semvec/pypi-packages huggingface dataset:
randomizer-ml 0.11.3
Training for models conforming to the scikit-learn api
License: MIT

# Randomizer ML

This library allows you to do randomizer-ML

You can see a talk about this library 

* [here](https://www.youtube.com/watch?v=AHQaQrii1vM&t=439s&ab_channel=DataScienceConnect)

[![Documentation Status](https://readthedocs.org/projects/honest-ml/badge/?version=latest)](https://honest-ml.readthedocs.io/en/latest/?badge=latest)
thepeer 0.1.0
A 3rd party developer friendly client package for thepeer
License: MIT
Requires Python: >=3.9,<4.0
Keywords: thepeer,api wrapper

# thepeer
A 3rd party developer friendly python client package for [thepeer](https://thepeer.co/)

## installation
`pip install thepeer`

## usage
Future versions of this package will provide a much better documentation. This
version was published to claim the package namespace. however, the package is quite
functional as is. First of, you want to import the client
```python

from thepeer import ThePeerClient, ChargeEvent, PaymentChannel
client = ThePeerClient(secret_key="<secret_key>") # you can omit the secret key param if
# the environmental variable THEPEER_SECRET_KEY is set.
response = client.users.all() # Fetch all indexed users.
print(response)

response = client.transactions.get("<transaction_id>") # Fetch a transaction.
print(response)

response = client.links.get_user_links("<user_reference>") # Fetch all linked accounts of a user.
print(response)

response = client.authorize_charge("<charge_reference>", 
                                   event=ChargeEvent.INSUFFICIENT_FUNDS) # Process a charge authorization request.
print(response)

response = client.generate_checkout(amount=10000, email="johndoe@example.com") # Generate a checkout.
print(response)

response = client.get_businesses(
    channel=PaymentChannel.DIRECT_CHARGE) # Fetch businesses based on the API they integrated.
print(response)
```
`ThePeerClient` has three attributes bound to it `users` for user related operations,
`transactions` for transaction related operations and `links` for link related operations.
It also provides additional methods `authorize_charge`, `generate_checkout` and `get_businessses`.
All methods on the client returns a `Response` with is a dataclass containing the `status_code`
and `data` returned from thepeer. This package also provides an async client which mirrors this
client and can come in handy in async context
```python
# note the following code should be tested in an async context to work
# e.g. `python -m asynio`
from thepeer import AsyncThePeerClient

client = AsyncThePeerClient(secret_key="<secret_key>") # you can omit the secret key param if
# the environmental variable THEPEER_SECRET_KEY is set.
response = await client.users.all() # Notice that the `all` method is identical to that
# on the `ThePeerClient` except that we had to await it here.
print(response)
```
All methods are type annotated and also provide docstrings for a smooth developer experience.
I hope you find this package useful.

## source code

- [https://github.com/gray-adeyi/thepeer](https://github.com/gray-adeyi/thepeer)

## license

- MIT
instacrawler 1.0.6
The fastest way to check someone's instagram feed/story.
License: MIT
Requires Python: >=3.7
Keywords: instacrawler,instagram,crawler,crawling,instagram-crawler,instagram-crawling

![PyPI - Version](https://img.shields.io/pypi/v/instacrawler?color=red)
![PyPI - Downloads](https://img.shields.io/pypi/dm/instacrawler?color=orange)
![PyPI - License](https://img.shields.io/pypi/l/instacrawler?color=green)
![PyPI - Python Version](https://img.shields.io/pypi/pyversions/instacrawler?color=blue)

# instacrawler
**instacrawler** is the fastest and simplest way to check someone's instagram feed/story.
- No instagram account required.
- Available on VM

You can find more detailed information in [Caution](#caution).

**<ins>If it helped you, please give me a star⭐️. Thank you!</ins>**


## Installation
- Python >= 3.7
```bash
pip install --upgrade pip
pip install instacrawler
```

## Quick start
```py
import instacrawler

instacrawler.get_latest_feed(username='starbucks')
# OUTPUT : (text, PIL.Image)

instacrawler.get_latest_story(username='starbucks')
# OUTPUT : PIL.Image
```

## Caution
- This library use the mirror site named [imgsed](https://imgsed.com/). So if the site changes, this may not be worked.
- Due to the nature of the mirror site, it is hard to identify fixed feeds.
- When a new feed/story is posted, it needs time to be reflected.
  - New feed : *maybe* up to 4 hours
  - New Story : *maybe* up to 3 hours