I have a requirement that users input some keywords, through which I can quickly help users find out the images in the Docker Register,we have more than 10,000 images in our warehouse. What command can we use to filter quickly? I only found /v2/_catelog in the Docker API, it doesn't cut it.
The whole step I need is as follows:
1、The front input box enters any character and tags
2、The back end helps query and returns the existing list by character
Related
Currently i'm on project scraping a data from website. The data is not a text or numeric value but it contains canvas element produced number phone as canvas image. My first method to scrape this data i'm using OCR Text Recognition in Power Automate Desktop which collect all text specifically from the webpage coordinates. I'm able to get the number, but it also scrapped unnecessary number and text from the coordinates. So i'm filter it using Recognize Entities In Text action in PDA(Power Automate Desktop) and able to filter the number phone.
But the problem is, when im running the action it will add new phone number to the new rows and also produced unnecessary number which is 000000 in the item list row.I tried to get rid of the unnecessary number by using remove item from the list action and it get rid of it. But it also remove my other item which is NULLED to differentiate which product does not contains phone number from the list.
I want the list result write to excel file, without removing NULLED from the list only remove 00000 from the list.So the list will be transfer to excel row by row
Summary
I'm looking to import a data table from a website that does not appear to have an API. The table is broken down to various images and text. The goal is to have all of the content available in a table to then reference for other sheets.
Issue
When I pull in the data, I get some of the text, none of the other images, and a reference to another table. I looked up some options, but none of them yielded anything but blank cells.
I also tried to use the =IMAGE() formula with a direct link to the images URLs, but there is a portion of the URL that is specific to the unit's release date, and as such, too dynamic to account for.
Excel Formula
=IMPORTHTML("https://gamepress.gg/pokemonmasters/database/sync-pair-list","table",3)
Unfortunately without an API it is going to be difficult to achieve what you aim here. These are the main reasons why:
PROBLEMS AND WORKAROUNDS
This table has nested tables that therefore need to be accessed separately. If you take a look at: =IMPORTHTML("https://gamepress.gg/pokemonmasters/database/sync-pair-list","table",4)
you will see how the table 4 of this HTML page is the stats of a random character of the main table. If you go for 5 or 6 you will realise that the nested tables are not even numerically ordered and that you cannot access them by accessing to the main table (i.e mainTable[0].nestedTable). A hard working approach to do this is to go one by one finding their corresponding stat table and placing next to it. For this I recommend extracting only the name field of the main table to be able to align each stat to their character. You can simply do this using:=INDEX(IMPORTHTML("https://gamepress.gg/pokemonmasters/database/sync-pair-list","table",3),0,1). You can find out more about INDEX here
IMPORTHTML cannot access images nor links so it will be very difficult to get the images in the last columns. A way to solve this is by using as you mentioned the image with its url like this: =IMAGE("https://gamepress.gg/pokemonmasters/sites/pokemonmasters/files/styles/30x30/public/2019-07/Electric.png?itok=fkRfkrFX"). You can find more info about inserting images here
CONCLUSION
To sum up, there is no easy way to solve this problem. The closest you can get is by:
Importing the name column.
Figuring out which tables belong to which character and placing them with next to their name.
Getting the image url of each weakness and type and add it to each character.
I am sorry this site does not have an API to make things smooth, good luck with your project and let me know if you need anything else or if you did not understand anything.
Here you can find more information about IMPORTHTML
I'm using the ptv api call for departures and can successfully return back three results. I'm trying to get Siri to dictate these to me in order but am not having much luck.
When the api is called it returns a bunch of information in an array for however many services you specify (three in my case), but I only want one of the lines to be dictated (scheduled_departure_utc), not the full array.
And I want to pull just this one line out of each of the three blobs of data that are returned so that Siri says...
the next trains to the city are (scheduled_departure_utc),(scheduled_departure_utc),(scheduled_departure_utc). Where (scheduled_departure_utc) is a short form of time (8:28am, 8:38am, 8:58am) as an example.
Any ideas?
I am trying to create a yahoo pipe that takes ideally takes all tweets tweeted at any point in time and filters down by a number of attributes to then display a filtered feed.
Basically in order this is what I want to happen:
Get a feed of all tweets at any one time.
Filter tweets by geolocation origin, i.e. UK,
Filter by a number of of different combinations of keywords.
Output as an RSS feed (though this isn't really the crucial stage as Yahoo Pipes takes care of this anyway)
Disclaimer: of course I understand that there are limits to the amount of tweets that could come through etc but I would like to cast the input net as wide as possible.
I have managed to get stages 3 & 4 working correctly and for the time being I am not really worrying about step 2 (although if you have any suggestions I am all ears), but stages 1 is where I am struggling. What I have attempted is using a Fetch Feed module with the URL - http://search.twitter.com/search.atom?q=lang:en - however it seems that this only pulls 15 tweets. Is there any way that I can pull more than 15 tweets every time the pipe is run, otherwise I think this may all be in vain.
FYI, here is the link to the pipe as it stands - http://pipes.yahoo.com/ludus247/182ef4a83885698428d57865da5cf85b
Thanks in advance!
I have already asked a similar question earlier but I have notcied that I have big constrain: I am working on small text sets suchs as user Tweets to generate tags(keywords).
And it seems like the accepted suggestion ( point-wise mutual information algorithm) is meant to work on bigger documents.
With this constrain(working on small set of texts), how can I generate tags ?
Regards
Two Stage Approach for Multiword Tags
You could pool all the tweets into a single larger document and then extract the n most interesting collocations from the whole collection of tweets. You could then go back and tag each tweet with the collocations that occur in it. Using this approach, n would be the total number of multiword tags that would be generated for the whole dataset.
For the first stage, you could use the NLTK code posted here. The second stage could be accomplished with just a simple for loop over all the tweets. However, if speed is a concern, you could use pylucene to quickly find the tweets that contain each collocation.
Tweet Level PMI for Single Word Tags
As also suggested here, For single word tags, you could calculate the point-wise mutual information of each individual word and the tweet itself, i.e.
PMI(term, tweet) = log [ P(term, tweet) / (P(term)*P(tweet))
Again, this will roughly tell you how much less (or more) surprised you are to come across the term in the specific document as appose to coming across it in the larger collection. You could then tag the tweet with a few terms that have the highest PMI with the tweet.
General Changes for Tweets
Some changes you might want to make when tagging with tweets include:
Only use a word or collocation as a tag for a tweet, if it occurs within a certain number or percentage of other tweets. Otherwise, PMI will tend to tag tweets with odd terms that occur in just one tweet but that are not seen anywhere else, e.g. misspellings and keyboard noise like ##$##$%!.
Scale the number of tags used with the length of each tweet. You might be able to extract 2 or 3 interesting tags for longer tweets. But, for a shorter 2 word tweet, you probably don't want to use every single word and collocation to tag it. It's probably worth experimenting with different cut-offs for how many tags you want to extract given the tweet length.
I have used a method earlier, for small text content such as SMSes, where I would just repeat the same line two times. Surprisingly, that works well for such content where a noun could well be the topic. I mean, you don't need it to repeat for it to be the topic.