semvec/pypi-packages huggingface dataset:
sengine-cli 1.4.9
S-Egnine CLI is a command line interface for the Sonic Engine extensions manager.

# S-Engine CLI (Sonic Engine CLI)

S-Engine CLI is a command-line interface for the Sonic Engine extensions manager.

## Installation

You can install S-Engine CLI using pip:

```bash
pip install sengine-cli
```

## Usage

After installation, you can use the `sengine-cli` command to interact with the Sonic Engine extensions manager.

### Example:

```bash
sengine-cli start my_config.yaml -l
```

- `start`: Command to start the Sonic Engine with the specified configuration file.
- `my_config.yaml`: Path to the configuration file.
- `-l` or `--logs`: Enable logging.

## Features

- Easy-to-use command-line interface.
- Manage extensions for the Sonic Engine effortlessly.
- No need to code anything, just use the CLI commands along with a configuration file.

## Configuration file

The configuration file is a YAML file that contains the configuration for the Sonic Engine. Here's an example:

```yaml
# Path: my_config.yaml
# Metadata section for general configuration
metadata:
  # Folder where extensions are stored
  extensions_folder: extensions

# Categories section for grouping extensions
categories:
  - name: feature
    description: Extensions that extract features from flows
  - name: inference
    description: Extensions that infer information from flows and request predictions
  - name: reporting
    description: Extensions that report the results

# Extensions section for defining individual extensions
extensions:
  - id: hello_world_feature_0
    category: feature
    # Source repository for the hello_world_feature_0 extension
    source: https://github.com/AhmedCoolProjects/sonic-engine-hello-world-feature.git
    # Configurations for controlling extension instances
    override:
      # Override the default extension instance configs for hello_world_feature_0
      hello_world_feature_0:
        branch: main
      # # Add a new extension instance named hello_world_feature_1 with different branch
      # hello_world_feature_1:
      #   branch: dup/1
      # # Override local configs for a new instance named hello_world_feature_2 _(i.e different description in this case)_
      # hello_world_feature_2:
      #   branch: main
      #   description: This is a new instance of the hello world feature extension overriding the default configs

  - id: hello_world_inference_0
    category: inference
    # Source repository for the hello_world_inference_0 extension
    source: https://github.com/AhmedCoolProjects/sonic-engine-hello-world-inference.git

  - id: hello_world_reporting_0
    category: reporting
    # Source repository for the hello_world_reporting_0 extension
    source: https://github.com/AhmedCoolProjects/sonic-engine-hello-world-reporting.git
```
sonic-engine-cli 1.4.8
S-Egnine CLI is a command line interface for the Sonic Engine extensions manager.

# S-Engine CLI (Sonic Engine CLI)

S-Engine CLI is a command-line interface for the Sonic Engine extensions manager.

## Installation

You can install S-Engine CLI using pip:

```bash
pip install sengine-cli
```

## Usage

After installation, you can use the `sengine-cli` command to interact with the Sonic Engine extensions manager.

### Example:

```bash
sengine-cli start my_config.yaml -l
```

- `start`: Command to start the Sonic Engine with the specified configuration file.
- `my_config.yaml`: Path to the configuration file.
- `-l` or `--logs`: Enable logging.

## Features

- Easy-to-use command-line interface.
- Manage extensions for the Sonic Engine effortlessly.
- No need to code anything, just use the CLI commands along with a configuration file.

## Configuration file

The configuration file is a YAML file that contains the configuration for the Sonic Engine. Here's an example:

```yaml
# Path: my_config.yaml
# Metadata section for general configuration
metadata:
  # Folder where extensions are stored
  extensions_folder: extensions

# Categories section for grouping extensions
categories:
  - name: feature
    description: Extensions that extract features from flows
  - name: inference
    description: Extensions that infer information from flows and request predictions
  - name: reporting
    description: Extensions that report the results

# Extensions section for defining individual extensions
extensions:
  - id: hello_world_feature_0
    category: feature
    # Source repository for the hello_world_feature_0 extension
    source: https://github.com/AhmedCoolProjects/sonic-engine-hello-world-feature.git
    # Configurations for controlling extension instances
    override:
      # Override the default extension instance configs for hello_world_feature_0
      hello_world_feature_0:
        branch: main
      # # Add a new extension instance named hello_world_feature_1 with different branch
      # hello_world_feature_1:
      #   branch: dup/1
      # # Override local configs for a new instance named hello_world_feature_2 _(i.e different description in this case)_
      # hello_world_feature_2:
      #   branch: main
      #   description: This is a new instance of the hello world feature extension overriding the default configs

  - id: hello_world_inference_0
    category: inference
    # Source repository for the hello_world_inference_0 extension
    source: https://github.com/AhmedCoolProjects/sonic-engine-hello-world-inference.git

  - id: hello_world_reporting_0
    category: reporting
    # Source repository for the hello_world_reporting_0 extension
    source: https://github.com/AhmedCoolProjects/sonic-engine-hello-world-reporting.git
```
dtrelib 0.2.6
Drive test report engine (DTRE) core library
Requires Python: >=3.7

# Drite test reporting engine core
Core library consist of 5 classes, providing main functions for work with clickhouse, tables, table streams and data processing.

## Query
Query class provide interaction with clickhouse database and (re)storing data into Redis caching database 

## ResultSet
ResultSet is a container of data with additional attributes

## ResultSetStream
ResultSetStream is made as a wrapper over ResultSet to make available file-by-file queries

## Processor
Processor consist of set of scalar and vector functions to process datasets in serial processing line.