semvec/pypi-packages huggingface dataset:
pypotree 1.0.5
Potree visualization for jypyter notebooks
Requires Python: >=2.7

# PyPotree (potree for jupyter notebooks and colab)

Allows to insert potree cells into jupyter and colab notebooks

[Gabriele Facciolo](mailto:gfacciol@gmail.com), Gabriele Facciolo, CMLA 2019

[**Try it on colab here**](https://colab.research.google.com/drive/1It3EbWy9W8Xf65ikP-_tpkVdJRmvwTQT)


# Installation and dependencies

The main source code repository for this project is https://github.com/cmla/pypotree
It is written in Python and contains Potree and PotreeConverter. It was tested with Python 3.5 and 3.6.

`pypotree` requires C and C++ developement tools.

`pypotree` can be installed with `pip`:

    pip install pypotree

# Usage

In a Python interpreter:

    >>> import pypotree 
    >>> import numpy as np
    >>> xyz = np.random.random((100000,3))
    >>> cloudpath = pypotree.generate_cloud_for_display(xyz)
    >>> pypotree.display_cloud_colab(cloudpath)
acrawler-prometheus 0.0.4
The handler working with aCrawler and Prometheus
Requires Python: >=3.6.0

# acrawler-prometheus

The handler works with [aCrawler](https://github.com/wooddance/aCrawler) and [Prometheus](http://prometheus.io/).

Export statistics for:

- Concurrent requests
- Task (Requests, Items) counts
- Queue status

## Installation

```bash
$ pip install acrawler_prometheus
```

## Usage

Add Handler:

```python
class MyCrawler(Crawler):
    middleware_config = {
        "acrawler_prometheus.PromExporter": 100,
    }

    config = {
        "PROMETHEUS_INTERVAL": 5
    }
```

Avaliable Config:

```python
PROMETHEUS_ADDR = "localhost"
PROMETHEUS_PORT = 8000
PROMETHEUS_INTERVAL = 1  # exporting interval, in second
```
cfn-macro 0.1.0
Core python package for cfnmacro library
Keywords: cfn_macro

=================
CFN Macro Library
=================






Core python package for cfnmacro library



Features
--------

* TODO

Credits
-------

This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage


=======
History
=======

0.1.0 (2019-08-24)
------------------

* First release on PyPI.
puredata-compiler 0.0.1
A tool for writing PureData patches

# PureData Compiler

This package allows you to write patches for [PureData](https://puredata.info) in Python.

## Install

```bash
python -m pip install puredata-compiler  # requires Python >=3.5
```

## Usage

The compiler gives you **creator functions** to compose a patch. These functions
add elements to the patch, using the content and connections you provide.

```python
from puredata_compiler import Patch, write_file


def example():
    """Patch that increments a counter"""
    patch = Patch()
    obj, msg, floatatom, connect = patch.get_creators('obj, msg, floatatom, connect')

    bang = msg('bang')
    delay_params = msg('500', new_row=0, new_col=1)
    delay_trig = obj('t b f', delay_params[0])
    delay = obj('delay', delay_trig[0], delay_trig[1])

    start_val = obj('f', (bang[0], delay[0]), x_pos=25, y_pos=125)
    increment = floatatom(new_row=0)
    current_val = obj('+', start_val[0], increment[0])
    # connect is different - it takes an existing element and adds connections,
    # so you can create circular structures
    connect(start_val, (), current_val[0])
    current_val_display = floatatom(current_val[0])

    return patch

if __name__ == "__main__":
    pd_example = example()
    write_file('pd_example.pd', str(pd_example))
```

### Result

![pd_example.pd](https://dylanburati.github.io/assets/puredata-compiler1.png)
AirStuff 0.1.2
Utilities to speedup AIR (Archivio Istituzionale della Ricerca) document upload, for HEP users
Requires Python: >=3.4

# AirStuff

This small utility helps the poor guys who need to import publications into the AIR (Archivio Istituzionale della Ricerca). By default the program points to the UniMI database https://air.unimi.it/

It automatizes the extraction of: title, full authors list, list of authors for a given institution (see -h), keyword from the address of the inspirehep web page.

## Install
The program needs gtk and its dependency, for example:

   * gcc or a c++ compiler
   * cairo: https://pycairo.readthedocs.io/en/latest/getting_started.html
   * gobject
   * cairo-gobject

Then possibly in a virtualenv:

    pip install airstuff

This can also help you to install dependencies.

## Run it
Just run:

    airstuff

Presently it is suggested to precompute the list of publications from air and inspire with:

    python airstuff/inspire.py --max-results 1000 --out inspire.txt --workers 15

and

    python airstuff/air.py --max-results 1000 --workers 20 --out air.txt

The last do not terminate. Terminate it when it stops to find results.

Then you can run with:

    python airstuff --air-file air.txt  --inspire-file inspire.txt

For other options (as adding additional authors) try `-h` option.

# Old version

    parse_inspire.py

![screenshot](https://raw.githubusercontent.com/wiso/AirStuff/master/screenshot.png)