semvec/pypi-packages huggingface dataset:
hiisi 0.0.4
Tools for easy handling of hdf5 files
License: MIT
Keywords: hdf5 hdf hiisi weather radar odim

Hiisi
======
The main idea behind hiisi module is to make the handling of hdf5 files as
fluent as possible. Module contains higher level tools such as search and
write methods that are build on top of h5py_ module.

HiisiHDF expands h5py.File class forms the base of the module.
Using HiisiHDF file handle, users can search metadata from the file
without any prior knowledge of the file structure. In addition, HiisiHDF contains
methods for listing the datasets and groups in the file and a convenient method
for creating and expanding hdf5 files.
 
HiisiHDF can be used as such or it can be used as base class for creating more
specialized file handles for different types of data files. An example of custom
data file handle is the hiisi.odim module that contains file handles for reading
weather radar data files that follow the OPERA odim data format.

.. _h5py: http://www.h5py.org/

Examples
--------
Open hdf5 file::

    >>> from hiisi import HiisiHDF
    >>> h5f = HiisiHDF('data.h5')

Get a list of datasets::

    >>> for dataset in h5f.datasets():
            print(dataset)
    '/dataset1/data1/data'
    '/dataset1/data2/data'
    '/dataset2/data1/data'
    '/dataset2/data2/data'

Retrieve all instances of certain attribute::

    >>> gen = h5f.attr_gen('elangle')
    >>> pair = gen.next()
    >>> print(pair.path)
    '/dataset1/where'
    >>> print(pair.value)
    0.5

Create a new hdf5 file with content::

    >>> h5f = HiisiHDF('newfile.h5', 'w')
    >>> filedict = {'/':{'attr1':'A'},
                    '/dataset1/data1/data':{'DATASET':np.zeros(100), 'quantity':'emptyarray'}, 'B':'b'}
    >>> h5f.create_from_filedict(filedict)

Find the names of the groups that contain an attribute with a certain value::

    >>> for result in h5f.search('elangle', 0.5, 0.1):
            print(result)        
    '/dataset1/where'

    >>> for result in h5f.search('quantity', 'DBZH'):
            print(result)
    '/dataset1/data2/what'
    '/dataset2/data2/what'
    '/dataset3/data2/what'
    '/dataset4/data2/what'
    '/dataset5/data2/what'
        
Find the names of the groups that contain a numerical attribute
with a certain value or a value that is within the given tolerance::

    >>> h5f.search('elangle', 0.5, tolerance=0.1)
    [u'/dataset1/where']


Installation
------------
Hiisi is dependent on **numpy** and **h5py** packages. If you have these dependencies already 
installed you can simply run ``pip install hiisi``.

Installing the dependencies and the package

.. code-block:: bash

    $ install pip
    $ pip install numpy
    $ pip install Cython
    $ pip install h5py
    $ pip install hiisi

License
-------
This code is licensed under the MIT open source license.
cloudflaredns-backup 1.8
CloudFlare DNS backup to BIND files
License: MIT
Keywords: cloudflare dns backup

CloudFlare DNS to RFC1035 converter 
===================================


.. image:: https://img.shields.io/pypi/v/cloudflaredns-backup.svg?style=flat-square
    :target: https://pypi.python.org/pypi/cloudflaredns-backup
    


.. image:: https://img.shields.io/pypi/dm/cloudflaredns-backup.svg?style=flat-square
        :target: https://pypi.python.org/pypi/cloudflaredns-backup


Simple tool for backing up your CloudFlare hosted DNS records in format acceptable by BIND (RFC1035)

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

.. code:: bash

    pip install cloudflaredns-backup

Usage
-----

*   get all your CloudFlare zones to console

    .. code:: bash

        cf-backup root@example.com 1234567890 # args
        CF_EMAIL=root@example.com CF_TOKEN=1234567890 cf-backup # env
        echo "root@example.com:1234567890" > credentials.cfg && cf-backup -c credentials.cfg # config file

*   get only example.com and example2.com zones (here and other - just args examples. ENV and cred-file are same)

    .. code:: bash

        cf-backup root@example.com 1234567890 -z example.com -z example2.com
    
    This example may be simplified as:
    
    .. code:: bash

        cf-backup root@example.com 1234567890 -z "example1.com example2.com"

*   Get only example.com, create if not exists folder and write zone to ./zones/example.com, and write NS in zone

    .. code:: bash

        cf-backup root@example.com 1234567890 -z example.com -o zones --ns ns.example.com


CHANGELOG
=========

v1.8
----

Serial is current timestamp if problems with "modified_on"


v1.7.4
------

Real SERIAL number for zones (last modified time in format YYYYmmddHH)

v1.7.3
------

Remove "Exported date" for sensitive tracking of zone-file (for example in Git)

v1.7.2
------

Possibility to add custom name servers for simplify backup deploy of zone.

v1.6
----

Add possibility to determine credentials in args/environment/file

v1.5
----

Small bug fixes

v1.4
----

Fix for unicode support in Python3

v1.3
----

Fix for unicode support in Python2

v1.2
----

Fix for NoneType objects

v1.1
----

Python2 support

v1.0b
-----

PyPI package

v1.0a
-----

Python2-3 cloudflare backup tool
ExtractLevelDomain 2.6.3
pass url to extract domain
License: MIT
Keywords: extract domain,fengyun

# ExtractLevelDomain
通过URL抽取各层各级的域名(一级域名,二级域名....) .  这模块本来是用来分析日志及数据分析的.

# Install Document:

pypi install
```
pip install ExtractLevelDomain
```

source install
```
git clone https://github.com/rfyiamcool/ExtractLevelDomain.git
cd ExtractLevelDomain
python setup.py install
```

# Usage Document:

```
import ExtractLevelDomain
filter = ExtractLevelDomain.ExtractLevelDomain()

#普通抽取域名,默认是最多匹配
print filter.parse_url('http://dmp.301.xiaorui.cc/redirect/xiaorui.cc')

#parse_url_level可以控制level级,可接收的参数两种参数 1 2 3 或"*"
print filter.parse_url_level('http://dmp.301.xiaorui.cc/redirect/xiaorui.cc',level=2)

#set_level设置level级别
filter.set_level(1)

print filter.parse_url_level('http://dmp.301.xiaorui.cc/redirect/xiaorui.cc',level=1)

#现实Level级别
print filter.level
```
django-lazy-choices 0.2.0
Lazy choices for Django models
License: MIT
Keywords: django

Django Lazy Choices
===================

.. image:: https://img.shields.io/travis/jamieconnolly/django-lazy-choices/master.svg
   :target: http://travis-ci.org/jamieconnolly/django-lazy-choices

.. image:: https://img.shields.io/codecov/c/github/jamieconnolly/django-lazy-choices/master.svg
   :target: https://codecov.io/github/jamieconnolly/django-lazy-choices?branch=master

.. image:: https://img.shields.io/pypi/l/django-lazy-choices.svg
   :target: https://github.com/jamieconnolly/django-lazy-choices/blob/master/LICENSE

.. image:: https://img.shields.io/pypi/v/django-lazy-choices.svg
   :target: https://pypi.python.org/pypi/django-lazy-choices

.. image:: https://img.shields.io/pypi/pyversions/django-lazy-choices.svg
   :target: https://pypi.python.org/pypi/django-lazy-choices

.. image:: https://img.shields.io/pypi/status/django-lazy-choices.svg
   :target: https://pypi.python.org/pypi/django-lazy-choices
accounting 1.0.0
accounting is a Python package providing simple and advanced number, money and currency formatting.
License: MIT

accounting
===============================

version number: 0.0.1
author: Bernard Ojengwa

Overview
--------

accounting is a Python package providing simple and advanced number, money and currency formatting.

Installation / Usage
--------------------

To install use pip:

    $ pip install accounting


Or clone the repo:

    $ git clone https://github.com/ojengwa/accounting.git
    $ python setup.py install
    
Contributing
------------

TBD

Example
-------

TBD