

Anaconda
72 likes
Completely free enterprise-ready Python distribution for large-scale data processing, predictive analytics, and scientific computing. Includes 100+ of the most popular Python packages for science, math, engineering, data analysis. Cross platform on Linux, Windows, Mac.
Cost / License
- Free Personal
- Proprietary
Application type
Platforms
- Mac
- Windows
- Linux
- Python
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Comments and Reviews
Generally provides a functional environment , and it supports powershell and many other shells.
Perhaps I am too much of a casual user but it seems quite big and slow. Dependencies failed me twice and screwed up the environment (luckily I restored from a backup).
More importantly, unless I am mistaken, the software may be free but using the repositories is not anymore for any organization over 200 people (read all universities, medium to large companies, administrations, NGO, etc). I understand they have to pay the bills but advertising it as free/open source is kinda misleading because without repos, what would you do with the software?
Anaconda is unbearably slow, even tab completion or getting
--helptakes about 3 seconds, and resolving an environment before installing something takes minutes. When the dependencies are broken and incompatible you spend hours removing and adding them to figure out the mess. It's painfully slow.The command line flags are unintuitive, there's several ways to do some things and no way to do others. It punishes you for not doing things its way, which is usually a weird way, and it sucks all your time away. It curates a culture of "just get this mess working and don't touch it again" which is why everyone who uses it has no focus on efficiency or quality.
Even the project name is a conflict - they renamed their project to have the same name as another open source packaging system that had already been around for 5 years. The system is supposed to manage conflicts and the name itself is a conflict.
The only reason why it exists is because it allows you to install specific dependencies on Windows that you'd have to build otherwise. It hasn't been replaced because data science people are used to waiting a long time for huge jobs to complete, and that's exactly what managing an anaconda environment is - a huge job with lots of waiting around and trying different things in between, waiting seconds between keystrokes and staring at an ascii spinner.
It's 4:15 AM and I've been messing around with it for 19 hours now, and I'm beginning to think that writing scripts that download and build my dependencies on Windows would have been faster than interacting with this ugly mess. Sure, it all works, but my Docker containers are gigabytes and there's tons of annoying things are wrong in subtle ways, irritating little things that take multiple hours to debug and aren't worth the time.
If you value your time, try to get by without it. It's now my backup plan and I'm going to change direction if I can, and if I can't I'll be pretty sad about this ugly mess defecating my project.
Unless I'm mistaken, this one qualifies as open-source. Looking at the EULA (http://docs.continuum.io/anaconda/eula.html) it allows redistribution, modification, and creation of derivative works, for any purpose. Am I wrong?