Big guns for big scale projects: Anaconda
May 10, 2021
Big guns for big scale projects: Anaconda
Score 7 out of 10
Vetted Review
Verified User
Overall Satisfaction with Anaconda
Anaconda is a great package manager for large-scale projects with multiple dependencies and support for multiple versions of python. It offers us out-of-the-box capabilities for major common data science use cases and projects. Really robust in terms of switching execution environment and offers granular control over the Conda virtual environments. It is used across our organization as it has really great community support and they offer solutions in case we are stuck as well.
- Python environment management.
- Package management.
- Out of the box installed with commonly used packages.
- Support for R as well.
- Has a learning curve before getting comfortable.
- Pretty heavy installation due to included packages.
- Only great for larger projects.
- Requires a lot of memory to run kernels.
- Different code editors like Spyder, Jupyter Lab, R studio.
- Centralized package management for projects.
- Inbuilt packages save time for installation.
- Less overhead in terms of package management.
- Robust changes for python virtual environment config.
- Requires high machine memory.
If the project is not large scale then Jupiter notebooks or Visual Studio Code serve well. If you don't have any dependency on Python versions, these IDEs can be well suited for fast development and deployment.
Do you think Anaconda delivers good value for the price?
Yes
Are you happy with Anaconda's feature set?
Yes
Did Anaconda live up to sales and marketing promises?
I wasn't involved with the selection/purchase process
Did implementation of Anaconda go as expected?
Yes
Would you buy Anaconda again?
Yes