semvec/pypi-packages huggingface dataset:
pragmatiks-agno-provider 0.84.0
Agno agent provider for Pragmatiks
Requires Python: >=3.13

# Agno Provider for Pragmatiks

Deploys Agno AI agents to Kubernetes clusters with reactive dependency management.

## Resources

### `agno/agent`

Deploys an Agno agent as a Kubernetes Deployment with a Service.

**Config:**
- `cluster` - GKE cluster dependency (required)
- `model` - Model dependency for LLM (required)
- `embeddings` - Embeddings dependency for RAG (optional)
- `vector_store` - Vector store dependency for RAG (optional)
- `instructions` - System instructions for the agent (optional)
- `image` - Container image (default: `ghcr.io/agno-ai/agno:latest`)
- `replicas` - Number of replicas (default: 1)

**Outputs:**
- `url` - In-cluster URL for agent API
- `ready` - Whether the deployment is ready

## Usage

```yaml
apiVersion: agno/v1
kind: agent
metadata:
  name: company-assistant
  namespace: demo
spec:
  cluster: $ref{ai-cluster}
  model: $ref{claude}
  embeddings: $ref{my-embeddings}
  vector_store: $ref{qdrant-collection}
  instructions: |
    You are a helpful assistant.
```
pragmatiks-kubernetes-provider 0.141.0
Generic Kubernetes resources using lightkube
Requires Python: >=3.13

# Kubernetes Provider

Generic Kubernetes resources for Pragmatiks using [lightkube](https://github.com/gtsystem/lightkube).

## Resources

| Resource | Description |
|----------|-------------|
| `kubernetes/service` | Kubernetes Service (ClusterIP, NodePort, LoadBalancer) |
| `kubernetes/configmap` | Kubernetes ConfigMap |
| `kubernetes/secret` | Kubernetes Secret |
| `kubernetes/statefulset` | Kubernetes StatefulSet with PVC templates |

## Usage

Resources require a GKE cluster dependency for authentication:

```yaml
resources:
  my-cluster:
    provider: gcp
    resource: gke
    config:
      project_id: my-project
      location: europe-west4
      name: my-cluster
      credentials: ${{ secrets.gcp_credentials }}

  my-service:
    provider: kubernetes
    resource: service
    config:
      cluster: ${{ my-cluster }}
      namespace: default
      type: ClusterIP
      selector:
        app: my-app
      ports:
        - port: 80
          target_port: 8080
```

## Installation

```bash
pip install pragmatiks-kubernetes-provider
```
pragmatiks-gcp-provider 0.130.0
GCP provider for Pragmatiks
Requires Python: >=3.13

# GCP Provider

GCP provider for Pragmatiks - manage Google Cloud resources declaratively.

## Available Resources

### Secret (gcp/secret)

Manages secrets in GCP Secret Manager using user-provided service account credentials.

```python
from gcp_provider import Secret, SecretConfig

# Define a secret
secret = Secret(
    name="my-api-key",
    config=SecretConfig(
        project_id="my-gcp-project",
        secret_id="api-key",
        data="super-secret-value",
        credentials={"type": "service_account", ...},  # or JSON string
    ),
)
```

**Config:**
- `project_id` - GCP project ID where the secret will be created
- `secret_id` - Identifier for the secret (must be unique per project)
- `data` - Secret payload data to store
- `credentials` - GCP service account credentials (JSON object or string)

**Outputs:**
- `resource_name` - Full GCP resource name (`projects/{project}/secrets/{id}`)
- `version_name` - Full version resource name including version number
- `version_id` - The version number as a string

## Installation

```bash
pip install pragmatiks-gcp-provider
```

## Development

### Testing

```bash
# Install dependencies
uv sync --dev

# Run tests
uv run pytest tests/
```

### Writing Tests

Use `ProviderHarness` to test lifecycle methods:

```python
from pragma_sdk.provider import ProviderHarness
from gcp_provider import Secret, SecretConfig

async def test_create_secret():
    harness = ProviderHarness()
    result = await harness.invoke_create(
        Secret,
        name="test-secret",
        config=SecretConfig(
            project_id="test-project",
            secret_id="my-secret",
            data="secret-value",
            credentials=mock_credentials,
        ),
    )
    assert result.success
    assert result.outputs.resource_name is not None
```

## Deployment

Push your provider to Pragmatiks platform:

```bash
pragma provider push
```
todo-cli-scolhoun 0.1.999
Simple file-backed to-do CLI
Requires Python: >=3.8

# To-Do List CLI (Python)

Minimal, file-backed to-do list CLI.

Install locally (editable) to get a `todo` command:

```bash
python -m pip install -e .
```

Then run:

```bash
todo add "Write report"
todo list
todo complete 0
todo remove 0
todo clear
```

Add with a due date:

```bash
todo add "Finish budget" --due 2026-02-15
todo add "Call client" --due tomorrow
```

If `todo` is not found, ensure your Python's `Scripts` directory is on your PATH (Windows) or use the same Python executable: `python -m todo`.

Run tests:

```bash
python -m pip install -r requirements.txt
python -m pytest -q
```