SQLAlchemy Flask run code after insert/update/delete - sqlalchemy

I am using Flask and a SQLAlchemy extension. Also I am using the declarative way to write my models as described in the extension's documentation.
For one of my models, I have some code I need to run after a new row has been inserted, updated or deleted. I was wondering how to do it? Ideally I would just add functions to the model.

Look at SQLAlchemy's Mapper Events. You can bind a callback function to the after_insert, after_update, and after_delete events.
Example:
from sqlalchemy import event
def after_insert_listener(mapper, connection, target):
# 'target' is the inserted object
print(target.id_user)
event.listen(User, 'after_insert', after_insert_listener)

Related

Access CSV Data Set Config variables in backend listener

I'm trying to fetch my variables from CSV Data config and add them to my backend listener in a distributed testing environment like this. FYI, it works on my local machine.
Here is my test plan:
Test Plan
CSV Data Config:
CSV config
My csv looks like this:
SELECT count(*) FROM github_events;simpleQuery
SELECT count(*) FROM github_events;medium
SELECT count(*) FROM github_events;complexQuery
SELECT count(*) FROM github_events;simpleQuery
Backend Listener:
Backend Listener
I'm setting the CSV config variables in the beanshell pre-processor like this:
props.put("query", "${QUERY}");
props.put("query_type", "${QUERY_TYPE}");
and that's why I have the ${__P(query)} ${__P(query_type)} in the backend listener.
The goal is to grab the QUERY and QUERY_TYPE from the CSV data config and send it to the backend listener.
Any help would be appreciated. Let me know if I need to add more info on here. Thank you!
Solution:
How I got this to work... kind of hacky but it'll work for what I need:
I created a JSR223 Postprocessor on my JDBC Request and added the following code:
import groovy.json.*
def my_query = vars.get("QUERY")
def my_query_type = vars.get("QUERY_TYPE")
json = JsonOutput.toJson([myQuery: my_query, myQueryType: my_query_type])
prev.setSamplerData(groovy.json.JsonOutput.prettyPrint(groovy.json.JsonOutput.toJson(json)))
This won't work if you need whatever is in your response Data but in my case, it was okay to replace. BTW, this only works with my distributed test. To make it work locally, you use prev.setResponseData instead. Hope this helps someone.
I don't think you can, as per JMeter 5.4.1 all fields of the Backend Listener are being populated in "testStarted" phase
the same applies to your custom listener
it means that JMeter Variables originating from the CSV Data Set Config don't exist at the time the Backend Listener is being initialized and your reference to JMeter Properties returns the default value of 1 as there are no such variables.
If you're looking for the possibility to dynamically send metrics to Azure you will need to replicate the code from the Azure Backend Listener in JSR223 Listener using Groovy language.
The only way how this could work on your local machine is that:
You run your test plan in GUI mode 1st time - it fails, but it sets the properties
You run your test plan in GUI mode 2nd time - it passes but uses the last values of the properties
etc.

Django MySQL Error (1146, "Table 'db_name.django_content_type' doesn't exist")

I am getting the error
django.db.utils.ProgrammingError: (1146, "Table 'db_name.django_content_type' doesn't exist")
when trying to do the initial migration for a django project with a new database that I'm deploying on the production server for the first time.
I suspected the problem might be because one of the the apps had a directory full of old migrations from a SQLite3 development environment; I cleared those out but it didn't help. I also searched and found references to people having the problem with multiple databases, but I only have one.
Django version is 1.11.6 on python 3.5.4, mysqlclient 1.3.12
Some considerations:
Are you calling ContentType.objects manager anywhere in your code that may be called before the db has been built?
I am currently facing this issue and need a way to check the db table has been built before I can look up any ContentTypes
I ended up creating a method to check the tables to see if it had been created, not sure if it will also help you:
def get_content_type(cls):
from django.contrib.contenttypes.models import ContentType
from django.db import connection
if 'django_content_type' in connection.introspection.table_names():
return ContentType.objects.get_for_model(cls)
else:
return None
As for migrations, my understanding is that they should always belong in your version control repo, however you can squash, or edit as required, or even rebuild them, this linked helps me with some migrations problems:
Reset Migrations
Answering my own question:
UMDA's comment was right. I have some initialization code for the django-import-export module that looks at content_types, and evidently I have never deployed the app from scratch in a new environment since I wrote it.
Lessons learned / solution:
will wrap the offending code in an exception block, since I should
only have this exception once when deploying in a new environment
test clean deployments in a new environment more regularly.
(edit to add) consider whether your migrationsdirectories belong in .gitignore. For my purposes they do.
(Relatively new to stackoverflow etiquette - how do I credit UMDA's comment for putting me on the right track?)
I had the same issue when trying to create a generic ModelView (where the model name would be passed as a variable in urls.py). I was handling this in a kind of silly way:
Bad idea: a function that returns a generic class-based view
views.py
from django.contrib.auth.mixins import LoginRequiredMixin
from django.contrib.contenttypes.models import ContentType
from django.views.generic.edit import DeleteView
def get_generic_delete_view(model_name):
model_type = ContentType.objects.get(app_label='myapp', model=model_name)
class _GenericDelete(LoginRequiredMixin, DeleteView):
model = model_type.model_class()
template_name = "confirm_delete.html"
return _GenericDelete.as_view()
urls.py
from django.urls import path, include
from my_app import views
urlpatterns = [
path("mymodels/<name>/delete/", views.get_generic_delete_view("MyModel"),
]
Anyway. Let's not dwell in the past.
This was fixable by properly switching to a class-based view, instead of whatever infernal hybrid is outlined above, since (according to this SO post) a class-based view isn't instantiated until request-time.
Better idea: actual generic class-based view
views.py
from django.contrib.auth.mixins import LoginRequiredMixin
from django.contrib.contenttypes.models import ContentType
from django.views.generic.edit import DeleteView
class GenericDelete(LoginRequiredMixin, DeleteView):
template_name = "confirm_delete.html"
def __init__(self, **kwargs):
model = kwargs.pop("model")
model_type = ContentType.objects.get(app_label='myapp', model=model)
self.model = model_type.model_class()
super().__init__()
urls.py
from django.urls import path, include
from my_app import views
urlpatterns = [
path("mymodels/<name>/delete/", views.GenericDelete.as_view(model="MyModel"),
]
May you make new and better mistakes.
Chipping in because maybe this option will appeal better in some scenarios.
Most of the project's imports usually cascade down from your urls.py. What I usually do, is wrap the urls.py imports in a try/except statement and only create the routes if all imports were successful.
What this accomplishes is to create your project's / app's routes only if the modules were imported. If there is an error because the tables do not yet exist, it will be ignored, and the migrations will be done. In the next run, hopefully, you will have no errors in your imports and everything will run smoothly. But if you do, it's easy to spot because you won't have any URLs. Also, I usually add an error log to guide me through the issue in those cases.
A simplified version would look like this:
# Workaround to avoid programming errors on greenfield migrations
register_routes = True
try:
from myapp.views import CoolViewSet
# More imports...
except Exception as e:
register_routes = False
logger.error("Avoiding creation of routes. Error on import: {}".format(e))
if register_routes:
# Add yout url paterns here
Now, maybe you can combine Omar's answer for a more sensible, less catch-all solution.

How to use flask-migrate with other declarative_bases

I'm trying to implement python-social-auth in Flask. I've ironed out tons of kinks whilst trying to interpret about 4 tutorials and a full Flask-book at the same time, and feel I've reached sort of an impasse with Flask-migrate.
I'm currently using the following code to create the tables necessary for python-social-auth to function in a flask-sqlalchemy environment.
from social.apps.flask_app.default import models
models.PSABase.metadata.create_all(db.engine)
Now, they're obviously using some form of their own Base, not related to my actual db-object. This in turn causes Flask-Migrate to completely miss out on these tables and remove them in migrations. Now, obviously I can remove these db-drops from every removal, but I can imagine it being one of those things that at one point is going to get forgotten about and all of a sudden I have no OAuth-ties anymore.
I've gotten this solution to work with the usage (and modification) of the manage.py-command syncdb as suggested by the python-social-auth Flask example
Miguel Grinberg, the author of Flask-Migrate replies here to an issue that seems to very closely resemble mine.
The closest I could find on stack overflow was this, but it doesn't shed too much light on the entire thing for me, and the answer was never accepted (and I can't get it to work, I have tried a few times)
For reference, here is my manage.py:
#!/usr/bin/env python
from flask.ext.script import Server, Manager, Shell
from flask.ext.migrate import Migrate, MigrateCommand
from app import app, db
manager = Manager(app)
manager.add_command('runserver', Server())
manager.add_command('shell', Shell(make_context=lambda: {
'app': app,
'db_session': db.session
}))
migrate = Migrate(app, db)
manager.add_command('db', MigrateCommand)
#manager.command
def syncdb():
from social.apps.flask_app.default import models
models.PSABase.metadata.create_all(db.engine)
db.create_all()
if __name__ == '__main__':
manager.run()
And to clarify, the db init / migrate / upgrade commands only create my user table (and the migration one obviously), but not the social auth ones, while the syncdb command works for the python-social-auth tables.
I understand from the github response that this isn't supported by Flask-Migrate, but I'm wondering if there's a way to fiddle in the PSABase-tables so they are picked up by the db-object sent into Migrate.
Any suggestions welcome.
(Also, first-time poster. I feel I've done a lot of research and tried quite a few solutions before I finally came here to post. If I've missed something obvious in the guidelines of SO, don't hesitate to point that out to me in a private message and I'll happily oblige)
After the helpful answer from Miguel here I got some new keywords to research. I ended up at a helpful github-page which had further references to, amongst others, the Alembic bitbucket site which helped immensely.
In the end I did this to my Alembic migration env.py-file:
from sqlalchemy import engine_from_config, pool, MetaData
[...]
# add your model's MetaData object here
# for 'autogenerate' support
# from myapp import mymodel
# target_metadata = mymodel.Base.metadata
from flask import current_app
config.set_main_option('sqlalchemy.url',
current_app.config.get('SQLALCHEMY_DATABASE_URI'))
def combine_metadata(*args):
m = MetaData()
for metadata in args:
for t in metadata.tables.values():
t.tometadata(m)
return m
from social.apps.flask_app.default import models
target_metadata = combine_metadata(
current_app.extensions['migrate'].db.metadata,
models.PSABase.metadata)
This seems to work absolutely perfectly.
The problem is that you have two sets of models, each with a different SQLAlchemy metadata object. The models from PSA were generated directly from SQLAlchemy, while your own models were generated through Flask-SQLAlchemy.
Flask-Migrate only sees the models that are defined via Flask-SQLAlchemy, because the db object that you give it only knows about the metadata for those models, it knows nothing about these other PSA models that bypassed Flask-SQLAlchemy.
So yeah, end result is that each time you generate a migration, Flask-Migrate/Alembic find these PSA tables in the db and decides to delete them, because it does not see any models for them.
I think the best solution for your problem is to configure Alembic to ignore certain tables. For this you can use the include_object configuration in the env.py module stored in the migrations directory. Basically you are going to write a function that Alembic will call every time it comes upon a new entity while generating a migration script. The function will return False when the object in question is one of these PSA tables, and True for every thing else.
Update: Another option, which you included in the response you wrote, is to merge the two metadata objects into one, then the models from your application and PSA are inspected by Alembic together.
I have nothing against the technique of merging multiple metadata objects into one, but I think it is not a good idea for an application to track migrations in models that aren't yours. Many times Alembic will not be able to capture a migration accurately, so you may need to make minor corrections on the generated script before you apply it. For models that are yours, you are capable of detecting these inaccuracies that sometimes show up in migration scripts, but when the models aren't yours I think you can miss stuff, because you will not be familiar enough with the changes that went into those models to do a good review of the Alembic generated script.
For this reason, I think it is a better idea to use my proposed include_object configuration to leave the third party models out of your migrations. Those models should be migrated according to the third party project's instructions instead.
I use two models as following:-
One which is use using db as
db = SQLAlchemy()
app['SQLALCHEMY_DATABASE_URI'] = 'postgresql://postgres:' + POSTGRES_PASSWORD + '#localhost/Flask'
db.init_app(app)
class User(db.Model):
pass
the other with Base as
Base = declarative_base()
uri = 'postgresql://postgres:' + POSTGRES_PASSWORD + '#localhost/Flask'
engine = create_engine(uri)
metadata = MetaData(engine)
Session = sessionmaker(bind=engine)
session = Session()
class Address(Base):
pass
Since you created user with db.Model you can use flask migrate on User and class Address used Base which handles fetching pre-existing table from the database.

Using toJSONPretty();

I am trying to work with JSON objects with DynamoDB and am having difficulty.
I'm trying to follow the tutorial:
http://aws.amazon.com/blogs/aws/dynamodb-update-json-and-more/
I wanted to use toJSONPretty(); on my object but the method is not recognized. I don't think I have the right gradle dependencies. I"m currently using:
compile 'com.amazonaws:aws-android-sdk-core:2.2.0'
compile 'com.amazonaws:aws-android-sdk-ddb:2.2.0'
compile 'com.amazonaws:aws-android-sdk-ddb-mapper:2.2.0'
Previously, my dynamo client was set up using the imports:
import com.amazonaws.services.dynamodbv2.AmazonDynamoDB;
import com.amazonaws.services.dynamodbv2.AmazonDynamoDBClient;
But looking at code from Dynamo/JSON tutorials, I see the import:
import com.amazonaws.services.dynamodbv2.document.DynamoDB;
This seems to be required if you want to use the type DynamoDB as it:
DynamoDB dynamo = new DynamoDB(new AmazonDynamoDBClient(...));
I don't understand the difference between these libraries or how they relate to each other. Help!
The DynamoDB class is a higher-level abstraction of the AmazonDynamoDB API. It you create it with an instance of the AmazonDynamoDB inteface or a Regions object. AmazonDynamoDBClient implements the AmazonDynamoDB interface. Even if you pass a Regions object, an instance of a class that implements AmazonDynamoDB is created behind the scenes. Then, you get a Table so that you can perform data-plane operations like GetItem and PutItem. The Item class is one that has a toJSONPretty method. To sum up, the DynamoDB class uses an implementation of the AmazonDynamoDB interface behind the scenes to provide you with Items that you can call toJSONPretty() on.

How to log SQL queries to a log file with CakePHP

I have a CakePHP 1.2 application that makes a number of AJAX calls using the AjaxHelper object. The AjaxHelper makes a call to a controller function which then returns some data back to the page.
I would like to log the SQL queries that are executed by the AJAX controller functions. Normally, I would just turn the debug level to 2 in config/core.php, however, this breaks my AJAX functionality because it causes the output SQL queries to be appended to the output that is returned to the client side.
To get around this issue, I would like to be able to log any SQL queries performed to a log file. Any suggestions?
I found a nice way of adding this logging functionality at this link:
http://cakephp.1045679.n5.nabble.com/Log-SQL-queries-td1281970.html
Basically, in your cake/libs/model/datasources/dbo/ directory, you can make a subclass of the dbo that you're using. For example, if you're using the dbo_mysql.php database driver, then you can make a new class file called dbo_mysql_with_log.php. The file would contain some code along the lines of the following:
App::import('Core', array('Model', 'datasource', 'dbosource', 'dbomysql'));
class DboMysqlWithLog extends DboMysql {
function _execute($sql) {
$this->log($sql);
return parent::_execute($sql);
}
}
In a nutshell, this class modifies (i.e. overrides) the _execute function of the superclass to log the SQL query before doing whatever logic it normally does.
You can modify your app/config/database.php configuration file to use the new driver that you just created.
This is a fantastic way to debug things like this, https://github.com/cakephp/debug_kit