semvec/pypi-packages huggingface dataset:
archi 0.2.3
Multi-format archive library based on libarchive
License: MIT
Keywords: libarchive,archive,compress,compression

# Archi

[![Build Status](https://whtsky.visualstudio.com/archi/_apis/build/status/whtsky.archi?branchName=master)](https://whtsky.visualstudio.com/archi/_build/latest?definitionId=2&branchName=master)

Multi-format archive library based on [libarchive](https://github.com/libarchive/libarchive) . Forked from [pyarchive](https://github.com/tailhook/pyarchive)

## Usage

```python
import archi

with open("test.tgz", "rb") as f:
    archive = archi.Archive(f)
for file in archive:
    print(file.filename)
    print(file.read())
```

Keep in mind that you **can't** store `Entry`s, they're freed as soon as the loop moves on to the next or ends. So this won't do:

```python
archi = archi.Archive('file.zip')
files = [f for f in archi]
files[0].filename # Address boundary error !
```

## Changelog

### v0.2.3

- (wheels) Upgrade bundled libarchive to [v3.4.3](https://github.com/libarchive/libarchive/releases/tag/v3.4.3)

### v0.2.2

- (wheels) Upgrade bundled libarchive to [v3.4.2](https://github.com/libarchive/libarchive/releases/tag/v3.4.2)
- (wheels) Build macOS wheels on macOS 10.14 (https://github.com/whtsky/archi/pull/6)

### v0.2.1

- (wheels) Upgrade bundled libarchive to [v3.4.1](https://github.com/libarchive/libarchive/releases/tag/v3.4.1)

### v0.2.0

- Add support for libarchive's `ARCHIVE_FAILED` error
- use PyMem_Malloc & PyMem_Free instead of alloca

### v0.1.1

- Fix binary wheels for macOS

## TODO

- [ ] compression
- [ ] build wheels for Windows: https://discuss.python.org/t/need-auditwheel-like-utility-for-other-platforms/2028 , https://discuss.python.org/t/packaging-dlls-on-windows/1401
torch-pdegraph 1.1.2
Running paritial difference equations (PDEs) on graphs
License: MIT
Requires Python: >=3.6

# Torch_pdegraph
Torch_pdegraph is a proof of concept that how one can solve PDEs (partial difference equations)  on graphs using the Message Passing class of torch_geometric and hence also benefits from the hardware acceleration. See the [video-presentation](https://www.youtube.com/watch?v=egUjPrJa2l4)

## What is a PDE on a graph?
The basic idea is that one can define the operators like, derivatives, gradients, laplacians on graphs and construct a PDE inspired from nature on graphs.
To know more about PDEs on graph.
- See the publications of [Elmoataz](https://elmoatazbill.users.greyc.fr/pub.html). 
- See also their [applications on pointclouds](https://elmoatazbill.users.greyc.fr/point_cloud/index.html)
- Classical PDEs on images by [Guillermo Sapiro](https://www.youtube.com/watch?v=ZAmig8cw7H8&list=PLEE9b2lRB-R0vii_n3A_3ec9F_Bp_U9Fh&index=2&t=3s)
- Be sure to play with the **jupyter-notebooks in the applications/** folder which presents few of their applications. Download the [data](https://drive.google.com/file/d/1I3IRe1HSoOyh5gBU-cGtLtATWboRMT3-/view?usp=sharing)
- Ref to operator_calculus.md for a brisk intro to calculus on graphs.

## Installation 
First [install](https://pytorch-geometric.readthedocs.io/en/latest/notes/installation.html) the torch_geometric. Then one can clone this project and install it locally:

```shell
pip install --upgrade pip
pip install .
```

Or do:


```shell
pip install --upgrade pip
pip install torch_pdegraph
```

## Running the notebooks
In the notebooks I am demonstrating few applications of pdes on images and pcd by creating simple knn-graphs on gpu. One will need [faiss](https://github.com/facebookresearch/faiss/blob/master/INSTALL.md) library to create the graphs.

To display the pcds inside the notebook I am using jupyter visualization feature in open3d which uses a jupyter widget, notebooks must be running to for the widget to function.

## To do:
- Add an interpolation application.
- Add a segmentation predefined pde.
amqp-py-client 0.0.2
simple rpc amqp python library on pike
License: MIT
Keywords: amqp_client

## usage

simple rpc amqp python library on pike

### consumer

```python
s = ServiceCreator('amqps://user:password@host.cloudamqp.com/vhost',
                   "exchangepypy")


def cb(msg):
    print(msg)
    return msg


s.consume("py.test", "", cb)

```

### rpc request

```python
s = ServiceCreator('amqps://user:password@host.cloudamqp.com/vhost',
                   "exchangepypy")


res,err = s.rpc_request("py.test", "sdsdsdsd", 0)
print(res,err)


```

### fire and forget

```python
s = ServiceCreator('amqps://user:password@host.cloudamqp.com/vhost',
                   "exchangepypy")

s.fire_and_forget("py.test", "cvvccvvcv")


```
api-bridge 0.0.7
Joining json API calls together
License: MIT
Requires Python: >=3.6
Keywords: api,json,web

APIBridge
=========

Joining **json** API calls together

---

[![Build Status](https://travis-ci.org/robin-weiland/APIBridge.svg?branch=master)](https://travis-ci.org/robin-weiland/APIBridge)
[![codecov](https://codecov.io/gh/robin-weiland/APIBridge/branch/master/graph/badge.svg)](https://codecov.io/gh/robin-weiland/APIBridge)
[![PyPI version](https://badge.fury.io/py/api-bridge.svg)](https://badge.fury.io/py/api-bridge)
[![MIT License](https://img.shields.io/badge/license-MIT-blue.svg?style=flat)](http://choosealicense.com/licenses/mit/)

---

# Installation

```batch
pip install api_bridge
```

# Usage

## The API-class

````python
API(url: str,
    method: Method = Method.GET,
    result_filter: Optional[Callable[[Dict[str, Any]], Dict[str, Any]]] = None,
    validate: Optional[Callable[[Dict[str, Any]], bool]] = None,
    post_data: Optional[Dict[str, Any]] = None
    )
````

*url* The url to run a request with

*method* The Enum from `api_bridge.methods.Method` [either `Method.GET` or `.POST`; defaults to `.GET`]

*result_filter* A filter for the retrieved json data `api_bridge.filter.Filter` [defaults to `None`]

 ---
 
````python
Filter(**out: str)
````
*out* The items of the filtered data

examples:

````python
Filter(lat='latitude', long='longitude')  # {'lat': data['latitude'], 'long': data['longitude']}

Filter(sunrise='results sunrise')  # spaces represent {'sunrise': data['results]['sunrise']}
````

---

*validate* An additional test based on the received data in addition to the http-status-code [defaults to None]

example:

````python
validate=lambda data: data['status'] == 'successful'
````

*post_data* Data if `Method.POST` was provided



    


## Requests

There are two ways to run a request

````python
from api_bridge.api import API
from api_bridge.filter import Filter
from api_bridge.container import Container

LOCATION_URL = 'https://ipapi.co/json/'
TIME_URL = 'https://api.sunrise-sunset.org/json?lat={lat}&lng={long}&date=today'
````

The `chain`-method
```python
result = API.chain(
            API(LOCATION_URL, result_filter=Filter(lat='latitude', long='longitude')),
            API(TIME_URL, validate=lambda response: response['status'] == 'OK', result_filter=Filter(sunrise='results sunrise'))
         )

result == {'sunrise': '4:08:10 AM'}
```

The (esoteric) operator-method ```>``` or ```>>```
````
result = API('https://ipapi.co/json/', result_filter=Filter(lat='latitude', long='longitude')) > \
                API('https://api.sunrise-sunset.org/json?lat={lat}&lng={long}&date=today', validate=lambda response:
                    response['status'] == 'OK', result_filter=Filter(sunrise='results sunrise')) > \
                Container()

result == {'sunrise': '4:08:10 AM'}
````

> *Important* the gt and rshift operator mehtod must terminate with an ````Operator()````, which can be treated a dict afterwards