Anaconda vs. Microsoft Visual Studio Code

I have asked all my juniors to work with Anaconda and Pycharm only, as this is the best combination for now. Coming to use cases: 1. When you have multiple applications using multiple Python variants, it is a really good tool instead of Venv (I never like it). 2. If you have to work on multiple tools and you are someone who needs to work on data analytics, development, and machine learning, this is good. 3. If you have to work with both R and Python, then also this is a good tool, and it provides support for both.

Incentivized

For low-end devices, it is a very good tool, but for devices that have decent RAM and decent CPU, I would recommend Android Studio for Android dev as it has more features, and for others, I will recommend agile IDEs like Cursor and Anti-Gravity, as they offer higher limits on AI models, and autocomplete is unlimited as well.

Incentivized

• Installing packages is very easy with Anaconda. Anaconda comes with 'anaconda navigator', a terminal-like utility from which you can easily install R packages and python libraries.
• Launching R and python IDEs as well as Jupyter notebooks from anaconda navigator is simple, and Anaconda makes it very easy to keep these packages up-to-date.
• I really like the fact that if you don't want to install the full version of Anaconda, you can opt to install a lightweight version (called Miniconda) that includes less python libraries and only core conda. I've installed it when I didn't want to take up as much disk space as Anaconda requires, but it works just the same.

Incentivized

• Integrate with the git repository very well.
• Integrated copilot chat is very helpful to write code snippets and helps beginners to start with coding and development.
• Great library of available extensions is one of the best features in Microsoft Visual Studio Code.
• Dedicated Testing option to configure pytest and others are quite handy to use.

Incentivized

• More graphics need in Spyder book. If you work for couple of years then you will be bored with the graphics.
• Extra tools are required for making it secure. We uses extra tools for adding Username /Password to Jupyter.
• R Studio Hangs a lot when open from Anaconda Navigator.

Incentivized

• The customization of key combinations should be more accessible and easier to change
• The auxiliary panels could be minimized or as floating tabs which are displayed when you click on them
• A monitoring panel of resources used by Microsoft Visual Studio Code or plugins and extensions would help a lot to be able to detect any malfunction of these

Incentivized

It's really good at data processing, but needs to grow more in publishing in a way that a non-programmer can interact with. It also introduces confusion for programmers that are familiar with normal Python processes which are slightly different in Anaconda such as virtualenvs.

Incentivized

Solid tool that provides everything you need to develop most types of applications. The only reason not a 10 is that if you are doing large distributed teams on Enterprise level, Professional does provide more tools to support that and would be worth the cost.

Incentivized

I am giving this rating because I have been using this tool since 2017, and I was in college at that time. Initially, I hesitated to use it as I was not very aware of the workings of Python and how difficult it is to manage its dependency from project to project. Anaconda really helped me with that. The first machine-learning model that I deployed on the Live server was with Anaconda only. It was so managed that I only installed libraries from the requirement.txt file, and it started working. There was no need to manually install cuda or tensor flow as it was a very difficult job at that time. Graphical data modeling also provides tools for it, and they can be easily saved to the system and used anywhere.

Incentivized

I rate Microsoft Visual Studio Code 9 out of 10 because it is best editor tool for development work. It has clean and simple interface. We can easily access the file navigation, search, git integration and extensions. It support multiple languages. overall it is very user friendly and works well for both new and experienced developers.

Incentivized

Overall, Microsoft Visual Studio Code is pretty reliable. Every so often, though, the app will experience an unexplained crash. Since it is a stand-alone app, connectivity or service issues don't occur in my experience. Restarting the app seems to always get around the problem, but I do make sure to save and backup current work.

Incentivized

Microsoft Visual Studio Code is pretty snappy in performance terms. It launches quickly, and tasks are performed quickly. I don't have a lot of integrations other than CoPilot, but I suspect that if the integration partner is provisioned appropriately that any performance impact would be pretty minimal. It doesn't have a lot of bells and whistles (unless you start adding plugins left and right).

Incentivized

Anaconda provides fast support, and a large number of users moderate its online community. This enables any questions you may have to be answered in a timely fashion, regardless of the topic. The fact that it is based in a Python environment only adds to the size of the online community.

Incentivized

Active development means filing a bug on the GitHub repo typically gets you a response within 4 days. There are plugins for almost everything you need, whether it be linting, Vim emulation, even language servers (which I use to code in Scala). There is well-maintained official documentation. The only thing missing is forums. The closest thing is GitHub issues, which typically has the answers but is hard to sift through -- there are currently 78k issues.

Incentivized

One of the main competitors to Anaconda can be Google products such as Colab. Colab gives you the flexibility to handle large datasets gives it an edge over Anaconda. But again, the ease of access and usability of Anaconda stacks up against Colab. Besides, Anaconda relies more on your machine which makes it safe to use.

Incentivized

The licensing of the IntelliJ IDEs is prohibitive, I cannot be sure that I can continue to leverage them as I move between clients.

Zed while interesting doesn't have the market or mindshare to be a daily driver working as part of a team. I wouldn't be able to benefit from many of the day to day automations and findings that the team invents during the course of delivery.

Incentivized

It is easily deployed with our Jamf Pro instance. There is actually very little setup involved in getting the app deployed, and it is fairly well self-contained and does not deploy a large amount of associated files. However, it is not particularly conducive to large project, multi-developer/department projects that involve some form of central integration.

Incentivized

• Positive impact - Multiple options for data presenting , visualizing and sharing. (Eg: R-Markdown).
• Positive impact - Ease of access to build complex machine learning models. (I work in NLP, it has multiple built in models to analyze the various contexts).
• Positive impact - Conda package let's to deal with external packages which can be used in Jupyter.

Incentivized

• It's one more development environment to learn - Negative
• It facilitates using Windows programmer resources on macOS projects - Positive
• It is fairly quick to learn, less time spent in training and skill development - Positive
• Integration with Copilot promotes "vibe coding" - Both Positive and Negative

Incentivized