As the Conda package ecosystem evolves and third-party software updates are released by Continuum and other providers, this may interfere with the stability of other codebases, such as STScI’s software. This page will proactively chronicle such events as they occur as well as provide workarounds to these issues.
Problematic Conda Versions¶
These versions of the conda package and environment management tool itself are known to cause problems when installing Astroconda packages, including pipeline environments. They are to be avoided if at all possible.
conda --version will display the version you have installed.
|Avoid use of Conda Version|
If you have an indicated version of conda installed you may want to upgrade to a newer version with
conda update conda
Once completed, check that the newly installed version is not indicated above as a problematic version. If it is indicated, you may have to downgrade to a previous version of conda in order to obtain one that has not been identified problematic.
conda search conda
will display a list of all versions of conda available. Select a version from the search list that does not appear in the table above and run
conda install conda=<version>.
If you spot a compatibility problem not listed here please let us know by sending an email to help[at]stsci.edu.
You may be affected by an issue if you have updated your AstroConda environment on or after the dates listed in each section below.
If you have installed or updated
stwcs into a Python 2.7 environment, be aware, the release of
stwcs (v1.4.0) is not compatible with Python 2.7.
stwcs v1.4.0 is known to negatively impact the following packages:
For anyone that has already installed
stwcs (v1.4.0), the latest release of
stsci-hst (v3.0.1) will automatically downgrade
stwcs to v1.3.2. This downgrade behavior will not be observed in environments where the installed version of
stwcs is less than v1.4.0.
As of 2018-02-01, the Python 2.7 release of
stwcs v1.4.0 was removed from the AstroConda channel.
Am I affected?¶
find you can scan your Conda environments for
stwcs v1.4.0. Be sure to replace
/home/example/miniconda3 with the path to your Anaconda or Miniconda installation. Depending on the number of environments installed and the seek time of your storage medium, this operation may take up to several minutes to complete.
$ find /home/example/miniconda3/envs \ -wholename '*/lib/python2.7/site-packages/stwcs/version.py' \ | xargs grep --color -H "__version__.*'1.4.0'"
If no matches are returned, then you are not affected by this release, and no action required.
Otherwise, you may see results such as:
~/miniconda3/envs/astroconda27/lib/python2.7/site-packages/stwcs/version.py:__version__ = '1.4.0' ~/miniconda3/envs/iraf27/lib/python2.7/site-packages/stwcs/version.py:__version__ = '1.4.0'
In this example output, the
iraf27 Conda environments require your attention.
Repairing your Environment(s)¶
Conda keeps a local cache of packages to help speed up installations and upgrades. In order to safeguard against reinstalling the incorrect version of
stwcs it is recommended that you purge this cache.
This operation will not adversely affect your Conda installation. Packages will be redownloaded during the next installation or upgrade operation.
$ conda clean --yes --index-cache --tarballs --packages
stsci-hst package for each affected environment:
$ conda update -n ENV_NAME_HERE stsci-hst
Or if you prefer to manually downgrade
stwcs, do this instead:
$ conda install -n ENV_NAME_HERE stwcs=1.3.2
The method used to install IRAF via AstroConda has changed!
Before today, AstroConda’s
iraf package provided a full IRAF installation in a single tarball. Not only did this take a long time to install, it has proven to be problematic, because updating even one line of code required us to repackage >700MBs of data. As of now, IRAF has been split into several smaller packages (
iraf.[pkg]) and controlled via a single meta-package:
iraf-all. The new
pyraf-all meta-package installs
pyraf along with packages identified to require
iraf. The installation section, Legacy Software Stack (with IRAF), has been updated to reflect the changes detailed below.
To install a new IRAF environment:
$ conda create -n iraf27 python=2.7 iraf-all pyraf-all stsci $ source activate iraf27
If you plan to update an existing “iraf27” environment, do the following:
$ conda install -n iraf27 iraf-all pyraf-all $ source activate iraf27
conda update will not work as expected in this case, due to the fact that the
iraf package no longer serves the same purpose. After
iraf-all has been installed you may continue to use
conda update --all to perform general updates.
Astropy removed yet another deprecated function in v2.0; namely
This function was called by
stpyfits, which gets used by in the HST pipeline
as called by the
drizzlepac to transparently handle
_raw.fits HST data.
The deprecation is addressed in order to allow the next release to work in the
operational HST calibration pipeline build, HSTDP 2017.2
>>> sdq = stpyfits.getdata("j9ot10icq_raw.fits", extname="DQ", extver=1) WARNING: AstropyDeprecationWarning: The NumCode class attribute is deprecated and may be removed in a future version. Use the module level constant BITPIX2DTYPE instead. [astropy.utils.decorators]
A collection of errant release candidate packages were published to the AstroConda public channel (http://ssb.stsci.edu/astroconda) on Friday, Apr 28, 2017 around 3:45pm and remained available for download until 10:30am on Tuesday, May 2, 2017. If you updated/upgraded any of the following packages during that window, you may have retrieved and installed software which is unsuitable for use due to untested behavior.
The affected packages:
If any of these errant packages appear in a
conda list of your environment, please revert to the last known-good release version by issuing a
conda install <package>=<goodversion> for each package.
We apologize for any inconvenience introduced by this unintended sofware release.
NumPy v1.12.0 modified the way array slicing is handled and triggered
a regression in the
acstools <= 2.0.6- 2.0.7 released (Feb 16, 2017)
pysynphot <= 0.9.8.5- 0.9.8.6 released (Feb 21, 2017)
One of the traceback messages to be aware of is as follows (traceback may be worded differently but usually complains about index not being an integer):
TypeError('slice indices must be integers or None or have an __index__ method',)
Recommended user actions:
acstoolsto version 2.0.7 (i.e.,
conda update acstools)
pysynphotto version 0.9.8.6 (i.e.,
conda update pysynphot)
Alternative user action:
numpyto version 1.11 (i.e.,
conda install numpy=1.11)
AstroPy v1.3 fully deprecated calls to
The following packages are known to be incompatible with this release:
calcos <= 3.1.8- 3.2.1 released (Jul 06, 2017)
costools <= 1.2.1- Bugfix pending
fitsblender <= 0.2.6- 0.3.0 released (Jan 17, 2017)
Recommended user actions:
fitsblenderto version 0.3.0 (i.e.,
conda update fitsblender)
Alternative user actions:
astropyto version 1.2.1 (i.e.,
conda install astropy=1.2.1)
A list of known deprecation warnings detected in regression tests managed by STScI Science Software Branch is available here. This list is refreshed daily from “dev” and “public” test results.
These deprecation warnings have been fixed in
which is now available in AstroConda: