semvec/pypi-packages huggingface dataset:
larry-birdy 0.0.1
A proof-of-concept sentence-oriented Twitter API client for Python, based on 'birdy'.
License: MIT
Keywords: twitter api tweet larry birdy search

# Larry Birdy

`Larry Birdy` is based on ['birdy'](https://github.com/inueni/birdy) and
is sentence-oriented (i.e. sprinkled with syntactic sugar).
Through an experimental (and fuzzy oop design) and proof-of-concept way,
you can make API calls with exprensiveness (and verbosity).

### Install
`pip install larry-birdy`

### Example
```python
from larry.twitter import RestAPI, p

API = RestAPI(CONSUMER_KEY,
              CONSUMER_SECRET,
              ACCESS_TOKEN,
              ACCESS_TOKEN_SECRET)

OWNER = API.verify_account_credentials(skip_status=True)

query = '#python #twitter -rt'
tweet_instances = API.search_tweets(q=query,
                                    result_type='recent',
                                    lang='en',
                                    count=10,
                                    tweet_mode='extended')

# You can write "sentences" like the following:

content_has_media = p.Does.this(status=tweet_instance).have_element('media')
                        # Does this [status] have (the) element ['media']?

hashtags_number = p.Find.for_element('hashtags').its_number_within(tweet_instance)
                    # Find, for (the) element ['hashtags'], its number within (this) [status].

mentions = p.Get.element('user_mentions').from_(tweet_instance)
            # Get (the) element ['user_mentions'], from (this) [status].

user = tweet_instance.user
user_is_following_owner = p.Is.this(user).following(OWNER)
                            # Is this [user] following [OWNER]?

try:
    API.retweet(tweet=tweet_instance, trim_user=True)
except Exception as error_message:
    print(error_message)
```
open3d-python 0.7.0.0
Open3D is an open-source library that supports rapid development of software that deals with 3D data.
License: MIT
Keywords: 3D reconstruction point cloud mesh RGB-D visualization

.. _introduction:

About This Project
#######################

Open3D is an open-source library that supports rapid development of software that deals with 3D data. The Open3D frontend exposes a set of carefully selected data structures and algorithms in both C++ and Python. The backend is highly optimized and is set up for parallelization. We welcome contributions from the open-source community.

If you use Open3D in an academic project, please cite our paper:
::

    @article{Zhou2018,
        author    = {Qian-Yi Zhou and Jaesik Park and Vladlen Koltun},
        title     = {{Open3D}: {A} Modern Library for {3D} Data Processing},
        journal   = {arXiv:1801.09847},
        year      = {2018},
    }

Core features
======================

* Basic 3D data structures
* Basic 3D data processing algorithms
* Scene reconstruction
* Surface alignment
* 3D visualization
* Python binding

Supported platforms
======================

The package has been tested on:

* Ubuntu 16.04 with Python 2.7 and 3.5
* Windows 10 with Python 2.7 and 3.5
* MacOS High Sierra 10.13.4 with Python 2.7

Resources
======================

* Website: `www.open3d.org <http://www.open3d.org>`_
* Code: `github.com/intel-isl/Open3D <https://github.com/intel-isl/Open3D>`_
* Document: `www.open3d.org/docs <http://www.open3d.org/docs>`_
* License: `The MIT license <https://opensource.org/licenses/MIT>`_