> (I dont know why people need that either, my vague impression is that scence-y types want complete pushbutton installation, typing a command == fail, I guess, I dont know).
It started in a way similar to how Active Perl started. An attempt to build a reliable, curated and "batteries included" solution. (But it went downhill very quickly).
So, what were the problems:
* Most importantly, using Python on Windows is a pain (it still is, but less so). Many Python packages rely on native libraries which they don't provide. Even if they ship with some binary blob, that blob is often just a wrapper to the actual library. But, at the time Conda was created, even a binary blob was not an option. If you wanted to install stuff, you had to compile it. And, compiling on MS Windows is a world of pain. Especially, if you compile something for Python. Again, credit where it's due, Python sort of fixed some of these problems... but just a tiny bit. It still sucks a lot. So, conda is more of a MSYS2 really: it's a Linux user-space in Windows (firstly), and Python on top of that. But, it kind of also doesn't want to admit it, so, it still pretends it's Windows... but with a bunch of Linux-ey stuff...
* Secondly, pip was a joke until about a year ago. It was not really a package manager (it still isn't) and it couldn't properly solve dependencies (it sort of does today, but poorly because of source-distributions). Conda, when it worked, was at least somewhat consistent. (But usually, it just hangs). Also, conda is a package manager (however awful). I.e. with pip you can run install once, and then you can run a different install command again in the same environment, and god help you to make sure you have consistent dependencies between packages. Conda, in principle, should always keep your environment consistent. (But it hangs more often than not). Also, there's no such thing as installing from source with conda. If you want to use source: git clone, install conda-build and suffer through non-existent documentation and get help from non-existent community of people building conda packages.
* Conda provides a curated set of packages (a.k.a default channel). Anyone worth their salt ditches that channel the moment they install conda and installs everything from conda-forge (cuz its got more stuffs!) So, they tried curated. Didn't work.
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In a sense, I think that what happened is that conda was too ambitious of a project, using wrong technology to implement it. It also didn't have good enough planning for the kind of ambition they had. So, every time they came to solve a real problem, they didn't have time, human resources and system resources to solve it well. They've accumulated technical debt at close-to-light speed and ended up being a huge mess nobody knows how to deal with.
Some of the obvious mistakes would be: creating too many releases of conflicting packages. They should've worked on some sort of LTS solution, where they release a set of packages with very permissive dependencies of very few versions that had been proven to work well together. Instead it's very common for conda packages to be very peculiar (and without real need to do so) about the versions of their dependencies.
Conda people didn't build good CI. They often release absolutely broken packages, and only discover it retrospectively from community input. (Tensorflow would be a great example). This creates a lot of problems with automatic updates.
Conda gave in to community pressure and decided to build integration with pip. It doesn't work well, and it's not possible to make it work well, but they added this and a lot of people instantly created dependencies on this feature.
Conda picked a bone with some of the infra tools outside of Python ecosystem. In particular with CMake. This just adds an extra aspect of pain trying to build conda packages / work with native libraries / wrappers. It might seem like a minor thing, but it prevented a lot of people who might otherwise release packages both for conda and PyPI from doing so. Often package that is released to conda is ported by someone who's not the package author. It also means that sometimes the names of packages differ between conda and PyPI for the same package.
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NB. In terms of amount of commands you need to type when working with conda vs with PyPI tools is not noticeably different. Conda is, perhaps, more organized, but is also more buggy due to trying to integrate with various shells in special ways, and failing quite a bit.