semvec/pypi-packages huggingface dataset:
dhx-utils-lib 1.7.9b306
DataHex Utility Library to help with building AWS SAM based application.

# DataHex Utility Library

The DataHex Utility library is a collection of utilities functions and classes that are useful for DataHex
applications. There are various reusable modules in this library so please refer to each section for the
respective usage guide.

## Installation 

This library is published to RZT Nexus and can be installed by using the command:

```
pip install dhx-utils-lib
```

# Catalog Service module

The catalog service module contains various handy functions to call the private catalog API for common
scenarios.

```
from dhx_utils.catalog import CatalogService
CatalogService(catalog_api=api).get_sub_data_asset_locations('83b294680f7a11ec9611a6f3ae174d1e', '2020-01-01', '2021-09-01', {'exchange_id': '151'})

[('151#2020-03-02', 's3://datalake-storage-dhx-dev-rozettatech/hl/assest_partitioned/D151/2020/03/02/'), ('151#2020-02-02', 's3://datalake-storage-dhx-dev-rozettatech/hl/assest_partitioned/D151/2020/02/02/')]
```

or let the util lib to build the catalog api path by using the env
```
from dhx_utils.catalog import CatalogService
#env could be dev, qa, prod, the catalog serveris would use url 'https://catalog.{env}.datahex.internal/dev'
_env = "dev"
CatalogService(env=_env).get_sub_data_asset_locations('83b294680f7a11ec9611a6f3ae174d1e', '2020-01-01', '2021-09-01', {'exchange_id': '151'})

[('151#2020-03-02', 's3://datalake-storage-dhx-dev-rozettatech/hl/assest_partitioned/D151/2020/03/02/'), ('151#2020-02-02', 's3://datalake-storage-dhx-dev-rozettatech/hl/assest_partitioned/D151/2020/02/02/')]
```
dhx-audit-client 1.0.11b42
General audit client for services using DataHex based solutions.

# Audit Client Library

Audit client library is a python package that allows DataHex services the ability to put events into a shared bus
providing the ability to meter, log, and trace the lineage of data as it flows through the DataHex services.

The library is published into Nexus.


## Usage

Setup pip to point to RoZetta's Nexus
mkdir ~/.pip
cat > ~/.pip/pip.conf << EOF
[global]
index-url= https://nexus.rozettatech.com/repository/pypi-all/simple
progress_bar = off
EOF


Make sure the caller of the client library has attached the correct IAM policy to perform put_events action.

Install the client library with the following command
pip install dhx-audit-client==<version>


Or Update the Requiremnts.txt
boto3==1.16.8
--extra-index-url https://nexus.rozettatech.com/repository/pypi-all/simple/
dhx-audit-client==<version>


Sample usage code

Initialise a new AuditClient instance with the required parameters: product, environment, service, component
and release_version, parent_execution_id (optional), event_bus_name (optional, see rules below).
The rules to get event_bus_name:
* If event_bus_name is specified in the parameter, it will be used.
* Otherwise, if a corresponding environment variable AUDIT_EVENT_BUS_NAME is set, the value of the variable
  will be used.
* If both are not specified, it will be derived from parameters product and environment defaulting to ${product}-${environment}-AuditEventBus.

from audit_client.audit_client import AuditClient
ac = AuditClient(product='dhx', environment='devhl', service='datahex_downloader',
                 component='ftp_downloader', release_version='datahex_downloader-v0.0.1',
                 parent_execution_id='some-id', event_bus_name='some_event_bus_name)


Start a new AuditSession instance , every time start_audit is called, and new execution ID will be generated.
If we want to keep the same execution ID, we can re-use the same AuditSession

sess = ac.start_audit()


Use AuditSession to put audit event to event bus.

action = 'SourceConnectionStartDetail'
result =  'CONNECTION_REFUSED'

event_details = {
   "Host": "ftp://ftp.morningstar.com/",
   "Protcol": "FTPS"
}
sess.put_audit_event(action, result, event_details
fcp89-sysml-v2-code-generator-web-gui 1.1.1
Web GUI for the SysML v2 code generator prototype.
Requires Python: >=3.9

***This is a demonstration project. It is not suitable for productive use.***

# SysML v2 Code Generator Web GUI

This is a prototype project for code generation from SysML v2 models
to demonstrate the potential of code generation in a SysML v2 context.

## Preconditions

For direct usage:

- python ^3.9
- pip
- web browser

For interactive debugging and development (recommended):

- poetry
- professional Python IDE

For hosting on a server:

- DevOps knowledge

Optional:

- SysML v2 Pilot Implementation for generation of own models (JupyterNotebook => JSON/API)

## Installation

Direct local usage:

```
pip install fcp89-sysml-v2-code-generator-web-gui
```

Webserver:
This is a standard flask application.
It is possible to host it within a server environment.
In that case individual steps and modifications are required.

Docker:
Be aware that this is only a simple integration.
```
docker build -t sysml-v2-code-generator-web-gui .
docker run -p 5000:5000 sysml-v2-code-generator-web-gui
```

## Basic Usage

Direct usage on local machine:

```
sysml-code-generator-web-gui
```

Open http://127.0.0.1:5000 in the browser.
jupyt-ai 0.1.0
Jupyt AI - Intelligent Assistant for Jupyter Notebooks
Requires Python: >=3.8
Keywords: jupyter, jupyterlab, jupyterlab-extension, ai, chat, assistant

# Jupyt
Jupyt is an intelligent assistant built on top of Jupyter Notebooks. 

## Prerequisites

- Node.js >= 16
- Python >= 3.8
- JupyterLab >= 4.0
- python3-full (for Ubuntu/Debian systems)

## How to run on your system


```bash
# Create and activate a virtual environment
python3 -m venv .venv
source .venv/bin/activate

# Install required packages
pip install jupyterlab==4.2.7
pip install -e .
(for ubuntu add --break-system-packages)

Then activate that environment in another terminal
1. In your first terminal:
```bash
# Watch for source changes and rebuild automatically
jlpm watch
```

2. In a second terminal:
```bash
# Run JupyterLab
jupyter lab
```

When you make changes to source files:
1. Save your changes
2. Wait for the rebuild message in the first terminal
3. Refresh your JupyterLab browser window

## Testing

```bash
# Run tests
jlpm test

# Run linting
jlpm lint
```

## Project Structure

FOLDER STRUCTURE:
- src: All the code files for the extension
- style: The css for the codebase
- lib: The build converted into javascript
hydra-yaml-lsp 0.1.1
Language Server Protocol implementation for Hydra YAML configuration files
Requires Python: >=3.12
Keywords: autocomplete, completion, configuration, editor, hydra, intellisense, language-server, language-server-protocol, lsp, vscode, yaml

# 🐉 hydra-yaml-lsp

![Python 3.12+](https://img.shields.io/badge/python-3.12+-blue.svg)
![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)
![Document Style](https://img.shields.io/badge/%20docstyle-google-3666d6.svg)

**hydra-yaml-lsp** is a Language Server Protocol implementation for [Hydra](https://hydra.cc) YAML configuration files, providing rich language features like code completion, syntax validation, and semantic highlighting to enhance the development experience with Hydra configuration files.

## ✨ Features

- 💡 Intelligent code completion for Hydra special keys (`_target_`, `_args_`, etc.)
- 🔍 Path completion for Python import paths in `_target_` values
- 🛠️ Argument completion for callable targets
- 🎨 Semantic token highlighting for special keys, target values, and interpolations
- ⚠️ YAML syntax validation and diagnostics
- 🔄 Support for Hydra interpolations (`${...}` syntax)
- 🔌 Easy integration with editor extensions (primary integration with VS Code)

## 📦 Installation

```bash
# Install with pip
pip install hydra-yaml-lsp

# For development setup
git clone https://github.com/your-repo/python-hydra-yaml.git
cd python-hydra-yaml/hydra-yaml-lsp
make venv  # Sets up virtual environment with all dependencies
```

## 🧰 Requirements

- Python 3.12+

## 📝 Usage

### Standalone Server

```sh
python -m hydra_yaml_lsp
```

### Using with VS Code Extension

The primary use case is through the VS Code extension:

1. Install the `python-hydra-yaml` extension in VS Code
2. Configure the extension to point to your Hydra configuration directory
3. Open any YAML file in that directory to activate the language features

## 🔧 Development

```bash
# Clone and setup development environment
git clone https://github.com/your-repo/python-hydra-yaml.git
cd python-hydra-yaml/hydra-yaml-lsp

# Install dependencies and set up virtual environment
make venv

# Run all tests
make test

# Run type checking
make type

# Run all checks (tests and type checking)
make run
```

## 📄 License

This project is licensed under the MIT License - see the [LICENSE](../LICENSE) file for details.
av-video 0.0.1
Convert videos to image frames and vice versa.
Requires Python: >=3.10

# PyAV-Video

[![GitHub][github_badge]][github_link] [![PyPI][pypi_badge]][pypi_link]

PyAV-Video converts videos to image frames and vice versa!



## Installation

Install PyAV-Video and its dependencies

```bash
pip install av-video
```



## Quickstart

Convert a video to image frames

```bash
from av_video import Video

with Video.open("example.mp4") as v:
    v.to_images()
```



## License

PyAV-Video has a MIT license, as found in the [LICENSE](https://github.com/imyizhang/PyAV-Video/blob/main/LICENSE) file.



## Contributing

Thanks for your interest in contributing to PyAV-Video! Please feel free to create a pull request.



## Changelog

**PyAV-Video 0.0.1**

* First release



[github_badge]: https://badgen.net/badge/icon/GitHub?icon=github&color=black&label
[github_link]: https://github.com/imyizhang/PyAV-Video



[pypi_badge]: https://badgen.net/pypi/v/av-video?icon=pypi&color=black&label
[pypi_link]: https://www.pypi.org/project/av-video