Following the doc at Adding custom page fields, im trying to add Todo's to a Task object/page model for them to be queryable via the api (same thing for todos, make parent Task queryable), however, the related field always returns an empty array (I would have expected the related (parent or child) Pages to be in the response:
class Task(Page):
CHOICES = [(i, i) for i in range(11)]
sub_order = models.IntegerField(default=1, choices=CHOICES)
content_panels = Page.content_panels + [
...
]
api_fields = [
APIField('title'),
APIField('todos'),
]
class Todo(Page):
CHOICES = [(i, i) for i in range(1, 11)]
sub_order = models.IntegerField(default=1, choices=CHOICES)
parent_page_types = ['app.Task']
page = models.ForeignKey('app.Task', on_delete=models.SET_NULL, null=True, blank=True, related_name='todos')
content_panels = Page.content_panels + [
...
]
api_fields = [
APIField('parent_page_types'),
APIField('sub_order'),
]
endpoint: .../api/v2/pages/?format=json&type=app.Task&fields=*
Response:
{
"meta": {
"total_count": 1
},
"items": [
{
"id": 18,
"meta": {
"type": "app.Task",
"detail_url": ".../api/v2/pages/18/",
"html_url": "theURL",
"slug": "aasdasdsad",
"show_in_menus": false,
"seo_title": "",
"search_description": "",
"first_published_at": "2019-02-05T14:13:09.596817Z"
},
"title": "aasdasdsad",
"parent_page_types": [
"app.ParentPageType"
],
"sub_order": 1,
"todos": [] <-------- EMPTY ?
}
]
}
UPDATE:
the sqlite db doesn't seem to be creating/adding the todos or tasks in the table when I create the records =/ . The field is showing up as null, still troubleshooting
Related
I am in no way an expert with groovy so please don't hold that against me.
I have JSON that looks like this:
{
"metrics": [
{
"name": "metric_a",
"help": "This tracks your A stuff.",
"type": "GAUGE",
"labels": [
"pool"
],
"unit": "",
"aggregates": [],
"meta": [
{
"category": "CAT A",
"deployment": "environment-a"
}
],
"additional_notes": "Some stuff (potentially)"
},
...
]
...
}
I'm using it as a source for automated documentation of all the metrics. So, I'm iterating through it in various ways to get the information I need. So far so good, I'm most of the way there. The problem is this all needs to be organized per the deployment environment. Meaning, multiple metrics will share the same value for deployment.
My thought was I could create a map with deployment as the key and the metric name for any metric that has a matching deployment as the value. Once I have that map, it should be easy for me to organize things the way they should be. I can't figure out how to do that. The result is all the metric names are added which is expected since I'm not doing anything to filter them out. I was thinking that groupBy would make sense here but I can't figure out how to use it effectively and frankly I'm not sure it will solve my problem by itself. Here is my code so far:
parentChild = [:]
children = []
metrics.each { metric ->
def metricName = metric.name
def depName = metric.meta.findResult{ it.deployment }
children.add(metricName)
parentChild.put(depName, children)
}
What is the best way to create a new map where the values for each key are based off a specific condition?
EDIT: The desired result would be each key in the resulting map would be a unique deployment value from all the metrics (as a string). Each value would be name of each metric that contains that deployment (as an array).
[environment-a:
[metric_a,metric_b,metric_c,...],
environment-b:
[metric_d,metric_e,metric_f,...]
...]
I would use a combo of withDefault() to pre-fill each map-entry value with a fresh TreeSet-instance (sorted no-duplicates set) and standard inject().
I reduced your sample data to the bare minimum and added some new nodes:
import groovy.json.*
String input = '''\
{
"metrics": [
{
"name": "metric_a",
"meta": [
{
"deployment": "environment-a"
}
]
},
{
"name": "metric_b",
"meta": [
{
"deployment": "environment-a"
}
]
},
{
"name": "metric_c",
"meta": [
{
"deployment": "environment-a"
},
{
"deployment": "environment-b"
}
]
},
{
"name": "metric_d",
"meta": [
{
"deployment": "environment-b"
}
]
}
]
}'''
def json = new JsonSlurper().parseText input
def groupedByDeployment = json.metrics.inject( [:].withDefault{ new TreeSet() } ){ res, metric ->
metric.meta.each{ res[ it.deployment ] << metric.name }
res
}
assert groupedByDeployment.toString() == '[environment-a:[metric_a, metric_b, metric_c], environment-b:[metric_c, metric_d]]'
If your metrics.meta array is supposed to have a single value, you can simplify the code by replacing the line:
metric.meta.each{ res[ it.deployment ] << metric.name }
with
res[ metric.meta.first().deployment ] << metric.name
I wrote an Elastic query which will check the condition (status="APPROVED") and Gets all approved_by objects.
This is my index (portfolio):
{
"settings": {},
"mappings": {
"portfolio": {
"properties": {
"status": {
"type": "keyword",
"normalizer": "lcase_ascii_normalizer"
},
"archived_at": {
"type": "date"
},
"approved_by": {
"id": "text",
"name":"text"
}
}
}
}
}
Currently I have 60 objects whose status are approved , so when i run the query it will show 60 objects,but in my case i am getting only one object(I debugged the code, total 60 objects are coming as expected, but still returning only single object), please help guys.
My query:
profiles = client.search(index='portfolio', doc_type='portfolio',
scroll='10m', size=1000,
body={
"query": {"match": {"status": "APPROVED"}}
})
sid = profiles['_scroll_id']
scroll_size = len(profiles['hits']['hits'])
while scroll_size > 0:
for info in profiles['hits']['hits']:
item = info['_source']
approved_by_obj = item.get('approved_by')
if approved_by_obj:
return (jsonify({"approved_by": approved_by_obj}))
Expected o/p format:
{
"approved_by": {
"id": "system",
"name": "system"
}
}
You're getting only one result because you're returning from your loop, effectively breaking out of it completely.
So, instead of returning from it, append the found approved_by_object to a list of your choice and then return that 60-member list:
profiles = client.search(index='portfolio', doc_type='portfolio',
scroll='10m', size=1000,
body={
"query": {"match": {"status": "APPROVED"}}
})
sid = profiles['_scroll_id']
scroll_size = len(profiles['hits']['hits'])
approved_hits_sources = [] # <-- add this
while scroll_size > 0:
for info in profiles['hits']['hits']:
item = info['_source']
approved_by_obj = item.get('approved_by')
if approved_by_obj:
approved_hits_sources.append({"approved_by": approved_by_obj}) # <--- append and not return
return jsonify({"approved_hits_sources": approved_hits_sources})
I have the following structure of JSON/Dict.
[
{
"childrens": [
{
"childrens": [
{
"name": "somenam1"
}
],
"name": "B999"
}
],
"name": "11111"
},
{
"childrens": [
{
"childrens": [
{
"name": "somename2"
},
{
"name": "somename3"
}
],
"name": "B5555"
},
{
"childrens": [
{
"name": "somename4"
}
],
"name": "B2222"
}
],
"name": "2222"
}
]
I want to iterate over all dictionaries and list inside root list and create single string for each dictionary inside root list.
Output will look like this (two lines):
1111|B999|somename1
2222|B5555|somename2|somename3|B2222|somename4
Also this is just an example i can have N nested childrens.
Looks like a good candidate for recursion:
def flatten(child):
if not child:
return child
return [child['name']] + [name for c in child.get('childrens', []) for name in flatten(c)]
In []:
for child in data:
print('|'.join(flatten(child)))
Out[]:
11111|B999|somenam1
2222|B5555|somename2|somename3|B2222|somename4
Sure you can just pass add a level arg and return that:
def flatten(child, level=0):
if not child:
return child
return [level] + [l for c in child.get('childrens', []) for l in flatten(c, level+1)]
In []:
for child in data:
print('|'.join(str(level) for level in flatten(child)))
Out[]:
0|1|2
0|1|2|2|1|2
Here's a solution by recursion
data_json = '[{"childrens":[{"childrens":[{"name":"somenam1"}],"name":"B999"}],"name":"11111"},{"childrens":[{"childrens":[{"name":"somename2"},{"name":"somename3"}],"name":"B5555"},{"childrens":[{"name":"somename4"}],"name":"B2222"}],"name":"2222"}]'
data = json.loads(data_json)
def get_names(data_dict):
if ("childrens" in data_dict):
ret_dict = "|".join(map(get_names, data_dict["childrens"]))
return data_dict["name"] + "|" + ret_dict
else:
return data_dict["name"]
def get_all_name(data):
for i in data:
print(get_names(i))
get_all_name(data)
[updated 17:15 on 28/09]
I'm manipulating json data of type:
[
{
"id": 1,
"title": "Sun",
"seeAlso": [
{
"id": 2,
"title": "Rain"
},
{
"id": 3,
"title": "Cloud"
}
]
},
{
"id": 2,
"title": "Rain",
"seeAlso": [
{
"id": 3,
"title": "Cloud"
}
]
},
{
"id": 3,
"title": "Cloud",
"seeAlso": [
{
"id": 1,
"title": "Sun"
}
]
},
];
After inclusion in the database, a node.js search using
db.documents.query(
q.where(
q.collection('test films'),
q.value('title','Sun')
).withOptions({categories: 'none'})
)
.result( function(results) {
console.log(JSON.stringify(results, null,2));
});
will return both the film titled 'Sun' and the films which have a seeAlso/title property (forgive the xpath syntax) = 'Sun'.
I need to find 1/ films with title = 'Sun' 2/ films with seeAlso/title = 'Sun'.
I tried a container query using q.scope() with no success; I don't find how to scope the root object node (first case) and for the second case,
q.where(q.scope(q.property('seeAlso'), q.value('title','Sun')))
returns as first result an item which matches all text inside the root object node
{
"index": 1,
"uri": "/1.json",
"path": "fn:doc(\"/1.json\")",
"score": 137216,
"confidence": 0.6202662,
"fitness": 0.6701325,
"href": "/v1/documents?uri=%2F1.json&database=Documents",
"mimetype": "application/json",
"format": "json",
"matches": [
{
"path": "fn:doc(\"/1.json\")/object-node()",
"match-text": [
"Sun Rain Cloud"
]
}
]
},
which seems crazy.
Any idea about how doing such searches on denormalized json data?
Laurent:
XPaths on JSON are supported by MarkLogic.
In particular, you might consider setting up a path range index to match /title at the root:
http://docs.marklogic.com/guide/admin/range_index#id_54948
Scoped property matching required either filtering or indexed positions to be accurate. An alternative is to set up another path range index on /seeAlso/title
For the match issue it would be useful to know the MarkLogic version and to see the entire query.
Hoping that helps,
I'm attempting a fairly basic task in arangodb, using the SUM() aggregate function.
Here is a working query which returns the right data (though not yet aggregated):
FOR m IN pkg_spp_RegMem
FILTER m.memberId == "40289"
COLLECT member = m.memberId INTO g
RETURN { "memberId" : member, "amount" : g[*].m[*].items }
This returns the following results:
[
{
"memberId": "40289",
"amount": [
[
{
"amount": 50,
"description": "some description"
}
],
[
{
"amount": 50,
"description": "some description"
},
{
"amount": 500,
"description": "some description"
},
{
"amount": 0,
"description": "some description"
}
],
[
{
"amount": 0,
"description": "some description"
},
]
]
}
]
I am using Collect to group the results because a given memberId may have multiple'RegMem' objects. As you can see from the query/results, each object has a list of smaller objects called 'items', with each item having an amount and a description.
I want to SUM() the amounts by member. However, adjusting the query like this does not work:
FOR m IN pkg_spp_RegMem
FILTER m.memberId == "40289"
COLLECT member = m.memberId INTO g
RETURN { "memberId" : member, "amount" : SUM(g[*].m[*].items[*].amount) }
It returns 0 because it apparently can't find a field in the expanded items list called amount.
Looking at the results I can sort of understand why: the results are being returned such that items is actually a list, of lists of objects with amount/description. But I don't understand how to reference or expand the un-named list correctly to return the amount field values for the SUM() function.
Ideally the query should return the memberId and total amount, one row per member such that I can remove the filter and execute for all members.
Many thanks in advance if you can help!
Martin
PS I've worked through the AQL tutorial on the arangodb website and checked out the manual but what would really help me is loads more example queries to look through. If anyone knows of a resource like that or wants to share some of their own, 'much obliged. Cheers!
Edited: Misread the question the first time. The first one can be seen in theedit history, as it also contains some hints:
I replicated your data by creating some documents in this format (and some with only one item):
{
"memberId": "40289",
"items": [
{
"amount": 50,
"description": "some description"
},
{
"amount": 500,
"description": "some description"
}
]
}
Based on some of those types of documents, your non-summarized query should indeed be looking like this:
FOR m IN pkg_spp_RegMem
FILTER m.memberId == "40289"
COLLECT member = m.memberId INTO g
RETURN { "memberId" : member, "amount" : g[*].m[*].items }
The data returned:
[
{
"memberId": "40289",
"amount": [
[
{
"amount": 50,
"description": "some description"
},
{
"amount": 0,
"description": "some description"
}
],
[
{
"amount": 50,
"description": "some description"
},
{
"amount": 0,
"description": "some description"
}
],
[
{
"amount": 50,
"description": "some description"
}
],
[
{
"amount": 50,
"description": "some description"
},
{
"amount": 500,
"description": "some description"
}
],
[
{
"amount": 0,
"description": "some description"
}
],
[
{
"amount": 50,
"description": "some description"
},
{
"amount": 500,
"description": "some description"
}
]
]
}
]
Based on the non summarized version, you need to loop through the items of the groups that have been generated by the collect function and do your SUM() there.
In order to be able to SUM the items you must FLATTEN() them into a single list, before summarizing them.
FOR m IN pkg_spp_RegMem
FILTER m.memberId == "40289"
COLLECT member = m.memberId INTO g
RETURN { "memberId" : member, "amount" : SUM(
FLATTEN(
(
FOR r in g[*].m[*].items
RETURN r[*].amount
)
)
)
}
This results in:
[
{
"memberId": "40289",
"amount": 1250
}
]