I have a pyramid game server app that uses sqlalchemy to read/write to postgres database. I want to read a certain table(call it games) from the database at the time this app is created. This games data will be used by one of my wsgi middleware, that is hooked in the app, to send statsd metrics. To do this, I added a subscriber in the main function of my app like:
config.add_subscriber(init_mw_data, ApplicationCreated)
Now, I want to read the games table in the following function:
def init_mw_data(event):
...
...
Anybody know how I can read games table inside the function init_mw_data ?
It based how you configured your application.
Default sqlalchemy template from pyramid-cookiecutter-starter have dbsession_factory.
So, you can do something like this:
def init_mw_data(event):
registry = event.app.registry
dbsession = registry['dbsession_factory']()
dbsession.query(...)
...
Related
For now I always created the structure and logic of my backend with Django. But when I insert data into the database I alwas did that directly via a http request to a php script.
When the projects grows it is getting pretty messy. As well, there were always complications with timestamps from the database to the backend.
I want to eliminate all these flaws but could not find any good example If I could just make a request to a certain view in Django, containing all the information I want to put into the database. Django and the database are on the same machine, but the data that is being inserted comes from different devices.
Maybe you could give me a hint how to search further for this
You can just create a python script and run that.
Assuming you have a virtualenv, ensure you have to activated. And put this in the root of your Django project.
#!/usr/bin/env python
import os
import django
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "myapp.settings")
django.setup()
# Import after setup, to ensure they are initiliazed properly.
from myapp.models import MyModel, OtherModel
if __name__ == "__main__":
# Create your objects.
obj = MyModel.objects.create(some_value="foo")
other_obj = OtherModel.objects.create(title="Bar", ref=obj)
You can also use transaction to ensure it only commits all or none.
from django.db import transaction
with transaction.atomic():
obj = MyModel.objects.create(some_value="foo")
other_obj = OtherModel.objects.create(title="Bar", ref=obj)
Should one of the creations fail, everything is rolled back. This prevent from ending up with a half filled or corrupt database.
I have a project that is connected to an external database and just have view access to it. So I created my models with managed=False flag.
I was wondering how can I find out in django that any change in that database is happened. Is there any solution in django or I should find a method to communicate between that database and my django app. like socket, database triggers and ...?
More details:
Image my models is like this:
class Alert(models.Model):
key = models.CharField(max_length=20)
class Meta:
managed = False
Now i want to be notified in django each time the database is updated. I want a signal to capture database updates and do something in django?
Let's say I need to create a lot of different documents/collections in firestore. I need to add it quickly, like copy and paste json. I can't do that with standard firebase console, because adding 100 documents will take me forever. Is there any solutions for to bulk create mock data with a given structure in firestore db?
If you switch to the Cloud Console (rather than Firebase Console) for your project, you can use Cloud Shell as a starting point.
From the Cloud Shell environment you'll find tools like node and python installed and available. Using whatever one you prefer, you can write a script using the Server Client libraries.
For example in Python:
from google.cloud import firestore
import random
MAX_DOCUMENTS = 100
SAMPLE_COLLECTION_ID = u'users'
SAMPLE_COLORS = [u'Blue', u'Red', u'Green', u'Yellow', u'White', u'Black']
# Project ID is determined by the GCLOUD_PROJECT environment variable
db = firestore.Client()
collection_ref = db.collection(SAMPLE_COLLECTION_ID)
for x in range(0, MAX_DOCUMENTS - 1):
collection_ref.add({
u'primary': random.choice(SAMPLE_COLORS),
u'secondary': random.choice(SAMPLE_COLORS),
u'trim': random.choice(SAMPLE_COLORS),
u'accent': random.choice(SAMPLE_COLORS)
})
While this is the easiest way to get up and running with a static dataset, it lives a little to be desired. Namely with Firestore, live dynamic data is needed to exercises it's functionally, such as real-time queries. For this task, using Cloud Scheduler & Cloud Functions is a relatively easy way to regularly updating sample data.
In addition to the sample generation code, you'll specific the update frequency in the Cloud Scheduler. For instance in the image below, */10 * * * * defines a frequency of every 10 minutes using the standard unix-cron format:
For non-static data, often a timestamp is useful. Firestore provides a way to have a timestamp from the database server added at write-time as one of the fields:
u'timestamp': firestore.SERVER_TIMESTAMP
It is worth noting that timestamps like this will hotspot in production systems if not sharded correctly. Typically 500 writes/second to the same collection is the maximum you will want so that the index doesn't hotspot. Sharding can be as simple something like as each user having their own collection (500 writes/second per user). However for this example, writing 100 documents every minute via a scheduled Cloud Function is definitely not an issue.
FireKit is a good resource to use for this purpose. It even allows sub-collections.
https://retroportalstudio.gumroad.com/l/firekit_free
I have a Rails app with MySql DB. It houses a lot of data on which we need to run some reports and create some dashboards. It requires some calculations. What are some ready to use solutions for this? Gems, tools or frameworks that can help getting it developed fast would help.
For charts you can use Fusion chart gem in rails
https://github.com/fusioncharts/rails-wrapper
In order to draw charts you need data in hash Like
Create one lib which will return hash data
example
class Dashboard
def initialize
# initialize here
end
def data_set
{
user_details: User.details,
profile_details: Profile.details
}
end
end
In particular model you can fetch data using queries.
For charts, you have to render charts as per documentation
I am trying to start a simple django app. I have been on it for days. I was able to this in flask in a few hrs.
I need advice on connecting to an external database to grab tables and display them on django pages.
This is my code in flask
#app.route("/topgroups")
def topgroups():
con = sql.connect("C:\\Users\\win10\\YandexDisk\\apps\\flask\\new_file.sqlite")
con.row_factory = sql.Row
cur = con.cursor()
cur.execute("SELECT domain, whois, Traffic, Groups,LE,adddate FROM do_1 where Groups in (75,86,66,58,67,57,68,85,48,56,76,77,46,65,47,64,45,55,74,54,44,33,34,43)")
rows = cur.fetchall();
return render_template("index.html", rows = rows)
I will give you the python answer but read until the end because you may be losing a lot on Django if you follow this approach.
Python comes with SQLite capabilities so you don't even need to install packages Python Docs:
Connect
import sqlite3
conn = sqlite3.connect('C:\\Users\\win10\\YandexDisk\\apps\\flask\\new_file.sqlite')
Want to ensure read only? from the docs
conn = sqlite3.connect('file:C:\\Users\\win10\\YandexDisk\\apps\\flask\\new_file.sqlite?mode=ro', uri=True)
Use
cur = conn.cursor()
... (just like for flask)
Note/ My recommendation
One of the biggest advantages of Django is:
Define your data models entirely in Python. You get a rich, dynamic database-access API for free — but you can still write SQL if needed.
And you'll loose a lot without it, from basic stuff like what you asked to even unit-testing capabilities.
Follow this tutorial to integrate your database: Integrating Django with a legacy database.
You may set manage=False and Django won't touch in those tables,
only create new ones to support the app.
If you just use that DB for some special purpose then give a look at Django Multiple databases