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import re, csv 

from cStringIO import StringIO 

 

from scrapy.http import TextResponse 

from scrapy.selector import XmlXPathSelector 

from scrapy import log 

from scrapy.utils.python import re_rsearch, str_to_unicode 

from scrapy.utils.response import body_or_str 

 

 

def xmliter(obj, nodename): 

    """Return a iterator of XPathSelector's over all nodes of a XML document, 

       given tha name of the node to iterate. Useful for parsing XML feeds. 

 

    obj can be: 

    - a Response object 

    - a unicode string 

    - a string encoded as utf-8 

    """ 

    HEADER_START_RE = re.compile(r'^(.*?)<\s*%s(?:\s|>)' % nodename, re.S) 

    HEADER_END_RE = re.compile(r'<\s*/%s\s*>' % nodename, re.S) 

    text = body_or_str(obj) 

 

    header_start = re.search(HEADER_START_RE, text) 

    header_start = header_start.group(1).strip() if header_start else '' 

    header_end = re_rsearch(HEADER_END_RE, text) 

    header_end = text[header_end[1]:].strip() if header_end else '' 

 

    r = re.compile(r"<%s[\s>].*?</%s>" % (nodename, nodename), re.DOTALL) 

    for match in r.finditer(text): 

        nodetext = header_start + match.group() + header_end 

        yield XmlXPathSelector(text=nodetext).select('//' + nodename)[0] 

 

 

def csviter(obj, delimiter=None, headers=None, encoding=None): 

    """ Returns an iterator of dictionaries from the given csv object 

 

    obj can be: 

    - a Response object 

    - a unicode string 

    - a string encoded as utf-8 

 

    delimiter is the character used to separate field on the given obj. 

 

    headers is an iterable that when provided offers the keys 

    for the returned dictionaries, if not the first row is used. 

    """ 

    encoding = obj.encoding if isinstance(obj, TextResponse) else encoding or 'utf-8' 

    def _getrow(csv_r): 

        return [str_to_unicode(field, encoding) for field in csv_r.next()] 

 

    lines = StringIO(body_or_str(obj, unicode=False)) 

    if delimiter: 

        csv_r = csv.reader(lines, delimiter=delimiter) 

    else: 

        csv_r = csv.reader(lines) 

 

    if not headers: 

        headers = _getrow(csv_r) 

 

    while True: 

        row = _getrow(csv_r) 

        if len(row) != len(headers): 

            log.msg("ignoring row %d (length: %d, should be: %d)" % (csv_r.line_num, len(row), len(headers)), log.WARNING) 

            continue 

        else: 

            yield dict(zip(headers, row))