semvec/pypi-packages huggingface dataset:
piecs 0.0.1b3
A collection of control and analysis code for experiments
Requires Python: >=3.6

# PIEC
 Python Integrated Experimental Control
 The goal of this repository is to provide a streamlined control scheme for lab experiments and allow for rapid development
 of new experimental procedures starting from a ferroelectric standpoint.
 Requires KEYSIGHT I/O Libraries, find them here: www.keysight.com/find/iosuite
ignite-feast 0.1.0
This package makes it possible to use Ignite as online store for Feast.
Requires Python: ==3.11.7

# ignite_feast

This package enables the use of Apache Ignite or GridGain as an online store for Feast, providing high-performance, in-memory data storage and retrieval for feature serving.

## Table of Contents
1. [Features](#features)
2. [Project Structure](#project-structure)
3. [Setup Instructions](#setup-instructions)
   - [Prerequisites](#prerequisites)
   - [Installation](#installation)
4. [API Reference](#api-reference)
5. [Building from Source](#building-from-source)
6. [Example](#example)

## Features

- **Ignite/GridGain Integration:** Leverages Ignite's in-memory database to provide online features for real-time model predictions.
- **Feature Management:** Feast manages feature definitions, versioning, and the synchronization between online and offline stores.

## Project Structure

The project consists of two main components:

1. **Ignite Online Store (`online_store.py`):** Sets up Apache Ignite as the online feature store.
2. **GridGain Online Store (`gridgain_online_store.py`):** Configures GridGain as the online feature store.

Both implementations provide similar functionality but are tailored to their respective systems.

## Setup Instructions

### Prerequisites

* Python 3.11.7
* Running Apache Ignite or GridGain cluster

### Installation

Install the package using pip:

```bash
pip install ignite_feast
```

## API Reference

### IgniteOnlineStore / GridGainOnlineStore

Both classes implement the following methods:

- `online_read(config, table, entity_keys, requested_features)`: Reads feature values from the online store.
- `online_write_batch(config, table, data, progress)`: Writes a batch of feature data to the online store.
- `update(config, tables_to_delete, tables_to_keep, entities_to_delete, entities_to_keep, partial)`: Updates the online store based on changes to the feature repository.
- `teardown(config, tables, entities)`: Cleans up the online store.

For detailed information on these methods, refer to the docstrings in the source code.

## Building from Source

1. Clone the repository:
   ```bash
   git clone https://github.com/gridgain-poc/ignite_feast.git
   cd ignite_feast
   ```

2. Install build dependencies:
   ```bash
   pip install -q build
   ```

3. Build the package:
   ```bash
   python -m build
   ```

This will create a distributable package in the `dist` directory.

## Example

For a comprehensive, real-world example of how to use this package, please refer to the following GitHub repository:

[CGM Ignite Feast Kafka Example](https://github.com/manini-zs/cgm_ignite_feast_kafka)

This repository provides a detailed implementation that demonstrates the integration of Ignite Online Store with Feast in a Continuous Glucose Monitoring (CGM) use case. It includes examples of configuration, feature definitions, and usage in different environments.
numeros-lotofacil 0.0.1
Sorteia numeros da lotofacil
Requires Python: >=3.8


# numeros_lotofacil_package

O pacote Ã© usado para criar sequencias de nÃºmeros para apostas da lotofacil.



## InstalaÃ§Ã£o

Use the package manager pip to install numeros_lotofacil_package

```pip instal numeros_lotofacil_package```
## Uso/Exemplos

```
from numeros_lotofacil import sorteio
sorteio_numeros()
```


## Autores

- [Thais Mendes](https://https://github.com/MendesTatah)
image-processing-devricart 0.0.1
My short description
Requires Python: >=3.8

# image_processing

Description. 
The package image_processing is used to:
	Processing:
		- Histrogram matching
		-	Structural similarity
		- Resize image

	Utils:
		- Read image
		- Save image
		- Plot image
		- Plot result
		- Plot histogram

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install package_name

```bash
pip install image_processing
```

## Author
Ricardo GonÃ§alves

## License
[MIT](https://choosealicense.com/licenses/mit/)
miltertest 1.0.0
Pure Python implementation of the milter protocol
Requires Python: >=3.8

# miltertest

This is a pure Python module implementing the milter protocol, based on
Chris Siebenmann's work in [python-milter-tools](https://github.com/siebenmann/python-milter-tools).

The main goal is to provide an acceptable interface for acting as
an MTA to test milter implementations; it may also be usable for
implementing milters, but there are better options for that.
do-function-addons 0.1.2
DigitalOcean functions addons. Typed Event and Context class.
Requires Python: >3.8

# DigitalOcean Function Addons

# How to use
1. Install from [PyPi](https://pypi.org/project/do_function_addons/)
2. Import `Event` and `Context` from `function_addons.request`
3. Change your DO Functions function signature to `(event: Event, context: Context)`
emmett-prometheus 0.2.0
Prometheus extension for Emmett framework
Requires Python: >=3.8
Keywords: emmett, monitoring, prometheus

# Emmett-Prometheus

Emmett-Prometheus is an [Emmett framework](https://emmett.sh) extension integrating [prometheus](https://prometheus.io) client.

Emmett-Prometheus is compatible both with Emmett and Emmett55.

## Installation

You can install Emmett-Prometheus using pip:

    pip install emmett-prometheus

And add it to your Emmett application:

```python
from emmett_prometheus import Prometheus

app.use_extension(Prometheus)
```

## Configuration

Here is the complete list of parameters of the extension configuration:

| param | default | description |
| --- | --- | --- |
| auto\_load | `True` | Automatically inject extension on routes and expose metrics |
| enable\_http\_metrics | `True` | Enable metrics collection on HTTP routes |
| enable\_ws\_metrics | `True` | Enable metrics collection on Websocket routes |
| enable\_sys\_metrics | `False` | Enable default Prometheus client system metrics collection |
| metrics\_route\_path | /metrics | Path for metrics route |
| metrics\_route\_hostname | | Hostname for metrics route |

You also have some additional customisations available (here we show the defaults):

```python
app.config.Prometheus.http_histogram_statuses = [200, 201]
app.config.Prometheus.http_histogram_exclude_methods = ["OPTIONS"]
app.config.Prometheus.http_histogram_buckets = [
    5, 35, 100, 200, 500, 1000, "INF"
]
app.config.Prometheus.exclude_routes = []
app.config.Prometheus.metrics_names={
    "http_counter": "emmett_request_count",
    "http_histogram": "emmett_request_latency",
    "ws_gauge": "emmett_websocket_gauge",
    "ws_recv_counter": "emmett_websocket_messages_recv_count",
    "ws_send_counter": "emmett_websocket_messages_send_count"
}
```

## License

Emmett-prometheus is released under BSD license.
do_function_addons 0.1.0
DigitalOcean functions addons. Typed Event and Context class.
Requires Python: >=3.12

# DigitalOcean Function Addons

# How to use
1. Install from pypi ``
2. Import `Event` and `Context` from `do_function_addons.request`
3. Change your DO Functions function signature to `(event: Event, context: Context)`