I am an old C programmer trying to learn Django ... trying to build a project that I want to make open source when completed.
I have a Django DB Model that stores IP addresses of hosts (basically a table storing DNS A records). I need to find the number of entries in the table that are in a specified range of IPs. I am using Python's ipaddress module to do operations on IP addresses.
class Hosts(models.Model):
host_name = models.CharField(max_length=50)
host_domain = models.CharField(max_length=50)
host_ipaddress = models.CharField(max_length=15)
host_macaddress = models.CharField(max_length=17)
host_ttl = models.IntegerField()
host_createdate = models.DateTimeField()
host_location = models.CharField(max_length=25)
In a method I am trying to calculate the number of hosts in a range:
from .models Hosts
import ipaddress
def ips_used(start_ip, end_ip):
used = Hosts.objects.filter(`your text`
ipaddress.IPv4Address(Hosts.host_ipaddress) >=
ipaddress.IPv4Address(start_ip),
ipaddress.IPv4Address(Hosts.host_ipaddress) <=
ipaddress.IPv4Address(end_ip)).count()
Error message:
ipaddress.AddressValueError: Expected 4 octets in <django.db.models.query_utils.DeferredAttribute object at 0x7f8aa64c8b20>
I know this query is not correct but I have tried quite a number of options but no luck thus far. Maybe I am barking up the wrong tree, so your guidance would be appreciated.
Dummy SQL might look like this:
SELECT COUNT(*) FROM hosts WHERE ipaddress.IPv4Address(host_ipaddress) >= ipaddress.IPv4Address(start_ip) AND ipaddress.IPv4Address(host_ipaddress) <= ipaddress.IPv4Address(end_ip);
Related
I am using the google cloud datastore python client to write an entity into the datastore which contains an embedded entity. An example entity might look like:
data_type: 1
raw_bytes: <unindexed blob>
values: <indexed embedded entity>
I checked the data from the console and the data is getting saved correctly and the values are present.
Next, I need to run a query from a python app engine application. I have represented the above as the following entity in my app engine code:
class DataValues(ndb.Model):
param1 = ndb.BooleanProperty()
param2 = ndb.IntegerProperty()
param3 = ndb.IntegerProperty()
class MyEntity(ndb.Expando):
data_type = ndb.IntegerProperty(required=True)
raw_bytes = ndb.BlobProperty()
values = ndb.StructuredProperty(DataValues)
One of the filters in the query depends on a property in values. Sample query code is as below:
MyEntity.query().filter(MyEntity.data_type == 1).filter(MyEntity.values.param1 == True).get()
I have created the corresponding composite index in my index.yaml
The query runs successfully but the resulting entity contains the embedded entity values as None. All other property values are present.
What can be the issue here ?
Add properties of DataValues entity as properties of the MyEntity.
This is a bit of a guess, but since datastore attributes are kind of keyed by both their name (in this case values) and the name of the "field type/class" (i.e. StructuredProperty), this might fix your problem:
class EmbeddedProperty(ndb.StructuredProperty):
pass
class MyEntity(ndb.Expando):
data_type = ndb.IntegerProperty(required=True)
raw_bytes = ndb.BlobProperty()
values = EmbeddedProperty(DataValues)
Give it a shot and let me know if values starts coming back non-null.
I struggled with the same problem, wanting to convert the embedded entity into a Python dictionary. One possible solution, although not a very elegant one, is to use a GenericProperty:
class MyEntity(ndb.Model):
data_type = ndb.IntegerProperty(required=True)
raw_bytes = ndb.BlobProperty()
values = ndb.GenericProperty()
values will then be read as an "Expando" object: Expando(param1=False,...). You can access the individual values with values.param1, values.param2 etc. I would prefer having a custom model class, but this should do the job.
Hopefully an easy problem for an experienced SQL person. I have an application which uses SQL Server, and I cannot perform this query in the application, so I'm hoping to back-door it, but I need help.
I have a table with a large list of emails and all its metadata. I'm trying to find email that is only between parties of this one company and flag them.
What I did was search where companyName.com is in To and From and marked a TagField as 1 (I did this through my application's front end).
Now what I need to do is search where any other possible values, ignoring companyName.com exist in To and From where I've already flagged them as 1 in TagField. From will usually just have one value, but To could have multiple, all formatted differently, but all separated by a semi-colon (I will probably have to apply this same search to CC and BCC columns, too).
Any thoughts?
Replace the ; with the empty string. Then check to see if the length changed. If there's one email address, there shouldn't be a ';'. You could also use the same technique to replace the company name with the empty string. Anything left would be the other companies.
select email_id, to_email
from yourtable
where TagField = 1 and len(to_email) <> len(replace(to_email,';',''))
This solution is based on the following thread
Number of times a particular character appears in a string
So I went an entirely different route and exported my data to a CSV and used Python to get to where I needed. Here's the code I used in case anybody needs it. What this returned for me was a list of DocIDs (unique identifiers that were in the CSV) where ever there was an email address in the To field that wasn't from one specific domain. I went into the original CSV and made sure all instances of this domain name were in all lowercase, too.
import csv
import tkinter as tk
from tkinter import filedialog
root = tk.Tk()
root.withdraw()
file_path = filedialog.askopenfilename()
sub = "domainname"
def findMultipleTo(dict):
for row in reader:
if row['To'].find(";") != -1:
toArray = row['To'].split(';')
newTo = [s for s in toArray if sub not in s]
row['To'] = newTo
else:
row['To'] = 'empty'
with open('location\\newCSV-BCCFieldSearch.csv', 'a') as f:
if row['To'] != "empty" and row['To'] != []:
print(row['DocID'], row['To'], file = f)
else:
pass
with open(file_path) as csvfile:
reader = csv.DictReader(csvfile)
findMultipleTo(reader)
I am building an order system on Google App Engine.
Suppose I have the following model of Order:
class Order(ndb.Model):
time: DateTimeProperty()
The date plus a serial number as a string is used as the id of one entity:
today = str(datetime.datetime.now())[:10].replace('-','')
# Fetch today's orders
orders = Order.query(...).order(-Order.time).fetch(1)
if len(orders)==0: # No entities: today's first order
orderNum = today + '00001'
else:
orderNum = str(int(orders[0].key.id())+1)
order = Order(id=orderNum)
order.date = datetime.datetime.now()
order.put()
Suppose there are multiple clerks and they may execute the program at the same time. An obvious problem is that they may obtain the same orderNum and actually write to the same entity.
How do I do to prevent such situation from happening?
You could use something similar to the code below.
#ndb.transactional(retries=3)
def create_order_if_not_exists(order):
exists = order.key.get()
if exists is not None:
raise Exception("Order already exists: ID=%s" % order.key.id())
order.put()
Or you can use Model's class method get_or_insert() that transactionally retrieves an existing entity or creates a new one. See details here.
Do I pay a penalty on query performance if I choose to query repeated property? For example:
class User(ndb.Model):
user_name = ndb.StringProperty()
login_providers = ndb.KeyProperty(repeated=true)
fbkey = ndb.Key("ProviderId", 1, "ProviderName", "FB")
for entry in User.query(User.login_providers == fbkey):
# Do something with entry.key
vs
class User(ndb.Model)
user_name = ndb.StringProperty()
class UserProvider(ndb.Model):
user_key = ndb.KeyProperty(kind=User)
login_provider = ndb.KeyProperty()
for entry in UserProvider.query(
UserProvider.user_key == auserkey,
UserProvider.login_provider == fbkey
):
# Do something with entry.user_key
Based on the documentation from GAE, it seems that Datastore take care of indexing and the first less verbose option would be using the index. However, I failed to find any documentation to confirm this.
Edit
The sole purpose of UserProvider in the second example is to create a one-to-many relationship between a user and it's login_provider. I wanted to understand if it worth the trouble of creating a second entity instead of querying on repeated property. Also, assume that all I need is the key from the User.
No. But you'll raise your write costs because each entry needs to be indexed, and write costs are based on the number of indexes updated.
I recently came across a number of articles pointing out to flatten the data for NoSQL databases. Coming from traditional SQL databases I realized I am replicating a SQL db bahaviour in GAE. So I started to refactor code where possible.
We have e.g. a social media site where users can become friends with each other.
class Friendship(ndb.Model):
from_friend = ndb.KeyProperty(kind=User)
to_friend = ndb.KeyProperty(kind=User)
Effectively the app creates a friendship instance between both users.
friendshipA = Friendship(from_friend = UserA, to_friend = userB)
friendshipB = Friendship(from_friend = UserB, to_friend = userA)
How could I now move this to the actual user model to flatten it. I thought maybe I could use a StructuredProperty. I know it is limited to 5000 entries, but that should be enough for friends.
class User(UserMixin, ndb.Model):
name = ndb.StringProperty()
friends = ndb.StructuredProperty(User, repeated=True)
So I came up with this, however User can't point to itself, so it seems. Because I get a NameError: name 'User' is not defined
Any idea how I could flatten it so that a single User instance would contain all its friends, with all their properties?
You can't create a StructuredProperty that references itself. Also, use of StructuredProperty to store a copy of User has additional problem of needing to perform a manual cascade update if a user ever modifies a property that is stored.
However, as KeyProperty accept String as kind, you can easily store the list of Users using KeyProperty as suggested by #dragonx. You can further optimise read by using ndb.get_multi to avoid multiple round-trip RPC calls when retrieving friends.
Here is a sample code:
class User(ndb.Model):
name = ndb.StringProperty()
friends = ndb.KeyProperty(kind="User", repeated=True)
userB = User(name="User B")
userB_key = userB.put()
userC = User(name="User C")
userC_key = userC.put()
userA = User(name="User A", friends=[userB_key, userC_key])
userA_key = userA.put()
# To retrieve all friends
for user in ndb.get_multi(userA.friends):
print "user: %s" % user.name
Use a KeyProperty that stores the key for the User instance.