semvec/pypi-packages huggingface dataset:
tag_wrap 1.0.6
A simple tag wrapping method for XML and HTML.
License: MIT
Keywords: tagwrap tag_wrap development xml html generation

tag_wrap
========

A simple tag and attribute generation tool.

Purpose
=======

Developed to simplify the generation of HTML and XML content.

Usage
=====

Syntax: ``wrap(tag_name, optional_attribute1="here", optional_attributeN="here, content_to_be_wrapped)``

You may specify any number of attributes and any number of items to wrap as well
as nesting tags themselves.

----

Examples
========

``import tag_wrap``

HTML Paragraph
--------------

``tag_wrap.wrap('p', "This is a paragraph.")``

Produces:

``<p>This is a paragraph.</p>``

Nested HTML with attributes and a nested body
---------------------------------------------

``tag_wrap.wrap('html', lang="en-US", wrap('body', 'Body content here'))``

Produces:

``<html lang="en-US"><body>Body content here</body></html>``

----

Authors
=======

Josh Whetton
umat 0.1.20
Unofficial SDK for MobileAppTracking Service APIs
License: MIT

Unofficial SDK for MobileAppTracking Service APIs
=================================================

Configuration file contents:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~

.. code:: ini

    [main]
    api_key = YOUR_API_KEY

    [export]
    advertiser_id = YOUR_ADVERTISER_ID
    timeout = 300  # seconde
    delay = 30  # seconde
    limit = 2000000

Using:
~~~~~~

.. code:: python

    # -*- coding: utf-8 -*-
    from umat import (
        AdvertiserReportCohortValues
        AdvertiserReportLogInstalls
    )
    from datetime import datetime


    config_filename = 'config.ini'


    log_endpoint = AdvertiserReportLogInstalls(config_filename)
    log_endpoint.params.start_date = datetime(2016, 1, 10, 9)
    log_endpoint.params.end_date = datetime(2016, 1, 10, 14)
    log_endpoint.params.timezone = 'utc'
    log_endpoint.params.fields = ['publisher_id', 'publisher.name', 'revenue_usd']
    result_df = log_endpoint.get_dataframe()


    cohort_endpoint = AdvertiserReportCohortValues(filename)
    cohort_endpoint.params.end_date = datetime(2016, 1, 10)
    cohort_endpoint.params.start_date = datetime(2016, 1, 10)
    cohort_endpoint.params.timezone = 'UTC'
    cohort_endpoint.params.fields = ['publisher_id', 'publisher.name', 'revenues_usd']
    cohort_endpoint.params.update({
        'aggregation_type': 'cumulative',
        'cohort_type': 'install',
        'interval': 'year_day',
    })
    result_df = cohort_endpoint.get_dataframe()