semvec/pypi-packages huggingface dataset:
ssakz 0.1.2
Client API for ssa.fai.kz
License: MIT

Python API client for ssa.fai.kz
================================

Install
-------

.. code:: bash

   pip install ssakz

Usage
-----

.. code:: python

   from ssakz import Client
   client = Client("<your API key>")

The API key is available upon registering at ssa.fai.kz

.. code:: python

   # Query near-miss events, starting from 2023-06-19,
   # where the minimal predicted distance between objects is less than 30 km
   nme = client.get_nme(rhigh=30, since='2023-06-19')

.. code:: python

   # Query space weather data (neutron flux)
   # starting one day ago
   nf = client.get_sw_neutrons(since='-1d')

Module functions
~~~~~~~~~~~~~~~~

-  ``get_nme`` - query data on near-miss events forecasts
-  ``get_sw_solar`` - query data on solar flux
-  ``get_sw_neutrons`` - query data on cosmic neutrons flux
-  ``get_sw_geomag`` - query data on geomagnetic field
-  ``get_sw_geomag_?``, with ``?`` being either ``x``, ``y`` or ``z`` -
   query data on geomagnetic field components
-  ``get_sw_k_index`` - query data on perturbation k-index

Dependency
----------

-  ``pyzmq`` (installed automatically with ``pip``)
tweeter-basic 0.1.1
Send tweets (with optional images) through the Twitter v2 API (OAuth 2.0) - authentication included
License: MIT
Keywords: tweet,twitter,v2,OAuth,OAuth2.0,API,images

# Tweeter Basic

Send tweets (with optional images) and authenticate through the Twitter v2 API (OAuth 2.0) using Python.

## Quick Start

Send a test tweet with the following steps:

- generate and set the following environment variables:
  - TWITTER_CONSUMER_API_KEY
  - TWITTER_CONSUMER_API_KEY_SECRET
  - TWITTER_ACCESS_TOKEN
  - TWITTER_ACCESS_TOKEN_SECRET
  - TWITTER_CLIENT_ID
  - TWITTER_CLIENT_SECRET
  - TWITTER_CALLBACK_URI <- must end in `/callback` (ie. `http://localhost/callback`)
- authorize the application (1 time only) to generate the seed `token.json` with the following:
  - build & run the token generation server by executing `Authenticate/authenticate.sh`
  - navigate with a browser to your [http://localhost/auth](http://localhost/auth)
- send a test tweet by executing `test/test.sh`

## Prerequisites

- Docker engine
- Twitter project with: 
  - v1.1 API read & write access
  - v2 API access

## 2do

- give a more verbose explanation of the steps
- write separate PyPI instructions

### future

- add geolocation to tweets:
  - try posting with the v1 API instead of v2:
    - https://developer.twitter.com/en/docs/twitter-api/v1/tweets/post-and-engage/api-reference/post-statuses-update
    - using this format: https://en.wikipedia.org/wiki/GeoJSON
  - wait for an answer to https://stackoverflow.com/questions/75817366/how-to-post-a-tweet-with-geo-data-using-twitter-api-v2-0
    - update forums when answer is found:
      - https://twittercommunity.com/t/how-tweet-with-latitude-longitude-information/189749

### related projects

- https://twitter.com/detroitships
- https://github.com/ezod/aistweet
- [testing grounds](https://twitter.com/HyperB0t)

### resources used

- helpful tutorials:
  - https://developer.twitter.com/en/docs/tutorials/creating-a-twitter-bot-with-python--oauth-2-0--and-v2-of-the-twi
  - https://dev.to/twitterdev/handling-refresh-tokens-in-the-oauth-20-authorization-code-flow-with-pkce-with-flask-481p
- [Twitter POST /2/tweets](https://developer.twitter.com/en/docs/twitter-api/tweets/manage-tweets/api-reference/post-tweets)
- [Twitter POST /1.1/media/uploads.json](https://developer.twitter.com/en/docs/twitter-api/v1/media/upload-media/api-reference/post-media-upload)
  - [v2 uploading future](https://trello.com/c/Zr9zDrJx/109-replacement-of-media-uploads-functionality)
- [media-upload.py](https://gist.github.com/jcipriano/133e44156837360197ba17e7113ddfbc)
nonebot-plugin-7s-roll 0.2.0
A roll dice plugin for nonebot
License: MIT
Requires Python: >=3.9,<4.0
Keywords: nonebot,dice,roll,trpg

# Roll Dice

扔骰子小工具。

0.2.0 版本支持 NoneBot2 2.0 正式版 API，不依赖任何特定 Adapter。

在 OneBot V11 下回复时支持 At。

## 使用

```python
# load your driver, set adapter, builtin plugin etc.
nonebot.load_plugin("nonebot_plugin_7s_roll")
nonebot.run()
```

其中 .env 文件除了 nonebot 的常规配置项外，还有可添加以下配置属性（示例中的是默认值）：

```env
# 命令名（在 at 机器人时使用， `@bot /roll 1d10`）
I7S_ROLL_COMMAND="roll"
# 关键字（直接使用，无需 at, `roll 1d10`）
I7S_ROLL_TRIGGER="roll"
```

## 命令

`roll <expr>[[ ]<operator>[ ]<target>]`

其中：

- `<expr>` 计算表达式，格式为
  - `<roll>[[ ][+|-][ ]<roll>]...`，其中 `roll` 不超过 20 项，其格式为：
    - `<times>[d|D]<faces>[ ][<policy>]`，其中
      - `<times>` 为投掷次数，不超过 20 次
      - `<faces>` 为骰子面数，不超过 1000 面
      - `<policy>` 为投掷方式，默认为 `sum`，可选方式有：
        - `sum` 求和
        - `min` 取最小值
        - `max` 取最大值
        - `avg` 取平均值
- `operator` 为比较运算，可以为
  - `>`、`大于`
  - `<`、`小于`
  - `>=`、`大于等于`
  - `<=`、`小于等于`
- `target` 为期望目标

## 举例

`roll 3d6`（在只有一个 `roll` 时，会显示的比较详细）:

```text
3d6 投掷结果

第 1 颗：5
第 2 颗：5
第 3 颗：6

总和为 16
```

`roll 3d10+2d6+1 >20`:

```text
3d10+2d6+1 投掷结果(目标 > 20)：
(5 + 1 + 9) + (4 + 5) + 1 = 25，通过
```

`roll 3d100max+4d10`

```text
3d100max+4d10 投掷结果
(max[35, 60, 29] = 60) + (1 + 1 + 5 + 8) = 75
```

## 截图

![screenshot-dice]

## LICENSE

MIT.

[screenshot-dice]: https://rikka.7sdre.am/files/8c6c5b15-0343-4d14-a203-422c7d6c634e.png
languageassistant 0.1.0
An LLM-powered language learning assistant
License: MIT
Requires Python: >=3.9,<3.11

# LanguageAssistant

[![PyPI](https://img.shields.io/pypi/v/languageassistant?style=flat-square)](https://pypi.python.org/pypi/languageassistant/)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/languageassistant?style=flat-square)](https://pypi.python.org/pypi/languageassistant/)
[![PyPI - License](https://img.shields.io/pypi/l/languageassistant?style=flat-square)](https://pypi.python.org/pypi/languageassistant/)

---

**Documentation**: [https://dagleaves.github.io/languageassistant](https://dagleaves.github.io/languageassistant)

**Source Code**: [https://github.com/dagleaves/languageassistant](https://github.com/dagleaves/languageassistant)

**PyPI**: [https://pypi.org/project/languageassistant/](https://pypi.org/project/languageassistant/)

---

LanguageAssistant is a large language model (LLM) powered foreign language learning assistant. This harnesses the
language capabilities of LLMs to provide verbal communication capabilities focused on learning foreign languages.

This project is largely a proof of concept, but has been setup to be extensible so that it could be used as a
backend for a full-fledged application utilizing a better UI, microphone recording, transcription, LLM prompts,
and/or multi-lingual text-to-speech.

Features of LanguageAssistant:
- [x] Full real-time vocal multilingual conversations
  - [x] Real-time voice transcription
  - [x] LLM text responses
  - [x] Multilingual text-to-speech
- [x] LLM agent for lesson planning

## Installation

```sh
pip install languageassistant
```

---