pyanyapi

Tools for convenient interface creation over various types of data in a declarative way.

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Project description

Tools for convenient interface creation over various types of data in declarative way.

Installation

The current stable release:

pip install pyanyapi

or:

easy_install pyanyapi

or from source:

$ sudo python setup.py install

Usage

Library provides an ability to create API over various content. Currently there are bundled tools to work with HTML, XML, CSV, JSON and YAML. Initially it was created to work with requests library.

Basic setup

Basic parsers can be declared in following way:

from pyanyapi import HTMLParser


class SimpleParser(HTMLParser):
    settings = {'header': 'string(.//h1/text())'}


>>> api = SimpleParser().parse('<html><body><h1>Value</h1></body></html>')
>>> api.header
Value

Or it can be configured in runtime:

from pyanyapi import HTMLParser


>>> api = HTMLParser({'header': 'string(.//h1/text())'}).parse('<html><body><h1>Value</h1></body></html>')
>>> api.header
Value

To get all parsing results as a dict there is parse_all method. All properties (include defined with @interface_property decorator) will be returned.

from pyanyapi import JSONParser

>>> JSONParser({
    'first': 'container > 0',
    'second': 'container > 1',
    'third': 'container > 2',
}).parse('{"container":["first", "second", "third"]}').parse_all()
{
    'first': 'first',
    'second': 'second',
    'third': 'third',
}

Complex setup

In some cases you may want to apply extra transformations to result list. Here comes “base-children” setup style.

from pyanyapi import HTMLParser


class SimpleParser(HTMLParser):
    settings = {
        'header': {
            'base': '//test',
            'children': 'text()|*//text()'
        }
    }


>>> api = SimpleParser().parse('<xml><test>123 </test><test><inside> 234</inside></test></xml>')
>>> api.test
['123', '234']

Settings inheritance

Settings attribute is merged from all ancestors of current parser.

from pyanyapi import HTMLParser


class ParentParser(HTMLParser):
    settings = {'parent': '//p'}


class FirstChildParser(ParentParser):
    settings = {'parent': '//override'}


class SecondChildParser(ParentParser):
    settings = {'child': '//h1'}


>>> FirstChildParser().settings['parent']
//override

>>> SecondChildParser().settings['parent']
//p

>>> SecondChildParser().settings['child']
//h1

>>> SecondChildParser({'child': '//more'}).settings['child']
//more

Results stripping

Parsers can automagically strip trailing whitespaces with strip=True option.

from pyanyapi import RegExpParser


>>> settings = {'p': 'string(//p)'}
>>> XMLParser(settings).parse('<p> Pcontent </p>').p
 Pcontent
>>> XMLParser(settings, strip=True).parse('<p> Pcontent </p>).p
Pcontent

HTML & XML

For HTML and XML based interfaces XPath 1.0 syntax is used for settings declaration. Unfortunately XPath 2.0 is not supported by lxml. XML is about the same as HTMLParser, but uses different lxml parser internally. Here is an example of usage with requests:

>>> import requests
>>> import pyanyapi
>>> parser = pyanyapi.HTMLParser({'header': 'string(.//h1/text())'})
>>> response = requests.get('http://example.com')
>>> api = parser.parse(response.text)
>>> api.header
Example Domain

If you need, you can execute more XPath queries at any time you want:

from pyanyapi import HTMLParser


>>> parser = HTMLParser({'header': 'string(.//h1/text())'})
>>> api = parser.parse('<html><body><h1>This is</h1><p>test</p></body></html>')
>>> api.header
This is
>>> api.parse('string(//p)')
test

XML Objectify

Lxml provide interesting feature - objectified interface for XML. It converts whole XML to Python object. This parser doesn’t require any settings. E.g:

from pyanyapi import XMLObjectifyParser


>>> XMLObjectifyParser().parse('<xml><test>123</test></xml>').test
123

JSON

Settings syntax in based on PostgreSQL statements syntax.

from pyanyapi import JSONParser


>>> JSONParser({'id': 'container > id'}).parse('{"container":{"id":"123"}}').id
123

Or you can access values in lists by index:

from pyanyapi import JSONParser


>>> JSONParser({'second': 'container > 1'}).parse('{"container":["first", "second", "third"]}').second
second

And executes more queries after initial parsing:

from pyanyapi import JSONParser


>>> api = JSONParser({'second': 'container > 1'}).parse('{"container":[],"second_container":[123]}')
>>> api.parse('second_container > 0')
123

YAML

Equal to JSON parser, but works with YAML data.

from pyanyapi import YAMLParser


>>> YAMLParser({'test': 'container > test'}).parse('container:\n    test: "123"').test
123

Regular Expressions Interface

In case, when data has bad format or is just very complex to be parsed with bundled tools, you can use parser based on regular expressions. Settings is based on Python’s regular expressions. It is most powerful parser, because of its simplicity.

from pyanyapi import RegExpParser


>>> RegExpParser({'error_code': 'Error (\d+)'}).parse('Oh no!!! It is Error 100!!!').error_code
100

And executes more queries after initial parsing:

from pyanyapi import RegExpParser


>>> api = RegExpParser({'digits': '\d+'}).parse('123abc')
>>> api.parse('[a-z]+')
abc

Also, you can pass flags for regular expressions on parser initialization:

from pyanyapi import RegExpParser


>>> RegExpParser({'test': '\d+.\d+'}).parse('123\n234').test
123
>>> RegExpParser({'test': '\d+.\d+'}, flags=re.DOTALL).parse('123\n234').test
123
234

CSV Interface

Operates with CSV data with simple queries in format ‘row_id:column_id’.

from pyanyapi import CSVParser


>>> CSVParser({'value': '1:2'}).parse('1,2,3\r\n4,5,6\r\n').value
6

Also, you can pass custom kwargs for csv.reader on parser initialization:

from pyanyapi import CSVParser


>>> CSVParser({'value': '1:2'}, delimiter=';').parse('1;2;3\r\n4;5;6\r\n').value
6

AJAX Interface

AJAX is very popular technology and often use JSON data with HTML values. Here is an example:

from pyanyapi import AJAXParser


>>> api = AJAXParser({'p': 'content > string(//p)'}).parse('{"content": "<p>Pcontent</p>"}')
>>> api.p
Pcontent

It use combination of XPath queries and PostgreSQL-based JSON lookups. Custom queries execution is also available:

from pyanyapi import AJAXParser


>>> api = AJAXParser().parse('{"content": "<p>Pcontent</p><span>123</span>"}')
>>> api.parse('content > string(//span)')
123

Custom Interface

You can easily declare your own interface. For that you should define execute_method method. And optionally perform_parsing. Here is an example of naive CSVInterface, which provide an ability to get column value by index. Also you should create separate parser for that.

from pyanyapi import BaseInterface, BaseParser


class CSVInterface(BaseInterface):

    def perform_parsing(self):
        return self.content.split(',')

    def execute_method(self, settings):
        return self.parsed_content[settings]


class CSVParser(BaseParser):
    interface_class = CSVInterface


>>> CSVParser({'second': 1}).parse('1,2,3').second
2

Extending interfaces

Also content can be parsed with regular Python code. It can be done with special decorators interface_method and interface_property.

Custom method example:

from pyanyapi import HTMLParser, interface_method


class ParserWithMethod(HTMLParser):
    settings = {'occupation': 'string(.//p/text())'}

    @interface_method
    def hello(self, name):
        return name + ' is ' + self.occupation


>>> api = ParserWithMethod().parse('<html><body><p>programmer</p></body></html>')
>>> api.occupation
programmer

>>> api.hello('John')
John is programmer

Custom property example:

from pyanyapi import HTMLParser, interface_property


class ParserWithProperty(HTMLParser):
    settings = {'p': 'string(.//p/text())', 'h1': 'string(.//h1/text())'}

    @interface_property
    def test(self):
        return self.h1 + ' ' + self.p


>>> api = ParserWithProperty().parse('<html><body><h1>This is</h1><p>test</p></body></html>')
>>> api.h1
This is

>>> api.p
test

>>> api.test
This is test

Certainly previous example can be done with more complex XPath expression, but in general case XPath is not enough.

Complex content parsing

Combined parsers

In situations, when particular content type is unknown before parsing, you can create combined parser, which allows you to use multiply different parsers transparently. E.g. some server usually returns JSON, but in cases of server errors it returns HTML pages with some text. Then:

from pyanyapi import CombinedParser, HTMLParser, JSONParser


class Parser(CombinedParser):
    parsers = [
        JSONParser({'test': 'test'}),
        HTMLParser({'error': 'string(//span)'})
    ]

>>> parser = Parser()
>>> parser.parse('{"test": "Text"}').content
Text
>>> parser.parse('<body><span>123</span></body>').error
123

Another example

Sometimes different content types can be combined inside single string. Often with AJAX requests.

{"content": "<span>Text</span>"}

You can work with such data in following way:

from pyanyapi import HTMLParser, JSONParser, interface_property


inner_parser = HTMLParser({'text': 'string(.//span/text())'})


class AJAXParser(JSONParser):
    settings = {'content': 'content'}

    @interface_property
    def text(self):
        return inner_parser.parse(self.content).text


>>> api = AJAXParser().parse('{"content": "<span>Text</span>"}')
>>> api.text
Text

Now AJAXParser is bundled in pyanyapi, but it works different. But anyway this example can be helpful for building custom parsers.

Python support

PyAnyAPI supports Python 2.6, 2.7, 3.2, 3.3, 3.4, 3.5, PyPy and partially PyPy3 and Jython. Unfortunately lxml doesn’t support PyPy3 and Jython, so HTML & XML parsing is not supported on PyPy3 and Jython.

Project details

These details have not been verified by PyPI

Project links

Homepage

Release history Release notifications | RSS feed

0.6.1

Nov 7, 2017

0.6.0

Aug 9, 2016

0.5.8

Jul 14, 2016

0.5.7

Jan 28, 2016

0.5.6

Nov 24, 2015

0.5.5

Nov 23, 2015

0.5.4

Nov 15, 2015

0.5.3

Oct 30, 2015

0.5.2

Oct 20, 2015

0.5.1

Oct 19, 2015

This version

0.5

Oct 4, 2015

0.4

Sep 29, 2015

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