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removed unused code for deprecated text search (#322)
* removed unused code for depricated text search Signed-off-by: Lorenz Herzberger <lorenzherzberger@gmail.com> * updated changelog Signed-off-by: Lorenz Herzberger <lorenzherzberger@gmail.com> --------- Signed-off-by: Lorenz Herzberger <lorenzherzberger@gmail.com>
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Lorenz Herzberger
GitHub
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@ -27,6 +27,7 @@ For reference, the possible headings are:
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## [2.2.4] - 2023-15-02
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* **Changed** migrated dependency management to poetry
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* **Removed** removed unused text_search related code
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## [2.2.3] - 2023-14-02
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* **Fixed** fixed voting/election backward compatibility issue (using planetmint-transactions >= 0.7.0) on the 2.2 main branch
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@ -116,41 +116,6 @@ def get_txids_filtered(conn, asset_ids, operation=None, last_tx=None):
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return (elem["id"] for elem in cursor)
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@register_query(LocalMongoDBConnection)
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def text_search(
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conn,
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search,
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*,
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language="english",
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case_sensitive=False,
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diacritic_sensitive=False,
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text_score=False,
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limit=0,
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table="assets"
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):
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cursor = conn.run(
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conn.collection(table)
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.find(
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{
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"$text": {
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"$search": search,
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"$language": language,
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"$caseSensitive": case_sensitive,
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"$diacriticSensitive": diacritic_sensitive,
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}
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},
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{"score": {"$meta": "textScore"}, "_id": False},
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)
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.sort([("score", {"$meta": "textScore"})])
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.limit(limit)
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)
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if text_score:
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return cursor
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return (_remove_text_score(obj) for obj in cursor)
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def _remove_text_score(asset):
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asset.pop("score", None)
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return asset
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@ -243,47 +243,6 @@ def get_txids_filtered(connection, asset_id, operation=None):
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raise NotImplementedError
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@singledispatch
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def text_search(
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conn,
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search,
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*,
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language="english",
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case_sensitive=False,
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diacritic_sensitive=False,
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text_score=False,
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limit=0,
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table=None
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):
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"""Return all the assets that match the text search.
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The results are sorted by text score.
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For more information about the behavior of text search on MongoDB see
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https://docs.mongodb.com/manual/reference/operator/query/text/#behavior
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Args:
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search (str): Text search string to query the text index
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language (str, optional): The language for the search and the rules for
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stemmer and tokenizer. If the language is ``None`` text search uses
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simple tokenization and no stemming.
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case_sensitive (bool, optional): Enable or disable case sensitive
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search.
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diacritic_sensitive (bool, optional): Enable or disable case sensitive
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diacritic search.
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text_score (bool, optional): If ``True`` returns the text score with
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each document.
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limit (int, optional): Limit the number of returned documents.
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Returns:
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:obj:`list` of :obj:`dict`: a list of assets
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Raises:
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OperationError: If the backend does not support text search
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"""
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raise OperationError("This query is only supported when running " "Planetmint with MongoDB as the backend.")
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@singledispatch
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def get_latest_block(conn):
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"""Get the latest commited block i.e. block with largest height"""
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@ -257,25 +257,6 @@ def get_txids_filtered(connection, asset_ids: list[str], operation: str = "", la
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return ids
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@register_query(TarantoolDBConnection)
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def text_search(conn, search, table=TARANT_TABLE_ASSETS, limit=0):
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pattern = ".{}.".format(search)
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field_no = 1 if table == TARANT_TABLE_ASSETS else 2 # 2 for meta_data
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res = conn.run(conn.space(table).call("indexed_pattern_search", (table, field_no, pattern)))
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to_return = []
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if len(res[0]): # NEEDS BEAUTIFICATION
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if table == TARANT_TABLE_ASSETS:
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for result in res[0]:
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to_return.append({"data": json.loads(result[0])["data"], "id": result[1]})
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else:
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for result in res[0]:
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to_return.append({TARANT_TABLE_META_DATA: json.loads(result[1]), "id": result[0]})
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return to_return if limit == 0 else to_return[:limit]
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@register_query(TarantoolDBConnection)
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def get_owned_ids(connection, owner: str) -> list[DbTransaction]:
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outputs = connection.run(connection.space(TARANT_TABLE_OUTPUT).select(owner, index="public_keys"))
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@ -496,18 +496,6 @@ class Planetmint(object):
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logger.warning("Invalid transaction (%s): %s", type(e).__name__, e)
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return False
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def text_search(self, search, *, limit=0, table="assets"):
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"""Return an iterator of assets that match the text search
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Args:
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search (str): Text search string to query the text index
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limit (int, optional): Limit the number of returned documents.
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Returns:
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iter: An iterator of assets that match the text search.
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"""
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return backend.query.text_search(self.connection, search, limit=limit, table=table)
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def get_assets(self, asset_ids) -> list[Asset]:
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"""Return a list of assets that match the asset_ids
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@ -80,90 +80,6 @@
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# for asset in assets:
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# assert query.get_asset(conn, asset['id'])
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#
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# @pytest.mark.skip
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# @pytest.mark.parametrize('table', ['assets', 'metadata'])
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# def test_text_search(table):
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# from planetmint.backend import connect, query
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# conn = connect()
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#
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# # Example data and tests cases taken from the mongodb documentation
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# # https://docs.mongodb.com/manual/reference/operator/query/text/
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# objects = [
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# {'id': 1, 'subject': 'coffee', 'author': 'xyz', 'views': 50},
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# {'id': 2, 'subject': 'Coffee Shopping', 'author': 'efg', 'views': 5},
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# {'id': 3, 'subject': 'Baking a cake', 'author': 'abc', 'views': 90},
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# {'id': 4, 'subject': 'baking', 'author': 'xyz', 'views': 100},
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# {'id': 5, 'subject': 'Café Con Leche', 'author': 'abc', 'views': 200},
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# {'id': 6, 'subject': 'Сырники', 'author': 'jkl', 'views': 80},
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# {'id': 7, 'subject': 'coffee and cream', 'author': 'efg', 'views': 10},
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# {'id': 8, 'subject': 'Cafe con Leche', 'author': 'xyz', 'views': 10}
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# ]
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#
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# # insert the assets
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# conn.db[table].insert_many(deepcopy(objects), ordered=False)
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#
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# # test search single word
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# assert list(query.text_search(conn, 'coffee', table=table)) == [
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# {'id': 1, 'subject': 'coffee', 'author': 'xyz', 'views': 50},
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# {'id': 2, 'subject': 'Coffee Shopping', 'author': 'efg', 'views': 5},
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# {'id': 7, 'subject': 'coffee and cream', 'author': 'efg', 'views': 10},
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# ]
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#
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# # match any of the search terms
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# assert list(query.text_search(conn, 'bake coffee cake', table=table)) == [
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# {'author': 'abc', 'id': 3, 'subject': 'Baking a cake', 'views': 90},
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# {'author': 'xyz', 'id': 1, 'subject': 'coffee', 'views': 50},
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# {'author': 'xyz', 'id': 4, 'subject': 'baking', 'views': 100},
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# {'author': 'efg', 'id': 2, 'subject': 'Coffee Shopping', 'views': 5},
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# {'author': 'efg', 'id': 7, 'subject': 'coffee and cream', 'views': 10}
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# ]
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#
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# # search for a phrase
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# assert list(query.text_search(conn, '\"coffee shop\"', table=table)) == [
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# {'id': 2, 'subject': 'Coffee Shopping', 'author': 'efg', 'views': 5},
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# ]
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#
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# # exclude documents that contain a term
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# assert list(query.text_search(conn, 'coffee -shop', table=table)) == [
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# {'id': 1, 'subject': 'coffee', 'author': 'xyz', 'views': 50},
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# {'id': 7, 'subject': 'coffee and cream', 'author': 'efg', 'views': 10},
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# ]
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#
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# # search different language
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# assert list(query.text_search(conn, 'leche', language='es', table=table)) == [
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# {'id': 5, 'subject': 'Café Con Leche', 'author': 'abc', 'views': 200},
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# {'id': 8, 'subject': 'Cafe con Leche', 'author': 'xyz', 'views': 10}
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# ]
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#
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# # case and diacritic insensitive search
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# assert list(query.text_search(conn, 'сы́рники CAFÉS', table=table)) == [
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# {'id': 6, 'subject': 'Сырники', 'author': 'jkl', 'views': 80},
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# {'id': 5, 'subject': 'Café Con Leche', 'author': 'abc', 'views': 200},
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# {'id': 8, 'subject': 'Cafe con Leche', 'author': 'xyz', 'views': 10}
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# ]
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#
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# # case sensitive search
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# assert list(query.text_search(conn, 'Coffee', case_sensitive=True, table=table)) == [
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# {'id': 2, 'subject': 'Coffee Shopping', 'author': 'efg', 'views': 5},
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# ]
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#
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# # diacritic sensitive search
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# assert list(query.text_search(conn, 'CAFÉ', diacritic_sensitive=True, table=table)) == [
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# {'id': 5, 'subject': 'Café Con Leche', 'author': 'abc', 'views': 200},
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# ]
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#
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# # return text score
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# assert list(query.text_search(conn, 'coffee', text_score=True, table=table)) == [
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# {'id': 1, 'subject': 'coffee', 'author': 'xyz', 'views': 50, 'score': 1.0},
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# {'id': 2, 'subject': 'Coffee Shopping', 'author': 'efg', 'views': 5, 'score': 0.75},
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# {'id': 7, 'subject': 'coffee and cream', 'author': 'efg', 'views': 10, 'score': 0.75},
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# ]
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#
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# # limit search result
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# assert list(query.text_search(conn, 'coffee', limit=2, table=table)) == [
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# {'id': 1, 'subject': 'coffee', 'author': 'xyz', 'views': 50},
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# {'id': 2, 'subject': 'Coffee Shopping', 'author': 'efg', 'views': 5},
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# ]
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#
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# @pytest.mark.skip
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# def test_write_metadata():
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@ -67,30 +67,6 @@ class TestBigchainApi(object):
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with pytest.raises(OperationError):
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b.store_bulk_transactions([tx])
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def test_text_search(self, b, alice):
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from planetmint.backend.tarantool.connection import TarantoolDBConnection
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if isinstance(b.connection, TarantoolDBConnection):
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warnings.warn(" :::::: This function is used only with :::::: ")
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return
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# define the assets
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asset1 = {"data": multihash(marshal({"msg": "Planetmint 1"}))}
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asset2 = {"data": multihash(marshal({"msg": "Planetmint 2"}))}
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asset3 = {"data": multihash(marshal({"msg": "Planetmint 3"}))}
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# create the transactions
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tx1 = Create.generate([alice.public_key], [([alice.public_key], 1)], assets=[asset1]).sign([alice.private_key])
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tx2 = Create.generate([alice.public_key], [([alice.public_key], 1)], assets=[asset2]).sign([alice.private_key])
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tx3 = Create.generate([alice.public_key], [([alice.public_key], 1)], assets=[asset3]).sign([alice.private_key])
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# write the transactions to the DB
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b.store_bulk_transactions([tx1, tx2, tx3])
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# get the assets through text search
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assets = list(b.text_search("planetmint"))
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assert len(assets) == 0
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@pytest.mark.usefixtures("inputs")
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def test_non_create_input_not_found(self, b, user_pk):
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from planetmint_cryptoconditions import Ed25519Sha256
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