I’m trying to run this notebook locally. I got the deno kernel in Jupyter working.
I get an error on the first line of code:
Stack trace:
TypeError: Relative import path "dotenv/config" not prefixed with / or ./ or ../
at async <anonymous>:1:22
Can anyone help?
Please, can you share with me good link to install Deno kernel?
I am facing the same issue
Did you find a solution, please?
hi guys.
Welcome to the community.
In order to run locally you have to setup your envirioment variables by your own.
Keep in mind that this courses wasn’t design to run locally. So, it might be a expect that some issues occur since your local envirioment doesn’t correspond to the same envirioment as the course envirioment
Also it might be necessary to download all the course files.
You can find then by clicking in the jupyter logo at the top left.
Best regards
IMO this whole course has little value if I can’t run things locally. The whole point is to build apps on our own. I suggest you guys spend more time explaining setup so that learners don’t have to experience this and can focus on the learning.
Even in the file folder I cannot find this dotenv/config folder or file. I did download a couple of the other files.
Did you go through the Jacob Lee GitHub repository?
After setting up the Deno project locally, I copied the deno.json file and it works!
Thank you for your feedback.
The propose of the course it is not to teach how to setup your envirioment, how to programming or such. It is to:
“Help you to learn new skills, tools, and concepts efficiently”.
If you want to prototype or take courses with a more practical approach, specializations are better suited for this.
The main objective of short courses is to develop a course that can be run on any computer. When running on the web browser, the course can reach most learners around the world. Designing this course requires a lot of costs such as cloud servers, web hosting, and so on.
Therefore, the course was designed to work in a very specific environment. This may explain the decision to use some versions of packages, develop custom packages, etc. This is the main reason why students had problems trying to run it locally line by line, assuming it would run in a totally different environment.
Designing a course that could run in a specific computer environment would be costly and lead to many incompatibilities and problems that would take a lot of work to resolve. Therefore, focusing on the course itself is the best way to use the resources available
This is the only way deeplearning.ai found out to make sure everyone interesting and learning new things regards de A.I field can have a free and democratic access to knolegged.
But deeplearning desire to learn everyone’s feedback in order to improve that available content.
So, please, send your feedback. At the end of every course it is a course feedback session where learners could share some suggestions.
I hope your understand the limitations of short courses to run locally.
Best regards
Are you aware of dotenv aproach to setup envirioment variables?
This file is a custom file related to short course envirioment. That file contain a sensitive data as API key and such.
So, it is understandable that that file wasn’t stored public.
To setup your envirioment you have to create your own config file in order to import it latter.
I hope this help.
Best regards
