# Copyright 2020 The SQLNet Company GmbH
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# of this software and associated documentation files (the "Software"), to
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# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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"""This module provides communication routines to access various databases.
The :func:`~getml.database.connect_greenplum`,
:func:`~getml.database.connect_mariadb`,
:func:`~getml.database.connect_mysql`,
:func:`~getml.database.connect_postgres`, and
:func:`~getml.database.connect_sqlite3` functions establish a
connection between a database and the getML engine. During the data
import using either the :meth:`~getml.data.DataFrame.read_db` or
:meth:`~getml.data.DataFrame.read_query` methods of a
:class:`~getml.data.DataFrame` instance or the corresponding
:func:`~getml.data.DataFrame.from_db` class method all data will be
directly loaded from the database into the engine without ever passing
the Python interpreter.
In addition, several auxiliary functions that might be handy during
the analysis and interaction with the database are provided.
"""
import json
import os
import pandas as pd
import getml.communication as comm
import getml.constants as constants
from getml.helpers import (
_str
)
# -----------------------------------------------------------------------------
[docs]class Connection():
"""
A handle to a database connection on the getML engine.
Args:
conn_id (str, optional): The name you want to use to reference the connection.
You can call it
anything you want to. If a database
connection with the same conn_id already exists, that connection
will be removed automatically and the new connection will take its place.
The default conn_id is "default", which refers to the default connection. If you
do not explicitly pass a connection handle to any function that relates to a
database, the default connection will be used automatically.
"""
def __init__(self, conn_id="default"):
self.conn_id = conn_id
def __repr__(self):
return str(self)
def __str__(self):
cmd = dict()
cmd["name_"] = self.conn_id
cmd["type_"] = "Database.describe_connection"
sock = comm.send_and_receive_socket(cmd)
msg = comm.recv_string(sock)
if msg != "Success!":
comm.engine_exception_handler(msg)
description = comm.recv_string(sock)
sock.close()
json_obj = json.loads(description)
json_obj["type"] = "Connection"
return _str(json_obj)
# -----------------------------------------------------------------------------
[docs]def connect_greenplum(
dbname,
user,
password,
host,
hostaddr,
port=5432,
time_formats=None,
conn_id="default"):
"""Creates a new Greenplum database connection.
But first, make sure your database is running and you can reach it
from via your command line.
Args:
dbname (str): The name of the database to which you want to connect.
user (str): User name with which to log into the Greenplum database.
password (str): Password with which to log into the Greenplum database.
host (str): Host of the Greenplum database.
hostaddr (str): IP address of the Greenplum database.
port(int, optional): Port of the Greenplum database.
The default port used by Greenplum is 5432.
If you do not know, which port to use, type the following into your
Greenplum client:
.. code-block:: sql
SELECT setting FROM pg_settings WHERE name = 'port';
time_formats (List[str], optional):
The list of formats tried when parsing time stamps.
The formats are allowed to contain the following
special characters:
* %w - abbreviated weekday (Mon, Tue, ...)
* %W - full weekday (Monday, Tuesday, ...)
* %b - abbreviated month (Jan, Feb, ...)
* %B - full month (January, February, ...)
* %d - zero-padded day of month (01 .. 31)
* %e - day of month (1 .. 31)
* %f - space-padded day of month ( 1 .. 31)
* %m - zero-padded month (01 .. 12)
* %n - month (1 .. 12)
* %o - space-padded month ( 1 .. 12)
* %y - year without century (70)
* %Y - year with century (1970)
* %H - hour (00 .. 23)
* %h - hour (00 .. 12)
* %a - am/pm
* %A - AM/PM
* %M - minute (00 .. 59)
* %S - second (00 .. 59)
* %s - seconds and microseconds (equivalent to %S.%F)
* %i - millisecond (000 .. 999)
* %c - centisecond (0 .. 9)
* %F - fractional seconds/microseconds (000000 - 999999)
* %z - time zone differential in ISO 8601 format (Z or +NN.NN)
* %Z - time zone differential in RFC format (GMT or +NNNN)
* %% - percent sign
conn_id (str, optional): The name to be used to reference the connection.
If you do not pass anything, this will create a new default connection.
Note:
Please note that this feature is **not supported on
Windows**. Please use :func:`~getml.database.connect_odbc`
instead.
By selecting an existing table of your database in
:func:`~getml.data.DataFrame.from_db` function, you can create
a new :class:`~getml.data.DataFrame` containing all its data.
Alternatively you can use the
:meth:`~.getml.data.DataFrame.read_db` and
:meth:`~.getml.data.DataFrame.read_query` methods to replace
the content of the current :class:`~getml.data.DataFrame`
instance or append further rows based on either a table or a
specific query.
You can also write your results back into the Greenplum
database. By passing the name for the destination table to
:meth:`getml.pipeline.Pipeline.transform`, the features
generated from your raw data will be written back. Passing
them into :meth:`getml.pipeline.Pipeline.predict`, instead,
makes predictions of the target variables to new, unseen data
and stores the result into the corresponding table.
"""
# -------------------------------------------
time_formats = time_formats or constants.TIME_FORMATS
# -------------------------------------------
# Prepare command.
cmd = dict()
cmd["name_"] = ""
cmd["type_"] = "Database.new"
cmd["db_"] = "greenplum"
cmd["host_"] = host
cmd["hostaddr_"] = hostaddr
cmd["port_"] = port
cmd["dbname_"] = dbname
cmd["user_"] = user
cmd["time_formats_"] = time_formats
cmd["conn_id_"] = conn_id
# -------------------------------------------
# Send JSON command to engine.
sock = comm.send_and_receive_socket(cmd)
# -------------------------------------------
# The password is sent separately, so it doesn't
# end up in the logs.
comm.send_string(sock, password)
# -------------------------------------------
# Make sure that everything went well.
msg = comm.recv_string(sock)
if msg != "Success!":
comm.engine_exception_handler(msg)
# -------------------------------------------
return Connection(conn_id=conn_id)
# -----------------------------------------------------------------------------
[docs]def connect_mariadb(
dbname,
user,
password,
host,
port=3306,
unix_socket="/var/run/mysqld/mysqld.sock",
time_formats=None,
conn_id="default"):
"""
Creates a new MariaDB database connection.
But first, make sure your database is running and you can reach it
from via your command line.
Args:
dbname (str): The name of the database to which you want to connect.
user (str): User name with which to log into the MariaDB database.
password (str): Password with which to log into the MariaDB database.
host (str): Host of the MariaDB database.
port (int, optional): Port of the MariaDB database.
The default port for MariaDB is 3306.
If you do not know which port to use, type
.. code-block:: sql
SELECT @@port;
into your MariaDB client.
unix_socket (str, optional): The UNIX socket used to connect to the MariaDB database.
If you do not know which UNIX socket to use, type
.. code-block:: sql
SELECT @@socket;
into your MariaDB client.
time_formats (List[str], optional):
The list of formats tried when parsing time stamps.
The formats are allowed to contain the following
special characters:
* %w - abbreviated weekday (Mon, Tue, ...)
* %W - full weekday (Monday, Tuesday, ...)
* %b - abbreviated month (Jan, Feb, ...)
* %B - full month (January, February, ...)
* %d - zero-padded day of month (01 .. 31)
* %e - day of month (1 .. 31)
* %f - space-padded day of month ( 1 .. 31)
* %m - zero-padded month (01 .. 12)
* %n - month (1 .. 12)
* %o - space-padded month ( 1 .. 12)
* %y - year without century (70)
* %Y - year with century (1970)
* %H - hour (00 .. 23)
* %h - hour (00 .. 12)
* %a - am/pm
* %A - AM/PM
* %M - minute (00 .. 59)
* %S - second (00 .. 59)
* %s - seconds and microseconds (equivalent to %S.%F)
* %i - millisecond (000 .. 999)
* %c - centisecond (0 .. 9)
* %F - fractional seconds/microseconds (000000 - 999999)
* %z - time zone differential in ISO 8601 format (Z or +NN.NN)
* %Z - time zone differential in RFC format (GMT or +NNNN)
* %% - percent sign
conn_id (str, optional): The name to be used to reference the connection.
If you do not pass anything, this will create a new default connection.
Note:
By selecting an existing table of your database in
:func:`~getml.data.DataFrame.from_db` function, you can create
a new :class:`~getml.data.DataFrame` containing all its data.
Alternatively you can use the
:meth:`~.getml.data.DataFrame.read_db` and
:meth:`~.getml.data.DataFrame.read_query` methods to replace
the content of the current :class:`~getml.data.DataFrame`
instance or append further rows based on either a table or a
specific query.
You can also write your results back into the MariaDB
database. By passing the name for the destination table to
:meth:`getml.pipeline.Pipeline.transform`, the features
generated from your raw data will be written back. Passing
them into :meth:`getml.pipeline.Pipeline.predict`, instead,
makes predictions
of the target variables to new, unseen data and stores the result into
the corresponding table.
"""
# -------------------------------------------
time_formats = time_formats or constants.TIME_FORMATS
# -------------------------------------------
# Prepare command.
cmd = dict()
cmd["name_"] = ""
cmd["type_"] = "Database.new"
cmd["db_"] = "mariadb"
cmd["host_"] = host
cmd["port_"] = port
cmd["dbname_"] = dbname
cmd["user_"] = user
cmd["unix_socket_"] = unix_socket
cmd["time_formats_"] = time_formats
cmd["conn_id_"] = conn_id
# -------------------------------------------
# Send JSON command to engine.
sock = comm.send_and_receive_socket(cmd)
# -------------------------------------------
# The password is sent separately, so it doesn't
# end up in the logs.
comm.send_string(sock, password)
# -------------------------------------------
# Make sure that everything went well.
msg = comm.recv_string(sock)
if msg != "Success!":
comm.engine_exception_handler(msg)
# -------------------------------------------
return Connection(conn_id=conn_id)
# -----------------------------------------------------------------------------
[docs]def connect_mysql(
dbname,
user,
password,
host,
port=3306,
unix_socket="/var/run/mysqld/mysqld.sock",
time_formats=None,
conn_id="default"):
"""
Creates a new MySQL database connection.
But first, make sure your database is running and you can reach it
from via your command line.
Args:
dbname (str): The name of the database to which you want to connect.
user (str): User name with which to log into the MySQL database.
password (str): Password with which to log into the MySQL database.
host (str): Host of the MySQL database.
port (int, optional): Port of the MySQL database.
The default port for MySQL is 3306.
If you do not know which port to use, type
.. code-block:: sql
SELECT @@port;
into your mysql client.
unix_socket (str, optional): The UNIX socket used to connect to the MySQL database.
If you do not know which UNIX socket to use, type
.. code-block:: sql
SELECT @@socket;
into your mysql client.
time_formats (List[str], optional):
The list of formats tried when parsing time stamps.
The formats are allowed to contain the following
special characters:
* %w - abbreviated weekday (Mon, Tue, ...)
* %W - full weekday (Monday, Tuesday, ...)
* %b - abbreviated month (Jan, Feb, ...)
* %B - full month (January, February, ...)
* %d - zero-padded day of month (01 .. 31)
* %e - day of month (1 .. 31)
* %f - space-padded day of month ( 1 .. 31)
* %m - zero-padded month (01 .. 12)
* %n - month (1 .. 12)
* %o - space-padded month ( 1 .. 12)
* %y - year without century (70)
* %Y - year with century (1970)
* %H - hour (00 .. 23)
* %h - hour (00 .. 12)
* %a - am/pm
* %A - AM/PM
* %M - minute (00 .. 59)
* %S - second (00 .. 59)
* %s - seconds and microseconds (equivalent to %S.%F)
* %i - millisecond (000 .. 999)
* %c - centisecond (0 .. 9)
* %F - fractional seconds/microseconds (000000 - 999999)
* %z - time zone differential in ISO 8601 format (Z or +NN.NN)
* %Z - time zone differential in RFC format (GMT or +NNNN)
* %% - percent sign
conn_id (str, optional): The name to be used to reference the connection.
If you do not pass anything, this will create a new default connection.
Note:
By selecting an existing table of your database in
:func:`~getml.data.DataFrame.from_db` function, you can create
a new :class:`~getml.data.DataFrame` containing all its data.
Alternatively you can use the
:meth:`~.getml.data.DataFrame.read_db` and
:meth:`~.getml.data.DataFrame.read_query` methods to replace
the content of the current :class:`~getml.data.DataFrame`
instance or append further rows based on either a table or a
specific query.
You can also write your results back into the MySQL
database. By passing the name for the destination table to
:meth:`getml.pipeline.Pipeline.transform`, the features
generated from your raw data will be written back. Passing
them into :meth:`getml.pipeline.Pipeline.predict`, instead,
makes predictions of the target variables to new, unseen data
and stores the result into the corresponding table.
"""
# -------------------------------------------
time_formats = time_formats or constants.TIME_FORMATS
# -------------------------------------------
# Prepare command.
cmd = dict()
cmd["name_"] = ""
cmd["type_"] = "Database.new"
cmd["db_"] = "mysql"
cmd["host_"] = host
cmd["port_"] = port
cmd["dbname_"] = dbname
cmd["user_"] = user
cmd["unix_socket_"] = unix_socket
cmd["time_formats_"] = time_formats
cmd["conn_id_"] = conn_id
# -------------------------------------------
# Send JSON command to engine.
sock = comm.send_and_receive_socket(cmd)
# -------------------------------------------
# The password is sent separately, so it doesn't
# end up in the logs.
comm.send_string(sock, password)
# -------------------------------------------
# Make sure that everything went well.
msg = comm.recv_string(sock)
if msg != "Success!":
comm.engine_exception_handler(msg)
# -------------------------------------------
return Connection(conn_id=conn_id)
# -----------------------------------------------------------------------------
[docs]def connect_odbc(
server_name,
user="",
password="",
escape_chars='"',
double_precision="DOUBLE PRECISION",
integer="INTEGER",
text="TEXT",
time_formats=None,
conn_id="default"):
"""
Creates a new ODBC database connection.
ODBC is standardized format that can be used to connect to almost any
database.
Before you use the ODBC connector, make sure the database is up and
running and that the appropriate ODBC drivers are installed.
Args:
server_name (str): The server name, as referenced in your .obdc.ini file.
user (str, optional): User name with which to log into the database.
You do not need to pass this, if it is already contained in your
.odbc.ini.
password (str, optional): Password with which to log into the database.
You do not need to pass this, if it is already contained in your
.odbc.ini.
escape_chars (str, optional): ODBC drivers are supposed to support
escaping table and column names using '"' characters irrespective of the
syntax in the target database. Unfortunately, not ODBC drivers
follow this standard. This is why some
tuning might be necessary.
The escape_chars value behaves as follows:
* If you pass an empty string, schema, table and column names will not
be escaped at all. This is not a problem unless some table
or column names are identical to SQL keywords.
* If you pass a single character, schema, table and column names will
be enveloped in that character: "TABLE_NAME"."COLUMN_NAME" (standard SQL)
or `TABLE_NAME`.`COLUMN_NAME` (MySQL/MariaDB style).
* If you pass two characters, table, column and schema names will be enveloped
between these to characters. For instance, if you pass "[]", the produced
queries look as follows: [TABLE_NAME].[COLUMN_NAME] (MS SQL Server style).
* If you pass more than two characters, the engine will throw an exception.
double_precision (str, optional): The keyword used for double precision columns.
integer (str, optional): The keyword used for integer columns.
text (str, optional): The keyword used for text columns.
time_formats (List[str], optional):
The list of formats tried when parsing time stamps.
The formats are allowed to contain the following
special characters:
* %w - abbreviated weekday (Mon, Tue, ...)
* %W - full weekday (Monday, Tuesday, ...)
* %b - abbreviated month (Jan, Feb, ...)
* %B - full month (January, February, ...)
* %d - zero-padded day of month (01 .. 31)
* %e - day of month (1 .. 31)
* %f - space-padded day of month ( 1 .. 31)
* %m - zero-padded month (01 .. 12)
* %n - month (1 .. 12)
* %o - space-padded month ( 1 .. 12)
* %y - year without century (70)
* %Y - year with century (1970)
* %H - hour (00 .. 23)
* %h - hour (00 .. 12)
* %a - am/pm
* %A - AM/PM
* %M - minute (00 .. 59)
* %S - second (00 .. 59)
* %s - seconds and microseconds (equivalent to %S.%F)
* %i - millisecond (000 .. 999)
* %c - centisecond (0 .. 9)
* %F - fractional seconds/microseconds (000000 - 999999)
* %z - time zone differential in ISO 8601 format (Z or +NN.NN)
* %Z - time zone differential in RFC format (GMT or +NNNN)
* %% - percent sign
conn_id (str, optional): The name to be used to reference the connection.
If you do not pass anything, this will create a new default connection.
Note:
By selecting an existing table of your database in
:func:`~getml.data.DataFrame.from_db` function, you can create
a new :class:`~getml.data.DataFrame` containing all its data.
Alternatively you can use the
:meth:`~.getml.data.DataFrame.read_db` and
:meth:`~.getml.data.DataFrame.read_query` methods to replace
the content of the current :class:`~getml.data.DataFrame`
instance or append further rows based on either a table or a
specific query.
You can also write your results back into the
database. By passing the name for the destination table to
:meth:`getml.pipeline.Pipeline.transform`, the features
generated from your raw data will be written back. Passing
them into :meth:`getml.pipeline.Pipeline.predict`, instead,
makes predictions of the target variables to new, unseen data
and stores the result into the corresponding table.
"""
# -------------------------------------------
time_formats = time_formats or constants.TIME_FORMATS
# -------------------------------------------
# Prepare command.
cmd = dict()
cmd["name_"] = ""
cmd["type_"] = "Database.new"
cmd["db_"] = "odbc"
cmd["server_name_"] = server_name
cmd["user_"] = user
cmd["escape_chars_"] = escape_chars
cmd["double_precision_"] = double_precision
cmd["integer_"] = integer
cmd["text_"] = text
cmd["time_formats_"] = time_formats
cmd["conn_id_"] = conn_id
# -------------------------------------------
# Send JSON command to engine.
sock = comm.send_and_receive_socket(cmd)
# -------------------------------------------
# The password is sent separately, so it doesn't
# end up in the logs.
comm.send_string(sock, password)
# -------------------------------------------
# Make sure that everything went well.
msg = comm.recv_string(sock)
if msg != "Success!":
comm.engine_exception_handler(msg)
# -------------------------------------------
return Connection(conn_id=conn_id)
# -----------------------------------------------------------------------------
[docs]def connect_postgres(
dbname,
user,
password,
host,
hostaddr,
port=5432,
time_formats=None,
conn_id="default"):
"""
Creates a new PostgreSQL database connection.
But first, make sure your database is running and you can reach it
from via your command line.
Args:
dbname (str): The name of the database to which you want to connect.
user (str): User name with which to log into the PostgreSQL database.
password (str): Password with which to log into the PostgreSQL database.
host (str): Host of the PostgreSQL database.
hostaddr (str): IP address of the PostgreSQL database.
port(int, optional): Port of the PostgreSQL database.
The default port used by PostgreSQL is 5432.
If you do not know, which port to use, type the following into your
PostgreSQL client
.. code-block:: sql
SELECT setting FROM pg_settings WHERE name = 'port';
time_formats (List[str], optional):
The list of formats tried when parsing time stamps.
The formats are allowed to contain the following
special characters:
* %w - abbreviated weekday (Mon, Tue, ...)
* %W - full weekday (Monday, Tuesday, ...)
* %b - abbreviated month (Jan, Feb, ...)
* %B - full month (January, February, ...)
* %d - zero-padded day of month (01 .. 31)
* %e - day of month (1 .. 31)
* %f - space-padded day of month ( 1 .. 31)
* %m - zero-padded month (01 .. 12)
* %n - month (1 .. 12)
* %o - space-padded month ( 1 .. 12)
* %y - year without century (70)
* %Y - year with century (1970)
* %H - hour (00 .. 23)
* %h - hour (00 .. 12)
* %a - am/pm
* %A - AM/PM
* %M - minute (00 .. 59)
* %S - second (00 .. 59)
* %s - seconds and microseconds (equivalent to %S.%F)
* %i - millisecond (000 .. 999)
* %c - centisecond (0 .. 9)
* %F - fractional seconds/microseconds (000000 - 999999)
* %z - time zone differential in ISO 8601 format (Z or +NN.NN)
* %Z - time zone differential in RFC format (GMT or +NNNN)
* %% - percent sign
conn_id (str, optional): The name to be used to reference the connection.
If you do not pass anything, this will create a new default connection.
Note:
Please note that this feature is **not supported on
Windows**. Please use :func:`~getml.database.connect_odbc`
instead.
By selecting an existing table of your database in
:func:`~getml.data.DataFrame.from_db` function, you can create
a new :class:`~getml.data.DataFrame` containing all its data.
Alternatively you can use the
:meth:`~.getml.data.DataFrame.read_db` and
:meth:`~.getml.data.DataFrame.read_query` methods to replace
the content of the current :class:`~getml.data.DataFrame`
instance or append further rows based on either a table or a
specific query.
You can also write your results back into the PostgreSQL
database. By passing the name for the destination table to
:meth:`getml.pipeline.Pipeline.transform`, the features
generated from your raw data will be written back. Passing
them into :meth:`getml.pipeline.Pipeline.predict`, instead,
makes predictions of the target variables to new, unseen data
and stores the result into the corresponding table.
"""
# -------------------------------------------
time_formats = time_formats or constants.TIME_FORMATS
# -------------------------------------------
# Prepare command.
cmd = dict()
cmd["name_"] = ""
cmd["type_"] = "Database.new"
cmd["db_"] = "postgres"
cmd["host_"] = host
cmd["hostaddr_"] = hostaddr
cmd["port_"] = port
cmd["dbname_"] = dbname
cmd["user_"] = user
cmd["time_formats_"] = time_formats
cmd["conn_id_"] = conn_id
# -------------------------------------------
# Send JSON command to engine.
sock = comm.send_and_receive_socket(cmd)
# -------------------------------------------
# The password is sent separately, so it doesn't
# end up in the logs.
comm.send_string(sock, password)
# -------------------------------------------
# Make sure that everything went well.
msg = comm.recv_string(sock)
if msg != "Success!":
comm.engine_exception_handler(msg)
# -------------------------------------------
return Connection(conn_id=conn_id)
# -----------------------------------------------------------------------------
[docs]def connect_sqlite3(
name=":memory:",
time_formats=None,
conn_id="default"):
"""Creates a new SQLite3 database connection.
SQLite3 is a popular in-memory database. It is faster than
distributed databases, like PostgreSQL, but less stable under massive
parallel access, consumes more memory and requires all contained
data sets to be loaded into memory, which might fill up too much
of your RAM, especially for large data set.
Args:
name (str, optional): Name of the sqlite3 file. If the file does not exist, it
will be created. Set to ":memory:" for a purely in-memory SQLite3
database.
time_formats (List[str], optional):
The list of formats tried when parsing time stamps.
The formats are allowed to contain the following
special characters:
* %w - abbreviated weekday (Mon, Tue, ...)
* %W - full weekday (Monday, Tuesday, ...)
* %b - abbreviated month (Jan, Feb, ...)
* %B - full month (January, February, ...)
* %d - zero-padded day of month (01 .. 31)
* %e - day of month (1 .. 31)
* %f - space-padded day of month ( 1 .. 31)
* %m - zero-padded month (01 .. 12)
* %n - month (1 .. 12)
* %o - space-padded month ( 1 .. 12)
* %y - year without century (70)
* %Y - year with century (1970)
* %H - hour (00 .. 23)
* %h - hour (00 .. 12)
* %a - am/pm
* %A - AM/PM
* %M - minute (00 .. 59)
* %S - second (00 .. 59)
* %s - seconds and microseconds (equivalent to %S.%F)
* %i - millisecond (000 .. 999)
* %c - centisecond (0 .. 9)
* %F - fractional seconds/microseconds (000000 - 999999)
* %z - time zone differential in ISO 8601 format (Z or +NN.NN)
* %Z - time zone differential in RFC format (GMT or +NNNN)
* %% - percent sign
conn_id (str, optional): The name to be used to reference the connection.
If you do not pass anything, this will create a new default connection.
Note:
By selecting an existing table of your database in
:func:`~getml.data.DataFrame.from_db` function, you can create
a new :class:`~getml.data.DataFrame` containing all its data.
Alternatively you can use the
:meth:`~.getml.data.DataFrame.read_db` and
:meth:`~.getml.data.DataFrame.read_query` methods to replace
the content of the current :class:`~getml.data.DataFrame`
instance or append further rows based on either a table or a
specific query.
You can also write your results back into the SQLite3
database. By passing the name for the destination table to
:meth:`getml.pipeline.Pipeline.transform`, the features
generated from your raw data will be written back. Passing
them into :meth:`getml.pipeline.Pipeline.predict`, instead,
makes predictions of the target variables to new, unseen data
and stores the result into the corresponding table.
"""
# -------------------------------------------
time_formats = time_formats or constants.TIME_FORMATS
# -------------------------------------------
# We want to use the absolute path, unless it is a pure
# in-memory version.
name_ = name
if name_ != ":memory":
os.path.abspath(name)
# -------------------------------------------
# Prepare command.
cmd = dict()
cmd["name_"] = name_
cmd["type_"] = "Database.new"
cmd["db_"] = "sqlite3"
cmd["time_formats_"] = time_formats
cmd["conn_id_"] = conn_id
# -------------------------------------------
# Send JSON command to engine.
sock = comm.send_and_receive_socket(cmd)
# -------------------------------------------
# The password is sent separately, so it doesn't
# end up in the logs. However, Sqlite3 does not
# need a password, so we just send a dummy.
comm.send_string(sock, "none")
# -------------------------------------------
# Make sure that everything went well.
msg = comm.recv_string(sock)
if msg != "Success!":
comm.engine_exception_handler(msg)
# -------------------------------------------
return Connection(conn_id=conn_id)
# -----------------------------------------------------------------------------
[docs]def copy_table(source_conn, target_conn, source_table, target_table=None):
"""
Copies a table from one database connection to another.
Args:
source_conn (:class:`~getml.database.Connection`): The database
connection to be copied from.
target_conn (:class:`~getml.database.Connection`): The database
connection to be copied to.
source_table (str): The name of the table in the source connection.
target_table (str, optional): The name of the table in the target
connection. If you do not explicitly pass a target_table, the
name will be identical to the source_table.
Example:
A frequent use case for this function is to copy data from a data source into
sqlite. This is a good idea, because sqlite is faster than most standard,
ACID-compliant databases and also you want to avoid messing up a productive
environment.
It is important to explicitly pass conn_id, otherwise the source connection
will be closed
when you create the target connection. What you pass as conn_id is entirely
up to you,
as long as the conn_id of the source and the target are different. It can
be any name you see fit.
>>> source_conn = getml.database.connect_odbc("MY-SERVER-NAME", conn_id="MY-SOURCE")
>>>
>>> target_conn = getml.database.connect_sqlite3("MY-SQLITE.db", conn_id="MY-TARGET")
>>>
>>> data.database.copy_table(
... source_conn=source_conn,
... target_conn=target_conn,
... source_table="MY-TABLE"
... )
"""
# -------------------------------------------
target_table = target_table or source_table
# -------------------------------------------
# Prepare command.
cmd = dict()
cmd["name_"] = ""
cmd["type_"] = "Database.copy_table"
cmd["source_conn_id_"] = source_conn.conn_id
cmd["target_conn_id_"] = target_conn.conn_id
cmd["source_table_"] = source_table
cmd["target_table_"] = target_table
# -------------------------------------------
# Send JSON command to engine.
comm.send(cmd)
# -----------------------------------------------------------------------------
[docs]def drop_table(
name, conn=None):
"""
Drops a table from the database.
Args:
name (str): The table to be dropped.
conn (:class:`~getml.database.Connection`, optional): The database connection to be used.
If you don't explicitly pass a connection, the engine will use the default connection.
"""
# -------------------------------------------
conn = conn or Connection()
# -------------------------------------------
# Prepare command.
cmd = dict()
cmd["name_"] = name
cmd["type_"] = "Database.drop_table"
cmd["conn_id_"] = conn.conn_id
# -------------------------------------------
# Send JSON command to engine.
comm.send(cmd)
# -----------------------------------------------------------------------------
[docs]def get(query, conn=None):
"""
Executes an SQL query on the database and returns the result as
a pandas dataframe.
Args:
query (str): The SQL query to be executed.
conn (:class:`~getml.database.Connection`, optional): The database connection to be used.
If you don't explicitly pass a connection, the engine will use the default connection.
"""
# -------------------------------------------
conn = conn or Connection()
# -------------------------------------------
# Prepare command.
cmd = dict()
cmd["name_"] = conn.conn_id
cmd["type_"] = "Database.get"
# -------------------------------------------
# Send JSON command to engine.
sock = comm.send_and_receive_socket(cmd)
# -------------------------------------------
# Send the actual query.
comm.send_string(sock, query)
# -------------------------------------------
# Make sure that everything went well.
msg = comm.recv_string(sock)
if msg != "Success!":
comm.engine_exception_handler(msg)
# -------------------------------------------
# Return results as pd.DataFrame.
json_str = comm.recv_string(sock)
sock.close()
return pd.read_json(json_str)
# -----------------------------------------------------------------------------
[docs]def execute(query, conn=None):
"""
Executes an SQL query on the database.
Please note that this is not meant to return results. If you want to
get results, use database.get(...) instead.
Args:
query (str): The SQL query to be executed.
conn (:class:`~getml.database.Connection`, optional): The database connection to be used.
If you don't explicitly pass a connection, the engine will use the default connection.
"""
# -------------------------------------------
conn = conn or Connection()
# -------------------------------------------
# Prepare command.
cmd = dict()
cmd["name_"] = conn.conn_id
cmd["type_"] = "Database.execute"
# -------------------------------------------
# Send JSON command to engine.
sock = comm.send_and_receive_socket(cmd)
# -------------------------------------------
# Send the actual query.
comm.send_string(sock, query)
# -------------------------------------------
# Make sure that everything went well.
msg = comm.recv_string(sock)
sock.close()
if msg != "Success!":
comm.engine_exception_handler(msg)
# -----------------------------------------------------------------------------
[docs]def get_colnames(name, conn=None):
"""
Lists the colnames of a table held in the database.
Args:
name (str): The name of the table in the database.
conn (:class:`~getml.database.Connection`, optional): The database connection to be used.
If you don't explicitly pass a connection, the engine will use the default connection.
"""
# -------------------------------------------
conn = conn or Connection()
# -------------------------------------------
# Prepare command.
cmd = dict()
cmd["name_"] = name
cmd["type_"] = "Database.get_colnames"
cmd["conn_id_"] = conn.conn_id
# -------------------------------------------
# Send JSON command to engine.
sock = comm.send_and_receive_socket(cmd)
# -------------------------------------------
# Make sure that everything went well.
msg = comm.recv_string(sock)
if msg != "Success!":
sock.close()
comm.engine_exception_handler(msg)
# -------------------------------------------
# Parse result as list.
arr = json.loads(comm.recv_string(sock))
sock.close()
return arr
# -----------------------------------------------------------------------------
[docs]def list_connections():
"""
Returns a list handles to all connections that are currently active on the
engine.
"""
# -------------------------------------------
# Prepare command.
cmd = dict()
cmd["name_"] = ""
cmd["type_"] = "Database.list_connections"
# -------------------------------------------
# Send JSON command to engine.
sock = comm.send_and_receive_socket(cmd)
# -------------------------------------------
# Make sure that everything went well.
msg = comm.recv_string(sock)
if msg != "Success!":
sock.close()
comm.engine_exception_handler(msg)
# -------------------------------------------
# Parse result as list.
arr = json.loads(comm.recv_string(sock))
sock.close()
return [Connection(elem) for elem in arr]
# -----------------------------------------------------------------------------
[docs]def list_tables(conn=None):
"""
Lists all tables and views currently held in the database.
Args:
conn (:class:`~getml.database.Connection`, optional): The database connection to be used.
If you don't explicitly pass a connection, the engine will use the default connection.
"""
# -------------------------------------------
conn = conn or Connection()
# -------------------------------------------
# Prepare command.
cmd = dict()
cmd["name_"] = conn.conn_id
cmd["type_"] = "Database.list_tables"
# -------------------------------------------
# Send JSON command to engine.
sock = comm.send_and_receive_socket(cmd)
# -------------------------------------------
# Make sure that everything went well.
msg = comm.recv_string(sock)
if msg != "Success!":
sock.close()
comm.engine_exception_handler(msg)
# -------------------------------------------
# Parse result as list.
arr = json.loads(comm.recv_string(sock))
sock.close()
return arr
# -----------------------------------------------------------------------------
[docs]def read_csv(
name,
fnames,
quotechar='"',
sep=',',
num_lines_read=0,
skip=0,
colnames=None,
conn=None):
"""
Reads a CSV file into the database.
Args:
name (str): Name of the table in which the data is to be inserted.
fnames (List[str]): The list of CSV file names to be read.
quotechar (str, optional): The character used to wrap strings. Default:`"`
sep (str, optional): The separator used for separating fields. Default:`,`
num_lines_read (int, optional): Number of lines read from each file.
Set to 0 to read in the entire file.
skip (int, optional): Number of lines to skip at the beginning of each
file (Default: 0).
colnames(List[str] or None, optional): The first line of a CSV file
usually contains the column names. When this is not the case, you need to
explicitly pass them.
conn (:class:`~getml.database.Connection`, optional): The database connection to be used.
If you don't explicitly pass a connection, the engine will use the default connection.
Example:
Let's assume you have two CSV files - *file1.csv* and
*file2.csv* . You can import their data into the database
using the following commands:
>>> stmt = data.database.sniff_csv(
... fnames=["file1.csv", "file2.csv"],
... name="MY_TABLE",
... sep=';'
... )
>>>
>>> getml.database.execute(stmt)
>>>
>>> stmt = data.database.read_csv(
... fnames=["file1.csv", "file2.csv"],
... name="MY_TABLE",
... sep=';'
... )
"""
# -------------------------------------------
conn = conn or Connection()
# -------------------------------------------
# Transform paths
fnames_ = [os.path.abspath(_) for _ in fnames]
# -------------------------------------------
# Prepare command.
cmd = dict()
cmd["name_"] = name
cmd["type_"] = "Database.read_csv"
cmd["fnames_"] = fnames_
cmd["quotechar_"] = quotechar
cmd["sep_"] = sep
cmd["skip_"] = skip
cmd["num_lines_read_"] = num_lines_read
cmd["conn_id_"] = conn.conn_id
if colnames is not None:
cmd["colnames_"] = colnames
# -------------------------------------------
# Send JSON command to engine.
comm.send(cmd)
# -----------------------------------------------------------------------------
[docs]def read_s3(
name,
bucket,
keys,
region,
sep=',',
num_lines_read=0,
skip=0,
colnames=None,
conn=None):
"""
Reads a list of CSV files located in an S3 bucket.
Args:
name (str): Name of the table in which the data is to be inserted.
bucket (str):
The bucket from which to read the files.
keys (List[str]): The list of keys (files in the bucket) to be read.
region (str):
The region in which the bucket is located.
sep (str, optional): The separator used for separating fields. Default:`,`
num_lines_read (int, optional): Number of lines read from each file.
Set to 0 to read in the entire file.
skip (int, optional): Number of lines to skip at the beginning of each
file (Default: 0).
colnames(List[str] or None, optional): The first line of a CSV file
usually contains the column names. When this is not the case, you need to
explicitly pass them.
conn (:class:`~getml.database.Connection`, optional): The database connection to be used.
If you don't explicitly pass a connection, the engine will use the default connection.
Example:
Let's assume you have two CSV files - *file1.csv* and
*file2.csv* - in the bucket. You can
import their data into the getML engine using the following
commands:
>>> getml.engine.set_s3_access_key_id("YOUR-ACCESS-KEY-ID")
>>>
>>> getml.engine.set_s3_secret_access_key("YOUR-SECRET-ACCESS-KEY")
>>>
>>> stmt = data.database.sniff_s3(
... bucket="your-bucket-name",
... keys=["file1.csv", "file2.csv"],
... region="us-east-2",
... name="MY_TABLE",
... sep=';'
... )
>>>
>>> getml.database.execute(stmt)
>>>
>>> stmt = data.database.read_s3(
... bucket="your-bucket-name",
... keys=["file1.csv", "file2.csv"],
... region="us-east-2",
... name="MY_TABLE",
... sep=';'
... )
You can also set the access credential as environment variables
before you launch the getML engine.
"""
# -------------------------------------------
conn = conn or Connection()
# -------------------------------------------
# Prepare command.
cmd = dict()
cmd["name_"] = name
cmd["type_"] = "Database.read_s3"
cmd["bucket_"] = bucket
cmd["keys_"] = keys
cmd["num_lines_read_"] = num_lines_read
cmd["region_"] = region
cmd["sep_"] = sep
cmd["skip_"] = skip
cmd["conn_id_"] = conn.conn_id
if colnames is not None:
cmd["colnames_"] = colnames
# -------------------------------------------
# Send JSON command to engine.
comm.send(cmd)
# -----------------------------------------------------------------------------
[docs]def sniff_csv(
name,
fnames,
num_lines_sniffed=1000,
quotechar='"',
sep=',',
skip=0,
colnames=None,
conn=None):
"""
Sniffs a list of CSV files.
Args:
name (str): Name of the table in which the data is to be inserted.
fnames (List[str]): The list of CSV file names to be read.
num_lines_sniffed (int, optional):
Number of lines analyzed by the sniffer.
quotechar (str, optional): The character used to wrap strings. Default:`"`
sep (str, optional): The separator used for separating fields. Default:`,`
skip (int, optional): Number of lines to skip at the beginning of each
file (Default: 0).
colnames(List[str] or None, optional): The first line of a CSV file
usually contains the column names. When this is not the case, you need to
explicitly pass them.
conn (:class:`~getml.database.Connection`, optional): The database connection to be used.
If you don't explicitly pass a connection, the engine will use the default connection.
Returns:
str: Appropriate `CREATE TABLE` statement.
"""
# -------------------------------------------
conn = conn or Connection()
# -------------------------------------------
# Transform paths
fnames_ = [os.path.abspath(_) for _ in fnames]
# -------------------------------------------
# Prepare command.
cmd = dict()
cmd["name_"] = name
cmd["type_"] = "Database.sniff_csv"
cmd["fnames_"] = fnames_
cmd["num_lines_sniffed_"] = num_lines_sniffed
cmd["quotechar_"] = quotechar
cmd["sep_"] = sep
cmd["skip_"] = skip
cmd["conn_id_"] = conn.conn_id
if colnames is not None:
cmd["colnames_"] = colnames
# -------------------------------------------
# Send JSON command to engine.
sock = comm.send_and_receive_socket(cmd)
# -------------------------------------------
# Make sure that everything went well.
msg = comm.recv_string(sock)
if msg != "Success!":
sock.close()
comm.engine_exception_handler(msg)
# -------------------------------------------
stmt = comm.recv_string(sock)
sock.close()
return stmt
# -----------------------------------------------------------------------------
[docs]def sniff_s3(
name,
bucket,
keys,
region,
num_lines_sniffed=1000,
sep=',',
skip=0,
colnames=None,
conn=None):
"""
Sniffs a list of CSV files located in an S3 bucket.
Args:
name (str): Name of the table in which the data is to be inserted.
bucket (str):
The bucket from which to read the files.
keys (List[str]): The list of keys (files in the bucket) to be read.
region (str):
The region in which the bucket is located.
num_lines_sniffed (int, optional):
Number of lines analysed by the sniffer.
sep (str, optional):
The character used for separating fields.
skip (int, optional):
Number of lines to skip at the beginning of each file.
colnames(List[str] or None, optional): The first line of a CSV file
usually contains the column names. When this is not the case, you need to
explicitly pass them.
conn (:class:`~getml.database.Connection`, optional): The database connection to be used.
If you don't explicitly pass a connection, the engine will use the default connection.
Returns:
str: Appropriate `CREATE TABLE` statement.
Example:
Let's assume you have two CSV files - *file1.csv* and
*file2.csv* - in the bucket. You can
import their data into the getML engine using the following
commands:
>>> getml.engine.set_s3_access_key_id("YOUR-ACCESS-KEY-ID")
>>>
>>> getml.engine.set_s3_secret_access_key("YOUR-SECRET-ACCESS-KEY")
>>>
>>> stmt = data.database.sniff_s3(
... bucket="your-bucket-name",
... keys=["file1.csv", "file2.csv"],
... region="us-east-2",
... name="MY_TABLE",
... sep=';'
... )
You can also set the access credential as environment variables
before you launch the getML engine.
"""
# -------------------------------------------
conn = conn or Connection()
# -------------------------------------------
# Prepare command.
cmd = dict()
cmd["name_"] = name
cmd["type_"] = "Database.sniff_s3"
cmd["bucket_"] = bucket
cmd["keys_"] = keys
cmd["num_lines_sniffed_"] = num_lines_sniffed
cmd["region_"] = region
cmd["sep_"] = sep
cmd["skip_"] = skip
cmd["conn_id_"] = conn.conn_id
if colnames is not None:
cmd["colnames_"] = colnames
# -------------------------------------------
# Send JSON command to engine.
sock = comm.send_and_receive_socket(cmd)
# -------------------------------------------
# Make sure that everything went well.
msg = comm.recv_string(sock)
if msg != "Success!":
sock.close()
comm.engine_exception_handler(msg)
# -------------------------------------------
stmt = comm.recv_string(sock)
sock.close()
return stmt
# -----------------------------------------------------------------------------