lock fails with conditional dependencies on sys_platform

tldr: Locking fails when a dependency isn’t available on the current platform, even though it’s declared conditional on the platform.

Background

I have a machine learning project where development happens on macOS and longer training runs on linux machines with gpus, for which I use tensorflow. Tensorflow uses different packages depending on if you use gpu or not (tensorflow vs tensorflow-gpu).

The availability for these packages looks like the following:
tensorflow==1.6.0: linux - ✅ | macOS ✅ tensorflow-gpu==1.6.0: linux - ✅ | macOS ❌

In the Pipfile the tensorflow requirement is specified as follows:

tensorflow = {version = "==1.6.0", sys_platform = "== 'darwin'"}
tensorflow-gpu = {version = "==1.6.0", sys_platform = "!= 'darwin'"}

Problem

If I create the Pipfile.lock on the linux machine, and the run pipenv sync with that lockfile on a mac everything installs fine. However, if I try to add a new requirement on a mac (e.g. pipenv install requests), which results in pipenv creating another lock, it fails because it can’t find the requirement tensorflow-gpu==1.6.0.

Describe your environment

1. OS Type: macOS Version 10.13.3
2. Python version: 3.5.2
3. Pipenv version: 11.1.7

Expected result

>> pipenv lock
Locking [dev-packages] dependencies…
Locking [packages] dependencies…

Or: to be able to use pipenv together with PEP508 dependency specification to do cross-platform development in situations where a specific package is only available on one platform.

Actual result

>> pipenv lock --verbose
Locking [dev-packages] dependencies…
Using pip: -i https://pypi.python.org/simple

                          ROUND 1
Current constraints:

Finding the best candidates:

Finding secondary dependencies:
------------------------------------------------------------
Result of round 1: stable, done

Locking [packages] dependencies…
Using pip: -i https://pypi.python.org/simple

                          ROUND 1
Current constraints:
  requests
  tensorflow==1.6.0
  tensorflow-gpu==1.6.0

Finding the best candidates:
  found candidate requests==2.18.4 (constraint was <any>)
  found candidate tensorflow==1.6.0 (constraint was ==1.6.0)
  found candidate tensorflow-gpu==1.6.0 (constraint was ==1.6.0)

Finding secondary dependencies:
Using pip: -i https://pypi.python.org/simple

                          ROUND 1
Current constraints:
  requests
  tensorflow==1.6.0
  tensorflow-gpu==1.6.0

Finding the best candidates:
  found candidate requests==2.18.4 (constraint was <any>)
  found candidate tensorflow==1.6.0 (constraint was ==1.6.0)
  found candidate tensorflow-gpu==1.6.0 (constraint was ==1.6.0)

Finding secondary dependencies:
  requests==2.18.4          requires certifi>=2017.4.17, chardet<3.1.0,>=3.0.2, idna<2.7,>=2.5, urllib3<1.23,>=1.21.1


CRITICAL:pip.index:Could not find a version that satisfies the requirement tensorflow-gpu==1.6.0 (from versions: 0.12.0rc1, 0.12.0, 0.12.1, 1.0.0, 1.0.1, 1.1.0rc1, 1.1.0rc2, 1.1.0)
Warning: Your dependencies could not be resolved. You likely have a mismatch in your sub-dependencies.
  You can use $ pipenv install --skip-lock to bypass this mechanism, then run $ pipenv graph to inspect the situation.
No matching distribution found for tensorflow-gpu==1.6.0

Steps to replicate

Pipfile:

[[source]]

name = "pypi"
url = "https://pypi.python.org/simple"
verify_ssl = true


[packages]

tensorflow-gpu = {version = "==1.6.0", sys_platform = "!= 'darwin'"}
tensorflow = {version = "==1.6.0", sys_platform = "== 'darwin'"}
requests = "*"


[dev-packages]



[requires]

python_version = "3.5"

On macOS run:

pipenv lock

[kennethreitz]

v11.1.8 released, which includes this fix!

[kennethreitz]

will investigate — thank you for the report!