PyFITS has built in a flexible scheme to verify FITS data being conforming to the FITS standard. The basic verification philosophy in PyFITS is to be tolerant in input and strict in output.

When PyFITS reads a FITS file which is not conforming to FITS standard, it will not raise an error and exit. It will try to make the best educated interpretation and only gives up when the offending data is accessed and no unambiguous interpretation can be reached.

On the other hand, when writing to an output FITS file, the content to be written must be strictly compliant to the FITS standard by default. This default behavior can be overwritten by several other options, so the user will not be held up because of a minor standard violation.

FITS Standard

Since FITS standard is a “loose” standard, there are many places the violation can occur and to enforce them all will be almost impossible. It is not uncommon for major observatories to generate data products which are not 100% FITS compliant. Some observatories have also developed their own sub-standard (dialect?) and some of these become so prevalent that they become de facto standards. Examples include the long string value and the use of the CONTINUE card.

The violation of the standard can happen at different levels of the data structure. PyFITS’s verification scheme is developed on these hierarchical levels. Here are the 3 PyFITS verification levels:

  1. The HDU List
  2. Each HDU
  3. Each Card in the HDU Header

These three levels correspond to the three categories of PyFITS objects: HDUList, any HDU (e.g. PrimaryHDU, ImageHDU, etc.), and Card. They are the only objects having the verify() method. Most other classes in PyFITS do not have a verify() method.

If verify() is called at the HDU List level, it verifies standard compliance at all three levels, but a call of verify() at the Card level will only check the compliance of that Card. Since PyFITS is tolerant when reading a FITS file, no verify() is called on input. On output, verify() is called with the most restrictive option as the default.

Verification Options

There are several options accepted by all verify(option) calls in PyFITS. In addition, they available for the output_verify argument of the following methods: close(), writeto(), and flush(). In these cases, they are passed to a verify() call within these methods. The available options are:


This option will raise an exception, if any FITS standard is violated. This is the default option for output (i.e. when writeto(), close(), or flush() is called. If a user wants to overwrite this default on output, the other options listed below can be used.


This option is the same as the ignore option but will send warning messages. It will not try to fix any FITS standard violations whether fixable or not.


This option will ignore any FITS standard violation. On output, it will write the HDU List content to the output FITS file, whether or not it is conforming to the FITS standard.

The ignore option is useful in the following situations:

  1. An input FITS file with non-standard formatting is read and the user wants to copy or write out to an output file. The non-standard formatting will be preserved in the output file.
  2. A user wants to create a non-standard FITS file on purpose, possibly for testing or consistency.

No warning message will be printed out. This is like a silent warning option (see below).


This option will try to fix any FITS standard violations. It is not always possible to fix such violations. In general, there are two kinds of FITS standard violations: fixable and non-fixable. For example, if a keyword has a floating number with an exponential notation in lower case ‘e’ (e.g. 1.23e11) instead of the upper case ‘E’ as required by the FITS standard, it is a fixable violation. On the other hand, a keyword name like ‘P.I.’ is not fixable, since it will not know what to use to replace the disallowed periods. If a violation is fixable, this option will print out a message noting it is fixed. If it is not fixable, it will throw an exception.

The principle behind fixing is to do no harm. For example, it is plausible to ‘fix’ a Card with a keyword name like ‘P.I.’ by deleting it, but PyFITS will not take such action to hurt the integrity of the data.

Not all fixes may be the “correct” fix, but at least PyFITS will try to make the fix in such a way that it will not throw off other FITS readers.


Same as fix, but will not print out informative messages. This may be useful in a large script where the user does not want excessive harmless messages. If the violation is not fixable, it will still throw an exception.

In addition, as of PyFITS version 3.3.0 the following ‘combined’ options are available:

  • fix+ignore
  • fix+warn
  • fix+exception
  • silentfix+ignore
  • silentfix+warn
  • silentfix+exception

These options combine the semantics of the basic options. For example silentfix+exception is actually equivalent to just silentfix in that fixable errors will be fixed silently, but any unfixable errors will raise an exception. On the other hand silentfix+warn will issue warnings for unfixable errors, but will stay silent about any fixed errors.

Verifications at Different Data Object Levels

We’ll examine what PyFITS’s verification does at the three different levels:

Verification at HDUList

At the HDU List level, the verification is only for two simple cases:

  1. Verify that the first HDU in the HDU list is a Primary HDU. This is a fixable case. The fix is to insert a minimal Primary HDU into the HDU list.
  2. Verify second or later HDU in the HDU list is not a Primary HDU. Violation will not be fixable.

Verification at Each HDU

For each HDU, the mandatory keywords, their locations in the header, and their values will be verified. Each FITS HDU has a fixed set of required keywords in a fixed order. For example, the Primary HDU’s header must at least have the following keywords:

SIMPLE =                     T /
BITPIX =                     8 /
NAXIS  =                     0

If any of the mandatory keywords are missing or in the wrong order, the fix option will fix them:

>>> hdu.header               # has a 'bad' header
SIMPLE =                     T /
NAXIS  =                     0
BITPIX =                     8 /
>>> hdu.verify('fix')          # fix it
Output verification result:
'BITPIX' card at the wrong place (card 2). Fixed by moving it to the right
place (card 1).
>>> h.header                 # voila!
SIMPLE =                     T / conforms to FITS standard
BITPIX =                     8 / array data type
NAXIS  =                     0

Verification at Each Card

The lowest level, the Card, also has the most complicated verification possibilities. Here is a lit of fixable and not fixable Cards:

Fixable Cards:

  1. floating point numbers with lower case ‘e’ or ‘d’
  2. the equal sign is before column 9 in the card image
  3. string value without enclosing quotes
  4. missing equal sign before column 9 in the card image
  5. space between numbers and E or D in floating point values
  6. unparseable values will be “fixed” as a string

Here are some examples of fixable cards:

>>> hdu.header[4:] # has a bunch of fixable cards
FIX1 = 2.1e23
FIX2= 2
FIX3 = string value without quotes
FIX4 2
FIX5 = 2.4 e 03
FIX6 = '2 10 '
>>> hdu.header[5]  # can still access the values before the fix
>>> hdu.header['fix4']
>>> hdu.header['fix5']
>>> hdu.verify('silentfix')
>>> hdu.header[4:]
FIX1 = 2.1E23
FIX2 = 2
FIX3 = 'string value without quotes'
FIX4 = 2
FIX5 = 2.4E03
FIX6 = '2 10 '

Unfixable Cards:

  1. illegal characters in keyword name

We’ll summarize the verification with a “life-cycle” example:

>>> h = pyfits.PrimaryHDU() # create a PrimaryHDU
>>> # Try to add an non-standard FITS keyword 'P.I.' (FITS does no allow
>>> # '.' in the keyword), if using the update() method - doesn't work!
>>> h['P.I.'] = 'Hubble'
ValueError: Illegal keyword name 'P.I.'
>>> # Have to do it the hard way (so a user will not do this by accident)
>>> # First, create a card image and give verbatim card content (including
>>> # the proper spacing, but no need to add the trailing blanks)
>>> c = pyfits.Card.fromstring("P.I. = 'Hubble'")
>>> h.header.append(c)  # then append it to the header
>>> # Now if we try to write to a FITS file, the default output
>>> # verification will not take it.
>>> h.writeto('pi.fits')
Output verification result:
HDU 0:
  Card 4:
    Unfixable error: Illegal keyword name 'P.I.'
  raise VerifyError
>>> # Must set the output_verify argument to 'ignore', to force writing a
>>> # non-standard FITS file
>>> h.writeto('pi.fits', output_verify='ignore')
# Now reading a non-standard FITS file
# pyfits is magnanimous in reading non-standard FITS file
>>> hdus ='pi.fits')
>>> hdus[0].header
SIMPLE =            T / conforms to FITS standard
BITPIX =            8 / array data type
NAXIS  =            0 / number of array dimensions
EXTEND =            T
P.I.   = 'Hubble'
>>> # even when you try to access the offending keyword, it does NOT
>>> # complain
>>> hdus[0].header['p.i.']
>>> # But if you want to make sure if there is anything wrong/non-standard,
>>> # use the verify() method
>>> hdus.verify()
Output verification result:
HDU 0:
  Card 4:
    Unfixable error: Illegal keyword name 'P.I.'

Verification using the FITS Checksum Keyword Convention

The North American FITS committee has reviewed the FITS Checksum Keyword Convention for possible adoption as a FITS Standard. This convention provides an integrity check on information contained in FITS HDUs. The convention consists of two header keyword cards: CHECKSUM and DATASUM. The CHECKSUM keyword is defined as an ASCII character string whose value forces the 32-bit 1’s complement checksum accumulated over all the 2880-byte FITS logical records in the HDU to equal negative zero. The DATASUM keyword is defined as a character string containing the unsigned integer value of the 32-bit 1’s complement checksum of the data records in the HDU. Verifying the the accumulated checksum is still equal to negative zero provides a fairly reliable way to determine that the HDU has not been modified by subsequent data processing operations or corrupted while copying or storing the file on physical media.

In order to avoid any impact on performance, by default PyFITS will not verify HDU checksums when a file is opened or generate checksum values when a file is written. In fact, CHECKSUM and DATASUM cards are automatically removed from HDU headers when a file is opened, and any CHECKSUM or DATASUM cards are stripped from headers when a HDU is written to a file. In order to verify the checksum values for HDUs when opening a file, the user must supply the checksum keyword argument in the call to the open convenience function with a value of True. When this is done, any checksum verification failure will cause a warning to be issued (via the warnings module). If checksum verification is requested in the open, and no CHECKSUM or DATASUM cards exist in the HDU header, the file will open without comment. Similarly, in order to output the CHECKSUM and DATASUM cards in an HDU header when writing to a file, the user must supply the checksum keyword argument with a value of True in the call to the writeto function. It is possible to write only the DATASUM card to the header by supplying the checksum keyword argument with a value of ‘datasum’.

Here are some examples:

>>> # Open the file pix.fits verifying the checksum values for all HDUs
>>> hdul ='pix.fits', checksum=True)
>>> # Open the file in.fits where checksum verification fails for the
>>> # primary HDU
>>> hdul ='in.fits', checksum=True)
Warning:  Checksum verification failed for HDU #0.
>>> # Create file out.fits containing an HDU constructed from data and
>>> # header containing both CHECKSUM and DATASUM cards.
>>> pyfits.writeto('out.fits', data, header, checksum=True)
>>> # Create file out.fits containing all the HDUs in the HDULIST
>>> # hdul with each HDU header containing only the DATASUM card
>>> hdul.writeto('out.fits', checksum='datasum')
>>> # Create file out.fits containing the HDU hdu with both CHECKSUM
>>> # and DATASUM cards in the header
>>> hdu.writeto('out.fits', checksum=True)
>>> # Append a new HDU constructed from array data to the end of
>>> # the file existingfile.fits with only the appended HDU
>>> # containing both CHECKSUM and DATASUM cards.
>>> pyfits.append('existingfile.fits', data, checksum=True)