data-transport/transport/sql.py

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"""
This file is intended to perform read/writes against an SQL database such as PostgreSQL, Redshift, Mysql, MsSQL ...
LICENSE (MIT)
Copyright 2016-2020, The Phi Technology LLC
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, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following 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 MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS 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.
@TODO:
- Migrate SQLite to SQL hierarchy
- Include Write in Chunks from pandas
"""
import psycopg2 as pg
import mysql.connector as my
import sys
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import sqlalchemy
if sys.version_info[0] > 2 :
from transport.common import Reader, Writer #, factory
else:
from common import Reader,Writer
import json
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from google.oauth2 import service_account
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from google.cloud import bigquery as bq
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from multiprocessing import Lock, RLock
import pandas as pd
import numpy as np
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import nzpy as nz #--- netezza drivers
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import copy
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import os
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class SQLRW :
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lock = RLock()
MAX_CHUNK = 2000000
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DRIVERS = {"postgresql":pg,"redshift":pg,"mysql":my,"mariadb":my,"netezza":nz}
REFERENCE = {
"netezza":{"port":5480,"handler":nz,"dtype":"VARCHAR(512)"},
"postgresql":{"port":5432,"handler":pg,"dtype":"VARCHAR"},
"redshift":{"port":5432,"handler":pg,"dtype":"VARCHAR"},
"mysql":{"port":3360,"handler":my,"dtype":"VARCHAR(256)"},
"mariadb":{"port":3360,"handler":my,"dtype":"VARCHAR(256)"},
}
def __init__(self,**_args):
_info = {}
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_info['dbname'] = _args['db'] if 'db' in _args else _args['database']
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self.table = _args['table'] if 'table' in _args else None
self.fields = _args['fields'] if 'fields' in _args else []
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self.schema = _args['schema'] if 'schema' in _args else ''
self._chunks = 1 if 'chunks' not in _args else int(_args['chunks'])
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self._provider = _args['provider'] if 'provider' in _args else None
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# _info['host'] = 'localhost' if 'host' not in _args else _args['host']
# _info['port'] = SQLWriter.REFERENCE[_provider]['port'] if 'port' not in _args else _args['port']
_info['host'] = _args['host']
_info['port'] = _args['port']
# if 'host' in _args :
# _info['host'] = 'localhost' if 'host' not in _args else _args['host']
# # _info['port'] = SQLWriter.PROVIDERS[_args['provider']] if 'port' not in _args else _args['port']
# _info['port'] = SQLWriter.REFERENCE[_provider]['port'] if 'port' not in _args else _args['port']
self.lock = False if 'lock' not in _args else _args['lock']
if 'username' in _args or 'user' in _args:
key = 'username' if 'username' in _args else 'user'
_info['user'] = _args[key]
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_info['password'] = _args['password'] if 'password' in _args else ''
if 'auth_file' in _args :
_auth = json.loads( open(_args['auth_file']).read() )
key = 'username' if 'username' in _auth else 'user'
_info['user'] = _auth[key]
_info['password'] = _auth['password'] if 'password' in _auth else ''
_info['host'] = _auth['host'] if 'host' in _auth else _info['host']
_info['port'] = _auth['port'] if 'port' in _auth else _info['port']
if 'database' in _auth:
_info['dbname'] = _auth['database']
self.table = _auth['table'] if 'table' in _auth else self.table
#
# We need to load the drivers here to see what we are dealing with ...
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# _handler = SQLWriter.REFERENCE[_provider]['handler']
_handler = _args['driver'] #-- handler to the driver
self._dtype = _args['default']['type'] if 'default' in _args and 'type' in _args['default'] else 'VARCHAR(256)'
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# self._provider = _args['provider']
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# self._dtype = SQLWriter.REFERENCE[_provider]['dtype'] if 'dtype' not in _args else _args['dtype']
# self._provider = _provider
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if _handler == nz :
_info['database'] = _info['dbname']
_info['securityLevel'] = 0
del _info['dbname']
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if _handler == my :
_info['database'] = _info['dbname']
del _info['dbname']
self.conn = _handler.connect(**_info)
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self._engine = _args['sqlalchemy'] if 'sqlalchemy' in _args else None
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def meta(self,**_args):
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schema = []
try:
if self._engine :
table = _args['table'] if 'table' in _args else self.table
if sqlalchemy.__version__.startswith('1.') :
_m = sqlalchemy.MetaData(bind=self._engine)
_m.reflect()
else:
_m = sqlalchemy.MetaData()
_m.reflect(bind=self._engine)
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schema = [{"name":_attr.name,"type":str(_attr.type)} for _attr in _m.tables[table].columns]
#
# Some house keeping work
_m = {'BIGINT':'INTEGER','TEXT':'STRING','DOUBLE_PRECISION':'FLOAT','NUMERIC':'FLOAT','DECIMAL':'FLOAT','REAL':'FLOAT'}
for _item in schema :
if _item['type'] in _m :
_item['type'] = _m[_item['type']]
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except Exception as e:
print (e)
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pass
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return schema
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def _tablename(self,name) :
return self.schema +'.'+name if self.schema not in [None, ''] and '.' not in name else name
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def has(self,**_args):
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return self.meta(**_args)
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# found = False
# try:
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# table = self._tablename(_args['table'])if 'table' in _args else self._tablename(self.table)
# sql = "SELECT * FROM :table LIMIT 1".replace(":table",table)
# if self._engine :
# _conn = self._engine.connect()
# else:
# _conn = self.conn
# found = pd.read_sql(sql,_conn).shape[0]
# found = True
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# except Exception as e:
# print (e)
# pass
# finally:
# if not self._engine :
# _conn.close()
# return found
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def isready(self):
_sql = "SELECT * FROM :table LIMIT 1".replace(":table",self.table)
try:
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_conn = self.conn if not hasattr(self,'_engine') else self._engine
return pd.read_sql(_sql,_conn).columns.tolist()
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except Exception as e:
pass
return False
def apply(self,_sql):
"""
This function applies a command and/or a query against the current relational data-store
:param _sql insert/select statement
@TODO: Store procedure calls
"""
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#
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_out = None
try:
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if _sql.lower().startswith('select') :
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_conn = self._engine if self._engine else self.conn
return pd.read_sql(_sql,_conn)
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else:
# Executing a command i.e no expected return values ...
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cursor = self.conn.cursor()
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cursor.execute(_sql)
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self.conn.commit()
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except Exception as e :
print (e)
finally:
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if not self._engine :
self.conn.commit()
# cursor.close()
def close(self):
try:
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self.conn.close()
except Exception as error :
print (error)
pass
class SQLReader(SQLRW,Reader) :
def __init__(self,**_args):
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super().__init__(**_args)
def read(self,**_args):
if 'sql' in _args :
_sql = (_args['sql'])
else:
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if 'table' in _args :
table = _args['table']
else:
table = self.table
# table = self.table if self.table is not None else _args['table']
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_sql = "SELECT :fields FROM "+self._tablename(table)
if 'filter' in _args :
_sql = _sql +" WHERE "+_args['filter']
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if 'fields' in _args :
_fields = _args['fields']
else:
_fields = '*' if not self.fields else ",".join(self.fields)
_sql = _sql.replace(":fields",_fields)
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#
# At this point we have a query we can execute gracefully
if 'limit' in _args :
_sql = _sql + " LIMIT "+str(_args['limit'])
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#
# @TODO:
# It is here that we should inspect to see if there are any pre/post conditions
#
return self.apply(_sql)
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def close(self) :
try:
self.conn.close()
except Exception as error :
print (error)
pass
class SQLWriter(SQLRW,Writer):
def __init__(self,**_args) :
super().__init__(**_args)
#
# In the advent that data typing is difficult to determine we can inspect and perform a default case
# This slows down the process but improves reliability of the data
# NOTE: Proper data type should be set on the target system if their source is unclear.
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self._cast = False if 'cast' not in _args else _args['cast']
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def init(self,fields=None):
if not fields :
try:
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table = self._tablename(self.table)
self.fields = pd.read_sql_query("SELECT * FROM :table LIMIT 1".replace(":table",table),self.conn).columns.tolist()
except Exception as e:
pass
finally:
pass
else:
self.fields = fields;
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def make(self,**_args):
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table = self._tablename(self.table) if 'table' not in _args else self._tablename(_args['table'])
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if 'fields' in _args :
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fields = _args['fields']
# table = self._tablename(self.table)
sql = " ".join(["CREATE TABLE",table," (", ",".join([ name +' '+ self._dtype for name in fields]),")"])
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else:
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schema = _args['schema'] if 'schema' in _args else []
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_map = _args['map'] if 'map' in _args else {}
sql = [] # ["CREATE TABLE ",_args['table'],"("]
for _item in schema :
_type = _item['type']
if _type in _map :
_type = _map[_type]
sql = sql + [" " .join([_item['name'], ' ',_type])]
sql = ",".join(sql)
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# table = self._tablename(_args['table'])
sql = ["CREATE TABLE ",table,"( ",sql," )"]
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sql = " ".join(sql)
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cursor = self.conn.cursor()
try:
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cursor.execute(sql)
except Exception as e :
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print (e)
# print (sql)
pass
finally:
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# cursor.close()
self.conn.commit()
pass
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def write(self,info,**_args):
"""
:param info writes a list of data to a given set of fields
"""
# inspect = False if 'inspect' not in _args else _args['inspect']
# cast = False if 'cast' not in _args else _args['cast']
if not self.fields :
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if type(info) == list :
_fields = info[0].keys()
elif type(info) == dict :
_fields = info.keys()
elif type(info) == pd.DataFrame :
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_fields = info.columns.tolist()
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# _fields = info.keys() if type(info) == dict else info[0].keys()
_fields = list (_fields)
self.init(_fields)
try:
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table = _args['table'] if 'table' in _args else self.table
#
# In SQL, schema can stand for namespace or the structure of a table
# In case we have a list, we are likely dealing with table structure
#
if 'schema' in _args :
if type(_args['schema']) == str :
self.schema = _args['schema'] if 'schema' in _args else self.schema
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elif type(_args['schema']) == list and not self.has(table=table):
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self.make(table=table,schema=_args['schema'])
pass
# self.schema = _args['schema'] if 'schema' in _args else self.schema
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table = self._tablename(table)
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_sql = "INSERT INTO :table (:fields) VALUES (:values)".replace(":table",table) #.replace(":table",self.table).replace(":fields",_fields)
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if type(info) == list :
_info = pd.DataFrame(info)
elif type(info) == dict :
_info = pd.DataFrame([info])
else:
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_info = pd.DataFrame(info)
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if _info.shape[0] == 0 :
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return
if self.lock :
SQLRW.lock.acquire()
#
# we will adjust the chunks here in case we are not always sure of the
if self._chunks == 1 and _info.shape[0] > SQLRW.MAX_CHUNK :
self._chunks = 10
_indexes = np.array_split(np.arange(_info.shape[0]),self._chunks)
for i in _indexes :
#
# In case we have an invalid chunk ...
if _info.iloc[i].shape[0] == 0 :
continue
#
# We are enabling writing by chunks/batches because some persistent layers have quotas or limitations on volume of data
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if self._engine is not None:
# pd.to_sql(_info,self._engine)
if self.schema in ['',None] :
rows = _info.iloc[i].to_sql(table,self._engine,if_exists='append',index=False)
else:
#
# Writing with schema information ...
rows = _info.iloc[i].to_sql(self.table,self._engine,schema=self.schema,if_exists='append',index=False)
else:
_fields = ",".join(self.fields)
_sql = _sql.replace(":fields",_fields)
values = ", ".join("?"*len(self.fields)) if self._provider == 'netezza' else ",".join(["%s" for name in self.fields])
_sql = _sql.replace(":values",values)
cursor = self.conn.cursor()
cursor.executemany(_sql,_info.iloc[i].values.tolist())
cursor.close()
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# cursor.commit()
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# self.conn.commit()
except Exception as e:
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print(e)
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pass
finally:
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if self._engine is None :
self.conn.commit()
if self.lock :
SQLRW.lock.release()
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# cursor.close()
pass
def close(self):
try:
self.conn.close()
finally:
pass
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class BigQuery:
def __init__(self,**_args):
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path = _args['service_key'] if 'service_key' in _args else _args['private_key']
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self.credentials = service_account.Credentials.from_service_account_file(path)
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self.dataset = _args['dataset'] if 'dataset' in _args else None
self.path = path
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self.dtypes = _args['dtypes'] if 'dtypes' in _args else None
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self.table = _args['table'] if 'table' in _args else None
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self.client = bq.Client.from_service_account_json(self.path)
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def meta(self,**_args):
"""
This function returns meta data for a given table or query with dataset/table properly formatted
:param table name of the name WITHOUT including dataset
:param sql sql query to be pulled,
"""
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table = _args['table'] if 'table' in _args else self.table
try:
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if table :
_dataset = self.dataset if 'dataset' not in _args else _args['dataset']
sql = f"""SELECT column_name as name, data_type as type FROM {_dataset}.INFORMATION_SCHEMA.COLUMNS WHERE table_name = '{table}' """
return self.read(sql=sql).to_dict(orient='records')
# ref = self.client.dataset(self.dataset).table(table)
# _schema = self.client.get_table(ref).schema
# return [{"name":_item.name,"type":_item.field_type,"description":( "" if not hasattr(_item,"description") else _item.description )} for _item in _schema]
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else :
return []
except Exception as e:
return []
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def has(self,**_args):
found = False
try:
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_has = self.meta(**_args)
found = _has is not None and len(_has) > 0
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except Exception as e:
pass
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return found
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class BQReader(BigQuery,Reader) :
def __init__(self,**_args):
super().__init__(**_args)
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def apply(self,sql):
self.read(sql=sql)
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pass
def read(self,**_args):
SQL = None
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table = self.table if 'table' not in _args else _args['table']
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if 'sql' in _args :
SQL = _args['sql']
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elif table:
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table = "".join(["`",table,"`"]) if '.' in table else "".join(["`:dataset.",table,"`"])
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SQL = "SELECT * FROM :table ".replace(":table",table)
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if not SQL :
return None
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if SQL and 'limit' in _args:
SQL += " LIMIT "+str(_args['limit'])
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if (':dataset' in SQL or ':DATASET' in SQL) and self.dataset:
SQL = SQL.replace(':dataset',self.dataset).replace(':DATASET',self.dataset)
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_info = {'credentials':self.credentials,'dialect':'standard'}
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return pd.read_gbq(SQL,**_info) if SQL else None
# return self.client.query(SQL).to_dataframe() if SQL else None
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class BQWriter(BigQuery,Writer):
lock = Lock()
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def __init__(self,**_args):
super().__init__(**_args)
self.parallel = False if 'lock' not in _args else _args['lock']
self.table = _args['table'] if 'table' in _args else None
self.mode = {'if_exists':'append','chunksize':900000,'destination_table':self.table,'credentials':self.credentials}
self._chunks = 1 if 'chunks' not in _args else int(_args['chunks'])
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def write(self,_info,**_args) :
try:
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if self.parallel or 'lock' in _args :
BQWriter.lock.acquire()
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_args['table'] = self.table if 'table' not in _args else _args['table']
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self._write(_info,**_args)
finally:
if self.parallel:
BQWriter.lock.release()
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def _write(self,_info,**_args) :
_df = None
if type(_info) in [list,pd.DataFrame] :
if type(_info) == list :
_df = pd.DataFrame(_info)
elif type(_info) == pd.DataFrame :
_df = _info
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if '.' not in _args['table'] :
self.mode['destination_table'] = '.'.join([self.dataset,_args['table']])
else:
self.mode['destination_table'] = _args['table'].strip()
if 'schema' in _args :
self.mode['table_schema'] = _args['schema']
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#
# Let us insure that the types are somewhat compatible ...
# _map = {'INTEGER':np.int64,'DATETIME':'datetime64[ns]','TIMESTAMP':'datetime64[ns]','FLOAT':np.float64,'DOUBLE':np.float64,'STRING':str}
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# _mode = copy.deepcopy(self.mode)
_mode = self.mode
# _df.to_gbq(**self.mode) #if_exists='append',destination_table=partial,credentials=credentials,chunksize=90000)
#
# Let us adjust the chunking here
self._chunkks = 10 if _df.shape[0] > SQLRW.MAX_CHUNK and self._chunks == 1 else self._chunks
_indexes = np.array_split(np.arange(_df.shape[0]),self._chunks)
for i in _indexes :
_df.iloc[i].to_gbq(**self.mode)
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pass
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#
# Aliasing the big query classes allowing it to be backward compatible
#
BigQueryReader = BQReader
BigQueryWriter = BQWriter