That was exactly the reason I was very close to adopting Docker recently. But then I realized it was a very rare problem, in my experience. Maybe it’s because I always worked in small teams of <= 10 people, or maybe the stuff I work on tends to not cause local dev problems frequently. But I definitely see how Docker can help a lot there.
Even on teams of small people (< 10 people) you can quickly run into issues if you don't develop in the same environment you deploy. For example at one company I worked for, developers would use pypi packages but the operations team required us to deploy using the version of the python package available on the Debian our hosts ran. This would create not infrequent discrepancies that certainly could have been dealt with a number of ways, but would have been pretty simple if we could just bundle a single environment and use it locally and in production. Vagrant and VirtualBox VMs are another alternative (that we did use too!) but Docker allows you to get even closer more easily if teams can agree on it.
Being in operations and as a dev, I can tell you that is something operations people are doing wrong. They make their own life harder. What about dependencies that are not in the repo? Will they be building their own packages? What if one of packages has a bug discovered in production, will they create their own package with a bugfix risking breaking system components that might depend on the old version. What when the OS version is EOL to migrate now your app needs to be tested with the new OS, because it is tied to it. I have seen an upgrade from Python 2.6 to 2.7 being unnecessarily painful because of this, even though Python 2.6 code can run on Python 2.7 without changes.
You absolutely want your application to be disconnected from the system you running it on. Languages like Python or Java were designed to run the same not only on different OS but also on different architecture, why would you be ruining that?
With Python I highly recommend if you use redhat or CentOS to use IUS repo which let's you choose exact Python version you want to use. Then create a virtualenv with the exact dependencies you need. If your ops are standing on the way of this they are misinformed, because what they are suggesting ads a lot of unnecessary work for themselves as well with no tangible gain.
