semvec/pypi-packages huggingface dataset:
TinderBot 0.0.3
A small example package

# TinderBot

You can easily automate your tinder likes using your own credentials. To read the full tutorial of how to get your request headers (credentials) kindly check my article on Medium: https://medium.com/@hfikry92/automate-likes-on-tinder-in-10-minutes-using-python-c16b42164dc6


# Coming soon Features!

  - Using keywords for random Super Likes
  - Integrating with an AI model
  - Wour suggestions are Encouraged (hfikry92@gmail.com) or send me a message on medium @hfikry92 


### Installation

Installing package:

```sh
pip install TinderBot 
```

Installing package through Google Colab, Kaggle or other cloud notebooks that allow package installations

```sh
!pip install TinderBot 
```


### Usage   


| Function | Parameters | Description |
| ------ | ------ | ------ |
| Constructor function | headersPath (String)| a text file path that contains the headers dictionary that is copied from the browser |
| likeNext | - | - |
|likeMany | maxLikes (optional integer)| The maximum number of automated likes |
| |  sleep (optional float) | The default value is 0.5, which is in seconds. It defines sleep time between likes [CANNOT BE LESS THAN 0.5 (SECONDS) or your account will be blocked on Tinder] |
| |  printProgress (optional boolan) | The default is True. it simply shows/hides the progress print |
|likeAll |  sleep (optional float) | The default value is 0.5, which is in seconds. It defines sleep time between likes [CANNOT BE LESS THAN 0.5 (SECONDS) or your account will be blocked on Tinder] |
| |  printProgress (optional boolan) | The default is True. it simply shows/hides the progress print |


### Example

```python
bot = TinderBot("headers_textfile.txt")
bot.likeAll()
#OR
bot.likeMany(maxLikes = 10, sleep = 1)
```



License
----

**Free Software, Hell Yeeahh**
gmaps 0.9.0
Google maps plugin for Jupyter notebooks
Keywords: ipython,jupyter,widgets

`gmaps` is a Jupyter plugin for embedding Google maps in Jupyter notebooks. It is designed to help visualize and interact with geographical data.

Useful links:

 - `Documentation and examples <http://jupyter-gmaps.readthedocs.io/en/latest/>`_
 - `Source code <https://github.com/pbugnion/gmaps>`_
 - `Issue tracker <https://github.com/pbugnion/gmaps/issues>`_
CategorizerAI 0.4.3
An AI to categorize finantial transactions

# Install

pip3 install CategorizerAI

# Usage, Example

There is an example database using a dataset with US government transactions.
The Config.py in the source root is a configuration to use it.
The updater script in the same location drives data acquisition and updating.

You can set up your own setup by studying the example. Copy over the Config.py
to somewhere in PYTHONPATH, the updater script to somewhere in your path,
and change them to your needs. 

The hardest part is tuning the AI for the particular data you have.
use FIRST_LAYER_NEURONS, SECOND_LAYER_NEURONS, BATCH_SIZE and EPOCHS in Config.py
for the tuning. Bigger is not always better!

It might happen that the neural net cannot learn the data with enough accuracy.
In this case it tells you so, and exits.
get-nic 0.0.3
Get Network Interface details

# get-nic


Get Network Interface details such as list of interfaces, ipaddress, mac addrress, status of nic, etc. 
Currently working for Linux. 

## Get Started


Pip install get_nic:
   ```
   pip3 install get_nic
   ```

### import

import module:
```
   from get_nic import getnic
```
### To get list of intefaces

Get list of network interfaces::
```
  getnic.interfaces()
```
Output
["eth0", "wlo1"]

### To get all interface details
From the interface list get details of all the interfaces::
   ```
   interfaces = getnic.interfaces()
   getnic.ipaddr(interfaces)
   ```
### To get selected interface details, example lo, eth0
Pass interface names in a list::
   ```
   interface_list = ['lo','etho']
   getnic.ipaddr(interface_list)
   ```