I have integrated devise to a model name User. When I try to run query on the User model in rails console it gives ArgumentError.
3.0.0 :007 > User.all
User Load (0.9ms) SELECT "users".* FROM "users" /* loading for inspect */ LIMIT $1 [["LIMIT", 11]]
Traceback (most recent call last):
ArgumentError (wrong number of arguments (given 0, expected 1))
it gives same type of error on User.first, User.last , User.find but works fine on User.count
User model
class User < ApplicationRecord
devise :database_authenticatable, :registerable,
:recoverable, :rememberable, :validatable, :lockable, :confirmable
has_many :addresses
belongs_to :default_address, foreign_key: :default_address_id, class_name: 'Address', optional: :true
has_one :cart
has_many :cart_items, through: :cart
has_many :purchases
has_many :purchase_items, through: :purchases
has_one_attached :profile_pic
after_commit :add_cart, only: %i(create)
validates :first_name, presence: true, length: { minimum: 3 }
validates :last_name, presence: true, length: { minimum: 3 }
validates :password, length: { minimum: 8 }, confirmation: true,
unless: Proc.new { |user| user.password.blank? }
validates :email, uniqueness: true , presence: true,
format: { with: /[^@\s]+@[^@\s]+/, message: "Must be valid address" }
validates :age, presence: true, numericality: { only_integer: true }
validates :school, presence: true, length: { minimum: 5 }
private
def add_cart
AddCartJob.perform_later(self)
end
end
DB schema for user
create_table "users", force: :cascade do |t|
t.string "first_name"
t.string "last_name"
t.string "email"
t.string "password_digest"
t.datetime "created_at", precision: 6, null: false
t.datetime "updated_at", precision: 6, null: false
t.integer "age"
t.string "school"
t.integer "default_address_id"
t.string "encrypted_password", default: "", null: false
t.string "reset_password_token"
t.datetime "reset_password_sent_at"
t.datetime "remember_created_at"
t.integer "sign_in_count", default: 0, null: false
t.datetime "current_sign_in_at"
t.datetime "last_sign_in_at"
t.string "current_sign_in_ip"
t.string "last_sign_in_ip"
t.stI am the Power BI/SSAS champion in my company. The power users in my company have often asked me this question because they felt that knowledge of SQL was already quite common. Why did MS choose DAX - when there was SQL already?
Some even went to the extent of comparing the VizQl language of Tableau which is nearly SQL.
Thank you.
Hey, I'd like to learn Indian Sign Language. internet is not turning out to be very helpful. So, I have the following questions:
- Is ISL used in India or ASL(American Sign Language) is preferred?
- Is there any online, free/paid course available for ISL?
I have found MongoDB like implementations:
- https://github.com/crcn/sift.js/
- https://github.com/kofrasa/mingo
but I am unable to find anything that would support Kibana Query Language.
Has anyone worked on anything comparable?
The site is trying to match the user's query to the contents of the images (not the image captions or any other image metadata) by using a neural net (source).
These images are not necessarily legally freely usable. If you want legally freely usable images, see the end of this post for 2 different web apps that search site Unsplash.
From https://twitter.com/Jacob__Jackson/status/1357143267213783045:
>19M images from Reddit, Instagram, and Pinterest
From https://twitter.com/Jacob__Jackson/status/1357139564272504833:
>it doesn't use CLIP directly, but it does use similar methods
There is evidence that the developer was working on this before CLIP was announced/released.
I am not affiliated with this site or anyone involved with it.
Example: search query "a tennis ball in a dog's mouth". One of the search results:
https://preview.redd.it/ttgmtprlrgf61.jpg?width=900&format=pjpg&auto=webp&s=9a615425df8ac1e1b5f57b7951dc0286e04cc0d0
Related: Evertrove - We made a usable ML-powered image search using OpenAI's CLIP - search millions of images
>Unsplash Image Search
>
>Using this notebook you can search for images from the Unsplash Dataset using natural language queries. The search is powered by OpenAI's CLIP neural network.
>
>This notebook uses the precomputed feature vectors for almost 2 million images from the full version of the Unsplash Dataset. If you want to compute the features yourself, see here.
>
>This project was created by Vladimir Haltakov and the full code is open-sourced on GitHub.
Steps to follow to do your first search in a given Colab session:
- Click this link.
- Sign into your Google account if you're not already signed in. Click the "S" button in the upper right to do this. Note: Being signed into a Google account has privacy ramifications, such as your Google search history being recorded in your Google account.
- Click somewhere (except the triangle) in the cell with the line that reads 'search_query = "Two dogs playing in the snow"'.
- Click menu item "Runtime->Run before". Wait until execution stops.
- Find the line that reads (or initially read) 'search_query = "Two dogs playing in the snow"'. Change "Two dogs playing in the snow" to your desired search query (include the quotes); example: 'search_query = "A clock with gold-colored numbers on a black background"'.
- (Optional) Find the line that reads (or initially read) 'search_unslash(search_query, photo_features, photo_ids, 3)'. Change 3 in that line to the number of search results that you want.
- Click the triangle to the left of the line that initially read 'search_query = "Two dogs playing in the snow"'. Wait for the search results.
Steps to follow to do more searches in a given Colab session: Do steps 5 to 7 above.
After you're done with your Google Colab session, optionally log out of your Google account due to the privacy ramifications of being logged into a Google a
... keep reading on reddit ➡I built a proof of concept for a structured query language for music xml and midi files. This project is extremely early in its development and is my first attempt at a novel query language. This is also a pet project I do in my free time. Feedback is welcome.
Project URL : https://github.com/Khalian/Modulo12
Here is also the language in action https://www.youtube.com/watch?v=p70I13TaQKg&ab_channel=ArunavSanyal
Hi! For my Master’s thesis I’m developing an interface which you can use to query OSM in natural language. E.g., you can ask questions like:
- Is there any café in walking distance of Heiliggeistkirche in Heidelberg?
- What is the closest drinking water fountain from Musée du Louvre in Paris?
- Tell me the distance between Kremlin in Moscow and the Houses of Parliament in London!
My system translates them (via a character-based RNN) into an intermediate query language, which is then used to get the answer via Overpass and Nominatim.
Check it out and let me know what you think! It’s currently at https://nlmaps.gorgor.de/
Also, I need more data to train it better. So I’m looking for people to ask new queries and correct the system if it’s wrong. 150 € for 400 queries. Take a look at the posting if you’re interested.
Why: In previous versions of SOQL, retrieving fields meant specifying all the names of all the fields you wanted to retrieve. Typically, this required first making an API call to describe the object to get the list of fields (or using the Object Manager) and then laboriously constructing a SOQL query to select all those fields. Further, such a query could exceed the query character limit for large complex queries that retrieve lots of data. The new FIELDS()
the function lets you select all the fields without knowing their names in advance. This eliminates the need for a round-trip to the server to prepare a SOQL statement, eliminates the need for research and a lot of typing, simplifies query statements, and makes it much easier to explore the shape of your objects.
How: Use FIELDS(ALL)
, FIELDS(STANDARD)
, or FIELDS(CUSTOM)
in your SELECT
statements. For more information, see FIELDS() in the SOQL and SOSL Reference.
for more check out the release notes: click here
I had a few Spanish ones yesterday, which I tried to get through, but I eventually just waited for the regular ones to pop up since I don’t know the language well. Today, I’m getting a lot of German queries, which I also do not understand. I have never told Lionbridge that I could understand these languages and I’m sure there are people in the areas that speak these languages that would be more than happy to do the tasks.
Permutive is looking for a software engineer to develop our edge-compute capabilities.
We would be excited to hear from experienced software engineers who are mathematically minded in their approach and have some commercial experience with embedded SDKs.
You will be working on our query language, which sits at the core of our platform and distributes computation to over a billion devices each month. Written in Haskell, this language currently supports segmentation, analytics, and model inference for users across the web.
This role is perfect for someone excited by contributing to a new computing paradigm through the lens of real-world business problems, who strives for perfection but also knows when to compromise and prioritise for the greater good of the team. There are numerous technical yet practical challenges to tackle, and there are novel questions that come with building a massively geo-distributed system which need answering.
We are remote-first with a London and NYC HQ and open to applications with eligibility to work in the UK.
You can find more details here or get in touch with alice@permutive.com if you have further questions!
