I want to check if my table is loaded correctly or not. If it is not loaded correctly then the number of records will be zero. I am using SQLCheckOperator to do this task.
This is the code
from airflow.operators.sql import SQLCheckOperator
from datetime import date, timedelta
CURRENT_DATE = str(date.today() - timedelta(2))
TABLE_NAME = "foo"
search_monolith_post_sanity = SQLCheckOperator(
task_id="search_monolith_post_sanity",
sql=f"SELECT COUNT(*) FROM `{TABLE_NAME}` WHERE feed_date = DATE_SUB('{CURRENT_DATE}', INTERVAL 1 DAY)",
bigquery_conn_id='bigquery_default',
use_legacy_sql=False,
dag=dag
)
I got the below error:
Executing SQL check: SELECT COUNT(*) FROM `foo` WHERE feed_date = DATE_SUB('2021-01-31', INTERVAL 1 DAY)
[2021-02-02 07:16:43,664] {taskinstance.py:1153} ERROR - 'NoneType' object has no attribute 'upper'
Traceback (most recent call last)
File "/usr/local/lib/airflow/airflow/models/taskinstance.py", line 986, in _run_raw_tas
result = task_copy.execute(context=context
File "/usr/local/lib/airflow/airflow/operators/sql.py", line 95, in execut
records = self.get_db_hook().get_first(self.sql
File "/usr/local/lib/airflow/airflow/operators/sql.py", line 116, in get_db_hoo
return BaseHook.get_hook(conn_id=self.conn_id
File "/usr/local/lib/airflow/airflow/hooks/base_hook.py", line 94, in get_hoo
connection = cls.get_connection(conn_id
File "/usr/local/lib/airflow/airflow/hooks/base_hook.py", line 87, in get_connectio
conn = random.choice(list(cls.get_connections(conn_id))
File "/usr/local/lib/airflow/airflow/hooks/base_hook.py", line 83, in get_connection
return secrets.get_connections(conn_id
File "/usr/local/lib/airflow/airflow/secrets/__init__.py", line 55, in get_connection
conn_list = secrets_backend.get_connections(conn_id=conn_id
File "/usr/local/lib/airflow/airflow/secrets/base_secrets.py", line 64, in get_connection
conn_uri = self.get_conn_uri(conn_id=conn_id
File "/usr/local/lib/airflow/airflow/secrets/environment_variables.py", line 39, in get_conn_ur
environment_uri = os.environ.get(CONN_ENV_PREFIX + conn_id.upper()
AttributeError: 'NoneType' object has no attribute 'upper
I have tried using BigQueryCheckOperator and CheckOperator instead of SQLCheckOperator but ran into error. If I replace BigQueryCheckOperator with BigQueryOperator the code works fine and I get zero as output.
I am new to airflow. Any help is much appreciated. Thanks !!
If you look at the line before the error message in the stacktrace.
environment_uri = os.environ.get(CONN_ENV_PREFIX + conn_id.upper()
AttributeError: 'NoneType' object has no attribute 'upper'
In this case the NoneType object that is having upper() called on it is conn_id.
If you're using Airflow 1.10.15 the documentation for this operator has a rather important Note buried at the bottom
Note that this is an abstract class and get_db_hook needs to be defined. Whereas a get_db_hook is hook that gets a single record from an external source.
Also note that the definition of the function appears to expect a conn_id parameter.
Assumption: You are using Airflow >= 2.0.0
Use the following code, notice usage of BigQueryCheckOperator and that I used gcp_conn_id instead of bigquery_conn_id.
from airflow.providers.google.cloud.operators.bigquery import BigQueryCheckOperator
from datetime import date, timedelta
CURRENT_DATE = str(date.today() - timedelta(2))
TABLE_NAME = "foo"
search_monolith_post_sanity = BigQueryCheckOperator(
task_id="search_monolith_post_sanity",
sql=f"SELECT COUNT(*) FROM `{TABLE_NAME}` WHERE feed_date = DATE_SUB('{CURRENT_DATE}', INTERVAL 1 DAY)",
gcp_conn_id='bigquery_default',
use_legacy_sql=False,
dag=dag
)
i keep getting the error
Traceback (most recent call last):
File "C:\Users\max\AppData\Local\Programs\Python\Python37\lib\tkinter\__init__.py", line 1705, in __call__
return self.func(*args)
File "G:\computing project\add to db.py", line 114, in get_items
C.execute(sql ,vari)
sqlite3.OperationalError: table inventory has no column named car_make
when attempting to insert values into mydatabse taken from tkinter
i have tried changing the names of the columns in order to see if that would solve the issue bit nothing has changed, i am using db browser in order to edit my database
from tkinter import*
import sqlite3
conn = sqlite3.connect("G:\computing project\database of cars.db")
C = conn.cursor()
import tkinter.messagebox
def get_items(self,*args,**kwargs): #this function gets the items from the entry boxes
self.carmake= self.carmake_e.get()
self.carmodel= self.carmodel_e.get()
self.regi= self.regi_e.get()
self.colour= self.colour_e.get()
self.cost= self.cost_e.get()
self.tcost= self.tcost_e.get()
self.sellprice= self.sellprice_e.get()
self.assumedprofit= self.assumedprofit_e.get()
self.assumedprofit= float(self.sellprice)- float(self.tcost)
if self.carmake == '' or self.carmodel == '' == self.colour == '':
print ("WRONG")
tkinter.messagebox.showinfo("error","please enter values for car make, model and colour")
else:
print("solid m8 ")
sql = "INSERT INTO inventory(car_make,car_model,registration_plate,colour,cost,total_cost,selling_price,assumed_profit) VALUES (?,?,?,?,?,?,?)"
vari=(self.carmake,self.carmodel,self.regi,self.colour,self.cost,self.tcost,self.sellprice,self.assumedprofit)
C.execute(sql ,vari)
# C.execute(sql(self.name,self.carmake,self.carmodel,self.regi,self.colour,self.cost,self.tcost,self.sellprice,self.assumedprofit))
conn.commit()
tkinter.messagebox.showinfo("success","succesfully added to databse")
I am trying to write a Python model which is capable of doing some processing in a PostgreSQL database using the multi-threading module and peewee.
In single core mode the code works, however, when I try to run the code with multiple cores I am running into a SSL error.
I would like to post the structure of my model in the hope that somebody can advice how to set of my model in a proper way. Currently, I have chosen to use an object oriented approach in which I make one connection which is shared in a pool. To clarify what I have done, I will now show the source code I have so far
I have three files: main.py, models.py and parser.py. The contents is the following
models.py defines the peewee postgresql table and makes a connection to the postgres server
import peewee as pw
from playhouse.pool import PooledPostgresqlExtDatabase
KVK_KEY = "id_number"
NAME_KEY = "name"
N_VOWELS_KEY = "n_vowels"
# initialise the data base
database = PooledPostgresqlExtDatabase(
"testdb", user="postgres", host="localhost", port=5432, password="xxxx",
max_connections=8, stale_timeout=300 )
class BaseModel(pw.Model):
class Meta:
database = database
only_save_dirty = True
# this class describes the format of the sql data base
class Company(BaseModel):
id_number = pw.IntegerField(primary_key=True)
name = pw.CharField(null=True)
n_vowels = pw.IntegerField(default=-1)
processor = pw.IntegerField(default=-1)
def connect_database(database_name, reset_database=False):
""" connect the database """
database.connect()
if reset_database:
database.drop_tables([Company])
database.create_tables([Company])
parser.py contains the CompanyParser class which is used as the engine of the code to do all the processing. It generates some artificial data which is stored to the postgresql database and then the run method is used to do some processing with the data already stored in the database
import pandas as pd
import numpy as np
import random
import string
import peewee as pw
from models import (Company, database, KVK_KEY, NAME_KEY)
import multiprocessing as mp
MAX_SQL_CHUNK = 1000
np.random.seed(0)
def random_name(size=8, chars=string.ascii_lowercase):
""" Create a random character string of 'size' characters """
return "".join(random.choice(chars) for _ in range(size))
def vowel_count(characters):
"""
Count the number of vowels in the string 'characters' and return as an integer
"""
count = 0
for char in characters:
if char in list("aeiou"):
count += 1
return count
class CompanyParser(mp.Process):
def __init__(self, number_of_companies=100, i_proc=None,
number_of_procs=1,
first_id=None, last_id=None):
if i_proc is not None and number_of_procs > 1:
mp.Process.__init__(self)
self.i_proc = i_proc
self.number_of_procs = number_of_procs
self.n_companies = number_of_companies
self.data_df: pd.DataFrame = None
self.first_id = first_id
self.last_id = last_id
def generate_data(self):
""" Create a dataframe with fake company data and id's """
id_list = np.random.randint(1000000, 9999999, self.n_companies)
company_list = np.array([random_name() for _ in range(self.n_companies)])
self.data_df = pd.DataFrame(data=np.vstack([id_list, company_list]).T,
columns=[KVK_KEY, NAME_KEY])
self.data_df.sort_values([KVK_KEY], inplace=True)
def store_to_database(self):
"""
Store the company data to a sql database
"""
record_list = list(self.data_df.to_dict(orient="index").values())
n_batch = int(len(record_list) / MAX_SQL_CHUNK) + 1
with database.atomic():
for cnt, batch in enumerate(pw.chunked(record_list, MAX_SQL_CHUNK)):
print(f"writing {cnt}/{n_batch}")
Company.insert_many(batch).execute()
def run(self):
print("Making query at {}".format(self.i_proc))
query = (Company.
select().
where(Company.id_number.between(self.first_id, self.last_id)))
print("Found {} companies".format(query.count()))
for cnt, company in enumerate(query):
print("Processing # {} - {}: company {}/{}".format(self.i_proc, cnt,
company.id_number,
company.name))
number_of_vowels = vowel_count(company.name)
company.n_vowels = number_of_vowels
company.processor = self.i_proc
print(f"storing number of vowels: {number_of_vowels}")
company.save()
Finally, my main script load the class stored in the models.py and parser.py and launches the code.
from models import (Company, connect_database)
from parser import CompanyParser
number_of_processors = 2
connect_database(None, reset_database=True)
# init an object of the CompanyParser and use the create database
parser = CompanyParser()
company_ids = Company.select(Company.id_number)
parser.generate_data()
parser.store_to_database()
n_companies = company_ids.count()
n_comp_per_proc = int(n_companies / number_of_processors)
print("Found {} companies: {} per proc".format(n_companies, n_comp_per_proc))
for i_proc in range(number_of_processors):
i_start = i_proc * n_comp_per_proc
first_id = company_ids[i_start]
last_id = company_ids[i_start + n_comp_per_proc - 1]
print(f"Running proc {i_proc} for id {first_id} until id {last_id}")
sub_parser = CompanyParser(first_id=first_id, last_id=last_id,
i_proc=i_proc,
number_of_procs=number_of_processors)
if number_of_processors > 1:
sub_parser.start()
else:
sub_parser.run()
In case that the number_of_processors = 1 this script works perfectly fine. It generates artificial data, stores it to the PostgreSQL database and does some processing on the data (it counts the number of vowels in the name and stores it to the n_vowels column)
However, in case I am trying to run this with 2 cores with number_of_processors = 2, I run into the following error
/opt/miniconda3/bin/python /home/eelco/PycharmProjects/multiproc_peewee/main.py
writing 0/1
Found 100 companies: 50 per proc
Running proc 0 for id 1020737 until id 5295565
Running proc 1 for id 5302405 until id 9891087
Making query at 0
Found 50 companies
Processing # 0 - 0: company 1020737/wqrbgxiu
storing number of vowels: 2
Making query at 1
Process CompanyParser-1:
Processing # 0 - 1: company 1086107/lkbagrbc
storing number of vowels: 1
Processing # 0 - 2: company 1298367/nsdjsqio
storing number of vowels: 2
Traceback (most recent call last):
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 2714, in execute_sql
cursor.execute(sql, params or ())
psycopg2.OperationalError: SSL error: sslv3 alert bad record mac
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/opt/miniconda3/lib/python3.7/multiprocessing/process.py", line 297, in _bootstrap
self.run()
File "/home/eelco/PycharmProjects/multiproc_peewee/parser.py", line 82, in run
company.save()
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 5748, in save
rows = self.update(**field_dict).where(self._pk_expr()).execute()
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 1625, in inner
return method(self, database, *args, **kwargs)
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 1696, in execute
return self._execute(database)
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 2121, in _execute
cursor = database.execute(self)
File "/opt/miniconda3/lib/python3.7/site-packages/playhouse/postgres_ext.py", line 468, in execute
cursor = self.execute_sql(sql, params, commit=commit)
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 2721, in execute_sql
self.commit()
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 2512, in __exit__
reraise(new_type, new_type(*exc_args), traceback)
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 186, in reraise
raise value.with_traceback(tb)
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 2714, in execute_sql
cursor.execute(sql, params or ())
peewee.OperationalError: SSL error: sslv3 alert bad record mac
Process CompanyParser-2:
Traceback (most recent call last):
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 2714, in execute_sql
cursor.execute(sql, params or ())
psycopg2.OperationalError: SSL error: decryption failed or bad record mac
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/opt/miniconda3/lib/python3.7/multiprocessing/process.py", line 297, in _bootstrap
self.run()
File "/home/eelco/PycharmProjects/multiproc_peewee/parser.py", line 72, in run
print("Found {} companies".format(query.count()))
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 1625, in inner
return method(self, database, *args, **kwargs)
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 1881, in count
return Select([clone], [fn.COUNT(SQL('1'))]).scalar(database)
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 1625, in inner
return method(self, database, *args, **kwargs)
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 1866, in scalar
row = self.tuples().peek(database)
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 1625, in inner
return method(self, database, *args, **kwargs)
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 1853, in peek
rows = self.execute(database)[:n]
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 1625, in inner
return method(self, database, *args, **kwargs)
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 1696, in execute
return self._execute(database)
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 1847, in _execute
cursor = database.execute(self)
File "/opt/miniconda3/lib/python3.7/site-packages/playhouse/postgres_ext.py", line 468, in execute
cursor = self.execute_sql(sql, params, commit=commit)
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 2721, in execute_sql
self.commit()
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 2512, in __exit__
reraise(new_type, new_type(*exc_args), traceback)
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 186, in reraise
raise value.with_traceback(tb)
File "/opt/miniconda3/lib/python3.7/site-packages/peewee.py", line 2714, in execute_sql
cursor.execute(sql, params or ())
peewee.OperationalError: SSL error: decryption failed or bad record mac
Process finished with exit code 0
Somehow something goes wrong as soon as the second thread start to do something with the database. Does somebody has advice to get this code working. I have tried the following already
Try the PooledPostgresDatabase and normal PostgresqlDatabase to
connect to the database. This leads to the same error
Try using sqlite in stead of postgres. This works for 2 cores, but only if the two processes are not interfering too much; otherwise I
can some locking problems. I was in the impression that postgres
would be better for doing multiprocessing then sqlite (is that true?)
When putting a break after launching the first process(so effectively using only one core), the code works, showing that the start method is called correctly.
Hopefully somebody can advise.
Regards
Eelco
After some searching on the internet today I found the solution for my problem here:github.com/coleifer. As coleifer mentions: you apparently first have to set up all the forks before you start connecting to the database. Based on this idea I have modified my code and it is working now.
For those interested I will post my python scripts again so you can see how I did it. This because I there is not so much explicit examples out there, so perhaps it may help others.
First of all, all the database and peewee modules are now moved into initialization functions which are only called inside the constructor of the CompanyParser class.
So models.py looks like
import peewee as pw
from playhouse.pool import PooledPostgresqlExtDatabase, PostgresqlDatabase, PooledPostgresqlDatabase
KVK_KEY = "id_number"
NAME_KEY = "name"
N_VOWELS_KEY = "n_vowels"
def init_database():
db = PooledPostgresqlDatabase(
"testdb", user="postgres", host="localhost", port=5432, password="xxxxx",
max_connections=8, stale_timeout=300)
return db
def init_models(db, reset_tables=False):
class BaseModel(pw.Model):
class Meta:
database = db
# this class describes the format of the sql data base
class Company(BaseModel):
id_number = pw.IntegerField(primary_key=True)
name = pw.CharField(null=True)
n_vowels = pw.IntegerField(default=-1)
processor = pw.IntegerField(default=-1)
if db.is_closed():
db.connect()
if reset_tables and Company.table_exists():
db.drop_tables([Company])
db.create_tables([Company])
return Company
Then, the worker class CompanyParser is defined in the parser.py script and looks like this
import multiprocessing as mp
import random
import string
import numpy as np
import pandas as pd
import peewee as pw
from models import (KVK_KEY, NAME_KEY, init_database, init_models)
MAX_SQL_CHUNK = 1000
np.random.seed(0)
def random_name(size=32, chars=string.ascii_lowercase):
""" Create a random character string of 'size' characters """
return "".join(random.choice(chars) for _ in range(size))
def vowel_count(characters):
"""
Count the number of vowels in the string 'characters' and return as an integer
"""
count = 0
for char in characters:
if char in list("aeiou"):
count += 1
return count
class CompanyParser(mp.Process):
def __init__(self, reset_tables=False,
number_of_companies=100, i_proc=None,
number_of_procs=1, first_id=None, last_id=None):
if i_proc is not None and number_of_procs > 1:
mp.Process.__init__(self)
self.i_proc = i_proc
self.reset_tables = reset_tables
self.number_of_procs = number_of_procs
self.n_companies = number_of_companies
self.data_df: pd.DataFrame = None
self.first_id = first_id
self.last_id = last_id
# initialise the database and models
self.database = init_database()
self.Company = init_models(self.database, reset_tables=self.reset_tables)
def generate_data(self):
""" Create a dataframe with fake company data and id's and return the array of id's"""
id_list = np.random.randint(1000000, 9999999, self.n_companies)
company_list = np.array([random_name() for _ in range(self.n_companies)])
self.data_df = pd.DataFrame(data=np.vstack([id_list, company_list]).T,
columns=[KVK_KEY, NAME_KEY])
self.data_df.drop_duplicates([KVK_KEY], inplace=True)
self.data_df.sort_values([KVK_KEY], inplace=True)
return self.data_df[KVK_KEY].values
def store_to_database(self):
"""
Store the company data to a sql database
"""
record_list = list(self.data_df.to_dict(orient="index").values())
n_batch = int(len(record_list) / MAX_SQL_CHUNK) + 1
with self.database.atomic():
for cnt, batch in enumerate(pw.chunked(record_list, MAX_SQL_CHUNK)):
print(f"writing {cnt}/{n_batch}")
self.Company.insert_many(batch).execute()
def run(self):
query = (self.Company.
select().
where(self.Company.id_number.between(self.first_id, self.last_id)))
for cnt, company in enumerate(query):
print("Processing # {} - {}: company {}/{}".format(self.i_proc, cnt, company.id_number,
company.name))
number_of_vowels = vowel_count(company.name)
company.n_vowels = number_of_vowels
company.processor = self.i_proc
try:
company.save()
except (pw.OperationalError, pw.InterfaceError) as err:
print("failed save for {} {}: {}".format(self.i_proc, cnt, err))
else:
pass
Finally, the main.py script which launches the processes:
from parser import CompanyParser
import time
def main():
number_of_processors = 2
number_of_companies = 10000
parser = CompanyParser(number_of_companies=number_of_companies, reset_tables=True)
company_ids = parser.generate_data()
parser.store_to_database()
n_companies = company_ids.size
n_comp_per_proc = int(n_companies / number_of_processors)
print("Found {} companies: {} per proc".format(n_companies, n_comp_per_proc))
if not parser.database.is_closed():
parser.database.close()
processes = list()
for i_proc in range(number_of_processors):
i_start = i_proc * n_comp_per_proc
first_id = company_ids[i_start]
last_id = company_ids[i_start + n_comp_per_proc - 1]
print(f"Running proc {i_proc} for id {first_id} until id {last_id}")
sub_parser = CompanyParser(first_id=first_id, last_id=last_id, i_proc=i_proc,
number_of_procs=number_of_processors)
if number_of_processors > 1:
sub_parser.start()
else:
sub_parser.run()
processes.append(sub_parser)
# this blocks the script until all processes are done
for job in processes:
job.join()
# make sure all the connections are closed
for i_proc in range(number_of_processors):
db = processes[i_proc].database
if not db.is_closed():
db.close()
print("Goodbye!")
if __name__ == "__main__":
start = time.time()
main()
duration = time.time() - start
print(f"Done in {duration} s")
As you can see, the database connection is done per process inside the class.
This example works and is a full example of multiprocessing + peewee and PostgreSQL. Hopefully this may help others. In case you have any comments or suggestions for improvement please let me know.
I did get this error too but with flask + peewee + rq in Heroku. Below is how I solved it:
If you have a simple app that you use with RQ, I would suggest to use SimpleWorker
RQ suggest to use rq.worker.HerokuWorker but I still received a ssl error with this.
The error appeared in a case where I have created a follow-up(chain) tasks, where execution of 1 depends on another tasks success.
Also I am using flask-rq2 but applies to normal usage as well as shown below:
# app.py
app = Flask(__name__)
app.config['RQ_WORKER_CLASS'] = os.getenv('RQ_WORKER_CLASS', 'rq.worker.Worker')
rq = RQ(app)
I solved it by changing the following in heroku config:
set your RQ_WORKER_CLASS to rq.worker.SimpleWorker
This is my code:
now = datetime.datetime.now().replace(microsecond=0)
curs.execute("SELECT name, msgDate, FROM test where msgDate=%s",(now))
I got these msgs:
File "C:\Python\lib\site-packages\mysql\connector\cursor.py", line 220, in _process_params
res = list(map(to_mysql,res))
TypeError: 'datetime.datetime' object is not iterable
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\projectse\Email\src\a.py", line 65, in <module>
curs.execute("SELECT name, msgDate FROM messages where msgDate=%s",(now))
File "C:\Python\lib\site-packages\mysql\connector\cursor.py", line 300, in execute
stmt = operation % self._process_params(params)
File "C:\Python\lib\site-packages\mysql\connector\cursor.py", line 225, in _process_params
"Failed processing format-parameters; %s" % e)
mysql.connector.errors.ProgrammingError: -1: Failed processing format-parameters;
'datetime.datetime' object is not iterable
Any tips?
I think you should replace:
curs.execute("SELECT name, msgDate, FROM test where msgDate=%s",(now))
with:
curs.execute("SELECT name, msgDate, FROM test where msgDate=%s",%(now))
and use this for your time variable:
import time
now=time.strftime('%Y-%m-%d %H:%M:%S')
Try seeing what now = str(datetime.datetime.now().replace(microsecond=0)) looks like in the python interpreter, if you're curious why that's a problem.
now = datetime.datetime(2012, 2, 23, 0, 0)
now.strftime('%m/%d/%Y')
curs.execute("SELECT name, msgDate, FROM test where msgDate=:now",dict(now=str(now))
please try converting date to string format and execute