--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/env/lib/python3.7/site-packages/boto/cloudsearch/search.py	Sat May 02 07:14:21 2020 -0400
@@ -0,0 +1,377 @@
+# Copyright (c) 2012 Mitch Garnaat http://garnaat.org/
+# Copyright (c) 2012 Amazon.com, Inc. or its affiliates.
+# All Rights Reserved
+#
+# Permission is hereby granted, free of charge, to any person obtaining a
+# copy of this software and associated documentation files (the
+# "Software"), to deal in the Software without restriction, including
+# without limitation the rights to use, copy, modify, merge, publish, dis-
+# tribute, sublicense, and/or sell copies of the Software, and to permit
+# persons to whom the Software is furnished to do so, subject to the fol-
+# lowing conditions:
+#
+# The above copyright notice and this permission notice shall be included
+# in all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
+# OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABIL-
+# ITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT
+# SHALL THE AUTHOR BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+# WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
+# IN THE SOFTWARE.
+#
+from math import ceil
+from boto.compat import json, map, six
+import requests
+
+
+class SearchServiceException(Exception):
+    pass
+
+
+class CommitMismatchError(Exception):
+    pass
+
+
+class SearchResults(object):
+    def __init__(self, **attrs):
+        self.rid = attrs['info']['rid']
+        # self.doc_coverage_pct = attrs['info']['doc-coverage-pct']
+        self.cpu_time_ms = attrs['info']['cpu-time-ms']
+        self.time_ms = attrs['info']['time-ms']
+        self.hits = attrs['hits']['found']
+        self.docs = attrs['hits']['hit']
+        self.start = attrs['hits']['start']
+        self.rank = attrs['rank']
+        self.match_expression = attrs['match-expr']
+        self.query = attrs['query']
+        self.search_service = attrs['search_service']
+
+        self.facets = {}
+        if 'facets' in attrs:
+            for (facet, values) in attrs['facets'].items():
+                if 'constraints' in values:
+                    self.facets[facet] = dict((k, v) for (k, v) in map(lambda x: (x['value'], x['count']), values['constraints']))
+
+        self.num_pages_needed = ceil(self.hits / self.query.real_size)
+
+    def __len__(self):
+        return len(self.docs)
+
+    def __iter__(self):
+        return iter(self.docs)
+
+    def next_page(self):
+        """Call Cloudsearch to get the next page of search results
+
+        :rtype: :class:`boto.cloudsearch.search.SearchResults`
+        :return: the following page of search results
+        """
+        if self.query.page <= self.num_pages_needed:
+            self.query.start += self.query.real_size
+            self.query.page += 1
+            return self.search_service(self.query)
+        else:
+            raise StopIteration
+
+
+class Query(object):
+
+    RESULTS_PER_PAGE = 500
+
+    def __init__(self, q=None, bq=None, rank=None,
+                 return_fields=None, size=10,
+                 start=0, facet=None, facet_constraints=None,
+                 facet_sort=None, facet_top_n=None, t=None):
+
+        self.q = q
+        self.bq = bq
+        self.rank = rank or []
+        self.return_fields = return_fields or []
+        self.start = start
+        self.facet = facet or []
+        self.facet_constraints = facet_constraints or {}
+        self.facet_sort = facet_sort or {}
+        self.facet_top_n = facet_top_n or {}
+        self.t = t or {}
+        self.page = 0
+        self.update_size(size)
+
+    def update_size(self, new_size):
+        self.size = new_size
+        self.real_size = Query.RESULTS_PER_PAGE if (self.size >
+            Query.RESULTS_PER_PAGE or self.size == 0) else self.size
+
+    def to_params(self):
+        """Transform search parameters from instance properties to a dictionary
+
+        :rtype: dict
+        :return: search parameters
+        """
+        params = {'start': self.start, 'size': self.real_size}
+
+        if self.q:
+            params['q'] = self.q
+
+        if self.bq:
+            params['bq'] = self.bq
+
+        if self.rank:
+            params['rank'] = ','.join(self.rank)
+
+        if self.return_fields:
+            params['return-fields'] = ','.join(self.return_fields)
+
+        if self.facet:
+            params['facet'] = ','.join(self.facet)
+
+        if self.facet_constraints:
+            for k, v in six.iteritems(self.facet_constraints):
+                params['facet-%s-constraints' % k] = v
+
+        if self.facet_sort:
+            for k, v in six.iteritems(self.facet_sort):
+                params['facet-%s-sort' % k] = v
+
+        if self.facet_top_n:
+            for k, v in six.iteritems(self.facet_top_n):
+                params['facet-%s-top-n' % k] = v
+
+        if self.t:
+            for k, v in six.iteritems(self.t):
+                params['t-%s' % k] = v
+        return params
+
+
+class SearchConnection(object):
+
+    def __init__(self, domain=None, endpoint=None):
+        self.domain = domain
+        self.endpoint = endpoint
+        if not endpoint:
+            self.endpoint = domain.search_service_endpoint
+
+    def build_query(self, q=None, bq=None, rank=None, return_fields=None,
+                    size=10, start=0, facet=None, facet_constraints=None,
+                    facet_sort=None, facet_top_n=None, t=None):
+        return Query(q=q, bq=bq, rank=rank, return_fields=return_fields,
+                     size=size, start=start, facet=facet,
+                     facet_constraints=facet_constraints,
+                     facet_sort=facet_sort, facet_top_n=facet_top_n, t=t)
+
+    def search(self, q=None, bq=None, rank=None, return_fields=None,
+               size=10, start=0, facet=None, facet_constraints=None,
+               facet_sort=None, facet_top_n=None, t=None):
+        """
+        Send a query to CloudSearch
+
+        Each search query should use at least the q or bq argument to specify
+        the search parameter. The other options are used to specify the
+        criteria of the search.
+
+        :type q: string
+        :param q: A string to search the default search fields for.
+
+        :type bq: string
+        :param bq: A string to perform a Boolean search. This can be used to
+            create advanced searches.
+
+        :type rank: List of strings
+        :param rank: A list of fields or rank expressions used to order the
+            search results. A field can be reversed by using the - operator.
+            ``['-year', 'author']``
+
+        :type return_fields: List of strings
+        :param return_fields: A list of fields which should be returned by the
+            search. If this field is not specified, only IDs will be returned.
+            ``['headline']``
+
+        :type size: int
+        :param size: Number of search results to specify
+
+        :type start: int
+        :param start: Offset of the first search result to return (can be used
+            for paging)
+
+        :type facet: list
+        :param facet: List of fields for which facets should be returned
+            ``['colour', 'size']``
+
+        :type facet_constraints: dict
+        :param facet_constraints: Use to limit facets to specific values
+            specified as comma-delimited strings in a Dictionary of facets
+            ``{'colour': "'blue','white','red'", 'size': "big"}``
+
+        :type facet_sort: dict
+        :param facet_sort: Rules used to specify the order in which facet
+            values should be returned. Allowed values are *alpha*, *count*,
+            *max*, *sum*. Use *alpha* to sort alphabetical, and *count* to sort
+            the facet by number of available result.
+            ``{'color': 'alpha', 'size': 'count'}``
+
+        :type facet_top_n: dict
+        :param facet_top_n: Dictionary of facets and number of facets to
+            return.
+            ``{'colour': 2}``
+
+        :type t: dict
+        :param t: Specify ranges for specific fields
+            ``{'year': '2000..2005'}``
+
+        :rtype: :class:`boto.cloudsearch.search.SearchResults`
+        :return: Returns the results of this search
+
+        The following examples all assume we have indexed a set of documents
+        with fields: *author*, *date*, *headline*
+
+        A simple search will look for documents whose default text search
+        fields will contain the search word exactly:
+
+        >>> search(q='Tim') # Return documents with the word Tim in them (but not Timothy)
+
+        A simple search with more keywords will return documents whose default
+        text search fields contain the search strings together or separately.
+
+        >>> search(q='Tim apple') # Will match "tim" and "apple"
+
+        More complex searches require the boolean search operator.
+
+        Wildcard searches can be used to search for any words that start with
+        the search string.
+
+        >>> search(bq="'Tim*'") # Return documents with words like Tim or Timothy)
+
+        Search terms can also be combined. Allowed operators are "and", "or",
+        "not", "field", "optional", "token", "phrase", or "filter"
+
+        >>> search(bq="(and 'Tim' (field author 'John Smith'))")
+
+        Facets allow you to show classification information about the search
+        results. For example, you can retrieve the authors who have written
+        about Tim:
+
+        >>> search(q='Tim', facet=['Author'])
+
+        With facet_constraints, facet_top_n and facet_sort more complicated
+        constraints can be specified such as returning the top author out of
+        John Smith and Mark Smith who have a document with the word Tim in it.
+
+        >>> search(q='Tim',
+        ...     facet=['Author'],
+        ...     facet_constraints={'author': "'John Smith','Mark Smith'"},
+        ...     facet=['author'],
+        ...     facet_top_n={'author': 1},
+        ...     facet_sort={'author': 'count'})
+        """
+
+        query = self.build_query(q=q, bq=bq, rank=rank,
+                                 return_fields=return_fields,
+                                 size=size, start=start, facet=facet,
+                                 facet_constraints=facet_constraints,
+                                 facet_sort=facet_sort,
+                                 facet_top_n=facet_top_n, t=t)
+        return self(query)
+
+    def __call__(self, query):
+        """Make a call to CloudSearch
+
+        :type query: :class:`boto.cloudsearch.search.Query`
+        :param query: A group of search criteria
+
+        :rtype: :class:`boto.cloudsearch.search.SearchResults`
+        :return: search results
+        """
+        url = "http://%s/2011-02-01/search" % (self.endpoint)
+        params = query.to_params()
+
+        r = requests.get(url, params=params)
+        body = r.content.decode('utf-8')
+        try:
+            data = json.loads(body)
+        except ValueError as e:
+            if r.status_code == 403:
+                msg = ''
+                import re
+                g = re.search('<html><body><h1>403 Forbidden</h1>([^<]+)<', body)
+                try:
+                    msg = ': %s' % (g.groups()[0].strip())
+                except AttributeError:
+                    pass
+                raise SearchServiceException('Authentication error from Amazon%s' % msg)
+            raise SearchServiceException("Got non-json response from Amazon. %s" % body, query)
+
+        if 'messages' in data and 'error' in data:
+            for m in data['messages']:
+                if m['severity'] == 'fatal':
+                    raise SearchServiceException("Error processing search %s "
+                        "=> %s" % (params, m['message']), query)
+        elif 'error' in data:
+            raise SearchServiceException("Unknown error processing search %s"
+                % json.dumps(data), query)
+
+        data['query'] = query
+        data['search_service'] = self
+
+        return SearchResults(**data)
+
+    def get_all_paged(self, query, per_page):
+        """Get a generator to iterate over all pages of search results
+
+        :type query: :class:`boto.cloudsearch.search.Query`
+        :param query: A group of search criteria
+
+        :type per_page: int
+        :param per_page: Number of docs in each :class:`boto.cloudsearch.search.SearchResults` object.
+
+        :rtype: generator
+        :return: Generator containing :class:`boto.cloudsearch.search.SearchResults`
+        """
+        query.update_size(per_page)
+        page = 0
+        num_pages_needed = 0
+        while page <= num_pages_needed:
+            results = self(query)
+            num_pages_needed = results.num_pages_needed
+            yield results
+            query.start += query.real_size
+            page += 1
+
+    def get_all_hits(self, query):
+        """Get a generator to iterate over all search results
+
+        Transparently handles the results paging from Cloudsearch
+        search results so even if you have many thousands of results
+        you can iterate over all results in a reasonably efficient
+        manner.
+
+        :type query: :class:`boto.cloudsearch.search.Query`
+        :param query: A group of search criteria
+
+        :rtype: generator
+        :return: All docs matching query
+        """
+        page = 0
+        num_pages_needed = 0
+        while page <= num_pages_needed:
+            results = self(query)
+            num_pages_needed = results.num_pages_needed
+            for doc in results:
+                yield doc
+            query.start += query.real_size
+            page += 1
+
+    def get_num_hits(self, query):
+        """Return the total number of hits for query
+
+        :type query: :class:`boto.cloudsearch.search.Query`
+        :param query: a group of search criteria
+
+        :rtype: int
+        :return: Total number of hits for query
+        """
+        query.update_size(1)
+        return self(query).hits
+
+
+