semvec/pypi-packages huggingface dataset:
whois 1.20240129.2
Python package for retrieving WHOIS information of domains.
Requires Python: >=3.9
Keywords: Python,domain,expiration,registrar,tld,whois

# github:python-whois
# pypi: whois

  * A Python package for retrieving WHOIS information of DOMAIN'S ONLY.

**NOTICE: AS OF 2024-02-03; THIS SOFTWARE IS NOW UNSUPPORTED**

ALL FURTHER ACTIONS WILL TAKE PLACE AT
[WhoisDomain](https://github.com/mboot-github/WhoisDomain)

For all further info:

  * see [WhoisDomain](https://github.com/mboot-github/WhoisDomain)
  * all future development will take place on WhoisDomain
tipe 1.1.0
Typed pipe
Requires Python: >=3.8,<4.0

[![PyPI](https://img.shields.io/pypi/v/tipe)](https://pypi.org/project/tipe/)

# Tipe - typed pipe

Tipe allows you to create constructions similar to [pipe operator](https://elixirschool.com/en/lessons/basics/pipe_operator), where result of a function used as an input of next function

## Instalation

```bash
pip install tipe
```


## Examples

```python
>>> from tipe import Pipe
>>> 
>>> Pipe(2).pipe(lambda x: x + 1).pipe(float).unwrap()
3.0
>>> Pipe([2, 3, 4]) \
...         .pipe(len) \
...         .pipe(lambda x: x + 1) \
...         .pipe(float) \
...         .unwrap()
4.0
>>> Pipe(2).pipe(range, 4).pipe(len).unwrap()
2
```

Equivalent for examples above would be

```python
>>> float(2+1)
3.0
>>> float(len([2, 3, 4]) + 1)
4.0
>>> len(range(2, 4))
2
```


## API

### `Pipe()`

To use `.pipe()` on a value wrap it with `Pipe` class

```python
>>> Pipe(2)
Pipe(2)
```

### `Pipe.pipe()`

Pass function to execute on `Pipe` value and additional params for it. Wraps function result in `Pipe` and returns it


### `Pipe.check()`

Like `Pipe.pipe()` but does not change the value inside `Pipe`. May be useful for debugging purposes

```python
>>> Pipe(2).pipe(lambda x: x ** x).check(print).pipe(float).unwrap()
4
4.0
```

### `Pipe.unwrap()`

Returns value from `Pipe`


### Short forms

For convenience you can use `P` as short version of `Pipe` and short versions of the methods:
- `p`: `pipe`
- `c`: `check`
- `u`: `unwrap`


## Types

`tipe` tries its best to stay typesafe, so every function knows what exactly what it returns as long as it is inferable from arguments
axon-serve 0.0.1
Simple package for ML Model serving with gRPC
Requires Python: >=3.8

# AxonServe

Simple package for ML Model serving with gRPC

## Installation

```bash
$ pip install axon_serve
```

## Usage

### Server

```python
from axon_serve import PredictionService, GRPCService

# implement PredictionService class
class TestPredictionService(PredictionService):
    def __init__(self)
        super().__init__()

	# override predict method with your custom prediction logic
	# model_input and return values must be numpy arrays
	# params is a dict with optional kwargs for model
    def predict(self, model_input, params):

        print("model_input: ", model_input.shape)
        print("params: ", params)

        return model_input

if __name__ == "__main__":
	# instantiate your prediction service
	test_prediction_service = TestPredictionService()

	# register it with GRPCService providing the port
	service = GRPCService(test_prediction_service, port=5005)

	# start the server
	service.start()
```

### Client

```python
from axon_serve import ModelServeClient

# instantiate the client providing host and port
serve_client = ModelServeClient(host="localhost", port=5005)

model_input = np.array([1, 2, 3])
params = {"test_param": true}

# call predict method to send request to server
result = serve_client.predict(model_input, params)

print(result.shape)
```

## TODOs

-   [ ] add tests
-   [ ] add support for secure channels
-   [ ] add support for arbitrary tensor serialization