semvec/pypi-packages huggingface dataset:
yt-channel-scraper 0.1.1
All in one Youtube Solution for python. Scrap, Fetch, Download anything from a Youtube Channel, Video.

# yt-channel-scraper
[![📦️Upload PyPi Package](https://github.com/priyanshu-panwar/yt-channel-scraper/actions/workflows/publish.yml/badge.svg)](https://github.com/priyanshu-panwar/yt-channel-scraper/actions/workflows/publish.yml) [![🧪Test](https://github.com/priyanshu-panwar/yt-channel-scraper/actions/workflows/test.yml/badge.svg)](https://github.com/priyanshu-panwar/yt-channel-scraper/actions/workflows/test.yml)

```
All in one Youtube Tool for Python.
```

Helps you fetch the following things of a youtube channel:
- channel_id
- videos (video_ids)
- video transcripts
- download videos

## channel_id
```
from yt_channel_scraper import YoutubeScraper

fy = YoutubeScraper("channel-link")
print(fy.get_channel_id())
```

## videos
```
from yt_channel_scraper import YoutubeScraper

fy = YoutubeScraper("channel-link")
print(fy.get_video_ids(limit=20)) # limit is number of latest videos you need
```

## video transcripts
```
from yt_channel_scraper import YoutubeScraper

fy = YoutubeScraper("channel-link")
v_ids = fy.get_video_ids(limit=20)
print(fy.get_video_transcript()) # fetch video transcripts of all videos
print(fy.get_video_transcript(video_id="video-id")) # fetch video transcript of single video
```

## download videos
```
from yt_channel_scraper import YoutubeDownloader

yd = YoutubeDownloader("video-link")
print(yd.get_download_streams()) # show the available streams to download with tags
yd.download_stream("tag") # give the tag from available streams whichever to download
yd.download_highest_resolution() # download highest resolution available
```
rdjohns-pg 1.6.5
Use for the multiple delete, update or insert and select!

# rdjohns_pg


Keep in mind that this tutorial showed you how to upload your package to Test PyPI, which isnâ€™t a permanent storage. The Test system occasionally deletes packages and accounts. It is best to use TestPyPI for testing and experiments like this tutorial.

When you are ready to upload a real package to the Python Package Index you can do much the same as you did in this tutorial, but with these important differences:
safepay-python 0.0.6
Safepay's python SDK for checkout integration
Requires Python: >=3.6

# Safepay Python SDK

Official python library for [Safepay API](https://getsafepay.com).

## Installation

### With Pip

```
pip install safepay-python
```

## Usage

Import and create a Safepay client by passing your config;

```python
from safepay_python.safepay import *

env = Safepay(
    {
        "environment": "sandbox",
        "apiKey": "sec_asd12-2342s-1231s",
        "v1Secret": "bar",
        "webhookSecret": "foo",
    }
)

```

You can now create payments and checkout links.

### Payments

#### Create payment

| Parameter  | Type         | Required |
| ---------- | ------------ | -------- |
| `amount`   | `number`     | Yes      |
| `currency` | `PKR`, `USD` | Yes      |

```python
payment_response = env.set_payment_details({"amount": 10000, "currency": "PKR"})

token = (payment_response['data'])['token']



# Pass `token` to create checkout link
```

### Checkout

#### Create checkout link

| Parameter     | Type      | Description                                   | Required |
| ------------- | --------- | --------------------------------------------- | -------- |
| `token`       | `string`  | Token from `env.set_payment_details`          | Yes      |
| `orderId`     | `string`  | Your internal invoice / order id              | No       |
| `cancelUrl`   | `string`  | Url to redirect to if user cancels the flow   | Yes      |
| `redirectUrl` | `string`  | Url to redirect to if user completes the flow | Yes      |
| `source`      | `string`  | Optional, defaults to `custom`                | No       |
| `webhooks`    | `boolean` | Optional, defaults to `false`                 | No       |

```python
checkout_url = env.get_checkout_url(
    {
        "beacon": token,
        "cancelUrl": "http://example.com/cancel",
        "orderId": "T800",
        "redirectUrl": "http://example.com/success",
        "source": "custom",
        "webhooks": True,
    }
)


# set webhooks = True if want to subscribe to webhooks
# redirect user to `url`
```

### Verification

#### Signature

| Parameter | Type     | Description                             | Required |
| --------- | -------- | --------------------------------------- | -------- |
| `sig`     | `string` | The `signature` string from your server | Yes      |
| `tracker` | `string` | The `tracker` string from your server   | Yes      |

```python
signature_verification = env.is_signature_valid({"sig": "abcd", "tracker": token})


# mark the invoice as paid if valid
# show an error if invalid
```

#### Webhook

| Parameter          | Type     | Description                             | Required |
| ------------------ | -------- | --------------------------------------- | -------- |
| `x-sfpy-signature` | `string` | The `signature` string from your server | Yes      |
| `data`             | `object` | The `data` object from your server      | Yes      |

```python
webhook_verification = env.is_webhook_valid(
    {"x-sfpy-signature": "abcd"}, {"data": data}
)



# mark the invoice as paid if valid
# show an error if invalid
```
docs-ranking-metrics 0.0.4
The package contains functions for calculating ranking metrics
Requires Python: >=3.7, <4
Keywords: test

# Описание
Данный репозиторий содержит реализацию алгоритмов ранжирования Bm25, LaBSE, MsMarcoST, MsMarcoCE 
с подсчетом метрик: 
* Top@1;
* Top@3;
* Top@5;
* Средняя позиция в выдачах (AverageLoc);
* Cредняя относительная позиция в выдачах (AverageRelLoc);
* Оценка как часто фейковый документ выше всех релевантных (FDARO@v1);
* Оценка как часто фейковый документ выше хотя бы одного релевантного (FDARO@v2);
* Частота попадания фейкового документа в топ 25% (UpQuartile).



# Установка
Для установки пакета воспользуйтесь командой
```
pip install docs-ranking-metrics
```

# Пример использования
Пример использования представлен в `examples/using_metrics.py`

```commandline
# Объявление метрик
metrics = [LaBSE(), Bm25()]
# Объявление класса агрегирующего обновление метрик
rank_metrics = RankingMetrics(metrics)

...

'''
Обновление значений метрик, где 
query - запрос по которому сгенерирован документ, 
sentences - массив документов,
labels - метки документов
'''
rank_metrics.update(query, sentences, labels)

...
# Получение значений подсчитанных метрик ввиде словаря
rank_metrics.get()
# Получение значений метрик при помощи функции show_metrics
rank_metrics.show_metrics()
```

Возможный вывод метода get:
```
{
    'LaBSE_AverageLoc': 10.5, 
    'Bm25_AverageLoc': 1.13513, 
    'LaBSE_Top@1': 0.0, 
    'LaBSE_Top@3': 0.013513, 
    'LaBSE_Top@5': 0.013513, 
    'Bm25_Top@1': 0.91891, 
    'Bm25_Top@3': 1.0, 
    'Bm25_Top@5': 1.0, 
    'LaBSE_FDARO': 0.6216, 
    'Bm25_FDARO': 1.0
}
```

Возможный вывод метода show_metrics():
```
LaBSE_AverageLoc: 4.5   Bm25_AverageLoc: 3.0   
-----------------------------
LaBSE_AverageRelLoc: 0.75   Bm25_AverageRelLoc: 0.5   
-----------------------------
LaBSE_Top@1: 0.0   Bm25_Top@1: 0.5   
LaBSE_Top@3: 0.5   Bm25_Top@3: 0.5   
LaBSE_Top@5: 0.5   Bm25_Top@5: 1.0   
-----------------------------
LaBSE_FDARO@v1: 0.5   Bm25_FDARO@v1: 0.5   
LaBSE_FDARO@v2: 0.5   Bm25_FDARO@v2: 0.5   
-----------------------------
LaBSE_UpQuartile: 0.5   Bm25_UpQuartile: 0.5 
```