I am getting less count than actual web ui that I download as csv.
There are around 35k entries but I am getting only 600 something.
Here is my code.
dimensions = ["sessionSource","customEvent:order_id","date","platform"]
metrics = ['sessions']
request = {
"requests": [
{
"dateRanges": [
{
"startDate": "2022-10-15",
"endDate": "2022-10-17"
}
],
"dimensions": [{'name': name} for name in dimensions],
"metrics": [{'name': name} for name in metrics],
"limit": 10,
"return_property_quota": True,
"keep_empty_rows": True,
"data_loss_from_other_row": False
}
]
}
analytics = build('analyticsdata', 'v1beta', credentials=credentials)
response = analytics.properties().batchRunReports(property=property_id,
body=request).execute()
report_data = defaultdict(list)
I see limit is set to 10 in your query. If this is set, the response will only contain 10 rows.
Related
I want to get/pull all the contacts with hs_leads_status = Open and i am using https://api.hubapi.com/contacts/v1/lists/all/contacts/all?count=100&property=phone&property=hs_lead_status&hs_lead_status=Open but it returns hs_leads_status = Closed as well.
How to pass the parameters correctly and achieve it?
This is not possible using the v1 API. You can however use the v3 API's search for this.
https://developers.hubspot.com/docs/api/crm/search
Using an filter group with EQ param should satisfy your usecase.
Finally get succeeded with:
POST - https://api.hubapi.com/crm/v3/objects/contacts/search?
Body - {
"properties": [
"firstname",
"lastname",
"phone",
"hs_lead_status"
],
"limit": 100,
"filterGroups": [
{
"filters": [
{
"propertyName": "hs_lead_status",
"operator": "EQ",
"value": "Open"
}
]
}
]
}
but the limitation is that it returns only 100 records with pagination.
This is a weird one.
I'm using datatables v1.10.19 with jQuery 3.3.1 and Bootstrap 3.3.7
My datatables grid is configured to display 1000 records (but you can change it to 2500, 5000 and "all").
I've only got about 60 records in my database.
It is using Server-Side processing to retrieve data.
When the grid loads, the pager displays 5 buttons plus an ellipses (as if there is even more).
And even weirder, if I change the drop-down to display "all" records, it acts as I would expect i.e. the pager has 1 page button.
The payloads are pretty much identical:
{
"data": {
"draw": 8,
"recordsTotal": 86,
"recordsFiltered": 66,
"data": [rows of data here]
},
"outcome": {
"opResult": "Success",
"message": ""
}
}
When you click on page 2, it does successfully retrieve a payload with 0 rows.
But there shouldn't be a page 2 available on the pager.
The config object for the datatable looks like this:
eventsSvr.buildConfig = function (url) {
return {
"processing": true,
"serverSide": true,
//"paging": true,
"ajax": {
url: url,
type: ajax.requestPOST,
dataSrc: 'data.data' // the path in the JSON structure to the array which will be the rows.
},
"order": [[1, "asc"]],
"lengthMenu": [[1000, 2500, 5000, -1], [1000, 2500, 5000, "All"]],
"initComplete": function (settings, json) {
eventsSvr.searchTextSpan.text('Search').removeClass('search-is-on');
},
"columns": eventsSvr.grid.columns,
"columnDefs": eventsSvr.grid.columnDefs,
dom: 'ltp'
};
I do have a bunch of custom searches on the page, so I've had to write a lot of code like this:
$.fn.dataTable.ext.search.push(
function (settings, data, dataIndex) {
var picker3 = $(eventsSvr.datePickerInputs[0]).data(icapp.kendoKey);
var picker4 = $(eventsSvr.datePickerInputs[1]).data(icapp.kendoKey);
var rowStartDate = moment(data[3], icapp.date.momentParseFormat).toDate();
var rowEndDate = moment(data[4], icapp.date.momentParseFormat).toDate();
... etc.
}
);
But the odd thing is the different behavior as between "All" records vs 1000 records.
As described above, select "All" records works (resulting in just 1 page button), but none of the other paging sizes work (i.e. 1000, 2500, 5000). The data for the 1 page does return, but I get 5 page buttons and an ellipses.
Any ideas why this would be happening?
When using server-side processing mode DataTables expects draw, recordsTotal and recordsFiltered to be root-level elements. Consider changing your repsonse to the following and you can remove dataSrc option.
{
"draw": 8,
"recordsTotal": 86,
"recordsFiltered": 66,
"data": [rows of data here],
"outcome": {
"opResult": "Success",
"message": ""
}
}
Alternatively you can manipulate the response before passing it to DataTables using function supplied as value for dataSrc option, but I would recommend keep things according to expected format for more readable code.
I am trying to do BPM and SoftLayer integration using Java REST client. On my initial analysis(as well as help form stack overflow),I found
Step 1) we to get getPriceItem list to have all IDs for next request.
https://username:api_key#api.softlayer.com/rest/v3/SoftLayer_Product_Package/2/getItemPrices?objectMask=mask[id,item[keyName,description],pricingLocationGroup[locations[id, name, longName]]]
and then do verify and place order POST call using respective APIs.
I am stucked on Step 1) as filtering here seems to be bit tricky. I am getting a json response of over 20000 lines.
I wanted to show similar data(just like SL Performance storage UI ) on my custom BPM UI . (One drop down to select type of storage, 2nd to show location, 3rd to show size and 4th would be IOPS) where user can select the items and place request.
Here I found, SL is something similar to this for populating the drop downs-
https://control.softlayer.com/sales/productpackage/getregions?_dc=1456386930027&categoryCode=performance_storage_iscsi&packageId=222&page=1&start=0&limit=25
Can't we have implementation where we can use control.softlayer.com just like SL instead of api.softlayer.com? In that case we can use similar logic to display data on UI.
Thanks
Anupam
Here, using the API, the steps for performance storage. For endure storage the steps are similar you just need to review the value for categoryCode and modify if it needed
you can get the locations using this method:
http://sldn.softlayer.com/reference/services/SoftLayer_Product_Package/getRegions
you just need to know the package of the storage e.g.
GET https://api.softlayer.com/rest/v3.1/SoftLayer_Product_Package/222/getRegions
then, you can get the storage size for that you can use the SoftLayer_Product_Package::getItems or SoftLayer_Product_Package::getItemPrices methods and a filter e.g.
GET https://api.softlayer.com/rest/v3.1/SoftLayer_Product_Package/222/getItemPrices?objectFilter={"itemPrices": {"categories": {"categoryCode": {"operation": "performance_storage_space"}},"locationGroupId": { "operation": "is null"}}}
Note: We are filtering the data to get the prices whose category code is "performance_storage_space" and we want the standard price locationGroupId = null
then, you can get the IOPS, you can use the same approach like above, but there is a dependency between the IOPS and storage space e.g.
GET https://api.softlayer.com/rest/v3.1/SoftLayer_Product_Package/222/getItemPrices?objectFilter={"itemPrices": { "attributes": { "value": { "operation": 20 } }, "categories": { "categoryCode": { "operation": "performance_storage_iops" } }, "locationGroupId": { "operation": "is null" } } }
Note: In the example we assume that selected storage space was "20", the prices for IOPS have an record called atributes, this record tell us the valid storage spaces of the IOPS, then we have other filters to get only the IOPS prices categoryCode = performance_storage_iops and we want only the standard prices locationGroupId=null
To selecting the storage type I do not think there is a method the only way I see is that you call the SoftLayer_Product_Package::getAllObjects method and filter the data to get the packages for endurance, performance and portable storage.
Just in case here an example using the Softlayer's Python client to order
"""
Order a block storage (performance ISCSI).
Important manual pages:
http://sldn.softlayer.com/reference/services/SoftLayer_Product_Order
http://sldn.softlayer.com/reference/services/SoftLayer_Product_Order/verifyOrder
http://sldn.softlayer.com/reference/services/SoftLayer_Product_Order/placeOrder
http://sldn.softlayer.com/reference/services/SoftLayer_Product_Package
http://sldn.softlayer.com/reference/services/SoftLayer_Product_Package/getItems
http://sldn.softlayer.com/reference/services/SoftLayer_Location
http://sldn.softlayer.com/reference/services/SoftLayer_Location/getDatacenters
http://sldn.softlayer.com/reference/services/SoftLayer_Network_Storage_Iscsi_OS_Type
http://sldn.softlayer.com/reference/services/SoftLayer_Network_Storage_Iscsi_OS_Type/getAllObjects
http://sldn.softlayer.com/reference/datatypes/SoftLayer_Location
http://sldn.softlayer.com/reference/datatypes/SoftLayer_Container_Product_Order_Network_Storage_Enterprise
http://sldn.softlayer.com/reference/datatypes/SoftLayer_Product_Item_Price
http://sldn.softlayer.com/blog/cmporter/Location-based-Pricing-and-You
http://sldn.softlayer.com/blog/bpotter/Going-Further-SoftLayer-API-Python-Client-Part-3
http://sldn.softlayer.com/article/Object-Filters
http://sldn.softlayer.com/article/Python
http://sldn.softlayer.com/article/Object-Masks
License: http://sldn.softlayer.com/article/License
Author: SoftLayer Technologies, Inc. <sldn#softlayer.com>
"""
import SoftLayer
import json
# Values "AMS01", "AMS03", "CHE01", "DAL05", "DAL06" "FRA02", "HKG02", "LON02", etc.
location = "AMS01"
# Values "20", "40", "80", "100", etc.
storageSize = "40"
# Values between "100" and "6000" by intervals of 100.
iops = "100"
# Values "Hyper-V", "Linux", "VMWare", "Windows 2008+", "Windows GPT", "Windows 2003", "Xen"
os = "Linux"
PACKAGE_ID = 222
client = SoftLayer.Client()
productOrderService = client['SoftLayer_Product_Order']
packageService = client['SoftLayer_Product_Package']
locationService = client['SoftLayer_Location']
osService = client['SoftLayer_Network_Storage_Iscsi_OS_Type']
objectFilterDatacenter = {"name": {"operation": location.lower()}}
objectFilterStorageNfs = {"items": {"categories": {"categoryCode": {"operation": "performance_storage_iscsi"}}}}
objectFilterOsType = {"name": {"operation": os}}
try:
# Getting the datacenter.
datacenter = locationService.getDatacenters(filter=objectFilterDatacenter)
# Getting the performance storage NFS prices.
itemsStorageNfs = packageService.getItems(id=PACKAGE_ID, filter=objectFilterStorageNfs)
# Getting the storage space prices
objectFilter = {
"itemPrices": {
"item": {
"capacity": {
"operation": storageSize
}
},
"categories": {
"categoryCode": {
"operation": "performance_storage_space"
}
},
"locationGroupId": {
"operation": "is null"
}
}
}
pricesStorageSpace = packageService.getItemPrices(id=PACKAGE_ID, filter=objectFilter)
# If the prices list is empty that means that the storage space value is invalid.
if len(pricesStorageSpace) == 0:
raise ValueError('The storage space value: ' + storageSize + ' GB, is not valid.')
# Getting the IOPS prices
objectFilter = {
"itemPrices": {
"item": {
"capacity": {
"operation": iops
}
},
"attributes": {
"value": {
"operation": storageSize
}
},
"categories": {
"categoryCode": {
"operation": "performance_storage_iops"
}
},
"locationGroupId": {
"operation": "is null"
}
}
}
pricesIops = packageService.getItemPrices(id=PACKAGE_ID, filter=objectFilter)
# If the prices list is empty that means that the IOPS value is invalid for the configured storage space.
if len(pricesIops) == 0:
raise ValueError('The IOPS value: ' + iops + ', is not valid for the storage space: ' + storageSize + ' GB.')
# Getting the OS.
os = osService.getAllObjects(filter=objectFilterOsType)
# Building the order template.
orderData = {
"complexType": "SoftLayer_Container_Product_Order_Network_PerformanceStorage_Iscsi",
"packageId": PACKAGE_ID,
"location": datacenter[0]['id'],
"quantity": 1,
"prices": [
{
"id": itemsStorageNfs[0]['prices'][0]['id']
},
{
"id": pricesStorageSpace[0]['id']
},
{
"id": pricesIops[0]['id']
}
],
"osFormatType": os[0]
}
# verifyOrder() will check your order for errors. Replace this with a call to
# placeOrder() when you're ready to order. Both calls return a receipt object
# that you can use for your records.
response = productOrderService.verifyOrder(orderData)
print(json.dumps(response, sort_keys=True, indent=2, separators=(',', ': ')))
except SoftLayer.SoftLayerAPIError as e:
print("Unable to place the order. faultCode=%s, faultString=%s" % (e.faultCode, e.faultString))
I am new to ravendb and trying it out to see if it can do the job for the company i work for .
i updated a data of 10K records to the server .
each data looks like this :
{
"ModelID": 371300,
"Name": "6310I",
"Image": "0/7/4/9/28599470c",
"MinPrice": 200.0,
"MaxPrice": 400.0,
"StoreAmounts": 4,
"AuctionAmounts": 0,
"Popolarity": 16,
"ViewScore": 0.0,
"ReviewAmount": 4,
"ReviewScore": 40,
"Cat": "E-Cellphone",
"CatID": 1100,
"IsModel": true,
"ParamsList": [
{
"ModelID": 371300,
"Pid": 188396,
"IntVal": 188402,
"Param": "Nokia",
"Name": "Manufacturer",
"Unit": "",
"UnitDir": "left",
"PrOrder": 0,
"IsModelPage": true
},
{
"ModelID": 371305,
"Pid": 398331,
"IntVal": 1559552,
"Param": "1.6",
"Name": "Screen size",
"Unit": "inch",
"UnitDir": "left",
"PrOrder": 1,
"IsModelPage": false
},.....
where ParamsList is an array of all the attributes of a single product.
after building an index of :
from doc in docs.FastModels
from docParamsListItem in ((IEnumerable<dynamic>)doc.ParamsList).DefaultIfEmpty()
select new { Param = docParamsListItem.IntVal, Cat = doc.Cat }
and a facet of
var facetSetupDoc = new FacetSetup
{
Id = "facets/Params2Facets",
Facets = new List<Facet> { new Facet { Name = "Param" } }
};
and search like this
var facetResults = session.Query<FastModel>("ParamNewIndex")
.Where(x => x.Cat == "e-cellphone")
.ToFacets("facets/Params2Facets");
it takes more than a second to query and that is on only 10K of data . where our company has more than 1M products in DB.
am i doing something wrong ?
In order to generate facets, you have to check for each & every individual value of docParamsListItem.IntVal. If you have a lot of them, that can take some time.
In general, you shouldn't have a lot of facets, since that make no sense, it doesn't help the user.
For integers, you usually use ranges, instead of the actual values.
For example, price within a certain range.
You use just the field for things like manufacturer, or the MegaPixels count, where you have lot number or items (about a dozen or two)
You didn't mention which build you are using, but we made some major improvements there recently.
As a total newbie I have been trying to get the geoNear command working in my rails application and it appear to be working fine. The major annoyance for me is that it is returning an array with strings rather than keys which I can call on to pull out data.
Having dug around, I understand that MongoMapper uses Plucky to turn the the query resultant into a friendly object which can be handled easily but I haven't been able to find out how to transform the result of my geoNear query into a plucky object.
My questions are:
(a) Is it possible to turn this into a plucky object and how do i do that?
(b) If it is not possible how can I most simply and systematically extract each record and each field?
here is the query in my controller
#mult = 3963 * (3.14159265 / 180 ) # Scale to miles on earth
#results = #db.command( {'geoNear' => "places", 'near'=> #search.coordinates , 'distanceMultiplier' => #mult, 'spherical' => true})
Here is the object i'm getting back (with document content removed for simplicity)
{"ns"=>"myapp-development.places", "near"=>"1001110101110101100100110001100010100010000010111010", "results"=>[{"dis"=>0.04356444023196527, "obj"=>{"_id"=>BSON::ObjectId('4ee6a7d210a81f05fe000001'),...}}], "stats"=>{"time"=>0, "btreelocs"=>0, "nscanned"=>1, "objectsLoaded"=>1, "avgDistance"=>0.04356444023196527, "maxDistance"=>0.0006301239824196907}, "ok"=>1.0}
Help is much appreciated!!
Ok so lets say you store the results into a variable called places_near:
places_near = t.command( {'geoNear' => "places", 'near'=> [50,50] , 'distanceMultiplier' => 1, 'spherical' => true})
This command returns an hash that has a key (results) which maps to a list of results for the query. The returned document looks like this:
{
"ns": "test.places",
"near": "1100110000001111110000001111110000001111110000001111",
"results": [
{
"dis": 69.29646421910687,
"obj": {
"_id": ObjectId("4b8bd6b93b83c574d8760280"),
"y": [
1,
1
],
"category": "Coffee"
}
},
{
"dis": 69.29646421910687,
"obj": {
"_id": ObjectId("4b8bd6b03b83c574d876027f"),
"y": [
1,
1
]
}
}
],
"stats": {
"time": 0,
"btreelocs": 1,
"btreelocs": 1,
"nscanned": 2,
"nscanned": 2,
"objectsLoaded": 2,
"objectsLoaded": 2,
"avgDistance": 69.29646421910687
},
"ok": 1
}
To iterate over the responses just iterate as you would over any list in ruby:
places_near['results'].each do |result|
# do stuff with result object
end