Parsing JavaScript objects into Python dictionaries
Project description
Usage
chompjs can be used in web scrapping for turning JavaScript objects embedded in pages into valid Python dictionaries.
>>> import chompjs >>> chompjs.parse_js_object('{"my_data": "test"}') {u'my_data': u'test'}
Think of it as a more powerful json.loads. For example, it can handle JSON objects containing embedded methods by storing their code in a string:
>>> import chompjs >>> js = """ ... var myObj = { ... myMethod: function(params) { ... // ... ... }, ... myValue: 100 ... } ... """ >>> chompjs.parse_js_object(js, json_params={'strict': False}) {'myMethod': 'function(params) {\n // ...\n }', 'myValue': 100}
An example usage with scrapy:
import chompjs import scrapy class MySpider(scrapy.Spider): # ... def parse(self, response): script_css = 'script:contains("__NEXT_DATA__")::text' script_pattern = r'__NEXT_DATA__ = (.*);' # warning: for some pages you need to pass replace_entities=True # into re_first to have JSON escaped properly script_text = response.css(script_css).re_first(script_pattern) try: json_data = chompjs.parse_js_object(script_text) except ValueError: self.log('Failed to extract data from {}'.format(response.url)) return # work on json_data
If the input string is not yet escaped and contains a lot of \\ characters, then unicode_escape=True argument might help to sanitize it:
>>> chompjs.parse_js_object('{\\\"a\\\": 12}', unicode_escape=True) {u'a': 12}
jsonlines=True can be used to parse JSON Lines:
>>> chompjs.parse_js_object('[1,2]\n[2,3]\n[3,4]', jsonlines=True) [[1, 2], [2, 3], [3, 4]]
By default chompjs tries to start with first { or [ character it founds, omitting the rest:
>>> chompjs.parse_js_object('<div>...</div><script>foo = [1, 2, 3];</script><div>...</div>') [1, 2, 3]
json_params argument can be used to pass options to underlying json_loads, such as strict or object_hook:
>>> import decimal >>> import chompjs >>> chompjs.parse_js_object('[23.2]', json_params={'parse_float': decimal.Decimal}) [Decimal('23.2')]
Rationale
In web scraping data often is not present directly inside HTML, but instead provided as an embedded JavaScript object that is later used to initialize the page, for example:
<html> <head>...</head> <body> ... <script type="text/javascript">window.__PRELOADED_STATE__={"foo": "bar"}</script> ... </body> </html>
Standard library function json.loads is usually sufficient to extract this data:
>>> # scrapy shell file:///tmp/test.html >>> import json >>> script_text = response.css('script:contains(__PRELOADED_STATE__)::text').re_first('__PRELOADED_STATE__=(.*)') >>> json.loads(script_text) {u'foo': u'bar'}
The problem is that not all valid JavaScript objects are also valid JSONs. For example all those strings are valid JavaScript objects but not valid JSONs:
"{'a': 'b'}"is not a valid JSON because it use'character to quote'{a: "b"}'is not a valid JSON because property name is not quoted at all'{"a": [1, 2, 3,]}'is not a valid JSON because there is an extra,character at the end of the array'{"a": .99}'is not a valid JSON because float value lacks a leading 0
As a result, json.loads fail to extract any of those:
>>> json.loads("{'a': 'b'}")
Traceback (most recent call last):
File "<console>", line 1, in <module>
File "/usr/lib/python2.7/json/__init__.py", line 339, in loads
return _default_decoder.decode(s)
File "/usr/lib/python2.7/json/decoder.py", line 364, in decode
obj, end = self.raw_decode(s, idx=_w(s, 0).end())
File "/usr/lib/python2.7/json/decoder.py", line 380, in raw_decode
obj, end = self.scan_once(s, idx)
ValueError: Expecting property name: line 1 column 2 (char 1)
>>> json.loads('{a: "b"}')
Traceback (most recent call last):
File "<console>", line 1, in <module>
File "/usr/lib/python2.7/json/__init__.py", line 339, in loads
return _default_decoder.decode(s)
File "/usr/lib/python2.7/json/decoder.py", line 364, in decode
obj, end = self.raw_decode(s, idx=_w(s, 0).end())
File "/usr/lib/python2.7/json/decoder.py", line 380, in raw_decode
obj, end = self.scan_once(s, idx)
ValueError: Expecting property name: line 1 column 2 (char 1)
>>> json.loads('{"a": [1, 2, 3,]}')
Traceback (most recent call last):
File "<console>", line 1, in <module>
File "/usr/lib/python2.7/json/__init__.py", line 339, in loads
return _default_decoder.decode(s)
File "/usr/lib/python2.7/json/decoder.py", line 364, in decode
obj, end = self.raw_decode(s, idx=_w(s, 0).end())
File "/usr/lib/python2.7/json/decoder.py", line 382, in raw_decode
raise ValueError("No JSON object could be decoded")
ValueError: No JSON object could be decoded
>>> json.loads('{"a": .99}')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/lib/python3.7/json/__init__.py", line 348, in loads
return _default_decoder.decode(s)
File "/usr/lib/python3.7/json/decoder.py", line 337, in decode
obj, end = self.raw_decode(s, idx=_w(s, 0).end())
File "/usr/lib/python3.7/json/decoder.py", line 355, in raw_decode
raise JSONDecodeError("Expecting value", s, err.value) from None
json.decoder.JSONDecodeError: Expecting value: line 1 column 7 (char 6)
chompjs library was designed to bypass this limitation and it allows to scrape such JavaScript objects into proper Python dictionaries:
>>> import chompjs
>>>
>>> chompjs.parse_js_object("{'a': 'b'}")
{u'a': u'b'}
>>> chompjs.parse_js_object('{a: "b"}')
{u'a': u'b'}
>>> chompjs.parse_js_object('{"a": [1, 2, 3,]}')
{u'a': [1, 2, 3]}
Internally chompjs use a parser written in C to iterate over raw string, fixing its issues along the way. The final result is then passed down to standard library's json.loads, ensuring a high speed as compared to full blown JavaScript parsers such as demjson.
>>> import json
>>> import _chompjs
>>>
>>> _chompjs.parse('{a: 1}')
'{"a":1}'
>>> json.loads(_)
{u'a': 1}
>>> chompjs.parse_js_object('{"a": .99}')
{'a': 0.99}
Installation
$ python3 -m venv venv
$ . venv/bin/activate
# pip install chompjs
To run unittests
$ python -m unittest
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