so I've been wondering if there is some kind of API to access the photos I have saved in the cloud in Lightroom CC. Google wasn't much help with this.
I know that from Lightroom Classic this can be done using SQL and the .lrcat file. But is there anyway to access the photos saved in the cloud by the newer Lightroom CC? JPEG previews are all I need.
You can find of the adobe APIs on Adobe.io:
https://www.adobe.io/
Specifically, you'll want the Lightroom API (there is also an API for Lightroom Classic):
https://www.adobe.io/apis/creativecloud/lightroom.html
The documentation for the Lightroom API can be found here:
https://www.adobe.io/apis/creativecloud/lightroom/docs.html
API Reference docs are here:
https://www.adobe.io/apis/creativecloud/lightroom/apidocs.html
After authenticating, you would use the catalog endpoint to retrieve your photos (assets).
Also: Lightroom API GitHub
https://github.com/AdobeDocs/lightroom-api-docs
Enjoy!
Related
I'm saving videos to Firebase Storage and creating a URL for it which I saving into Cloud Firestore. So when ever someone watch a video I call the URL and Firebase downloads it. That increased my project costs enormously.
The question that I have is, is there a way to save the mp4 files cheaper?
And maybe also make it faster to download?
The best solution will be if I can like I used before. So in the new solution, also use the download URL which I saved in cloud Firestore. So that I don't need change too much. My Project is using Flutter in client side.
I created a mobile app, where user can upload videos for example like Instagram or TikTok.
I'm willing to pay if you freelancer and can help.
You can use Youtube or Vimeo to store your videos for free (Vimeo is limited to 500mb).
Then you can use a package from pub.dev to display these videos.
YouTube package (does not support to download the file, only playback)
Vimeo package (max 500mb, then you have to pay)
So both have their advantages and disadvantages.
It is possible to upload videos to YouTube using Google API. There is an example done using flutter which can be ideal for your use-case. Have a look at this video on youtube.
I've essentially been using firebase for storage and my last computer got wiped, and I'm trying to download all the sites files that I've been hosting on firebase. I can't figure out how to do this and the answers I've found seem overcomplicated.
There is no built-in FTP console for Google Cloud Storage. But you can use the Firebase API to get your files from it.
Also see FTP to Google Storage for an example FTP server that a developer made on top of Google Cloud Storage.
All my app's data is stored in Firebase. I'd like to build some reports with my data that aren't necessarily accessible through the web/app front-end. I don't see any good options for this in the Console. Has anyone found a good reporting solution for Firebase? I am looking for something like Crystal Reports or just an easy way to render Firebase data based on a query.
Thanks,
Rima.
I found a issue with the solution above. Firebase stores its data in JSON format, which cannot be consumed by solutions such as BigQuery, because it is expecting JSONL format and you get an error. It beats me why Google are not providing an elegant solution when integrating between two of their products, but I believe they have something planned.
Firebase does not have any "built-in" reporting tools other than the defined querying APIs.
If your database is small, you dump the JSON from the Firebase Console and then manually run analysis on it.
If your database is large, you can upgrade to the Flame or Blaze plans and sign up for daily private backups. This will create a JSON dump in the background without affecting your database performance and store it in the cloud. You could then use tools to grab that dump and perform advanced reporting on it.
1) Via BigQuery
Official Docs:
https://cloud.google.com/bigquery/docs/loading-data-cloud-firestore
Codelab Walkthrough:
https://codelabs.developers.google.com/codelabs/modern-data-pipeline-firestore-bigquery-dataflow-templates/index.html?index=..%2F..next17
Connect whatever BI tool you want to BigQuery. Google Data Studio is
free as is Metabase. Almost every Enterprise BI tool has a BigQuery
connector.
From https://www.reddit.com/r/Firebase/comments/arps42/reportingbi_tools_and_firestore/
2) Via "Custom Data Sources"
Cloud Firestore (and probably Realtime-Db) has a RESTFUL API. Many popular reporting tools support "custom", "restful", "ajax", and/or "HTTP" sources.
You should search your favorite reporting tools, and internet search accordingly.
I can see that Stimulsoft seems to support custom/RESTFUL sources. A PowerBI data connector seems to provide a lot of latitude - https://github.com/Microsoft/DataConnectors
Of course, this means that you need to create several data sources, and they probably won't be as optimised as a built-in source type. For example, the report engine probably won't know how to translate any front-end UI filters into custom-source query filters. Perhaps some platforms support the ability for you to create your own adaptors.
Is there a better way to download the google cloud datastore docs for offline viewing than to use a web crawler?
I have not found anything yet! Thanks!
Sorry but we don't currently support this for any of the documentation hosted on developers.google.com.
We have a client requirement to upload documents (Word Doc and possibly PDF) to our Azure hosted application and have full text search on the document.
My understanding is that SQL Azure doesn't support full text indexing so I can't just store them in the DB.
Has anyone done anything similar? If so how? Are there any Nuget packages or things I can install into the Azure role etc when I create it? Is blob storage serachable/indexable?
Any ideas?
I would suggest using Lucene.NET along with your data. Take a look at:
http://code.msdn.microsoft.com/windowsazure/Azure-Library-for-83562538
If you are doing this now and you are using Azure. It is best to combine this with Azure Search Service. It has stacks of features and you can add text and meta data to allow fast searching. It has various options options indexing blob etc blob indexing