.1.1

A Python client for interacting with 1C systems via OData v3, providing ORM-like functionality, data validation, and query construction.

OData1C - A Python OData Client for 1C Systems

OData1C is a Python client designed to interact with 1C systems via their OData v3 REST endpoints.
This client aims to simplify and streamline common tasks such as querying entities, applying filters and expansions, creating and updating data, and handling related entities. It uses Pydantic for data validation and Requests for HTTP communication.

While originally inspired by PyOData1C (with only essential OData capabilities for 1C), OData1C has been refined with clearer structure, comprehensive English docstrings, improved maintainability, and extensibility.

Key Features

• OData Integration: Communicates with 1C OData endpoints (primarily tested with OData v3).
• Data Validation: Leverages Pydantic for serialization, deserialization, and validation of model data.
• ORM-Like Interface: Define your entity models as Pydantic classes inheriting from ODataModel, and use OData and ODataManager classes to interact with the server.
• Complex Query Building:
  • Filtering: Apply filters using Django-style lookups or Q objects.
  • Expansion: Fetch related nested entities via $expand.
  • Pagination: Limit and skip results using $top and $skip.
• Chaining API: Methods like filter(), expand(), top(), and skip() return the manager instance, allowing method chaining and cleaner query construction.
• Error Handling: Provides domain-specific exceptions, validation error accumulation, and flexible error handling strategies.
• Context Manager Support: Use Connection as a context manager (with ... as ...) to ensure proper resource cleanup.

Installation

pip install odata1c-client

Dependencies

• Python >= 3.12
• Pydantic >= 2.7.0
• Requests >= 2.32.0

Usage

Below is a sample usage example showing how to define models and query data:

from uuid import UUID

from requests.auth import HTTPBasicAuth
from pydantic import Field

from OData1C.connection import Connection
from OData1C.models import ODataModel
from OData1C.odata.manager import OData


class MeasureUnitModel(ODataModel):
    uid: UUID = Field(alias='Ref_Key', exclude=True)
    name: str = Field(alias='Description', max_length=6)


class NomenclatureModel(ODataModel):
    uid: UUID = Field(alias='Ref_Key', exclude=True)
    code: str = Field(alias='Code', max_length=12)
    name: str = Field(alias='Description', max_length=200)
    measure_unit: MeasureUnitModel = Field(alias='Measure_Unit')

    nested_models = {
        'measure_unit': MeasureUnitModel
    }


class NomenclatureOdata(OData):
    database = 'database_name'
    entity_model = NomenclatureModel
    entity_name = 'Catalog_Nomenclature'


with Connection('ODATA_HOST',
                'ODATA_PROTOCOL',
                HTTPBasicAuth('ODATA_USERNAME', 'ODATA_PASSWORD')) as conn:
    nomenclatures = (
        NomenclatureOdata.manager(conn)
        .expand('measure_unit')
        .filter(code__in=['00-123', '00-456'])
        .all(ignore_invalid=True)
    )

    for item in nomenclatures:
        print(item.name, item.measure_unit.name)

You can find more examples in OData1C/example.

Connection Class

The Connection class provides an interface for sending HTTP requests to the 1C OData server. It can be instantiated directly or used as a context manager (with ... as ...) to handle session lifecycle automatically. Its constructor requires parameters such as host (the domain or IP of the 1C server), protocol (e.g. http or https), and authentication (e.g. HTTPBasicAuth). You can also specify connection_timeout and read_timeout to control network timings. Internally, Connection uses the Requests library.

Example usage:

with Connection(
        host='my1c.domain.ru',
        protocol='http',
        authentication=HTTPBasicAuth('user', 'pass')) as conn:
    # Perform OData operations here

Or without a context manager:

conn = Connection(
  host='my1c.domain.ru',
  protocol='http',
  authentication=HTTPBasicAuth('user', 'pass'))
# Perform OData operations here

Defining Models

Models must inherit from ODataModel (a Pydantic BaseModel subclass). Use nested_models to specify related models for $expand queries:

class MyNestedModel(ODataModel):
    # Define fields and aliases as needed

class MyModel(ODataModel):
    # Define fields and aliases
    nested_models = {
        'some_related_field': MyNestedModel
    }

Working with OData Entities

Create a subclass of OData and define:

• database: The service root or database name.
• entity_model: The Pydantic model class for data validation.
• entity_name: The OData entity set name.

class FooOdata(OData):
    database = 'my1cdb'
    entity_model = MyModel
    entity_name = 'bar'

ODataManager

Obtain a manager instance and perform operations:

manager = FooOdata.manager(conn)
items = manager.all()

Common Methods in ODataManager:

• all(ignore_invalid=False): Executes a GET request and returns validated entities. If ignore_invalid=True, skips invalid objects and accumulates errors in validation_errors.

• create(data): Sends a POST request to create a new entity. data can be either a dictionary or an instance of the entity_model (for example, MyModel) representing the new entity.

• get(guid): Fetches a single entity by GUID.

• update(guid, data): Updates an entity identified by GUID using PATCH. data can be either a dictionary or an instance of the entity_model (for example, MyModel) containing the fields to update.

• post_document(guid, operational_mode=False): Posts (commits) a document by GUID.

• unpost_document(guid): Unposts (reverts) a previously posted document by GUID.

• expand(*fields): Specifies which related entities to $expand. Accepts positional string arguments - field names for which related entities should be retrieved. The passed field names must be declared in the entity_model.nested_models (for example, MyModel.nested_models) dictionary.

• filter(...): Applies $filter conditions. It accepts keyword arguments as conditions (lookups in Django style) or positional Q objects. Lookup format: field__operator__annotation where:

  • field is the model field name;
  • operator is one of eq, ne, gt, ge, lt, le, in (defaults to eq if omitted);
  • annotation (optional) can be GUID or datetime.

  manager.filter(foo='abc')
  manager.filter(bar__gt=100)
  manager.filter(uid_1c__in__guid=[...])
  

• skip(n), top(n): Applies $skip and $top for pagination.

Filtering with Q

For complex filters, use Q objects and combine them with logical operators:

from OData1C.odata.query import Q

manager.filter(Q(name='Ivanov') & Q(age__gt=30))

Debugging

The ODataManager object has request and response attributes after executing a request. These hold instances of ODataRequest and requests.Response, respectively. You can inspect them for debugging:

with Connection(
        host='my1c.domain.ru',
        protocol='http',
        authentication=HTTPBasicAuth('user', 'pass')) as conn:
    manager = FooOdata.manager(conn)
    bars = manager.top(3).all()
    pprint(manager.request)
    pprint(manager.response.json())

Contributing

Contributions are welcome! Please open issues or submit pull requests for improvements or bug fixes.