Anaconda vs. Microsoft Visual Studio

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

It's useful for app development, debugging, and testing. I've been using it for two years and have seen it grow into a fantastic tool. All of the features, NuGet packages, and settings that enable different types of projects are fantastic. It also has a connection to Azure DevOps and Git. It's a fantastic product that's simple to use.

• 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

• Rock solid intellisense. For C# and VB.Net code, the intellisense provided by Visual Studio is hands down the best. If you find that you have a hard time remembering parameters of functions, or what object names were, the intellisense will rescue you and help me be an efficient developer.
• Super fast and simple to use debugger for C# and VB. Everything in the debugger is handed to you on a silver platter. When you stop on a break point, it immediately shows you the local variables, the call stack, and even your current memory usage. Setting up watch variables is super simple and you can even make breakpoints conditional so it will only stop on certain conditions.
• Hides the tedious tasks. There are quite a few things like publishing, creating click once deployments, and adding/removing settings in the project files that can be really time consuming when trying to do it by hand (such as if you don't have access to Visual Studio and you need to make changes). Visual Studio hides all the tedium from you by making nice point and click interfaces to get things done quickly.

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

• Certain settings and features can sometimes be challenging to locate. The interface isn't always intuitive.
• Sometimes there are too many ways to do the same thing. For example, users can quickly add a new workspace in Source Control Explorer when a local path shows as "Not Mapped," but it doesn't indicate that the user might want to check the dropdown list of workspaces. The shortcut of creating a new workspace by clicking on the "Not Mapped" link can lead to developers creating too many workspaces and causing workspace management to become unwieldy. If the shortcut link were removed, the user would be forced to use the Workspace dropdown. While it can add an extra step to the process, workspaces would be managed more easily, and this would enforce consistency. At the very least, there should be a high-level administrative setting to hide the shortcut link.

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

VS is the best and is required for building Microsoft applications. The quality and usefulness of the product far out-weight the licensing costs associated with it.

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

The thing I like the most is Visual Studio doesn't suffer from Microsoft's over eager marketing department who feel they need to redesign the UI (think Office and windows) which forces users to loose large amounts of productivity having to learn software that they had previously known.

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

Between online forums like StackOverflow, online documentation, MSDN forums, and the customer support options, I find it very easy to get support for Visual Studio IDE when I need it. If desired, one can also download the MSDN documentation about the IDE and have it readily available for any support needs.

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

I personally feel Visual Studio IDE has [a] better interface and [is more] user friendly than other IDEs. It has better code maintainability and intellisense. Its inbuilt team foundation server help coders to check on their code then and go. Better nugget package management, quality testing and gives features to extract TRX file as result of testing which includes all the summary of each test case.

• 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

• Using the integration between Visual Studio and our source control service, the cost of re-work and losing code is drastically reduced.
• Paid versions of Visual Studio enable developers to be so much more productive than hacked-together open source solutions that it's hard to imagine developing in Windows without it.
• When combined with support subscriptions and the vast array of free online help options available, Visual Studio saves our developers time by keeping them coding and testing, not wasting their time trying to guess their way out of problems or spend endless hours online hoping to find answers.

Incentivized