Known Issues

While most bugs and issues are managed using the astropy issue tracker, this document lists issues that are too difficult to fix, may require some intervention from the user to workaround, or are due to bugs in other projects or packages.

Issues listed on this page are grouped into two categories: The first is known issues and shortcomings in actual algorithms and interfaces that currently do not have fixes or workarounds, and that users should be aware of when writing code that uses Astropy. Some of those issues are still platform-specific, while others are very general. The second category is common issues that come up when configuring, building, or installing Astropy. This also includes cases where the test suite can report false negatives depending on the context/ platform on which it was run.

Known deficiencies

Quantities lose their units with some operations

Quantities are subclassed from numpy’s ndarray and in some numpy operations (and in scipy operations using numpy internally) the subclass is ignored, which means that either a plain array is returned, or a Quantity without units. E.g.:

>>> import astropy.units as u
>>> import numpy as np
>>> q = u.Quantity(np.arange(10.), u.m)
>>> np.hstack((q,q)) 
<Quantity [0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 0., 1., 2., 3., 4., 5.,
           6., 7., 8., 9.] (Unit not initialised)>
>>> ratio = (3600 * u.s) / (1 * u.h)
>>> ratio 
<Quantity 3600. s / h>
>>> np.array(ratio) 
>>> np.array([ratio]) 

Work-arounds are available for some cases. For the above:

<Quantity 285. m2>

>>> np.array( 

>>> u.Quantity([q, q]).flatten() 
<Quantity [0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 0., 1., 2., 3., 4., 5.,
           6., 7., 8., 9.] m>

An incomplete list of specific functions which are known to exhibit this behavior follows.


Care has to be taken when setting array slices using Quantities:

>>> a = np.ones(4)
>>> a[2:3] = 2*
>>> a 
array([1., 1., 2., 1.])
>>> a = np.ones(4)
>>> a[2:3] = 1*
>>> a 
array([1., 1., 1., 1.])

Either set single array entries or use lists of Quantities:

>>> a = np.ones(4)
>>> a[2] = 1*
>>> a 
array([1.  , 1.  , 0.01, 1.  ])
>>> a = np.ones(4)
>>> a[2:3] = [1*]
>>> a 
array([1.  , 1.  , 0.01, 1.  ])

Both will throw an exception if units do not cancel, e.g.:

>>> a = np.ones(4)
>>> a[2] = 1* 
Traceback (most recent call last):
TypeError: only dimensionless scalar quantities can be converted to Python scalars


Quantities lose their units when broadcasted

When broadcasting Quantities, it is necessary to pass subok=True to broadcast_to, or else a bare ndarray will be returned:

>>> q = u.Quantity(np.arange(10.), u.m)
>>> b = np.broadcast_to(q, (2, len(q)))
>>> b 
array([[0., 1., 2., 3., 4., 5., 6., 7., 8., 9.],
       [0., 1., 2., 3., 4., 5., 6., 7., 8., 9.]])
>>> b2 = np.broadcast_to(q, (2, len(q)), subok=True)
>>> b2 
<Quantity [[0., 1., 2., 3., 4., 5., 6., 7., 8., 9.],
           [0., 1., 2., 3., 4., 5., 6., 7., 8., 9.]] m>

This is analogous to the case of passing a Quantity to array:

>>> a = np.array(q)
>>> a 
array([0., 1., 2., 3., 4., 5., 6., 7., 8., 9.])
>>> a2 = np.array(q, subok=True)
>>> a2 
<Quantity [0., 1., 2., 3., 4., 5., 6., 7., 8., 9.] m>


Quantities float comparison with np.isclose fails

Comparing Quantities floats using the numpy function isclose fails on numpy 1.9 as the comparison between a and b is made using the formula

\[|a - b| \le (a_\textrm{tol} + r_\textrm{tol} \times |b|)\]

This will result in the following traceback when using this with Quantities:

>>> from astropy import units as u, constants as const
>>> import numpy as np
>>> np.isclose(500 *, 300 * / u.s)
Traceback (most recent call last):
astropy.units.core.UnitsError: Can only apply 'add' function to dimensionless quantities when other argument is not
a quantity (unless the latter is all zero/infinity/nan)

An easy solution is:

>>> np.isclose(500 *, 300 * / u.s, atol=1e-8 * / u.s) 

Quantities in np.linspace failure on numpy 1.10

linspace does not work correctly with quantities when using numpy 1.10.0 to 1.10.5 due to a bug in numpy. The solution is to upgrade to numpy 1.10.6 or later, in which the bug was fixed.

mmap support for on GNU Hurd

On Hurd and possibly other platforms flush() on memory-mapped files is not implemented, so writing changes to a mmap’d FITS file may not be reliable and is thus disabled. Attempting to open a FITS file in writeable mode with mmap will result in a warning (and mmap will be disabled on the file automatically).


Bug with unicode endianness in io.fits for big-endian processors

On big-endian processors (e.g. SPARC, PowerPC, MIPS), string columns in FITS files may not be correctly read when using the interface. This will be fixed in a subsequent bug fix release of Astropy (see bug report here)

Color printing on Windows

Colored printing of log messages and other colored text does work in Windows but only when running in the IPython console. Colors are not currently supported in the basic Python command-line interpreter on Windows.

Build/installation/test issues

Anaconda users should upgrade with conda, not pip

Upgrading Astropy in the anaconda python distribution using pip can result in a corrupted install with a mix of files from the old version and the new version. Anaconda users should update with conda update astropy. There may be a brief delay between the release of Astropy on PyPI and its release via the conda package manager; users can check the availability of new versions with conda search astropy.

Locale errors in MacOS X and Linux

On MacOS X, you may see the following error when running

ValueError: unknown locale: UTF-8

This is due to the LC_CTYPE environment variable being incorrectly set to UTF-8 by default, which is not a valid locale setting.

On MacOS X or Linux (or other platforms) you may also encounter the following error:

  stderr = stderr.decode(stdio_encoding)
TypeError: decode() argument 1 must be str, not None

This also indicates that your locale is not set correctly.

To fix either of these issues, set this environment variable, as well as the LANG and LC_ALL environment variables to e.g. en_US.UTF-8 using, in the case of bash:

export LANG="en_US.UTF-8"
export LC_ALL="en_US.UTF-8"
export LC_CTYPE="en_US.UTF-8"

To avoid any issues in future, you should add this line to your e.g. ~/.bash_profile or .bashrc file.

To test these changes, open a new terminal and type locale, and you should see something like:

$ locale

If so, you can go ahead and try running again (in the new terminal).

Creating a Time object fails with ValueError after upgrading Astropy

In some cases, have users have upgraded Astropy from an older version to v1.0 or greater they have run into the following crash when trying to create a Time object:

>>> from astropy.time import Time
>>> datetime = Time('2012-03-01T13:08:00', scale='utc') 
Traceback (most recent call last):
ValueError: Input values did not match any of the formats where
the format keyword is optional [u'astropy_time', u'datetime',
u'jyear_str', u'iso', u'isot', u'yday', u'byear_str']

This problem can occur when there is a version mismatch between the compiled ERFA library (this is included as part of Astropy in most distributions), and the version of the Astropy Python source.

This can have a number of causes. The most likely is that when installing the new Astropy version, your previous Astropy version was not fully uninstalled first, resulting in a mishmash of versions. Your best bet is to fully remove Astropy from its installation path, and reinstall from scratch using your preferred installation method. How to remove the old version may be a simple matter if removing the entire astropy/ directory from within the site-packages directory it is installed in. However, if in doubt, ask how best to uninstall packages from your preferred Python distribution.

Another possible cause of this, in particular for people developing on Astropy and installing from a source checkout, is simply that your Astropy build directory is unclean. To fix this, run git clean -dfx. This removes all build artifacts from the repository that aren’t normally tracked by git. Make sure before running this that there are no untracked files in the repository you intend to save. Then rebuild/reinstall from the clean repo.

Failing logging tests when running the tests in IPython

When running the Astropy tests using astropy.test() in an IPython interpreter some of the tests in the astropy/tests/ might fail, depending on the version of IPython or other factors. This is due to mutually incompatible behaviors in IPython and py.test, and is not due to a problem with the test itself or the feature being tested.


Some docstrings can not be displayed in IPython < 0.13.2

Displaying long docstrings that contain Unicode characters may fail on some platforms in the IPython console (prior to IPython version 0.13.2):

In [1]: import astropy.units as u

In [2]: u.Angstrom?
Out[2]: ERROR: UnicodeEncodeError: 'ascii' codec can't encode character u'\xe5' in
position 184: ordinal not in range(128) []

This can be worked around by changing the default encoding to utf-8 by adding the following to your file:

import sys

Note that in general, this is not recommended, because it can hide other Unicode encoding bugs in your application. However, in general if your application does not deal with text processing and you just want docstrings to work, this may be acceptable.

The IPython issue:

Compatibility issues with pytest 3.7 and later

Due to a bug in pytest related to test collection, the tests for the core astropy package for version 2.0.x (LTS), and for packages using the core package’s test infrastructure and being tested against 2.0.x (LTS) will not be executed correctly with pytest 3.7, 3.8, or 3.9. The symptom of this bug is that no tests or only tests in RST files are collected. In addition, astropy 2.0.x (LTS) is not compatible with pytest 4.0 and above as in this case deprecation errors from pytest can cause tests to fail. Therefore, when testing against astropy v2.0.x (LTS), pytest 3.6 or earlier versions should be used. These issues do not occur in version 3.0.x and above of the core package.

There is also an unrelated issue that also affects more recent versions of astropy when testing with pytest 4.0 and later, which can cause issues when collecting tests - in this case, the symptom is that the test collection hangs and/or appears to run the tests recursively. If you are maintaining a package that was created using the astropy package template, then this can be fixed by updating to the latest version of the file. The root cause of this issue is that pytest now tries to pick up the top-level test() function as a test, so we need to make sure that we set a test.__test__ attribute on the function to False.