cloth | ORM over Cloud Bigtable by Golang | Object-Relational Mapping library
kandi X-RAY | cloth Summary
kandi X-RAY | cloth Summary
ORM over Cloud Bigtable by Golang.
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Top functions reviewed by kandi - BETA
- setValue sets the value of the given value .
- Main entry point
- getBytes returns the bytes of a field .
- ReadItems deserializes a bigtable . ReadItem from a slice of data .
- SetColumnQualifiers sets a column Qualifiers field .
- SetColumns mutates a bigtable . Mutation .
- init initializes BigTable
- GetBigtableTagInfo returns TagInfo from a tag string .
- ReadColumnQualifier extracts column qualifier from bigtable .
- GenerateColumnsMutation is used to generate a new mutation .
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Community Discussions
Trending Discussions on cloth
QUESTION
I know it's basic and too easy for you people, but I'm a beginner who needs your help. I'm struggling to make binary classifier with CNN. My final goal is to check accuracy over 0.99
I import both MNIST and FASHION_MNIST to identify if it's number or clothing. So there are 2 category. I want to categorize 0-60000 as 0, and 60001-120000 as 1. I will use binary_crossentropy.
but I dont know how to start from the beginning. How can I use vstack hstack at first to combine MNIST and FASHION_MNIST?
This is how I tried so far
...ANSWER
Answered 2021-Jun-10 at 03:15They're images so better treat them as images and don't reshape them to vectors.
Now the answer of the question. Suppose you have mnist_train_image and fashion_train_image, both have (60000, 28, 28) input shape.
What you want to do is consist of 2 parts, combining inputs and making the targets.
First the inputsAs you've already wrote in the question, you can use np.vstack like this
QUESTION
I'm new to Google Maps API and using streetview.
I want to display the tag in each place in streetview the once I screenshot.
(see there is orange and blue tag eg. restaurant, cafe, clothing store)
I was able to pin some places type using the Places API and it pin on maps but did not pin on streetview.
ANSWER
Answered 2021-Jun-09 at 09:40If you need the markers to be visible on both the map and on Street View, just create the markers on map and panorama.
See my comments in the code. I also modified the center point and pano heading so that a Marker is in view when loaded.
QUESTION
Is there a way to uniquely identify a transaction from a QFX file (downloaded from a bank) and the list of transactions fetched from plaid?
There is FITID in the QFX file and transaction_id in plaid transaction list. But is there any common unique identifier for both QFX file and Plaid transaction?
QFX file:
...ANSWER
Answered 2021-Jun-09 at 18:33I think you've kind of answered your own question -- as you can see from the responses you pasted in, there isn't a shared id field across both the QFX file and the Plaid response.
That said, you could probably do some processing on the name, memo, date, and amount fields to match them up and get a very close to accurate correlation between QFX transactions and Plaid transactions.
QUESTION
I need to create column as dictionary using existing column. df:
...ANSWER
Answered 2021-Jun-09 at 05:11Use named aggregation for both new values per groups in lambda function with Series.value_counts and to_dict, second column is first changed by () in DataFrame.assign and aggregate by GroupBy.last, in last step use DataFrame.join:
QUESTION
I'm trying to get some insight in this room for optimization for a SQL query (BigQuery). I have this segment of a WHERE clause that needs to include all instances where h.isEntrance is TRUE or where h.hitNumber = 1. I've tested it back and forth with CASE statements, and with OR statements for them, and the results aren't wholly conclusive.
It seems like the CASE is faster for shorter data pulls, and the OR is faster for longer data pulls, but that doesn't make sense to me. Is there a difference between these or is it likely something else driving this difference? Is one faster/is there another better option for incorporating this logical requirement into my query? Below the statement is my full query for context in case that's helpful.
Also open to any other optimizations I may have overlooked within this query as lowering the runtime for this query is paramount to its usefulness.
Thanks!
...ANSWER
Answered 2021-Jun-08 at 15:46From a code craft viewpoint alone, I would probably always write your CASE expression as this:
QUESTION
I would like to ask a question about a possible solution for an e-commerce database design in terms of scalability and flexibility.
We are going to use MongoDB and Node on the backend.
I included an image for you to see what we have so far. We currently have a Products table that can be used to add a product into the system. The interesting part is that we would like to be able to add different types of products to the system with varying attributes.
For example, in the admin management page, we could select a Clothes item where we should fill out a form with fields such as Height, Length, Size ... etc. The question is how could we model this way of structure in the database design?
What we were thinking of was creating tables such as ClothesProduct and many more and respectively connect the Products table to one of these. But we could have 100 different tables for the varying product types. We would like to add a product type dynamically from the admin management. Is this possible in Mongoose? Because creating all possible fields in the Products table is not efficient and it would hit us hard for the long-term.
Maybe we should just create separate tables for each unique product type and from the front-end, we would select one of them to display the correct form?
Could you please share your thoughts?
Thank you!
...ANSWER
Answered 2021-Jun-07 at 09:46We've got a mongoose backend that I've been working on since its inception about 3 years ago. Here some of my lessons:
Mongodb is noSQL: By linking all these objects by ID, it becomes very painful to find all products of "Shop A": You would have to make many queries before getting the list of products for a particular shop (shop -> brand category -> subCategory -> product). Consider nesting certain objects in other objects (e.g. subcategories inside categories, as they are semantically the same). This will save immense loading times.
Dynamically created product fields: We built a (now) big module that allows user to create their own databse keys & values, and assign them to different objects. In essence, it looks something like this:
QUESTION
I'm taking part in Code in Place 2021 and for my final project I developed a Madlibs generator using Python and Tkinter, and the code is functional and works the way I want it to, but obviously it's pretty long and convoluted. I was hoping some of you guys could offer some suggestions on how to make my code more concise and get rid of any unncessary lines!
I pasted all of the code below:
...ANSWER
Answered 2021-Jun-05 at 18:00You can reduce your code to half if you use for loop and list.
Here is an example, you can modify the below code according to your need:
QUESTION
Result Right Now , want to ignore dulicate
...ANSWER
Answered 2021-Jun-01 at 16:34You can remove duplicates by selecting DISTINCT values or by GROUPing. DISTINCT will return only distinct values across all the columns you selected. GROUPing will group rows into summary rows by the fields you group by.
Here either adding DISTINCT after your SELECT statement, or including all the fields in your SELECT statement in your GROUP BY statement should return distinct records. Because you grouped by id_product which is not in the SELECT statement, it will not remove duplicates.
Examples in code would be:
Updating SELECT statement to include DISTINCT
QUESTION
I recently started learning JavaScript and ran into a problem.
I wrote a little code that counts elements inside a nested array, but the code breaks when adding an element to the first nested array. I don't understand what the problem is.
...
ANSWER
Answered 2021-Jun-01 at 22:10var totalItems = function () {
for (var i = 0; i <= clothes.length; i++) {
var total = 0;
for (var k = 0; k < clothes[i].length; k++) {
total = total + clothes[k].length;
}
return total
}
};
QUESTION
I am trying to perform entity matching for the first time and want to "get rid" of the obvious matches first, so I can focus working with the fuzzy cases. I have a dataset of almost 600.000 entries containing information about clothes.
What I need is all different prices of the suppliers that have the same id, color and size.
Here is an example:
...ANSWER
Answered 2021-May-31 at 11:30My idea is two concatenate two dataframes - one dataframe without duplicates and dataframes where we have prices for each type. I believe it could be done by using fewer lines, but I will give you my solution as there are no other:
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