Overall Satisfaction with Anaconda
The usage of Anaconda is not yet standard through the organization, but many people at my organization use it as the best way to create a standardized Python environment. In particular, the Miniconda distribution is preferred for deployment of Python-based containers, as it allows for a better, finer-grained installation in containers. For desktop users, the full Anaconda distribution is used, as it comes with several packages that are used throughout the organization: Astropy, NumPy, Matplotlib, Pandas, and others.
- Management of custom environments
- Support for standardizing deployments
- Deployment in containers using Miniconda
- Update of Conda packages is becoming slower. The 4.7 update was welcome, but seems to be regressing again.
- Anaconda (and especially Miniconda) has simplified our deployment strategy.
Anaconda has 64-bit support in the community edition, and package management is more in line with the way we think.
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?
Yes
Did implementation of Anaconda go as expected?
Yes
Would you buy Anaconda again?
Yes
Anaconda Feature Ratings
Using Anaconda
Pros | Cons |
---|---|
Like to use Relatively simple Easy to use Technical support not required Well integrated Consistent Quick to learn Convenient Feel confident using Familiar | None |
- Environment Update
- Package Management
- Managing non-standard channels