semvec/pypi-packages huggingface dataset:
seele-web 0.0.5
Website packaged for UF in Japan, Summer 2024

Project Description:

  This app will provide an educational infographic and personalized disaster preparation checklist based on a user's specific circumstance. The website also generates an easy to understand graphic that the user may download. 

Build and Install Server Commands:

    pip install seele

Repository Link:

  https://github.com/JMalegni/DisasterPrepApp

Run Executable and Initialization commands:

    seele_start

Contributors:

  Joseph Malegni, Christian Ferrer, Nicholas DeSanctis, Xael Font, Logan Chenicek

Credit to Prabhat Mishra as a guideline for a Django/Bootstrap Project:
https://github.com/prabhatx/django-basic-project
freetakserver-ui 2.2.1
an optional UI for FreeTAKServer
Requires Python: <4.0,>=3.11

# FTS Web UI
![image](https://user-images.githubusercontent.com/60719165/177003787-c1322f17-a55e-4d81-a0a1-25c6178cb42e.png)

FTS Web UI allows administrators to easily manage the [FTS](https://github.com/FreeTAKTeam/FreeTakServer) server.
This component requires a working backend. The WebUI is a completely separate application connecting to  the FTS backend. 
It uses an API to seamless query server functions. Depending on his deployment, may or may not be  seen from remote machines.

This [video](https://www.youtube.com/watch?v=ot3PNY903ns&t=3sa), provides an overview of most features described in the [user manual](https://github.com/FreeTAKTeam/FreeTakServer/blob/master/docs/FTS%20UI%20Documention.pdf)


## Installation and configuration
This section provides an overview of the installation process. Refer to the online [documentation](https://freetakteam.github.io/FreeTAKServer-User-Docs/Installation/Linux/Install/) for details. 

To install FTS and the UI type in a console
```
sudo python3 -m pip install FreeTAKServer[ui]
```
Setup your Configuration
your administrator will need to configure the following files
```
Config.py for the UI
MainConfig.py for FTS
```

### Start FTS

```
nohup sudo python3 -m FreeTAKServer.controllers.services.FTS 
```

## Start the WebUI
in the console type navigate to the installation path

```
cd /usr/local/lib/python3.8/dist-packages/FreeTAKServer-UI
```

```
nohup   sudo python3 run.py
```

## Dashboard Features

- SQLite,  
- Alembic (DB schema migrations)
- Modular design with **Blueprints**
- Session-Based authentication (via **flask_login**)
- Forms validation
 
- **MIT License**
k8s-to-azure-container-app 0.1.0
Migrate Kubernetes deployments into Azure Container Apps
Requires Python: >=3.6

# K8sToAzureContainerApp

**Overview**

K8sToAca is a Python tool designed to streamline the process of transitioning Kubernetes namespaces into Azure Container App environments. Leveraging the Kubernetes API, this tool retrieves all deployment objects within the specified namespace and generates Azure Container Apps deployment in YAMLs, JSON or Terraform(in Beta). Additionally, it provides a shell script containing commands necessary for deploying the generated deployment files using the Azure CLI.


## Parameters

| Parameter | Mandatory | Description |
|-|-|-|
| `namespace`           | True      | The Kubernetes namespace to be migrated.                 |
| `context`             | True      | The name of the Kubernetes config context for the cluster. |
| `aca_resource_group`  | True      | The Azure Resource Group where the Container App Environment exists. |
| `aca_environment`     | True      | The name of the Azure Container App Environment.         |
| `output`              | False     | Output format values (yaml, json, terraform). Terraform output is in preview. Default value: yaml |
| `outputpath`          | False     | Output folder. Default value: current path               |



## Features
K8sToAzureContainerApp can generate deployment scripts in YAML format from a specified Kubernetes namespace. Currently, it supports migrating the following objects:

- **POD**:
  - Deployment
  - Pod
  - Horizontal Pod Autoscaler
- **Configuration**:
  - Secrets
- **Storage**:
  - Volumes
- **Network/Exposure**:
  - Ingress
  - Service
  - Endpoint

## Installation
You can install K8sToAca using pip:

1. **pip install**: Run the following command:
    ```bash
    pip3 install k8s-to-azure-container-app
    ```

1. **Generate a package**:
    
    Alternatively, you can download the source code and follow these steps for a manual installation:
   
    ```bash
    pip install -e .
    ```

## Usage

Run K8sToAca using the following command:

```bash
K8sToAca --namespace my_name_space --context cluster_context --aca_resource_group target_resource_group --aca_environment target_container_app_environment_name
```
Replace the placeholders with your actual values.

Deploy to Azure deployment script:

```cmd
./deployment.sh 
```

## Recomendation

Install Azure CLI using https://learn.microsoft.com/en-us/cli/azure/install-azure-cli

Ensure your Azure CLI and the Azure Container Apps extension are up to date by executing the following commands:

```bash
az upgrade
az extension add -n containerapp --upgrade
```

## License
This tool is licensed under the MIT License. See the [LICENSE](LICENSE) file for more information.
datamap.posmo-datamarket-sdk 1.0.0a4
SDK for interacting with Posmo DataMarket API
Requires Python: >=3.8

# Posmo DataMarket SDK

This is a Python SDK for interacting with the Posmo DataMarket API.

## Usage

Install with pip:
```
pip install datamap.posmo-datamarket-sdk
```

Import Posmo DataMarket client:
```python
from datamap.posmo_datamarket_sdk import PosmoDataMarket
```

Initialize client:
```python
datamarket = PosmoDataMarket(project_code='project', username='username', password='password')
```

Optionally you can provide username and password in environment variables:
- Username: `POSMO_USERNAME`
- Password: `POSMO_PASSWORD`

### Client methods

#### query(*query*)

Executes provided SQL query and returns result.

```python
result = datamarket.query('SELECT * FROM moving;')
```

#### schema()

Opens database schema documentation in default browser.

```python
datamarket.schema()
```
AdvancedCodingSkills 0.1.0
In response to the dynamic demands of student life, we present our Multi-Purpose Program—a flexible application carefully designed to meet the unique needs of students and beyond. Beyond its usefulness for students, this application extends its functionality to anyone seeking efficient task management, expense tracking, and a touch of entertainment a game(sudoku).For Saving Method we have used JSON and the whole project is coded using inheritance.
Requires Python: >=3.6

In response to the dynamic demands of student life, we present our Multi-Purpose Program—a flexible application carefully designed to meet the unique needs of students and beyond. Beyond its usefulness for students, this application extends its functionality to anyone seeking efficient task management, expense tracking, and a touch of entertainment a game(sudoku).For Saving Method we have used JSON and the whole project is coded using inheritance.
SMPCbox 1.0.6
A framework for implementation of secure multi party computation protocols
Keywords: python, protocols, multi party computation, MPC, secure multi party computation, SMPC


SMPCbox is a framework which can be used to implement Secure Multi Party Computation (SMPC) protocols.
The idea behind the project is to provide a way to easily test protocols, visualise protocol execution
and gather statistics on protocol execution.
This framework is meant to help researchers and students to better understand SMPC protocols.