How to overcome "datetime.datetime not JSON serializable"?

Question

I have a basic dict as follows:

sample = {} sample['title'] = "String" sample['somedate'] = somedatetimehere 

When I try to do jsonify(sample) I get:

TypeError: datetime.datetime(2012, 8, 8, 21, 46, 24, 862000) is not JSON serializable 

What can I do such that my dictionary sample can overcome the error above?

Note: Though it may not be relevant, the dictionaries are generated from the retrieval of records out of mongodb where when I print out str(sample['somedate']), the output is 2012-08-08 21:46:24.862000.

Answer 1

Building on other answers, a simple solution based on a specific serializer that just converts datetime.datetime and datetime.date objects to strings.

from datetime import date, datetime  def json_serial(obj):     """JSON serializer for objects not serializable by default json code"""      if isinstance(obj, (datetime, date)):         return obj.isoformat()     raise TypeError ("Type %s not serializable" % type(obj)) 

As seen, the code just checks to find out if object is of class datetime.datetime or datetime.date, and then uses .isoformat() to produce a serialized version of it, according to ISO 8601 format, YYYY-MM-DDTHH:MM:SS (which is easily decoded by JavaScript). If more complex serialized representations are sought, other code could be used instead of str() (see other answers to this question for examples). The code ends by raising an exception, to deal with the case it is called with a non-serializable type.

This json_serial function can be used as follows:

from datetime import datetime from json import dumps  print dumps(datetime.now(), default=json_serial) 

The details about how the default parameter to json.dumps works can be found in Section Basic Usage of the json module documentation.

Answer 2

My quick & dirty JSON dump that eats dates and everything:

json.dumps(my_dictionary, indent=4, sort_keys=True, default=str) 

default is a function applied to objects that aren't serializable.
In this case it's str, so it just converts everything it doesn't know to strings. Which is great for serialization but not so great when deserializing (hence the "quick & dirty") as anything might have been string-ified without warning, e.g. a function or numpy array.