Is this ok ?

  Python 3.13.3 (main, May 21 2025, 07:49:52) [GCC 14.2.0] on linux
  Type "help", "copyright", "credits" or "license" for more 
 information.
  >>> import json
  >>>
 
 json.loads('47234762761726473624762746721647624764380000000000000000000000000000000000000000000')
 47234762761726473624762746721647624764380000000000000000000000000000000000000000000

▲ teddyh 2 months ago | parent | next [-]

I prefer

  >> import json, decimal
  >> j = "47234762761726473624762746721647624764380000000000000000000000000000000000000000000"
  >> json.loads(j, parse_float=decimal.Decimal, parse_int=decimal.Decimal)
  Decimal('47234762761726473624762746721647624764380000000000000000000000000000000000000000000')

This way you avoid this problem:

  >> import json
  >> j = "0.47234762761726473624762746721647624764380000000000000000000000000000000000000000000"
  >> json.loads(j)
  0.47234762761726473

And instead can get:

  >> import json, decimal
  >> j = "0.47234762761726473624762746721647624764380000000000000000000000000000000000000000000"
  >> json.loads(j, parse_float=decimal.Decimal, parse_int=decimal.Decimal)
  Decimal('0.47234762761726473624762746721647624764380000000000000000000000000000000000000000000')

▲ sevensor 2 months ago | parent | prev | next [-]

Just cross your fingers and hope for the best if your data is at any point decoded by a json library that doesn’t support bigints? Python’s ability to handle them is beside the point of they get mangled into ieee754 doubles along the way.

▲ jazzyjackson 2 months ago | parent | prev [-]

yes, python falls into the sane language category with arbitrary-precision arithmetic

▲ faresahmed 2 months ago | parent [-]

Not so much,

    >>> s="1"+"0"*4300
    >>> json.loads(s)
    ...
    ValueError: Exceeds the limit (4300 digits) for integer string conversion: 
    value has 4301 digits; use sys.set_int_max_str_digits() to increase the limit

This was done to prevent DoS attacks 3 years ago and have been backported to at least CPython 3.9 as it was considered a CVE.

Relevant discussion: https://news.ycombinator.com/item?id=32753235

Your sibling comment suggests using decimal.Decimal which handles parsing >4300 digit numbers (by default).

	▲	lifthrasiir 2 months ago \| parent [-]
		This should be interpreted as a stop-gap measure before a subquadratic algorithm can be adopted. Take a look at _pylong.py in new enough CPython.