{
    "info": {
        "author": "SQream Technologies",
        "author_email": "info@sqream.com",
        "bugtrack_url": null,
        "classifiers": [
            "License :: OSI Approved :: BSD License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3"
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        "description": ".. role:: bash(code)\n   :language: bash\n\n===== \nPython connector for SQream DB\n===== \n\n**Version:**  2.1.4a5\n\n**Supported SQream DB versions:** 1.13 onward\n\nInstalling\n----------\n\nInstall with `pip`, by running\n:bash:`pip install pysqream`.\n\nUsage example:\n----------\n\n.. code-block:: python\n\n    ## Import and establish a connection  \n    #  ---------------------------------   \n    import pysqream\n\n    # version information\n    print pysqream.version_info()\n\n    con = pysqream.Connector()\n    # Connection parameters: IP, Port, Database, Username, Password, Clustered, Timeout(sec)\n    sqream_connection_params = '127.0.0.1', 5000, 'master', 'sqream', 'sqream', False, 30\n    con.connect(*sqream_connection_params)\n\n\n    ## Run queries using the API \n    #  -------------------------     \n    # Create a table\n    statement = 'create or replace table table_name (int_column int)'\n    con.prepare(statement)\n    con.execute()\n    con.close()\n\n    # Insert sample data\n    statement = 'insert into table_name(int_column) values (5), (6)'\n    con.prepare(statement)\n    con.execute()\n    con.close()\n\n    # Retreive data\n    statement = 'select int_column from table_name'\n    con.prepare(statement)\n    con.execute()\n    con.next_row()\n\n    # Pull out the actual data\n    first_row_int = con.get_int(1)\n    con.next_row()\n    second_row_int = con.get_int(1)\n    con.next_row()\n    print (first_row_int, second_row_int)\n    con.close()\n\n\n    ## After running all statements\n    #  ----------------------------\n    con.close_connection()\n\n\nExample of GET data loop:\n----------\n\n.. code-block:: python\n\n    # Here we create the according table by\n    # executing a \"create or replace table table_name (int_column int, varchar_column varchar(10))\" statement\n\n    row1 = []\n    row2 = []\n\n    statement = 'select int_column, varchar_column from table_name'\n    con.prepare(statement)\n    con.execute()\n\n    while con.next_row():\n        row1.append(con.get_int(1))\n        row2.append(con.get_string(2))\n\n    con.close()\n    con.close_connection()\n\nExample of a SET data loop for data loading:\n----------\n.. code-block:: python\n\n    # here we create the according table by executing a \n    # \"create or replace table table_name (int_column int, varchar_column varchar(10))\" statement\n\n    row1 = [1,2,3]\n    row2 = [\"s1\",\"s2\",\"s3\"]\n    length_of_arrays = 3\n\n    # each interogation symbol represent a column to which the network insertion can push\n    statement = 'insert into table_name(int_column, varchar_column) values(?, ?)' \n    con.prepare(statement)\n    con.execute()\n\n    for idx in range(length_of_arrays):\n        con.set_int(1, row1[idx])      # we put a value at column 1 of the table\n        con.set_varchar(2, row2[idx])  # we put a value at column 2 of the table\n        con.next_row()\n\n    con.close()\n    con.close_connection()\n\nExample inserting from a csv to SQream\n----------\n.. code-block:: python\n\n    def insert_from_csv(con,table_name,csv_filename, field_delimiter = ',', null_markers = []):\n\n        # get info on the columns for the insert statement\n\n        # you can get this info after preparing the insert, but we need to at\n        # least know the number of columns to be able to construct the insert\n        # statement\n\n        with pysqream.sqream_run(con,f\"select * from {table_name} limit 0\") as con:\n            column_types = con.get_column_types()\n\n\n        def parse_datetime(v):\n            try:\n                return datetime.datetime.strptime(row[i], '%Y-%m-%d %H:%M:%S.%f')\n            except ValueError:\n                try: \n                    return datetime.datetime.strptime(row[i], '%Y-%m-%d %H:%M:%S')\n                except ValueError:\n                    return datetime.datetime.strptime(row[i], '%Y-%m-%d')\n\n        # insert the csv\n        qstring = \",\".join(['?'] * len(column_types))\n        with pysqream.sqream_run(con, f\"insert into {table_name} values ({qstring})\") as con:\n            with open(csv_filename, mode='r') as csv_file:\n                csv_reader = csv.reader(csv_file, delimiter=field_delimiter)\n                for row in csv_reader:\n                    for i,(t,v) in enumerate(zip(column_types, row)):\n                        ii = i + 1\n                        if row[i] in null_markers:\n                            con.set_null(ii)\n                        elif t.tid == 'Tinyint':\n                            con.set_ubyte(ii, int(row[i]))\n                        elif t.tid == \"Smallint\":\n                            con.set_short(ii, int(row[i]))\n                        elif t.tid == \"Int\":\n                            con.set_int(ii, int(row[i]))\n                        elif t.tid == \"Bigint\":\n                            con.set_long(ii, int(row[i]))\n                        elif t.tid == \"Real\":\n                            con.set_float(ii, float(row[i]))\n                        elif t.tid == \"Float\":\n                            con.set_double(ii, float(row[i]))\n                        elif t.tid == \"Date\":\n                            dt = datetime.datetime.strptime(row[i], \"%Y-%m-%d\")\n                            dt = datetime.date(dt.year, dt.month, dt.day)\n                            con.set_date(ii, dt)\n                        elif t.tid == \"DateTime\":\n                            dt = parse_datetime(row[i])\n                            con.set_datetime(ii, dt)\n                        elif t.tid == \"Varchar\":\n                            con.set_varchar(ii, row[i])\n                        elif t.tid == \"NVarchar\":\n                            con.set_nvarchar(ii, row[i])\n                    con.next_row()\n\nExample saving the results of a query to a csv file\n----------\n.. code-block:: python\n\n    def save_query(con, query, csv_filename, field_delimiter, null_marker):\n\n        with pysqream.sqream_run(con, query) as con:\n            column_types = con.get_column_types()\n            with open(csv_filename, 'x', newline='') as csvfile:\n                wr = csv.writer(csvfile, delimiter=field_delimiter,quoting=csv.QUOTE_MINIMAL)\n                while con.next_row():\n                    csv_row = []\n                    for i,t in enumerate(column_types):\n                        ii = i + 1\n                        if con.is_null(ii):\n                            csv_row.append(null_marker)\n                        elif t.tid == 'Tinyint':\n                            csv_row.append(con.get_ubyte(ii))\n                        elif t.tid == \"Smallint\":\n                            csv_row.append(con.get_short(ii))\n                        elif t.tid == \"Int\":\n                            csv_row.append(con.get_int(ii))\n                        elif t.tid == \"Bigint\":\n                            csv_row.append(con.get_long(ii))\n                        elif t.tid == \"Real\":\n                            csv_row.append(con.get_float(ii))\n                        elif t.tid == \"Float\":\n                            csv_row.append(con.get_double(ii))\n                        elif t.tid == \"Date\":\n                            csv_row.append(con.get_date(ii))\n                        elif t.tid == \"DateTime\":\n                            csv_row.append(con.get_datetime(ii))\n                        elif t.tid == \"Varchar\":\n                            csv_row.append(con.get_varchar(ii))\n                        elif t.tid == \"NVarchar\":\n                            csv_row.append(con.get_nvarchar(ii))\n                    wr.writerow(csv_row)\n\nAPI Reference\n-------------\n\nAll functions are accessed through the Connector class imported from pysqream.py:\n\n**Initialization - Termination**\n\n.. code-block:: python\n\n    import pysqream\n    con = pysqream.Connector()\n\n    # arg types are: string, integer, string, string, string, boolean, integer\n    con.connect(ip, port, database, username, password, clustered, timeout) \n\n    # closes the statement (to do after execute + necessary fetch/put to close the statement and be \n    # able to open another one through prepare())\n    con.close() \n\n    # closes the connection completely, destructing the socket, a call to \"connect(..)\" needs to be done do continue\n    con.close_connection() \n\n\n**High level protocol functions**\n\n.. code-block:: python\n\n    con.prepare(statement) #string of the query to run\n    con.execute()\n\n    # if the statement is an insert it produces a put and for select it produces a fetch, rows are \n    # incremented through that function (see Usage example)\n    con.next_row() \n\n**Get column based data**\n\nBy column id or column name (integer or string)\n\n.. code-block:: python\n\n    is_null(col_id_or_col_name)\n    get_bool(col_id_or_col_name)\n    get_ubyte(col_id_or_col_name)\n    get_short(col_id_or_col_name)\n    get_int(col_id_or_col_name)\n    get_long(col_id_or_col_name)\n    get_float(col_id_or_col_name)\n    get_double(col_id_or_col_name)\n    get_date(col_id_or_col_name)\n    get_datetime(col_id_or_col_name)\n    get_varchar(col_id_or_col_name)\n    get_nvarchar(col_id_or_col_name)\n\n\n**Set column based data**\n\nBy column id\n\n.. code-block:: python\n\n    set_null(col)\n    set_bool(col, val)\n    set_ubyte(col, val)\n    set_short(col, val)\n    set_int(col, val)\n    set_long(col, val)\n    set_float(col, val)\n    set_double(col, val)\n    set_date(col, val)\n    set_datetime(col, val)\n    set_varchar(col, val)\n    set_nvarchar(col, val)\n\n\n",
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