| Name | uncertainty-engine JSON |
| Version |
0.7.0
JSON |
| download |
| home_page | None |
| Summary | SDK for the Uncertainty Engine |
| upload_time | 2025-08-04 09:36:43 |
| maintainer | Jamie Donald-McCann |
| docs_url | None |
| author | digiLab Solutions Ltd. |
| requires_python | <3.13,>=3.10 |
| license | None |
| keywords |
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| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Python SDK for the Uncertainty Engine
[](https://badge.fury.io/py/uncertainty-engine) [](https://pypi.org/project/uncertainty-engine/)
## Requirements
- Python >=3.10, <3.13
- Valid Uncertainty Engine account
## Installation
```bash
pip install uncertainty-engine
```
With optional dependencies:
```bash
pip install "uncertainty_engine[vis,notebook,data]"
```
## Usage
### Setting your username and password
To run and queue workflows you must have your Uncertainty Engine username and password set up. To do this you can run the following in your terminal:
```bash
export UE_USERNAME="your_username"
export UE_PASSWORD="your_password"
```
### Creating a client
All interactions with the Uncertainty Engine API are performed via a `Client`. The client can be defined as follows:
```python
from uncertainty_engine import Client
client = Client()
```
To create a `Client` for a named environment:
```python
from uncertainty_engine import Client
client = Client(env="<NAME>")
# For example:
client = Client(env="dev")
```
To create a `Client` for a custom environment:
```python
from uncertainty_engine import Client, Environment
client = Client(
env=Environment(
cognito_user_pool_client_id="<COGNITO USER POOL APPLICATION CLIENT ID>",
core_api="<UNCERTAINTY ENGINE CORE API URL>",
region="<REGION>",
resource_api="<UNCERTAINTY ENGINE RESOURCE SERVICE API URL>",
),
)
# For example:
client = Client(
env=Environment(
cognito_user_pool_client_id="3n437fei4uhp4ouj8b4mmt09l9",
core_api="https://s0r8fczyag.execute-api.eu-west-2.amazonaws.com",
region="eu-west-2",
resource_api="https://hmqdnx48x6.execute-api.eu-west-2.amazonaws.com",
),
)
```
### Running a node
```python
from pprint import pprint
from uncertainty_engine import Client, Environment
from uncertainty_engine.nodes.basic import Add
# Set up the client
client = Client(
env=Environment(
cognito_user_pool_client_id="<COGNITO USER POOL APPLICATION CLIENT ID>",
core_api="<UNCERTAINTY ENGINE CORE API URL>",
region="<REGION>",
resource_api="<UNCERTAINTY ENGINE RESOURCE SERVICE API URL>",
),
)
# Create a node
add = Add(lhs=1, rhs=2)
# Run the node on the server
response = client.run_node(add)
# Get the result
result = response.outputs
pprint(result)
```
For more some more in-depth examples checkout our [example notebooks](https://github.com/digiLab-ai/uncertainty-engine-sdk/tree/dev/examples).
## Support
For any support needs please visit our [support page](https://support.uncertaintyengine.ai).
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"description": "\n\n# Python SDK for the Uncertainty Engine\n\n[](https://badge.fury.io/py/uncertainty-engine) [](https://pypi.org/project/uncertainty-engine/)\n\n## Requirements\n\n- Python >=3.10, <3.13\n- Valid Uncertainty Engine account\n\n## Installation\n\n```bash\npip install uncertainty-engine\n```\n\nWith optional dependencies:\n\n```bash\npip install \"uncertainty_engine[vis,notebook,data]\"\n```\n\n## Usage\n\n### Setting your username and password\n\nTo run and queue workflows you must have your Uncertainty Engine username and password set up. To do this you can run the following in your terminal:\n\n```bash\nexport UE_USERNAME=\"your_username\"\nexport UE_PASSWORD=\"your_password\"\n```\n\n### Creating a client\n\nAll interactions with the Uncertainty Engine API are performed via a `Client`. The client can be defined as follows:\n\n```python\nfrom uncertainty_engine import Client\n\nclient = Client()\n```\n\nTo create a `Client` for a named environment:\n\n```python\nfrom uncertainty_engine import Client\n\nclient = Client(env=\"<NAME>\")\n\n# For example:\nclient = Client(env=\"dev\")\n```\n\nTo create a `Client` for a custom environment:\n\n```python\nfrom uncertainty_engine import Client, Environment\n\nclient = Client(\n env=Environment(\n cognito_user_pool_client_id=\"<COGNITO USER POOL APPLICATION CLIENT ID>\",\n core_api=\"<UNCERTAINTY ENGINE CORE API URL>\",\n region=\"<REGION>\",\n resource_api=\"<UNCERTAINTY ENGINE RESOURCE SERVICE API URL>\",\n ),\n)\n\n# For example:\nclient = Client(\n env=Environment(\n cognito_user_pool_client_id=\"3n437fei4uhp4ouj8b4mmt09l9\",\n core_api=\"https://s0r8fczyag.execute-api.eu-west-2.amazonaws.com\",\n region=\"eu-west-2\",\n resource_api=\"https://hmqdnx48x6.execute-api.eu-west-2.amazonaws.com\",\n ),\n)\n```\n\n### Running a node\n\n```python\nfrom pprint import pprint\n\nfrom uncertainty_engine import Client, Environment\nfrom uncertainty_engine.nodes.basic import Add\n\n# Set up the client\nclient = Client(\n env=Environment(\n cognito_user_pool_client_id=\"<COGNITO USER POOL APPLICATION CLIENT ID>\",\n core_api=\"<UNCERTAINTY ENGINE CORE API URL>\",\n region=\"<REGION>\",\n resource_api=\"<UNCERTAINTY ENGINE RESOURCE SERVICE API URL>\",\n ),\n)\n\n# Create a node\nadd = Add(lhs=1, rhs=2)\n\n# Run the node on the server\nresponse = client.run_node(add)\n\n# Get the result\nresult = response.outputs\n\npprint(result)\n```\n\nFor more some more in-depth examples checkout our [example notebooks](https://github.com/digiLab-ai/uncertainty-engine-sdk/tree/dev/examples).\n\n## Support\n\nFor any support needs please visit our [support page](https://support.uncertaintyengine.ai).\n",
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