Skip to main content

How to upgrade your python version to 3.7 in ubuntu to avoid problems?

I wanted to download a package some days ago which gave an error 'doesn't contain python>=3.7'; which meant that I didn't have python of versions more than or equal to 3.7. So I went ahead and downloaded and faced certain problems. That's why I am writing this article.

One line work:

The only thing you need to do for this is write in bash:

sudo apt update -y
sudo apt install python3.7

Now this part is important. In many tutorials, you may have seen the following line:


sudo update-alternatives --install /usr/bin/python python3 /usr/bin/python3.7 2
sudo update-alternatives --config python3

Now doing this last line, tutorials will tell you to selection 3.7 as the default option. That is where your system may go wrong. I did the same. And then the following three problem came up:
(1) there is a red circle in notification bar with a white dash inside it. This says, some error happened while checking for updates.
(2) You will not be able to access the software center.
(3) Your terminal will not open.

Now at this point, your terminal path is actually broken as well as the software center. What you need to do if you have already done this and facing one of these problems, is that:

Open the terminal from desktop > right click on open space > select open terminal from list opened > write the following line again in terminal
sudo update-alternatives --config python3


Now choose a version of python less than or equal to 3.6 this time. Then restart your pc once. Then see. The notification circle will be gone; your terminal will start and all the things will be fine again.
Important thing is, your default version will still not be 3.7 or more than that. So when you need to download things or use python 3.7 or so on; please create a virtual environment with that specific python version and then use it.
Thanks for reading! comment below to let me know about anything related to this.

Comments

Popular posts from this blog

Mastering SQL for Data Science: Top SQL Interview Questions by Experience Level

Introduction: SQL (Structured Query Language) is a cornerstone of data manipulation and querying in data science. SQL technical rounds are designed to assess a candidate’s ability to work with databases, retrieve, and manipulate data efficiently. This guide provides a comprehensive list of SQL interview questions segmented by experience level—beginner, intermediate, and experienced. For each level, you'll find key questions designed to evaluate the candidate’s proficiency in SQL and their ability to solve data-related problems. The difficulty increases as the experience level rises, and the final section will guide you on how to prepare effectively for these rounds. Beginner (0-2 Years of Experience) At this stage, candidates are expected to know the basics of SQL, common commands, and elementary data manipulation. What is SQL? Explain its importance in data science. Hint: Think about querying, relational databases, and data manipulation. What is the difference between WHERE ...

What is Bort?

 Introduction: Bort, is the new and more optimized version of BERT; which came out this october from amazon science. I came to know about it today while parsing amazon science's news on facebook about bort. So Bort is the newest addition to the long list of great LM models with extra-ordinary achievements.  Why is Bort important? Bort, is a model of 5.5% effective and 16% total size of the original BERT model; and is 20x faster than BERT, while being able to surpass the BERT model in 20 out of 23 tasks; to quote the abstract of the paper,  ' it obtains performance improvements of between 0 . 3% and 31%, absolute, with respect to BERT-large, on multiple public natural language understanding (NLU) benchmarks. ' So what made this achievement possible? The main idea behind creation of Bort is to go beyond the shallow depth of weight pruning, connection deletion or merely factoring the NN into different matrix factorizations and thus distilling it. While methods like know...

Spacy errors and their solutions

 Introduction: There are a bunch of errors in spacy, which never makes sense until you get to the depth of it. In this post, we will analyze the attribute error E046 and why it occurs. (1) AttributeError: [E046] Can't retrieve unregistered extension attribute 'tag_name'. Did you forget to call the set_extension method? Let's first understand what the error means on superficial level. There is a tag_name extension in your code. i.e. from a doc object, probably you are calling doc._.tag_name. But spacy suggests to you that probably you forgot to call the set_extension method. So what to do from here? The problem in hand is that your extension is not created where it should have been created. Now in general this means that your pipeline is incorrect at some level.  So how should you solve it? Look into the pipeline of your spacy language object. Chances are that the pipeline component which creates the extension is not included in the pipeline. To check the pipe eleme...