semvec/pypi-packages huggingface dataset:
vws-web-tools 2026.2.20
Tools for interacting with the Vuforia Web Services (VWS) website.
Requires Python: >=3.12
Keywords: vuforia, vws

|Build Status| |PyPI|

VWS-Web-Tools
=============

Tools for interacting with the VWS (Vuforia Web Services) website.

Installation
------------

.. code-block:: shell

   pip install vws-web-tools

This is tested on Python |minimum-python-version|\+.

Usage
-----

.. code-block:: console

   $ export VWS_EMAIL_ADDRESS="[YOUR-EMAIL]"
   $ export VWS_PASSWORD="[YOUR-PASSWORD]"
   $ TIME="$(date +%s%N | cut -b1-13)"
   $ vws-web-tools create-vws-license --license-name "my-licence-$TIME"
   $ vws-web-tools create-vws-cloud-database --license-name "my-licence-$TIME" --database-name "my-database-$TIME"
   $ vws-web-tools show-database-details --database-name "my-database-$TIME"

Python API
----------

This project also exposes a Python API.
See the `Python API reference <https://vws-python.github.io/vws-web-tools/python-api.html>`__.

Full documentation
------------------

See the `full documentation <https://vws-python.github.io/vws-web-tools/>`__ for more information including how to contribute.

.. |Build Status| image:: https://github.com/VWS-Python/vws-web-tools/actions/workflows/ci.yml/badge.svg?branch=main
   :target: https://github.com/VWS-Python/vws-web-tools/actions
.. |PyPI| image:: https://badge.fury.io/py/VWS-Web-Tools.svg
   :target: https://badge.fury.io/py/VWS-Web-Tools
.. |minimum-python-version| replace:: 3.12
agentwarden 0.1.2
Security and access control for AI Agents
Requires Python: >=3.9

# AgentWarden SDK

Security and permission management for AI Agents.

## Installation
```bash
pip install agentwarden
```

## Quick Start
```python
from agentwarden import AgentWarden

# Initialize with your API key
guard = AgentWarden(api_key="your-api-key")

# Check if agent can execute an action
result = guard.check(
    agent_id="agent-001",
    action="stripe.refund",
    context={"amount": 50}
)

if result.allowed:
    # Execute your action
    stripe.refund.create(amount=50)
    
    # Log the action
    guard.log("agent-001", "stripe.refund", "success")
else:
    print(f"Action blocked: {result.reason}")
```

## Helper Method
```python
def refund_payment():
    return stripe.refund.create(amount=50)

# Check, execute, and log automatically
result = guard.execute(
    "agent-001",
    "stripe.refund",
    refund_payment,
    context={"amount": 50}
)
```

## Documentation

Visit [https://agentwarden.io](https://agentwarden.io) for full documentation.

## License

MIT License
auto-playwright 0.2.0
Plain English to Playwright Python Automation
Requires Python: <4.0,>=3.10

# auto-playwright

Plain-English `.flow` files → Playwright (Python) runner.

## Install

### Poetry

```bash
poetry install
```

Dev tools (pytest/formatters) via extras:

```bash
poetry install --extras dev
# or
poetry install --all-extras
```

### pip

```bash
pip install .

# Dev tools
pip install '.[dev]'
```

## Run

```bash
poetry run ap examples/amazon_search.flow
```

### Safety / Logging env vars

- `AUTO_PLAYWRIGHT_ALLOWED_DOMAINS` (optional): comma-separated hostname allowlist for **top-level** navigations.
  - Supports exact hosts (`example.com`) and wildcards (`*.example.com`).
  - If unset/empty, no allowlist is enforced.

- `AUTO_PLAYWRIGHT_POLICY_FILE` (optional): YAML policy file path.
  - `allowed_domains`: additional domain allowlist.
  - `blocked_actions`: DSL actions to block globally (for governance), e.g. `["sleep"]`.
  - Example policy: `tools/runtime_policy.example.yaml`

- `AUTO_PLAYWRIGHT_PERSISTENT_PROFILE` (optional, default `0`): use persistent browser profile (`1`/`true`) vs isolated ephemeral context (default).
- `AUTO_PLAYWRIGHT_PROFILE_DIR` (optional): profile path used when persistent profile is enabled.

- Logs and `run_report.*` are automatically redacted for common secrets (tokens/keys in env + URL query params).

Run a directory (batch mode):

```bash
poetry run ap examples/
```

## Artifacts / Output layout

Each run writes all artifacts under:

```
output/<flow>/<timestamp>/
  run_report.json
  run_report.html
  artifacts/
    trace.zip              (optional)
    video/                 (optional)
    errors/error_step_*.png
    code/                  (debug/dump-code)
    final/                 (final healed test)
    flows/                 (generated flow, if different)
```

## Debug / code generation

Generate both plain + intelligent code and keep the browser open:

```bash
poetry run ap examples/amazon_search.flow --debug
```

Generate code only (no execution):

```bash
poetry run ap examples/amazon_search.flow --dump-code
```

## Tracing / Video / Screenshots

```bash
poetry run ap examples/amazon_search.flow --trace on
poetry run ap examples/amazon_search.flow --trace on-failure

poetry run ap examples/amazon_search.flow --video on
poetry run ap examples/amazon_search.flow --video on-failure

# enabled by default; use --no-screenshot-on-failure to disable
poetry run ap examples/amazon_search.flow --no-screenshot-on-failure
```

## Tests (unit / smoke)

No real browser/network is used in tests.

```bash
poetry run pytest
```
sbatchman 1.0.2
A utility to create, launch and monitor code experiments on SLURM, PBS, or local machines.
Requires Python: >=3.8

<p align="center" style="padding: 0; margin: 0;">
    <img src="https://github.com/LorenzoPichetti/SbatchMan/blob/main/docs/images/SbatchManLogo.png" alt="SbatchManLogo" style="width: 6cm;">
<p>

# SbatchMan

A utility to create, launch, and monitor code experiments on SLURM, PBS, or local machines.

# Documentation

You can find a comprehensive documentation at [https://sbatchman.readthedocs.io/en/latest/](https://sbatchman.readthedocs.io/en/latest/)

PyPi project: [https://pypi.org/project/sbatchman/](https://pypi.org/project/sbatchman/)
scanpydoc 0.17.2
A series of Sphinx extensions to get maintainable numpydoc style documentation.
Requires Python: >=3.12

scanpydoc |pypi| |docs| |tests| |checks| |cov|
==============================================

A collection of Sphinx extensions similar to (but more flexible than) numpydoc.

Check the self-documenting documentation at https://icb-scanpydoc.readthedocs-hosted.com

.. |pypi| image:: https://img.shields.io/pypi/v/scanpydoc.svg
   :target: https://pypi.org/project/scanpydoc/
   :alt: PiPI version
.. |docs| image:: https://readthedocs.com/projects/icb-scanpydoc/badge/
   :target: https://icb-scanpydoc.readthedocs-hosted.com/
   :alt: doc build status
.. |tests| image:: https://github.com/theislab/scanpydoc/actions/workflows/ci.yml/badge.svg
   :target: https://github.com/theislab/scanpydoc/actions/workflows/ci.yml
   :alt: python test status
.. |checks| image:: https://results.pre-commit.ci/badge/github/theislab/scanpydoc/main.svg
   :target: https://results.pre-commit.ci/latest/github/theislab/scanpydoc/main
   :alt: pre-commit.ci status
.. |cov| image:: https://codecov.io/gh/theislab/scanpydoc/branch/main/graph/badge.svg
   :target: https://codecov.io/gh/theislab/scanpydoc
   :alt: coverage
gllm-pipeline-binary 0.4.34
A library containing components related to Gen AI applications pipeline orchestration.
Requires Python: <3.13,>=3.11

# GLLM Pipeline

## Description
A library containing components related to Gen AI applications pipeline orchestration, including routers, steps, and utility functions for building and managing AI application workflows.

---

## Installation

### Prerequisites

Mandatory:
1. Python 3.11+ — [Install here](https://www.python.org/downloads/)
2. pip — [Install here](https://pip.pypa.io/en/stable/installation/)
3. uv — [Install here](https://docs.astral.sh/uv/getting-started/installation/)

Extras (required only for Artifact Registry installations):
1. gcloud CLI (for authentication) — [Install here](https://cloud.google.com/sdk/docs/install), then log in using:
   ```bash
   gcloud auth login
   ```

---

### Option 1: Install from Artifact Registry

This option requires authentication via the `gcloud` CLI.

```bash
uv pip install \
  --extra-index-url "https://oauth2accesstoken:$(gcloud auth print-access-token)@glsdk.gdplabs.id/gen-ai-internal/simple/" \
  gllm-pipeline
```

---

### Option 2: Install from PyPI

This option requires no authentication.
However, it installs the **binary wheel** version of the package, which is fully usable but **does not include source code**.

```bash
uv pip install gllm-pipeline-binary
```

---

## Local Development Setup

### Prerequisites

1. Python 3.11+ — [Install here](https://www.python.org/downloads/)
2. pip — [Install here](https://pip.pypa.io/en/stable/installation/)
3. uv — [Install here](https://docs.astral.sh/uv/getting-started/installation/)
4. gcloud CLI — [Install here](https://cloud.google.com/sdk/docs/install), then log in using:

   ```bash
   gcloud auth login
   ```
5. Git — [Install here](https://git-scm.com/downloads)
6. Access to the [GDP Labs SDK GitHub repository](https://github.com/GDP-ADMIN/gl-sdk)

---

### 1. Clone Repository

```bash
git clone git@github.com:GDP-ADMIN/gl-sdk.git
cd gl-sdk/libs/gllm-pipeline
```

---

### 2. Setup Authentication

Set the following environment variables to authenticate with internal package indexes:

```bash
export UV_INDEX_GEN_AI_INTERNAL_USERNAME=oauth2accesstoken
export UV_INDEX_GEN_AI_INTERNAL_PASSWORD="$(gcloud auth print-access-token)"
export UV_INDEX_GEN_AI_USERNAME=oauth2accesstoken
export UV_INDEX_GEN_AI_PASSWORD="$(gcloud auth print-access-token)"
```

---

### 3. Quick Setup

Run:

```bash
make setup
```

---

### 4. Activate Virtual Environment

```bash
source .venv/bin/activate
```

---

## Local Development Utilities

The following Makefile commands are available for quick operations:

### Install uv

```bash
make install-uv
```

### Install Pre-Commit

```bash
make install-pre-commit
```

### Install Dependencies

```bash
make install
```

### Update Dependencies

```bash
make update
```

### Run Tests

```bash
make test
```

---

## Contributing

Please refer to the [Python Style Guide](https://docs.google.com/document/d/1uRggCrHnVfDPBnG641FyQBwUwLoFw0kTzNqRm92vUwM/edit?usp=sharing)
for information about code style, documentation standards, and SCA requirements.