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Support pre-installed SciPy on Python #2650
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@thedrow Could you give estimates on how long those packages take to compile? |
Since Travis has a consistent environment, you might be able to just create a travis-ci wheel repository that pip will install from automatically. This will people install these projects in a pre-compiled fashion (and make things go faster) without needing to compile them during image build. |
Seconded, would love to see better scientific python support |
Hi, I was wondering if the miniconda workaround is still the preferred way of installing Numpy and Scipy. Basically if you do any kind of scientific computing using Python, you are going to use Numpy and Scipy. Note also that it is very tricky to install them using |
The default Travis-CI system image does not include scipy, so including it in requirements.txt will yield a build error. The current workaround employs miniconda to install both numpy and scipy, as referenced in travis-ci/travis-ci#2650. An alternate approach is proposed in travis-ci/travis-ci#2638.
Another workaround is to use |
Has there been any development on this issue? Whether it be a scientific-python distribution we can access, or is the current fix still to use work arounds? |
Nowadays there are pre-compiled binary wheels for NumPy and SciPy available via pip, which work nicely with TravisCI, e.g.
If you leave out the |
@peterjc When I copy&paste your pip install command I get PS: This is my first day as Travis user & the very first line of code I wrote into the .travis.yml file was for installing scipy, leading me here... |
@thorade You probably need to first do |
This trick is suggested in: travis-ci/travis-ci#2650
scipy is causing issues with travis-ci, trying some tips off travis-ci/travis-ci#2650
Use pip as opposed to apt-get to install numpy as Travis uses a virtualenv. See travis-ci/travis-ci#2650
Closing this now. Perhaps we can also document #2650 (comment). |
two approaches at play here; before this CL is a gist[1] by third-party to travis; *as of* this CL is a comment[2] about "it works this way" on the travis-ci issue queue. hopefully the latter is correct [1]: https://gist.github.com/dan-blanchard/7045057 [2]: travis-ci/travis-ci#2650 (comment)
See: travis-ci/travis-ci#2650 (comment) 3 and travis-ci/travis-ci#2650 (comment) 6 cross fingers!
Install NumPy and SciPy from PyPi binaries. See travis-ci/travis-ci#2650
See issue travis-ci/travis-ci#2650 for the suggestion to update pip and request the wheels for scipy and numpy. travis-ci/travis-ci#2650 (comment)
I found that using pip to install binaries worked really well for me- I was able to cut my testing in Python 3.4 down from 9 minutes to less than 1 minute. Python 3.5 and 3.6 already have numpy in their environments, so this didn't speed them up by more than a few seconds. I just added this to the install section: My complete .travis.yml |
Many Python packages depend on SciPy so it would be helpful to have a recent SciPy installed for each supported Python platform. It can be installed manually using a quite simple process (as I've described in #2638), but it takes about 15 minutes, and it is not easy to guess the requirements without referring to this ticket.
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