I am working to calculate the difference between two times in ionic.
I am using AngularFire and my tree looks like this:
{
"users": {
"name": {
"17": {
"10": {
"2017": {
"-Kwfm1k9_A74PzlmijUJ": {
"date": "17/10/2017",
"hora": "17:20:58",
"status": "In"
},
"-Kwfm8wEJ8Oob4YFvNNu": {
"date": "17/10/2017",
"hora": "17:21:27",
"status": "Out"
},
"-KwfoKkPJMt2g8AQNmxq": {
"date": "17/10/2017",
"hora": "17:31:00",
"status": "In"
},
"-Kwfp0BOAGnM-2_MfziP": {
"date": "17/10/2017",
"hora": "17:33:58",
"status": "Out"
},
"-KwfqW5XKpUNedda4rZz": {
"date": "17/10/2017",
"hora": "17:40:31",
"status": "In"
},
"-Kwg0pQDlI3FMV3BPNaa": {
"date": "17/10/2017",
"hora": "18:29:58",
"status": "Out"
}
}
}
}
}
}
}
I would like to get a difference between the first and second, third and fourth, fifth and sixth, remembering that they are related by the tag "Status".
First In - Out = difference
Second In - Out = difference
Third In - Out = difference
Always doing the difference between the In's and Out's.
In's are for when a person come in the room. Out's are for when a person come out of the room. I want to record the time a person spend inside of a room.
So the results would be:
"17:20:58" - "17:21:27" = 00:01:29
"17:31:00" - "17:33:58" = 00:02:58
"17:40:31" - "18:29:58" = 00:49:27
Do you have any tip on refactoring this code so it works fine?
Remembering I'm using Ionic 3 with AngularFire4
Appreciate the help.
To achieve your goal I recommend you to restructure your data. For now, there is no real relation between the IN's and OUT's.
A possible approach would be to create some node which wraps the checkIn and the checkOut. Let's call it session. Each time a user checks in a new session get's created and each time a user checks out a session get's closed.
Your structure could look similar to this:
"sessions": {
"uid": { // or name or whatever
"17-10-2017": { // not sure if you need the date in the structure, but if you need it make a single node like this
"-Kwfm1k9_A74PzlmijUJ": { // this is a session create it on each check in
"checkin": 1508354574, // timestamp
"checkout": 1508354584
},
}
}
}
Here's a code example (just to give you an idea how it could look like):
var ref = firebase.database().ref("sessions/uid"); // uid must be dynamic
// checkin
ref.push({
checkin: firebase.database.ServerValue.TIMESTAMP // make sure to use the servers timestamp
}); // creates a new session with a pushkey as id
// checkout
ref.child('sessionId').update({
checkout: firebase.database.ServerValue.TIMESTAMP
});
// stats
ref.child('sessionId').once('value', function(snap) {
var session = snap.val();
var difference = session.checkout - session.checkin;
// now you have the difference in milliseconds or seconds depending on your timestamp format. this can be formatted whatever unit you want e.g. minutes, hours...
});
Hope this gives you an idea, how it could be done.
Related
I'm having trouble validating a schema in Postman using tv4 inside the tests tab - it is always returning a true test, no matter what I feed it. I am at a complete loss and could really use a hand - here is my example JSON Response, and my tests:
I've tried a ton of variations from every Stack Overflow/tutorial I could find and nothing will work - it always returns true.
//Test Example
var jsonData = JSON.parse(responseBody);
const schema = {
"required" : ["categories"],
"properties": {
"categories": {
"required" : ["aStringOne", "aStringTwo", "aStringThree" ],
"type": "array",
"properties" : {
"aStringOne": {"type": "string" },
"aStringTwo": {"type": "null" },
"aStringThree": {"type": "boolean" }
}
}
}
};
pm.test('Schema is present and accurate', () => {
var result=tv4.validateMultiple(jsonData, schema);
console.log(result);
pm.expect(result.valid).to.be.true;
});
//Response Example
{
"categories": [
{
"aStringOne": "31000",
"aStringTwo": "Yarp",
"aStringThree": "More Yarp Indeed"
}
]
}
This should return false, as all three properties are strings but its passing. I'm willing to use a different validator or another technique as long as I can export it as a postman collection to use with newman in my CI/CD process. I look forward to any help you can give.
I would suggest moving away from using tv4 in Postman, the project isn't actively supported and Postman now includes a better (in my opinion), more actively maintained option called Ajv.
The syntax is slightly different but hopefully, this gives you an idea of how it could work for you.
I've mocked out your data and just added everything into the Tests tab - If you change the jsonData variable to pm.response.json() it will run against the actual response body.
var jsonData = {
"categories": [
{
"aStringOne": "31000",
"aStringTwo": "Yarp",
"aStringThree": "More Yarp Indeed"
}
]
}
var Ajv = require('ajv'),
ajv = new Ajv({logger: console, allErrors: true}),
schema = {
"type": "object",
"required": [ "categories"],
"properties": {
"categories": {
"type": "array",
"items": {
"type": "object",
"required": [ "aStringOne", "aStringTwo", "aStringThree" ],
"properties": {
"aStringOne": { "type": "string" },
"aStringTwo": { "type": "integer"},
"aStringThree": { "type": "boolean"},
}
}
}
}
}
pm.test('Schema is valid', function() {
pm.expect(ajv.validate(schema, jsonData), JSON.stringify(ajv.errors)).to.be.true
});
This is an example of it failing, I've included the allErrors flag so that it will return all the errors rather than just the first one it sees. In the pm.expect() method, I've added JSON.stringify(ajv.errors) so you can see the error in the Test Result tab. It's a little bit messy and could be tidied up but all the error information is there.
Setting the properties to string show the validation passing:
If one of the required Keys is not there, it will also error for this too:
Working with schemas is quite difficult and it's not easy to both create them (nested arrays and objects are tricky) and ensure they are doing what you want to do.
There are occasions where I thought something should fail and it passed the validation test. It just takes a bit of learning/practising and once you understand the schema structures, they can become extremely useful.
I have a database containing a structure similar to the one shown below. Since I am not allowed to make it public I am using the following keys:
i = {0,1,2,3....}
All a(i) represent single key/value pairings e.g. userName: "awesome"
With the below structure, every time a User wants to create new Stuff these are the steps I currently take
Store images to FIRStorage and retrieve their respective downloadURL
Then I add the Stuff to FIRDatabase. At this point I add all of the info related to a(i) because they're all under a single child; Stuff.UUID, hence I send one huge dictionary consisting of the data.
The issue arises in adding data to the mini-dictionaries. Because they are in different paths, I have to individually make requests to all of them as shown below
I then add location info
Followed by the respective child of timeStamp
The images information is next to be updated
Subscribe the User to respective Stuff.UUID
Lastly add the User.UUID to the members portion of Stuff
Is it possible to reduce steps 3-7?
As a follow up, is it possible to add values into different paths with one call?
PS: Link to what the code of the above demo might look like. Due to confidentiality stuff I am not allowed to post the actual code.
{
"Users":
{
"JglJnGDXcqLq6m844pZ":
{
a(0),
a(1),
a(2),
a(3),
a(4),
a(5),
"Stuff":
{
"fcWpzduhpPn8XR6Zqca": true,
"gfntTr6TkDwZ439jkW8": true
}
}
},
"Stuff":
{
"fcWpzduhpPn8XR6Zqca":
{
a(0),
a(1),
a(2),
a(3),
a(4),
a(5),
a(6),
a(7),
"location":
{
"latitude":"-17.41439",
"longitude":"-5.85170"
},
"timestamp":
{
"created":
{
a(0),
a(1),
a(2),
a(3),
a(4),
a(5),
},
"lastModified":
{
a(0),
a(1),
a(2),
a(3),
a(4),
a(5),
}
},
"images":
{
"B4FaR6wfJAeXqJ29T33":
{
"imageURL": "https://google.com"
}
},
"members":
{
"JglJnGDXcqLq6m844pZ": true,
"DpHAfrqL4eqbR8QNgHg": true
}
}
}
}
I've seen the firefeed example, but unfortunately it's a little lacking in functionality and I'm not sure how to move forward.
Given a data structure of users and posts:
{
"posts":
"12": {
"uid": 14,
"message": "This is my message #16 #55"
"timestamp": 1459361875666
"mentions": {
0: 16,
1: 55
}
}
"13": {
"uid": 55,
"message": "This is another message"
"timestamp": 1469861245622,
"mentions": null
}
}
"users": {
"14": {
"following": {
1: 16,
2: 55
}
}
"16": {
"following": {
0: 55
}
}
"55": {
"following": {
0: 14
}
}
}
}
How would I construct the query to bring back all the posts for users I'm following, as well as the posts I'm mentioned in? I can't find any recent documentation on advanced queries...
For example, if I am user 16, I should see all posts by user 55 (a user I am following) PLUS the post (id 12) by user 14 since they mentioned me in descending timestamp order.
Should I rethink the way the data is structured for performance purposes?
Any help would be greatly appreciated.
EDIT: restructured IDs to be unique
all the posts for users I'm following
// Reference
var ref = firebase.database().ref("users").child("some-user").child("following");
// Data call
ref.once("value).then(function(snapshot) {
// Iterate each following
snapshot.forEach(function(childSnapshot) {
// value
var childData = childSnapshot.val();
var followRef = firebase.database().ref("posts").orderByChild("uid").equalTo(i);
followRef.once("value").then(function(grandChildSnapshot) {
// RETURN OF ALL POSTS
}
});
});
Objects must have unique keys inside so for your data structure make sure they're not all called post, I recommend using push() and they would all get unique ids.
posts I'm mentioned in?
"users": {
"user": {
"id": 14,
"following": {
1: 16,
2: 55
},
mentioned: {
some-post: the-user,
...
}
}
...
You can keep your data structure the way it is, but also add to each follower the posts he is mentioned in.
// When post is pushed, get all users mentioned
...
var ref = firebase.database().ref("users").child(some-mentioned-user).child("mentioned");
ref.update({ <some-post> : <user-who-posted> });
After
var mentionedRef = firebase.database().ref("users").child(some-mentioned-user).child("mentioned");
mentionedRef.once("value").then(function(snapshot) {
// Iterate each following
snapshot.forEach(function(childSnapshot) {
// key
var childKey = childSnapshot.key();
var postRef = firebase.database().ref("posts").child(childKey);
postRef.once("value").then(function(grandChildSnapshot) {
// RETURN OF ALL POSTS
})
});
});
Comment with any questions.
I'm writing Alexa skills and want to write a skill to store the speaker's words.
For example, if I say, 'Alexa, save {whatever I say}', it should save the words in some string.
Now from what I understand, the intent schema something should be like
{
intents:[
"intent" : "SaveIntent"
]
}
and utterances like
SaveIntent save
SaveIntent store
In this case, how do I store '{whatever I say}'?
To capture free-form speech input (rather than a defined list of possible values), you'll need to use the AMAZON.LITERAL slot type. The Amazon documentation for the Literal slot type describes a use case similar to yours, where a skill is created to take any phrase and post it to a Social Media site. This is done by creating a StatusUpdate intent:
{
"intents": [
{
"intent": "StatusUpdate",
"slots": [
{
"name": "UpdateText",
"type": "AMAZON.LITERAL"
}
]
}
]
}
Since it uses the AMAZON.LITERAL slot type, this intent will be able to capture any arbitrary phrase. However, to ensure that the speech engine will do a decent job of capturing real-world phrases, you need to provide a variety of example utterances that resemble the sorts of things you expect the user to say.
Given that in your described scenario, you're trying to capture very dynamic phrases, there's a couple things in the documentation you'll want to give extra consideration to:
If you are using the AMAZON.LITERAL type to collect free-form text
with wide variations in the number of words that might be in the slot,
note the following:
Covering this full range (minimum, maximum, and all in between) will
require a very large set of samples. Try to provide several hundred
samples or more to address all the variations in slot value words as
noted above.
Keep the phrases within slots short enough that users can
say the entire phrase without needing to pause.
Lengthy spoken input can lead to lower accuracy experiences, so avoid
designing a spoken language interface that requires more than a few
words for a slot value. A phrase that a user cannot speak without
pausing is too long for a slot value.
That said, here's the example Sample Utterances from the documentation, again:
StatusUpdate post the update {arrived|UpdateText}
StatusUpdate post the update {dinner time|UpdateText}
StatusUpdate post the update {out at lunch|UpdateText}
...(more samples showing phrases with 4-10 words)
StatusUpdate post the update {going to stop by the grocery store this evening|UpdateText}
If you provide enough examples of different lengths to give an accurate picture of the range of expected user utterances, then your intent will be able to accurately capture dynamic phrases in real uses cases, which you can access in the UpdateText slot. Based on this, you should be able to implement an intent specific to your needs.
Important: AMAZON.LITERAL is deprecated as of October 22, 2018. Older skills built with AMAZON.LITERAL do continue to work, but you must migrate away from AMAZON.LITERAL when you update those older skills, and for all new skills.
Instead of using AMAZON.LITERAL, you can use a custom slot to trick alexa into passing the free flow text into the backend.
You can use this configuration to do it:
{
"interactionModel": {
"languageModel": {
"invocationName": "siri",
"intents": [
{
"name": "SaveIntent",
"slots": [
{
"name": "text",
"type": "catchAll"
}
],
"samples": [
"{text}"
]
}
],
"types": [
{
"name": "catchAll",
"values": [
{
"name": {
"value": "allonymous isoelectrically salubrity apositia phantomize Sangraal externomedian phylloidal"
}
},
{
"name": {
"value": "imbreviate Bertie arithmetical undramatically braccianite eightling imagerially leadoff"
}
},
{
"name": {
"value": "mistakenness preinspire tourbillion caraguata chloremia unsupportedness squatarole licitation"
}
},
{
"name": {
"value": "Cimbric sigillarid deconsecrate acceptableness balsamine anostosis disjunctively chafflike"
}
},
{
"name": {
"value": "earsplitting mesoblastema outglow predeclare theriomorphism prereligious unarousing"
}
},
{
"name": {
"value": "ravinement pentameter proboscidate unexigent ringbone unnormal Entomophila perfectibilism"
}
},
{
"name": {
"value": "defyingly amoralist toadship psoatic boyology unpartizan merlin nonskid"
}
},
{
"name": {
"value": "broadax lifeboat progenitive betel ashkoko cleronomy unpresaging pneumonectomy"
}
},
{
"name": {
"value": "overharshness filtrability visual predonate colisepsis unoccurring turbanlike flyboy"
}
},
{
"name": {
"value": "kilp Callicarpa unforsaken undergarment maxim cosenator archmugwump fitted"
}
},
{
"name": {
"value": "ungutted pontificially Oudenodon fossiled chess Unitarian bicone justice"
}
},
{
"name": {
"value": "compartmentalize prenotice achromat suitability molt stethograph Ricciaceae ultrafidianism"
}
},
{
"name": {
"value": "slotter archae contrastimulant sopper Serranus remarry pterygial atactic"
}
},
{
"name": {
"value": "superstrata shucking Umbrian hepatophlebotomy undreaded introspect doxographer tractility"
}
},
{
"name": {
"value": "obstructionist undethroned unlockable Lincolniana haggaday vindicatively tithebook"
}
},
{
"name": {
"value": "unsole relatively Atrebates Paramecium vestryish stockfish subpreceptor"
}
},
{
"name": {
"value": "babied vagueness elabrate graphophonic kalidium oligocholia floccus strang"
}
},
{
"name": {
"value": "undersight monotriglyphic uneffete trachycarpous albeit pardonableness Wade"
}
},
{
"name": {
"value": "minacious peroratory filibeg Kabirpanthi cyphella cattalo chaffy savanilla"
}
},
{
"name": {
"value": "Polyborinae Shakerlike checkerwork pentadecylic shopgirl herbary disanagrammatize shoad"
}
}
]
}
]
}
}
}
You can try using the slot type AMAZON.SearchQuery. So you intent would be something like this
{
"intents": [
{
"intent": "SaveIntent",
"slots": [
{
"name": "UpdateText",
"type": "AMAZON.SearchQuery"
}
]
}
]
}
as of end of 2018 I am using SearchQuery to get whatever the user says.
It does work, and I have it on production systems.
But you have to ask the user something and fill the slot.
For example:
Define a slot type of SearchQuery named query (choose whatever name you want)
Add sample utterances in the slot prompts like I want to watch {query} or {query} or I want {query}
Make a question to the user for slot filling
const message = 'What movie do you want to watch?'
handlerInput
.responseBuilder
.speak(message)
.reprompt(message)
.addElicitSlotDirective('query')
.getResponse();
Updated: This answer isn't true. mentioned in the comments there is the Amazon.Literal Slot type that should allow this.
Alexa doesn't currently support access to the users raw speech input. It may be possible in the future, or you can look at some other voice to text API's such as Google's.
The only way to do this currently with Alexa would be to have a set list of words that the user could say that it would save.
To do that you can follow one of Amazon's examples of using a custom slot type. Then put all of the possible words that the user would say into that category.
(8/5/17) Unfortunately this feature was removed from Amazon with the elimination of AMAZON.LITERALS.
However, depending on how interested you are in capturing free form inputs you may be satisfied with an input MODE that captures one word, name, city, number, letter, symbol, etc. at a time and strings them together into a single variable with no message in between.
I've worked on a password input mode that can be modified to collect and concatenate user inputs. While your input would be slower, if you optimize your lambda function you may be able to achieve a fast user experience for entering a few sentences. The structure is what's important. The code could easily be adapted.
How to give input to Amazon Alexa Skills Kit (ASK) mixed string with numbers?
https://stackoverflow.com/a/45515598/8408056
Here is the better possible way to achieve what you were looking for. After trying several methods, I have got the complete words of the statement asked Alexa.
You need to make the following setup in your Alexa skill (name of intent, slot name, and slot type you can choose as per your need)
Setting up Intent
Setting up custom slot type
After setting up your Alexa skill, you can invoke your skill, keep some response for launch request and say anything you want, and you can catch the entire words or text as shown here.
"intent": {
"name": "sample",
"confirmationStatus": "NONE",
"slots": {
"sentence": {
"name": "sentence",
"value": "hello, how are you?",
"resolutions": {
"resolutionsPerAuthority": [
{
"authority": "xxxxxxx",
"status": {
"code": "xxxxxxx"
}
}
]
},
"confirmationStatus": "NONE",
"source": "USER"
}
}
}
Note*: In this method, you will need to handle utterances properly if there are more than one intent.
I'm building an app where I need to process 5k+ tasks in small batches. For that I have a queue of tasks that is stored in a Firebase. I'd like to be able to pull certain amount of tasks with empty status, update their status and write back.
Currently I don't see how I can pull data where a certain field is empty. Is it possible? If not, what would be the alternative solution?
UPDATED 02/12. Here is the data structure that I have:
{
"-KAMnc89C5Yi_ef18ewc" : {
"0": {
"url": "https://excample.com/url",
"status": "done"
},
"1": {
"url": "https://excample.com/url1"
},
"2": {
"url": "https://excample.com/ur2"
},
"3": {
"url": "https://excample.com/ur3"
}
}
And this is the query I'm using:
queueRef.orderByChild('status').equalTo(null).limitToFirst(1).once('value', function(snapshot) {
console.log(snapshot.val());
});
queueRef points to "-KAMnc89C5Yi_ef18ewc" from the data above.
I expect to get one object - "1", but instead I'm getting all of them. Is there something I'm missing?
Firebase doesn't allow you to store a property without a value. That simply means that the property doesn't exist.
Luckily this doesn't really matter too much, because this seems to work. Given this data structure:
{
"-KADbswYg3FiQF78mmUf": {
"name": "task1",
"status": "done"
},
"-KADbugr7QzTx0s93Fs0": {
"name": "task2"
},
"-KADbvKvBgiAXxnQvoBp": {
"name": "task3"
}
}
This works:
ref.orderByChild('status').equalTo(null).once('value', function(snapshot) {
console.log(snapshot.val());
})
This prints task2 and task3.
Use the DataSnapshot.exists()
This will returns true if this snapshot contains any data. If not it will return false. According to the documentation here. It is slightly more efficient than using snapshot.val() !== null.
With a data structure like this:
{
"girlfriend": {
"first": "Pamala",
"last": "Anderson"
}
}
And a firebase call like this:
var ref = new Firebase("https://myURL/girlfriend/Pamala");
ref.once("value", function(snapshot) {
var a = snapshot.exists();
// a === true
var b = snapshot.child("girlfriend").exists();
// b === true
var c = snapshot.child("girlfriend/first").exists();
// c === true
var d = snapshot.child("girlfriend/middle").exists();
// d === false (because there is no "name/middle" girlfriend in the data snapshot)
});