semvec/pypi-packages huggingface dataset:
bearychat-py 0.3.1
A simple package for interacting with bearychat.
License: MIT

# bearychat-py

A simple package for interacting with [bearychat][bc]'s API.

[bc]: http://bearychat.com

[![Build Status](https://travis-ci.org/bcho/bearychat-py.svg)](https://travis-ci.org/bcho/bearychat-py)


## Usage

### Incoming Message

```python
>>> import bearychat
>>> bearychat.Incoming('https://hook.bearychat.com').with_text('hello, world').push()
```

## Installation

```bash
pip install bearychat-py
```


## LICENSE

MIT
icanhasfile 0.1.0
COMPUTR, U HAS FILE. I CAN HAS IT?
License: MIT

icanhasfile is a Python module that helps you locate and operate on files using
glob searches.

installashun
------------

Run the following command to install icanhasfile:

.. code-block:: bash

 $ pip install --pre icanhasfile

usage
-----

To get the help dialog, run one of the following commands:

.. code-block:: bash

 $ icanhasfile --help
 $ icanhasfile -h
 $ icanhasfile -?

The general command syntax is below. For a list of options, see the help
dialog. In the first form, you provide an explicit path to search; in the
second, the search is executed in the current directory.

.. code-block:: bash

 $ icanhasfile [options] <path> <filepattern>
 $ icanhasfile [options] <filepattern>


examplez
--------
As an example, let's say we have the following directory structure:

.. code-block:: bash

 +-- pom.xml
 +-- LICENSE.txt
 |
 +-- dir1/
 |   |
 |   \-- pom.xml
 |
 +-- dir2/
 |   |
 |   +-- assembly.xml
 |   +-- pom.xml
 |   \-- version.txt
 |
 +-- dir3/
     |
     \-- context.xml

If you are searching for *pom.xml* and want to give the absolute path to the
top-level directory, issue the command below. You will be prompted to choose
from three matching files:

.. code-block:: bash

 $ icanhasfile /path/to/top-level/dir pom.xml
 [0] pom.xml
 [1] dir1/pom.xml
 [2] dir2/pom.xml
 Choose a number (q to quit):

If you are already in the top-level directory and are searching for *pom.xml*,
issue the command below. You will be prompted to choose from three matching
files:

.. code-block:: bash

 $ icanhasfile pom.xml
 [0] pom.xml
 [1] dir1/pom.xml
 [2] dir2/pom.xml
 Choose a number (q to quit):

If you are already in the top-level directory and are searching for *all* xml
files, issue the command below. You will be prompted to choose from five
matching files:

.. code-block:: bash

 $ icanhasfile '*.xml'
 [0] pom.xml
 [1] dir1/pom.xml
 [2] dir2/assembly.xml
 [3] dir2/pom.xml
 [4] dir3/context.xml
 Choose a number (q to quit):

By default, the selected file will be opened using your $EDITOR. However, you
can also provide a **--command** option to use a different command on your
path. In the example below, we will just *cat* out the file. Also, as it is
run in the icanhasfile source directory and there is only a single matching
file, the file is cat'd without asking the user to choose from multiple
matching files:

.. code-block:: bash

 $ icanhasfile.py --command cat . MANIFEST.in
 include LICENSE.txt
 include README.rst
exlogging 0.1.5
Supports to setup python standard logging package.
License: MIT
Keywords: log logging logger

.. image:: https://travis-ci.org/narusemotoki/exlogging.svg?branch=master
    :target: https://travis-ci.org/narusemotoki/exlogging


exlogging
#########

Supports to setup python standard logging package.

How to use
==========

The way to use exlogging almost same with Python standard logging. First, you can call init function with config dict. After that, completely same with logging.

.. code-block:: python

    import exlogging

    config = {
        'file': {
            'level': 'debug',
            'filename': '/path/to/logfile'
        }
        # You can conbinate with other handlers.
    }

    # If you call init function without second parameter(name), exlogging setup root logger.
    exlogging.init(config)

    bloging.debug("Hello exlogging!")

    # If you want to use named logger, you can call init function with config and name
    exlogging.init(config, 'example')

    # You can access named logger via getLogger function
    example_logger = exlogging.getLogger('example')
    example_logger.info('You named logger')

exlogging or getLogger response object has `debug`, `info`, `warning`, `error`, `exception` and `critical` functions. If you pass  'warning` as `level` in config dict to init function, when you call `warning`, `error`, `critical` or `critical`, it will be logged, but when you call `info` or `debug` function, it is not logged.

Logger is common in your application, so you can setup logger via exlogging at your application entry point, you can use the logger anywhere.

Handlers
========

Common settings
---------------

All handlers have level and format.

Levels
++++++

   * critical
   * error
   * warning
   * info
   * debug
   * notset

Format
++++++

If you don't pass log_format here, exlogging uses this format: %(levelname)s %(name)s - %(asctime)s - File: %(pathname)s - Line: %(lineno)d - Func: %(funcName)s Message: %(message)s

See https://docs.python.org/3.5/library/logging.html#logrecord-attributes

FileHandler
-----------

When you call logger function, record the message in file at filename.

.. code-block:: python

    'file': {
        'level': str, # requirement
        'format': str, # optional
        'filename': str # requirement
    }

RotatingFileHandler
-------------------

When you call logger function, record the message in file at filename.

.. code-block:: python

    'file': {
        'level': str, # requirement
        'format': str, # optional
        'filename': str, # requirement
        'max_bytes': int, # optional
        'backup_count': int # optional
    }

EmailHandler
------------

When you call logger function, send an email with the message.

.. code-block:: python

    'email': {
        'level': str, # requirement
        'format': str, # optional
        'smtp_host': str, # requirement
        'smtp_port': int, # requirement
        'email_from': str, # requirement
        'email_to': str, # requirement
        'email_subject': str, # requirement
        'smtp_username': str, # requirement
        'smtp_password': str # requirement
    }
ezprettyjson 0.1.1
easy json: dynamic exploration of a dict or json in the notebook
License: MIT
Keywords: json,dict,javascript

ezprettyjson
============

| ez stands for easy.
| A convenient and flexible way to explore large json or dictionaries in
  the IPython notebook.
| Heavily inpired by `this javascript library`_

See the `example notebook`_

.. _this javascript library: http://caldwell.github.io/renderjson/
.. _example notebook: http://nbviewer.ipython.org/github/oscar6echo/ezprettyjson/blob/master/demo_ezprettyjson.ipynb
ezmarkdown 0.1.2
easy markdown: Write markdown in IPython notebook and generate standalone HTML file from it, picking the cells to output
License: MIT
Keywords: markdown,export,notebook,HTML

ezmarkdown
==========

**ezmarkdown** stands for easy MarkDown.

| `MarkDown`_ is a convenient way to write formatted documents.
| It was created with the goal of enabling people to “to write using an
  easy-to-read, easy-to-write plain text format, and optionally convert
  it to structurally valid HTML”.
| See `this cheatsheet`_.

This module enables to write MarkDown in an IPython notebook and export
some or all the cells in the notebook as a standalone HTML document.

| The export module uses nbconvert.
| Several export templates are available:
| * Output cells only
| * Input cells only
| * Input and output cells
| * Output cells with toggle input cells
| * Input cells with toggle output cells

See the `example notebook`_

.. _MarkDown: http://en.wikipedia.org/wiki/Markdown
.. _this cheatsheet: https://github.com/adam-p/markdown-here/wiki/Markdown-Cheatsheet
.. _example notebook: http://nbviewer.ipython.org/github/oscar6echo/ezmarkdown/blob/master/demo_ezmarkdown.ipynb
django-rest-api 0.1.5
Django REST API
License: MIT

Django REST API
===============

Installation
------------

.. code:: bash

    $ pip install django-rest-api

You must use Django 1.6 or higher.

Documentation
-------------

To begin with, you should read how to create your different API routes: `URL Routing <https://github.com/skies-io/django-rest-api/wiki/URL-Routing>`_.

Then, you need to learn how to return your responses using our format: `Responses format <https://github.com/skies-io/django-rest-api/wiki/Responses-format>`_.

Finally, it could be useful to know why it is advisable to return the results in JSON: `Format results server side <https://github.com/skies-io/django-rest-api/wiki/Format-results-server-side>`_.
You could also custom the format results on the client side: `Format results client side <https://github.com/skies-io/django-rest-api/wiki/Format-results-client-side>`_.

Two other helpful pages:

- `Get Data <https://github.com/skies-io/django-rest-api/wiki/Get-Data>`_: to retrieve data from the request.
- `Auth Session <https://github.com/skies-io/django-rest-api/wiki/Auth-Session>`_: to add an authentication system to your API.

Example
-------

You can see an example which use all functionalities of the plugin `here <https://github.com/skies-io/django-rest-api/tree/master/example>`_.
Elasticsearch-Raven 1.5.0
Proxy that allows to send logs from Raven to Elasticsearch.
License: MIT

elasticsearch-raven
===================

|Build Status|

Proxy that allows to log from raven to elasticsearch.

Installation
------------

Package
~~~~~~~

elasticsearch-raven can be installed as a normal Python package. Example
installation for pip:

::

    $ pip install elasticsearch-raven

Configuration
-------------

settings.py
~~~~~~~~~~~

Configure Ravan to your proxy location

::

    RAVEN_CONFIG = {
        'dsn': 'protocol://public:secret@host:port/index',
    }

public:secret is required by Raven, for valid Sentry dsn pattern, but it
doesn't affect log sending.

Indexes are formatted with actual date. Suggested format:

**basic-index-{0:%Y.%m.%d}** will result in **basic-index-YYYY.MM.DD**

Environment Variables
~~~~~~~~~~~~~~~~~~~~~

Define elasticsearch location by setting environment variable
ELASTICSEARCH\_HOST (default: 'localhost:9200')

::

    export ELASTICSEARCH_HOST='localhost:9100'

If you use your elasticsearch with https protocol, you should set
environment variable USE\_SSL to True

::

    export USE_SSL=True

To use http authentication just set ELASTICSEARCH\_AUTH variable using
'login:password' format

::

    export ELASTICSEARCH_AUTH=login:password

Usage
-----

Option 1: wsgi
~~~~~~~~~~~~~~

You can run wsgi.py with any http server that supports wsgi. Example
using python simple HTTP server.

::

     #!/usr/bin/env python
     from elasticsearch_raven.wsgi import application
     from wsgiref.simple_server import make_server

     httpd = make_server('', 8000, application)
     httpd.serve_forever()

Option 2: UDP server
~~~~~~~~~~~~~~~~~~~~

You can run udp server with command:

::

    elasticsearch-raven.py host port

.. |Build Status| image:: https://travis-ci.org/pozytywnie/elasticsearch-raven.svg?branch=master
   :target: https://travis-ci.org/pozytywnie/elasticsearch-raven
DataStructuresSerialized 0.0.3
python data structures(tuple list OrderedDict) serialized
License: MIT
Keywords: data structures list serialized deserialization

|

NAME
====

    python data structures list serialized and deserialization


|

SYNOPSIS
========

.. code-block::


    from DataStructuresSerialized import DataStructuresSerialized

    city       = ["China", "010", "beijing"]
    separator  = '|'
    serialized = DataStructuresSerialized(city, separator).getSerializedString()
    print(serialized)

    DataStructuresSerialized $ China|010|beijing

    cityString = "China|010|beijing"
    separator  = '|'
    city       = DataStructuresSerialized(city, separator).getDeserializationStruct()
    print(city)

    DataStructuresSerialized $ ['China', '10', 'beijing']

    cityString = "China|010|beijing"
    separator  = '|'
    index      = 1
    newString  = "000"
    city       = DataStructuresSerialized(cityString, separator)

    city.update(index, newString)
    newCityString = city.getSerializedString()

    print(newCityString)

    DataStructuresSerialized $ China|000|beijing


|

DESCRIPTION
===========

getSerializedString
-------------------
    return serialized string, only support list data structures serialized

getDeserializationStruct
------------------------
    return deserialization list data struct

update
------
    update serialized string or list data structures some substring