In jupyter notebooks a whole bunch of things that are effectively files can be represented, for example videos or images. This is one of their core strengths.
Is it possible to actually store a file in a notebook so that afterwards you can open the ipynb and still download the file when the backend is no longer running?
Microsoft's Azure claims to offer integration with jupyterlab, which I would be quite keen to use (editing code in a browser really starts to irritate one after a while). However, I am using Rmd files in jupyterlab so as to maintain the notebooks in git.
When I tried to connect to jupyterlab from azure by clicking the "open in vscode" button I just got an editor for the Rmd file itself which didn't seem very helpful.
Is there a way of using Rmd files in jupyterlab with vscode? (preferrably without a whole bunch of exporting and importing using e.g. jupytext)
We can extend U-SQL scripts with R/Python code in Azure Data Lake Analytics, but how can we do it locally?
Install U-SQL Advanced Analytics extensions in your Data Lake Analytics Account
1.1 Launch your Azure Portal
1.2 Navigate to your Data Lake Analytics Account
1.3 Click Sample Scripts
1.4 Click More and select Install U-SQL Extensions
1.5 Wait until the extensions have finished installing (2GB)
1.6 Have you waited? Then go to your Data Lake Analytics Account
1.7 Navigate to your default Data Lake Store Account
1.8 Click on Data Explorer and verify that a folder /usqlext exists
Get your USQL Local Run path
2.1 Launch your Visual Studio
2.2 Select Tools > Options > Azure Data Lake > General
2.3 Under U-SQL Local Run, find and copy the value for DataRoot
2.4 The value will look like this: C:\Users\username\AppData\Local\USQLDataRoot
Copy U-SQL Advanced Analytics extensions from Azure to your localhost
3.1 Use a powershell script or ... go to the next line
3.2 Launch Microsoft Azure Storage Explorer (great tool, install it)
3.3 Locate your default Data Lake Store, the one of your Data Lake Analytics Account
3.4 Open data explorer and Download the folder /usqlext to your USQL Local Run's path
3.5 The full path should look like this: C:\Users\username\AppData\Local\USQLDataRoot\usqlext
Final step, register all Azure U-SQL Extensions under U-SQL Local Run
4.1 Launch your Visual Studio
4.2 Start a new U-SQL project
4.3 Open the file C:\Users\username\AppData\Local\USQLDataRoot\usqlext\RegisterAll.usql
4.4 Copy the text into your own U-SQL script
4.5 Run it in Local Execution mode
4.6 Once the script finishes...
You will be able to use all the U-SQL Advanced Analytics features (Python, R, Cognitive) on your own machine and explore all the samples in \usqlext\samples!
Have a nive day!
This answer does not apply directly to the OP, but this article is the closest match to the issue that I had. Knowing others may find this article while searching for the solution, I am recording my answer to this thread.
Problem: In the Azure Portal (not locally), if you choose "Install Azure U-SQL Extensions", the job eventually fails with a non-descript error.
What is happening behind the scenes is that all of the files are copying into storage, but the assemblies fail to register. We have to create a job manually to register the assemblies.
Answer:
Open Data Explorer
Navigate to /usqlext
Download the file "RegisterAll.usql". Open in Notepad, and copy the text
Create a new Job. Paste in the text.
Execute the job.
Assemblies will be registered (verify by checking Catalog->master->Assemblies). You can now run the Cognition and Python samples.
I want to make a file upload with ember.js. I am using ember 1.9 with django the file I want to upload is an xml file i want to give the user the possibility to upload up to 4 files. I have seen some older solutions from back in 2013 but was wander if there is something new you might suggest.
P.S. I am not using ember CLI.
I have opensource project needed to be uploaded to GitHub when I upload it unzipped it takes a lot of time to do so
so I'm asking for a way to upload it zipped and unzip it after uploading it
thanks in advance :)
You will have no choice but to do a regular git push. This will be as fast as uploading a zipped archive, maybe even faster.
Try using ssh and not https for your remote connection.