I have run into an issue using attempting to add values from two different columns together in a query, namely that some of them contain numbers. This means that the built in Concat does not work as it requires strings or chars.
Considering how one can cast variables as other datatypes in SQL I don't see why I wouldn't be able to do that in Django.
cast(name as varchar(100))
I would assume that one would do it as follows in Django using the Concat function in combination with Cast.
queryset.annotate(new_col=Concat('existing_text_col', Cast('existing_integer_col', TextField())).get())
The above obviously does not work, so does anyone know how to actually do this?
The use case if anyone wonders are sending jenkins urls saved as fragments as a whole. So one url would be:
base_url: www.something.com/
url_fragment: name/
url_number: 123456
I ended up writing a serializer that inherits from the base serializer that contains the urls fragments and a lot of other things. In it I made a MethodField for my complete url and defined a getter function that loaded in the different fragments and added them together. I also redeclared the fragmented fields to None.
The code inside the new serializer is:
complete = serpy.MethodField("get_copmlete")
serverUrl = serpy.Field(attr=None, call=False, required=False)
jobName = serpy.Field(attr=None, call=False, required=False)
buildNumber = serpy.Field(attr=None, call=False, required=False)
def get_complete(self, obj):
return obj.server_url + obj.job_name + '/' + str(obj.build_number)
Related
There are the following attributes in client_output
weights_delta = attr.ib()
client_weight = attr.ib()
model_output = attr.ib()
client_loss = attr.ib()
After that, I made the client_output in the form of a sequence through
a = tff.federated_collect(client_output) and round_model_delta = tff.federated_map(selecting_fn,a)in here . and I declared
`
#tff.tf_computation() # append
def selecting_fn(a):
#TODO
return round_model_delta
in here. In the process of averaging on the server, I want to average the weights_delta by selecting some of the clients with a small loss value. So I try to access it via a.weights_delta but it doesn't work.
The tff.federated_collect returns a tff.SequenceType placed at tff.SERVER which you can manipulate the same way as for example client dataset is usually handled in a method decorated by tff.tf_computation.
Note that you have to use the tff.federated_collect operator in the scope of a tff.federated_computation. What you probably want to do[*] is pass it into a tff.tf_computation, using the tff.federated_map operator. Once inside the tff.tf_computation, you can think of it as a tf.data.Dataset object and everything in the tf.data module is available.
[*] I am guessing. More detailed explanation of what you would like to achieve would be helpful.
I'm building a tree in Graphviz and I can't seem to be able to get the feature names to show up, I have defined a list with the feature names like so:
names = list(df.columns.values)
Which prints:
['Gender',
'SuperStrength',
'Mask',
'Cape',
'Tie',
'Bald',
'Pointy Ears',
'Smokes']
So the list is being created, later I build the tree like so:
export_graphviz(tree, out_file=ddata, filled=True, rounded=True, special_characters=False, impurity=False, feature_names=names)
But the final image still has the feature names listed like X[]:
How can I get the actual feature names to show up? (Cape instead of X[3], etc.)
I can only imagine this has to do with passing the names as an array of the values. It works fine if you pass the columns directly:
export_graphviz(tree, out_file=ddata, filled=True, rounded=True, special_characters=False, impurity=False, feature_names=df.columns)
If needed, you can also slice the columns:
export_graphviz(tree, out_file=ddata, filled=True, rounded=True, special_characters=False, impurity=False, feature_names=df.columns[5:])
Please forgive me if my question does not make sense.
What im trying to do is to inject in values for query parameters
GET1 File
Scenario:
Given path 'search'
And param filter[id] = id (default value or variable from another feature file)
POST1 File
Scenario:
def newid = new id made by a post call
def checkid = read call(GET1) {id : newid}
like if one of my feature files creates a new id then i want to do a get call with the above scenario. therefore i need a parameter there which takes in the new id.
On the other hand if i do not have an id newly created or the test creating it is not part of the suite. i want to still be able to run the above mentioned scenario but this time it has a default value to it.
Instead of param use params. It is designed so that any keys with null values are ignored.
After the null is set on the first line below, you can make a call to another feature, and overwrite the value of criteria. If it still is null, no params will be set.
* def criteria = null
Given path 'search'
And params { filter: '#(criteria)' }
There are multiple other ways to do this, also refer to this set of examples for data-driven search params: dynamic-params.feature
The doc on conditional logic may also give you some ideas.
I have three models:
class Customer(models.Model):
pass
class IssueType(models.Model):
pass
class IssueTypeConfigPerCustomer(models.Model):
customer=models.ForeignKey(Customer)
issue_type=models.ForeignKey(IssueType)
class Meta:
unique_together=[('customer', 'issue_type')]
How can I find all tuples of (custmer, issue_type) where there is no IssueTypeConfigPerCustomer object?
I want to avoid a loop in Python. A solution which solves this in the DB would be preferred.
Background: for every customer and for every issue-type, there should be a config in the DB.
If you can afford to make one database trip for each issue type, try something like this untested snippet:
def lacking_configs():
for issue_type in IssueType.objects.all():
for customer in Customer.objects.filter(
issuetypeconfigpercustomer__issue_type=None
):
yield customer, issue_type
missing = list(lacking_configs())
This is probably OK unless you have a lot of issue types or if you are doing this several times per second, but you may also consider having a sensible default instead of making a config object mandatory for each combination of issue type and customer (IMHO it is a bit of a design-smell).
[update]
I updated the question: I want to avoid a loop in Python. A solution which solves this in the DB would be preferred.
In Django, every Queryset is either a list of Model instances or a dict (values querysets), so it is impossible to return the format you want (a list of tuples of Model) without some Python (and possibly multiple trips to the database).
The closest thing to a cross product would be using the "extra" method without a where parameter, but it involves raw SQL and knowing the underlying table name for the other model:
missing = Customer.objects.extra(
select={"issue_type_id": 'appname_issuetype.id'},
tables=['appname_issuetype']
)
As a result, each Customer object will have an extra attribute, "issue_type_id", containing the id of one IssueType. You can use the where parameter to filter based on NOT EXISTS (SELECT 1 FROM appname_issuetypeconfigpercustomer WHERE issuetype_id=appname_issuetype.id AND customer_id=appname_customer.id). Using the values method you can have something close to what you want - this is probably enough information to verify the rule and create the missing records. If you need other fields from IssueType just include them in the select argument.
In order to assemble a list of (Customer, IssueType) you need something like:
cross_product = [
(customer, IssueType.objects.get(pk=customer.issue_type_id))
for customer in
Customer.objects.extra(
select={"issue_type_id": 'appname_issuetype.id'},
tables=['appname_issuetype'],
where=["""
NOT EXISTS (
SELECT 1
FROM appname_issuetypeconfigpercustomer
WHERE issuetype_id=appname_issuetype.id
AND customer_id=appname_customer.id
)
"""]
)
]
Not only this requires the same number of trips to the database as the "generator" based version but IMHO it is also less portable, less readable and violates DRY. I guess you can lower the number of database queries to a couple using something like this:
missing = Customer.objects.extra(
select={"issue_type_id": 'appname_issuetype.id'},
tables=['appname_issuetype'],
where=["""
NOT EXISTS (
SELECT 1
FROM appname_issuetypeconfigpercustomer
WHERE issuetype_id=appname_issuetype.id
AND customer_id=appname_customer.id
)
"""]
)
issue_list = dict(
(issue.id, issue)
for issue in
IssueType.objects.filter(
pk__in=set(m.issue_type_id for m in missing)
)
)
cross_product = [(c, issue_list[c.issue_type_id]) for c in missing]
Bottom line: in the best case you make two queries at the cost of legibility and portability. Having sensible defaults is probably a better design compared to mandatory config for each combination of Customer and IssueType.
This is all untested, sorry if some homework was left for you.
I'm currently trying to create an Endeca query using the Java API for a URLENEQuery. The current query is:
collection()/record[CONTACT_ID = "xxxxx" and SALES_OFFICE = "yyyy"]
I need it to be:
collection()/record[(CONTACT_ID = "xxxxx" or CONTACT_ID = "zzzzz") and
SALES_OFFICE = "yyyy"]
Currently this is being done with an ERecSearchList with CONTACT_ID and the string I'm trying to match in an ERecSearch object, but I'm having difficulty figuring out how to get the UrlENEQuery to generate the or in the correct fashion as I have above. Does anyone know how I can do this?
One of us is confused on multiple levels:
Let me try to explain why I am confused:
If Contact_ID and Sales_Office are different dimensions, where Contact_ID is a multi-or dimension, then you don't need to use EQL (the xpath like language) to do anything. Just select the appropriate dimension values and your navigation state will reflect the query you are trying to build with XPATH. IE CONTACT_IDs "ORed together" with SALES_OFFICE "ANDed".
If you do have to use EQL, then the only way to modify it (provided that you have to modify it from the returned results) is via string manipulation.
ERecSearchList gives you ability to use "Search Within" functionality which functions completely different from the EQL filtering, though you can achieve similar results by using tricks like searching only specified field (which would be separate from the generic search interface") I am still not sure what's the connection between ERecSearchList and the EQL expression above?
Having expressed my confusion, I think what you need to do is to use String manipulation to dynamically build the EQL expression and add it to the Query.
A code example of what you are doing would be extremely helpful as well.