I'm trying to create a class method that can run some code after its execution.
In pytest we have this functionality with fixtures:
#pytest.fixture
def db_connection(conn_str: str):
connection = psycopg2.connect(conn_str)
yield connection
connection.close() # this code will be executed after the test is done
Using this fixture in some test guarantees that connection will be closed soon after the test finishes. This behavior is described here, in the Teardown section.
When I try to do it in my own class methods, I didn't get the same result.
class Database:
def __call__(self, conn_str: str):
conn = psycopg2.connect(conn_str)
yield conn
print("Got here")
conn.close()
database = Database()
conn = next(database())
cur = conn.cursor()
cur.execute("select * from users")
result = cur.fetchall()
conn.commit()
result
The output is the data in users table, but I never see the "Got here" string, so I'm guessing this code after the yield keyword never runs.
Is there a way to achieve this?
What you are trying to do is implement a context manager; the similarly to a Pytext fixture is incidental.
You can do this with contextmanager.contextlib
from contextlib import contextmanager
#contextmanager
def db_connection(conn_str):
connection = psycopg2.connect(conn_str)
yield connection
connection.close()
with db_connection(...) as db:
...
or define Database.__enter__ and Database.__exit__ explicitly:
class Database:
def __init__(self, conn_str: str):
self.conn_str = conn_str
def __enter__(self):
self.conn = psycopg2.connect(self.conn_str)
return self.conn
def __exit__(self, *args):
print("Got here")
self.conn.close()
with Database(...) as db:
...
(You can use the connection returned by psycopg2.connect as a context manager itself.)
You need another next call to have it run the code after the yield:
database = Database()
gen = database() # Saved the generator to a variable
conn = next(gen)
cur = conn.cursor()
cur.execute("select * from users")
result = cur.fetchall()
conn.commit()
next(gen) # Triggers the latter part of the function
Also note, when you exhaust a generator, it raises a StopIteration exception as you'll see. You'll need to catch that as well.
Related
I'm trying to create the api on my linux PC. At this moment I have support for some basic requests which were done just for testing. My api works in cooperation with uswgi+nginx+flask. And now I'm trying to add connection to the database. For this purpose I had installed MySQL and created database. But I don't understand how to connect from the api to database. For example here is code of the script which can connect to the DB but it works separately of the api:
try:
connection = mysql.connector.connect(host='localhost',
database='tired_db',
user='test',
password='pw')
if connection.is_connected():
mycursor = connection.cursor()
mycursor.execute("SHOW TABLES")
for x in mycursor:
print(x)
return connection
except Error as e:
print("Error while connecting to MySQL", e)
finally:
if connection.is_connected():
mycursor.close()
connection.close()
print("MySQL connection is closed")
and it works correctly. I thought that maybe I can call this connection like some metaclass:
import mysql.connector
from mysql.connector import Error
class DbProvider(type):
#property
def my_data(cls):
try:
connection = mysql.connector.connect(host='localhost',
database='tired_db',
user='test',
password='pw')
if connection.is_connected():
mycursor = connection.cursor()
mycursor.execute("SHOW TABLES")
for x in mycursor:
print(x)
return connection
except Error as e:
print("Error while connecting to MySQL", e)
finally:
if connection.is_connected():
mycursor.close()
connection.close()
print("MySQL connection is closed")
class MyClass(metaclass=DbProvider):
pass
if __name__ == "__main__":
MyClass.my_data
but I think that such stuff can be done with more efficient way. For example here is some request in the api:
#app.route("/api/login", methods = ['POST'])
def logIn():
return "all is ok"
and the idea is that for example I have to connect during this request to the DB and check whether a user exists or not and if all is ok generate+save some token to the database. I don't understand whether it is important to keep connection alive during all api uptime or only during requests. And also is it important to close connection after an every request or we have to keep alive it forever. And also how to call connection from separate class, or I have to have all stuff in one file together with api calls.
You can write a connection manager class that connects to the database, performs operations, and closes the connection.
import mysql.connector
from mysql.connector import Error
class ConnectionManager:
def __init__(self, host, database, user, password):
self.host = host
self.database = database
self.user = user
self.password = password
def __enter__(self):
try:
self.connection = mysql.connector.connect(
host=self.host,
database=self.database,
user=self.user,
password=self.password
)
if self.connection.is_connected():
self.cursor = self.connection.cursor()
return self.cursor
except Error as e:
print("Error while connecting to MySQL", e)
def __exit__(self, type, value, traceback):
if self.connection.is_connected():
self.cursor.close()
self.connection.close()
print("MySQL connection is closed")
#app.route("/api/login", methods = ['POST'])
def logIn():
with ConnectionManager('localhost', 'tired_db', 'test', 'pw') as cursor:
cursor.execute("SELECT * FROM users WHERE username = %s", ('test_user',))
result = cursor.fetchone()
if result:
# generate and save token
return "all is ok"
else:
return "user not found"
I've been refactoring my psycopg2 code using functions, previously I had it all on a try-except-finally block, however I'm not quite sure how to implement a context-manager to handle the connection and cursor. My SQL queries work and look like this:
def random_query(schema, table, username, number_of_files):
random_query = sql.SQL("SELECT * FROM {schema}.{table} WHERE username = {username} ORDER BY RANDOM() LIMIT {limit}").format(
schema=sql.Identifier(schema),
table=sql.Identifier(table),
username=sql.Literal(username),
limit=sql.Literal(number_of_files)
)
cursor.execute(random_query)
return cursor.fetchone()
def insert_query(schema, table, values):
insert_query = sql.SQL("INSERT INTO {schema}.{table}(shortcode, username, filename, extension) VALUES ({shortcode}, {username}, {filename}, {extension})").format(
schema=sql.Identifier(schema),
table=sql.Identifier(table),
shortcode=sql.Literal(values[0]),
username=sql.Literal(values[1]),
filename=sql.Literal(values[2]),
extension=sql.Literal(values[3])
)
cursor.execute(insert_query)
conn.commit()
First version:
#contextmanager
def get_connection():
connection = psycopg2.connect(**DB_CONNECTION)
try:
yield connection
except Exception as err:
connection.rollback()
print('Error: ', err)
raise
finally:
if (connection):
connection.close()
print("Connection is closed.")
#contextmanager
def get_cursor(connection):
cursor = connection.cursor()
try:
yield cursor
finally:
cursor.close()
with get_connection() as conn, get_cursor(conn) as cursor:
random_record = random_query('test_schema', 'test_table', 'username', 1)
insert_query('test_schema', 'test_table2', random_record)
Second version:
#contextmanager
def sql_connection():
connection = psycopg2.connect(**DB_CONNECTION)
cursor = connection.cursor()
try:
yield connection,cursor
except Exception as err:
connection.rollback()
print('Error : ', err)
raise
finally:
if (connection):
cursor.close()
connection.close()
print("Connection is closed")
with sql_connection() as (conn, cursor):
random_record = random_query('test_schema', 'test_table', 'username', 1)
insert_query('test_schema', 'test_table2', random_record)
My questions are:
Is there any difference between the first and the second version? Which one is preferable?
As you can see in insert_query, there is a line that calls conn.commit() From the documentation, I understand that this is not necessary if we are using a context manager. Can I remove them?
Changed in version 2.5: if the connection is used in a with statement,
the method is automatically called if no exception is raised in the
with block.
Neither version is preferable, you are still over complicating things by duplicating behavior. Per the example here Connection:
import psycopg2
connection = psycopg2.connect(**DB_CONNECTION)
with connection:
with connection.cursor() as cur:
cur.execute(<sql>)
with connection:
with connection.cursor() as cur:
cur.execute(<other_sql>)
Committing, rollback on the connection and closing of cursor is done for you. All you have to do is connection.close() when you no longer want to use the connection.
I'm trying to write a load testing script using locust in python (it uses gevent & greenlet for multithreading internally as per my understanding); but my script is getting stuck when I try to put a db connection (postgres) back to connection pool inside a thread. I have defined connection pool variable as gloabl & then trying to create & put connections back inside threads; I have no experience in threading; not sure if these lines marked inside ** quotes are the reason locust gets stuck -
#events.test_start.add_listener # executes one time at the start of test run
def on_test_start(**kw):
**global t_pool** # connection pool variable defined as global
conn_st = config(fname = os.path.join('.', 'db'), instance = 'xxx')
try:
t_pool = pool.ThreadedConnectionPool(1, 100, **conn_st)
#cur = db.cursor()
except Exception as err:
#db = None
raise DatabaseError("DB Connection could not be established - %s" %(err))
#contextmanager
def get_con():
con = t_pool.getconn()
try:
yield con
finally:
**t_pool.putconn(con)**
def send_xxx():
ind = random.randint(0, (len(xxx_data['yyy'])-1))
body['toeknx'] = xxx_data['yyy'][ind]
res = requests.post(url, headers=headers, json=body)
res.raise_for_status()
with get_con() as con:
cur = con.cursor()
while True:
cur.execute("test query")
token = cur.fetchone()
if token is None:
continue
else:
cur.execute("another test query")
out = cur.fetchone()
if zzz:
continue
else:
cur.execute("final test query")
out1 = cur.fetchone()
time_diff = out1[1] - out1[0]
cur.close()
You need to use psycogreen to make psycopg2 gevent-friendly.
Something like:
import gevent
import gevent.monkey
gevent.monkey.patch_all()
import psycogreen.gevent
psycogreen.gevent.patch_psycopg()
Full example here:
https://github.com/SvenskaSpel/locust-plugins/blob/master/locust_plugins/listeners.py
I'm trying to set up a MySQL connection pool and have my worker processes access the already established pool instead of setting up a new connection each time.
I'm confused if I should pass the database cursor to each process, or if there's some other way to do this? Shouldn't MySql.connector do the pooling automatically? When I check my log files, many, many connections are opened and closed ... one for each process.
My code looks something like this:
PATH = "/tmp"
class DB(object):
def __init__(self):
connected = False
while not connected:
try:
cnxpool = mysql.connector.pooling.MySQLConnectionPool(pool_name = "pool1",
**config.dbconfig)
self.__cnx = cnxpool.get_connection()
except mysql.connector.errors.PoolError:
print("Sleeping.. (Pool Error)")
sleep(5)
except mysql.connector.errors.DatabaseError:
print("Sleeping.. (Database Error)")
sleep(5)
self.__cur = self.__cnx.cursor(cursor_class=MySQLCursorDict)
def execute(self, query):
return self.__cur.execute(query)
def isValidFile(self, name):
return True
def readfile(self, fname):
d = DB()
d.execute("""INSERT INTO users (first_name) VALUES ('michael')""")
def main():
queue = multiprocessing.Queue()
pool = multiprocessing.Pool(None, init, [queue])
for dirpath, dirnames, filenames in os.walk(PATH):
full_path_fnames = map(lambda fn: os.path.join(dirpath, fn),
filenames)
full_path_fnames = filter(is_valid_file, full_path_fnames)
pool.map(readFile, full_path_fnames)
if __name__ == '__main__':
sys.exit(main())
First, you're creating a different connection pool for each instance of your DB class. The pools having the same name doesn't make them the same pool
From the documentation:
It is not an error for multiple pools to have the same name. An application that must distinguish pools by their pool_name property should create each pool with a distinct name.
Besides that, sharing a database connection (or connection pool) between different processes would be a bad idea (and i highly doubt it would even work correctly), so each process using it's own connections is actually what you should aim for.
You could just initialize the pool in your init initializer as a global variable and use that instead.
Very simple example:
from multiprocessing import Pool
from mysql.connector.pooling import MySQLConnectionPool
from mysql.connector import connect
import os
pool = None
def init():
global pool
print("PID %d: initializing pool..." % os.getpid())
pool = MySQLConnectionPool(...)
def do_work(q):
con = pool.get_connection()
print("PID %d: using connection %s" % (os.getpid(), con))
c = con.cursor()
c.execute(q)
res = c.fetchall()
con.close()
return res
def main():
p = Pool(initializer=init)
for res in p.map(do_work, ['select * from test']*8):
print(res)
p.close()
p.join()
if __name__ == '__main__':
main()
Or just use a simple connection instead of a connection pool, as only one connection will be active in each process at a time anyway.
The number of concurrently used connections is implicitly limited by the size of the multiprocessing.Pool.
#!/usr/bin/python
# -*- coding: utf-8 -*-
import time
import mysql.connector.pooling
dbconfig = {
"host":"127.0.0.1",
"port":"3306",
"user":"root",
"password":"123456",
"database":"test",
}
class MySQLPool(object):
"""
create a pool when connect mysql, which will decrease the time spent in
request connection, create connection and close connection.
"""
def __init__(self, host="172.0.0.1", port="3306", user="root",
password="123456", database="test", pool_name="mypool",
pool_size=3):
res = {}
self._host = host
self._port = port
self._user = user
self._password = password
self._database = database
res["host"] = self._host
res["port"] = self._port
res["user"] = self._user
res["password"] = self._password
res["database"] = self._database
self.dbconfig = res
self.pool = self.create_pool(pool_name=pool_name, pool_size=pool_size)
def create_pool(self, pool_name="mypool", pool_size=3):
"""
Create a connection pool, after created, the request of connecting
MySQL could get a connection from this pool instead of request to
create a connection.
:param pool_name: the name of pool, default is "mypool"
:param pool_size: the size of pool, default is 3
:return: connection pool
"""
pool = mysql.connector.pooling.MySQLConnectionPool(
pool_name=pool_name,
pool_size=pool_size,
pool_reset_session=True,
**self.dbconfig)
return pool
def close(self, conn, cursor):
"""
A method used to close connection of mysql.
:param conn:
:param cursor:
:return:
"""
cursor.close()
conn.close()
def execute(self, sql, args=None, commit=False):
"""
Execute a sql, it could be with args and with out args. The usage is
similar with execute() function in module pymysql.
:param sql: sql clause
:param args: args need by sql clause
:param commit: whether to commit
:return: if commit, return None, else, return result
"""
# get connection form connection pool instead of create one.
conn = self.pool.get_connection()
cursor = conn.cursor()
if args:
cursor.execute(sql, args)
else:
cursor.execute(sql)
if commit is True:
conn.commit()
self.close(conn, cursor)
return None
else:
res = cursor.fetchall()
self.close(conn, cursor)
return res
def executemany(self, sql, args, commit=False):
"""
Execute with many args. Similar with executemany() function in pymysql.
args should be a sequence.
:param sql: sql clause
:param args: args
:param commit: commit or not.
:return: if commit, return None, else, return result
"""
# get connection form connection pool instead of create one.
conn = self.pool.get_connection()
cursor = conn.cursor()
cursor.executemany(sql, args)
if commit is True:
conn.commit()
self.close(conn, cursor)
return None
else:
res = cursor.fetchall()
self.close(conn, cursor)
return res
if __name__ == "__main__":
mysql_pool = MySQLPool(**dbconfig)
sql = "select * from store WHERE create_time < '2017-06-02'"
p = Pool()
for i in range(5):
p.apply_async(mysql_pool.execute, args=(sql,))
Code above creates a connection pool at the beginning, and get connections from it in execute(), once the connection pool has been created, the work is to remain it, since the pool is created only once, it will save the time to request for a connection every time you would like to connect to MySQL.
Hope it helps!
You created multiple DB object instance. In mysql.connector.pooling.py, pool_name is only a attribute to let you make out which pool it is. There is no mapping in the mysql pool.
So, you create multiple DB instance in def readfile(), then you will have several connection pool.
A Singleton is useful in this case.
(I spent several hours to find it out. In Tornado framework, each http get create a new handler, which leads to making a new connection.)
There may be synchronization issues if you're going to reuse MySQLConnection instances maintained by a pool, but just sharing a MySQLConnectionPool instance between worker processes and using connections retrieved by calling the method get_connection() would be okay, because a dedicated socket would be created for each MySQLConnection instance.
import multiprocessing
from mysql.connector import pooling
def f(cnxpool: pooling.MySQLConnectionPool) -> None:
# Dedicate connection instance for each worker process.
cnx = cnxpool.get_connection()
...
if __name__ == '__main__':
cnxpool = pooling.MySQLConnectionPool(
pool_name='pool',
pool_size=2,
)
p0 = multiprocessing.Process(target=f, args=(cnxpool,))
p1 = multiprocessing.Process(target=f, args=(cnxpool,))
p0.start()
p1.start()
I'm not sure if this is possible, but I'm looking for a way to reconnect to mysql database when the connection is lost. All the connections are held in a gevent queue but that shouldn't matter I think. I'm sure if I put some time in, I can come up with a way to reconnect to the database. However I was glancing pymysql code and I saw that there is a 'ping' method in Connection class, which I'm not sure exactly how to use.
The method looks like it will reconnect first time but after that it switched the reconnect flag to False again? Can I use this method, or is there a different way to establish connection if it is lost? Even if it is not pymysql how do people tackle, database servers going down and having to re-establish connection to mysql server?
def ping(self, reconnect=True):
''' Check if the server is alive '''
if self.socket is None:
if reconnect:
self._connect()
reconnect = False
else:
raise Error("Already closed")
try:
self._execute_command(COM_PING, "")
return self._read_ok_packet()
except Exception:
if reconnect:
self._connect()
return self.ping(False)
else:
raise
Well, I've got the same problem in my application and I found a method on the PyMySQL documentation that pings to the server and check if the connection was closed or not, if it was closed, then it reconnects again.
from pymysql import connect
from pymysql.cursors import DictCursor
# create the connection
connection = connect(host='host', port='port', user='user',
password='password', db='db',
cursorclass=DictCursor)
# get the cursor
cursor = connection.cursor()
# if the connection was lost, then it reconnects
connection.ping(reconnect=True)
# execute the query
cursor.execute(query)
I hope it helps.
Finally got a working solution, might help someone.
from gevent import monkey
monkey.patch_socket()
import logging
import gevent
from gevent.queue import Queue
import pymysql as db
logging.basicConfig(level=logging.DEBUG)
LOGGER = logging.getLogger("connection_pool")
class ConnectionPool:
def __init__(self, db_config, time_to_sleep=30, test_run=False):
self.username = db_config.get('user')
self.password = db_config.get('password')
self.host = db_config.get('host')
self.port = int(db_config.get('port'))
self.max_pool_size = 20
self.test_run = test_run
self.pool = None
self.time_to_sleep = time_to_sleep
self._initialize_pool()
def get_initialized_connection_pool(self):
return self.pool
def _initialize_pool(self):
self.pool = Queue(maxsize=self.max_pool_size)
current_pool_size = self.pool.qsize()
if current_pool_size < self.max_pool_size: # this is a redundant check, can be removed
for _ in xrange(0, self.max_pool_size - current_pool_size):
try:
conn = db.connect(host=self.host,
user=self.username,
passwd=self.password,
port=self.port)
self.pool.put_nowait(conn)
except db.OperationalError, e:
LOGGER.error("Cannot initialize connection pool - retrying in {} seconds".format(self.time_to_sleep))
LOGGER.exception(e)
break
self._check_for_connection_loss()
def _re_initialize_pool(self):
gevent.sleep(self.time_to_sleep)
self._initialize_pool()
def _check_for_connection_loss(self):
while True:
conn = None
if self.pool.qsize() > 0:
conn = self.pool.get()
if not self._ping(conn):
if self.test_run:
self.port = 3306
self._re_initialize_pool()
else:
self.pool.put_nowait(conn)
if self.test_run:
break
gevent.sleep(self.time_to_sleep)
def _ping(self, conn):
try:
if conn is None:
conn = db.connect(host=self.host,
user=self.username,
passwd=self.password,
port=self.port)
cursor = conn.cursor()
cursor.execute('select 1;')
LOGGER.debug(cursor.fetchall())
return True
except db.OperationalError, e:
LOGGER.warn('Cannot connect to mysql - retrying in {} seconds'.format(self.time_to_sleep))
LOGGER.exception(e)
return False
# test (pytest compatible) -------------------------------------------------------------------------------------------
import logging
from src.py.ConnectionPool import ConnectionPool
logging.basicConfig(level=logging.DEBUG)
LOGGER = logging.getLogger("test_connection_pool")
def test_get_initialized_connection_pool():
config = {
'user': 'root',
'password': '',
'host': '127.0.0.1',
'port': 3305
}
conn_pool = ConnectionPool(config, time_to_sleep=5, test_run=True)
pool = conn_pool.get_initialized_connection_pool()
# when in test run the port will be switched back to 3306
# so the queue size should be 20 - will be nice to work
# around this rather than test_run hack
assert pool.qsize() == 20
The easiest way is to check the connection right before sending a query.
You can do this by creating a small class that contains two methods: connect and query:
import pymysql
import pymysql.cursors
class DB:
def connect(self):
self.conn = pymysql.connect(
host=hostname,
user=username,
password=password,
db=dbname,
charset='utf8mb4',
cursorclass=pymysql.cursors.DictCursor,
port=3306)
def query(self, sql):
try:
cursor = self.conn.cursor()
cursor.execute(sql)
except pymysql.OperationalError:
self.connect()
cursor = self.conn.cursor()
cursor.execute(sql)
return cursor
db = DB()
Now, whenever you send a query using db.query("example SQL") the request is automatically prepared to encounter a connection error and reconnects using self.connect() if it needs to.
Remember: This is a simplified example. Normally, you would want to let PyMySQL help you escape special characters in your queries. To do that, you would have to add a 2nd parameter in the query method and go from there.
the logic is quite simple, if connection close then try to reconnect for several times in this case I use max tries for 15 times to reconnect or ping.
import pymysql, pymysql.cursors
conn = pymysql.connect(
host=hostname,
user=username,
password=password,
db=dbname,
charset='utf8mb4',
cursorclass=pymysql.cursors.DictCursor,
)
cursor = conn.cursor()
# you can do transactions to database and when you need conn later, just make sure the server is still connected
if conn.open is False:
max_try = 15
try = 0
while conn.open is False:
if try < max_try:
conn.ping() # autoreconnect is true by default
try +=1
# check the conn again to make sure it connected
if conn.open:
# statements when conn is successfully reconnect to the server
else:
# it must be something wrong : server, network etc
Old but I encountered a similar problem for accessing hosted db within programs. The solution I ended up using was to create a decorator to automatically reconnect when making a query.
given a connection function:
def connect(self):
self.conn = mysql.connector.connect(host=self.host, user=self.user,
database=self.database, password=self.password)
self.cursor = self.conn.cursor()
print("Established connectionn...")
I created
def _reconnect(func):
#wraps(func)
def rec(self,*args,**kwargs):
try:
result = func(self,*args,**kwargs)
return result
except (mysql.connector.Error, mysql.connector.Warning) as e:
self.connect()
result = func(self,*args,**kwargs)
return result
return rec
Such that any function using the connection can now be decorated as so
#_reconnect
def check_user_exists(self,user_id):
self.cursor.execute("SELECT COUNT(*) FROM _ where user_id={};".format(user_id))
if self.cursor.fetchall()[0][0]==0:
return False
else:
return True
This decorator will re-establish a connection and rerun any function involving a query to the db.
You can use a property to keep the connection alive every time you do querying:
import pymysql
import pymysql.cursors
import pandas as pd
class DB:
def __init__(self, hostname='1.1.1.1', username='root', password='password',
database=None, port=3306, charset="utf8mb4"):
self.hostname = hostname
self.database = database
self.username = username
self.password = password
self.port = port
self.charset = charset
self.connect()
#property
def conn(self):
if not self.connection.open:
print('Going to reconnect')
self.connection.ping(reconnect=True)
return self.connection
def connect(self):
self.connection = pymysql.connect(
host=self.hostname,
user=self.username,
password=self.password,
db=self.database,
charset=self.charset,
cursorclass=pymysql.cursors.DictCursor,
port=self.port)
def query(self, sql):
return pd.read_sql_query(sql, con=self.conn)
db = DB(hostname='1.1.1.1', username='root', password='password', database=None, port=3306, charset="utf8mb4")