semvec/pypi-packages huggingface dataset:
rpc-over-redis 0.0.5
Remote Procedure Call over Redis on Python
Requires Python: >=3.9

# Remote Procedure Call over Redis

This library provides an RPC implementation over Redis.   
To forward a request from the client to the service for the execution of the method, 
`Redis Streams` is used together with `Consumer Groupss` to distribute requests.  
To forward the result of the method execution from the service to the client, 
`Redis PubSub` is used with unique client and request identifiers


## Features
- Transparent forwarding of arguments and return value
- Supports/forces the use of Python type hints
- Built-in consistency check client-side with the server-side
- Supports multiple server-side instances at the same time, balancing via Redis
- Zeroconf, does not require open ports, addresses, HTTP API implementation, etc. Only Redis.
- Uses the built-in capabilities of Redis 5.0+ to forwarding in both directions

## Installation
```pip install rpc-over-redis```

## Using

First, you need to declare the server-side (service) app:  
`server.py`
```python
import os
from rpc_over_redis.core import RPCOverRedisService

redis_url = os.environ['REDIS_URL']     # REDIS_URL=redis://:password@redis/0

# initializing server-side
r = RPCOverRedisService(
    redis_url,
    'SmartEchoService'
)

@r.register
def echo() -> None:
    print('echo is called')
    pass

r.run_forever()
```

Then, you need to create a header class with empty methods.  
Now you can use it like a regular class. The arguments and the return value will be transparently passed through Redis
```python
import os
from rpc_over_redis.core import RPCOverRedisClient

class SmartEchoService(RPCOverRedisClient):
    def __init__(self, conn_url: str):
        super().__init__(conn_url, self.__class__.__name__, strict_validate_schema=True)

    def echo(self) -> None:
        ...

# initializing client-side
client = SmartEchoService(os.environ['REDIS_URL'])       # REDIS_URL=redis://:password@redis/0

# execute remote methods as local class methods...
client.echo()  # none returned
```

More examples see [here](https://github.com/mark99i/rpc-over-redis/tree/master/examples)

## Additional options
// TODO

## Limitations
- Only built-in types that allow to be converted to json/string should be used as arguments and return values.
query_quiver 0.0.4
Support brainstorming for technical blog using your Google Chrome history.
Requires Python: >=3.11,<4.0

![QueryQuiver](https://raw.githubusercontent.com/marutaku/QueryQuiver/main/logos/query_quiver_banner.png)

<div style="display: flex; gap: 8px">

[![Check code](https://github.com/marutaku/QueryQuiver/actions/workflows/ci.yml/badge.svg)](https://github.com/marutaku/QueryQuiver/actions/workflows/ci.yml)

![PyPI - Version](https://img.shields.io/pypi/v/query_quiver)

![PyPI - Python Version](https://img.shields.io/pypi/pyversions/query_quiver)

![PyPI - Wheel](https://img.shields.io/pypi/wheel/query_quiver)

</div>

# QueryQuiver

QueryQuiver estimates your interests based on your past Google Chrome search history and suggests technical article ideas that you might be comfortable writing about.

## Install

<!-- ```shell
pip install queryquiver
```

or If you want to install from source code, you can install it as follows.
 -->

```shell
pip install git+https://github.com/marutaku/QueryQuiver
```

## Usage

Please close Google Chrome before using this tool.

The tool references the SQLite database used internally by Google Chrome.

While using GoogleChrome, this SQLite database will be locked and an error will occur.

```shell
queryquiver generate
```

### Options

```shell
queryquiver generate --help

NAME
    queryquiver generate - Generate idea of tech articles from Google Chrome history

SYNOPSIS
    queryquiver generate <flags>

DESCRIPTION
    Generate idea of tech articles from Google Chrome history

FLAGS
    -q, --query_history_limit=QUERY_HISTORY_LIMIT
        Type: int
        Default: 20
    -n, --number_of_ideas=NUMBER_OF_IDEAS
        Type: int
        Default: 5
    -c, --chrome_history_path=CHROME_HISTORY_PATH
        Type: Optional[str | None]
        Default: None
    -o, --openai_api_key=OPENAI_API_KEY
        Type: Optional[str | None]
        Default: None
    -d, --debug=DEBUG
        Type: bool
        Default: False
    -l, --language=LANGUAGE
        Type: str
        Default: 'en'
    -u, --use_gpt4=USE_GPT4
        Type: bool
        Default: False
```

## Developer information

### setup

```shell
make setup
```

### test

```shell
make test
```

### lint

```shell
make lint
```

### format

```shell
make format
```
django-unfold-admin 0.1.0
RTL Unfold Django Admin Panel Theme

![enter image description here](https://img.shields.io/badge/Django-092E20?style=for-the-badge&logo=django&logoColor=green) ![enter image description here](https://img.shields.io/badge/Tailwind_CSS-38B2AC?style=for-the-badge&logo=tailwind-css&logoColor=white)


## RTL Unfold Django Admin Panel Theme
This project is forked from https://github.com/unfoldadmin/django-unfold with RTL support.
<hr>

![Screenshot1](https://github.com/SaeedRz96/django-unfold-admin/blob/master/screenshots/loginform.png)

## How to install?
1.using pip to install package
```bash
pip install django-unfold-admin
```
2.add `unfold` to *settings.py* `INSTALLED_APPS`:
```python
    # settings.py
    INSTALLED_APPS = [
        "unfold",  # before django.contrib.admin
        "django.contrib.admin",
        .
        .
        .
    ]
```


3.now you can use `ModelAdmin` class defined in `unfold.admin` in *admin.py* :
```python
    # admin.py
    
    from django.contrib import admin
    from unfold.admin import ModelAdmin
    
    @admin.register(MyModel)
    class CustomAdminClass(ModelAdmin):
        pass
```

thats that! 

## Features

 - RTL support
 - Dark mode is available
 - Persian font Vazir included
 - Responsive design


## ScreenShots
![Screenshot2](https://github.com/SaeedRz96/django-unfold-admin/blob/master/screenshots/lightmode.png)

![Screenshot3](https://github.com/SaeedRz96/django-unfold-admin/blob/master/screenshots/darkmode.png)
teas 0.1.1
Tools for the Extraction and Analysis of Spectra from JWST observations
Keywords: python,astronomy,jwst,spectroscopy

==================================================================================
``teas`` - Tools for the Extraction and Analysis of Spectra from JWST observations
==================================================================================

.. image:: https://img.shields.io/pypi/v/teas?style=flat&logo=pypi&logoColor=%23ffd242&color=%23336c9d
   :target: https://pypi.org/project/teas/
   :alt: PyPI - Version

.. image:: https://img.shields.io/badge/powered%20by-AstroPy-orange.svg?style=flat
    :target: https://www.astropy.org
    :alt: Powered by Astropy

.. image:: https://img.shields.io/badge/powered%20by-STScI-blue.svg?colorA=707170&colorB=3e8ddd&style=flat
  :target: http://www.stsci.edu
  :alt: Powered by STScI

``teas`` is a package of utilities to analyze spectra from the James Webb Space Telescope. It provides tools to align and process JWST data products, extract 1D spectra from 3D integral-field-unit data cubes from NIRSpec and MIRI MRS, and create images of observed regions with NIRCam observations.

Features:
---------

* Extract 1D spectra from 3D IFU data from NIRSpec and MIRI MRS
* Create images of spectrally imaged regions using NIRCam data
* Align and reproject the WCS of data cubes and images
* Find the field of view of NIRSpec or MIRI MRS data products within NIRCam images
* Fit the continuum using either an anchors-and-splines fitting or  linear regression
* Stitch together spectra
* Shift, scale, and normalize spectrum flux

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

It is recommended to install ``teas`` in a new environment to avoid
version conflicts with other packages. To do this, run:

.. code-block:: bash

   conda create --name teas-env python=3.9


Then, activate the environment and install the package. The latest released version can be installed with pip:

.. code-block:: bash

  conda activate teas-env
  pip install teas --upgrade