I've just been moving some code over to a Ubuntu 16.04.2 anaconda setup, and am getting a type error I don't understand when calling code which works fine across numerous other machines.
The error replicates for me just off of the list all tennis markets sample code in the repo below, as well as a request like:
from betfair import Betfair
client = Betfair("app key needed here", "path to ssh key here")
client.login(username, password)
client.keep_alive()
client.list_market_book(market_ids=['1.135391020'], price_projection=dict(priceData=['EX_BEST_OFFERS']))
or
from betfair.models import MarketFilter
event_types = client.list_event_types(
MarketFilter(text_query='tennis')
)
print(len(event_types)) # 2
print(event_types[0].event_type.name) # 'Tennis'
tennis_event_type = event_types[0]
markets = client.list_market_catalogue(
MarketFilter(event_type_ids=[tennis_event_type.event_type.id])
)
markets[0].market_name
Both throw the following type error despite identical code working on a windows installation:
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-3-69b51cf78438> in <module>()
1 event_types = client.list_event_types(
----> 2 MarketFilter(text_query='tennis')
3 )
4 print(len(event_types)) # 2
5 print(event_types[0].event_type.name) # 'Tennis'
<decorator-gen-125> in list_event_types(self, filter, locale)
/home/user/anaconda2/lib/python2.7/site-packages/betfair/utils.pyc in requires_login(func, *args, **kwargs)
121 self = args[0]
122 if self.session_token:
--> 123 return func(*args, **kwargs)
124 raise exceptions.NotLoggedIn()
/home/user/anaconda2/lib/python2.7/site-packages/betfair/betfair.pyc in list_event_types(self, filter, locale)
148 'listEventTypes',
149 utils.get_kwargs(locals()),
--> 150 model=models.EventTypeResult,
151 )
152
/home/user/anaconda2/lib/python2.7/site-packages/betfair/betfair.pyc in make_api_request(self, base, method, params, codes, model)
87 utils.check_status_code(response, codes=codes)
88 result = utils.result_or_error(response)
---> 89 return utils.process_result(result, model)
90
91 # Authentication methods
/home/user/anaconda2/lib/python2.7/site-packages/betfair/utils.pyc in process_result(result, model)
81 return result
82 if isinstance(result, collections.Sequence):
---> 83 return [model(**item) for item in result]
84 return model(**result)
85
/home/user/anaconda2/lib/python2.7/site-packages/betfair/meta/models.pyc in __init__(self, **data)
24 def __init__(self, **data):
25 super(BetfairModel, self).__init__()
---> 26 self.import_data(data)
27
28 def import_data(self, data, **kwargs):
/home/user/anaconda2/lib/python2.7/site-packages/betfair/meta/models.pyc in import_data(self, data, **kwargs)
28 def import_data(self, data, **kwargs):
29 kwargs['strict'] = False
---> 30 return super(BetfairModel, self).import_data(data, **kwargs)
/home/user/anaconda2/lib/python2.7/site-packages/schematics/models.pyc in import_data(self, raw_data, recursive, **kwargs)
269 The data to be imported.
270 """
--> 271 data = self._convert(raw_data, trusted_data=_dict(self), recursive=recursive, **kwargs)
272 self._data.converted.update(data)
273 if kwargs.get('validate'):
/home/user/anaconda2/lib/python2.7/site-packages/schematics/models.pyc in _convert(self, raw_data, context, **kwargs)
293 should_validate = getattr(context, 'validate', kwargs.get('validate', False))
294 func = validate if should_validate else convert
--> 295 return func(self._schema, self, raw_data=raw_data, oo=True, context=context, **kwargs)
296
297 def export(self, field_converter=None, role=None, app_data=None, **kwargs):
/home/user/anaconda2/lib/python2.7/site-packages/schematics/transforms.pyc in convert(cls, mutable, raw_data, **kwargs)
427
428 def convert(cls, mutable, raw_data=None, **kwargs):
--> 429 return import_loop(cls, mutable, raw_data, import_converter, **kwargs)
430
431
/home/user/anaconda2/lib/python2.7/site-packages/schematics/transforms.pyc in import_loop(schema, mutable, raw_data, field_converter, trusted_data, mapping, partial, strict, init_values, apply_defaults, convert, validate, new, oo, recursive, app_data, context)
153 field_context = context
154 try:
--> 155 value = _field_converter(field, value, field_context)
156 except (FieldError, CompoundError) as exc:
157 errors[serialized_field_name] = exc
/home/user/anaconda2/lib/python2.7/site-packages/schematics/transforms.pyc in __call__(self, *args)
354
355 def __call__(self, *args):
--> 356 return self.func(*args)
357
358
/home/user/anaconda2/lib/python2.7/site-packages/schematics/transforms.pyc in import_converter(field, value, context)
382 if value is None or value is Undefined:
383 return value
--> 384 return field.convert(value, context)
385
386
/home/user/anaconda2/lib/python2.7/site-packages/schematics/types/compound.pyc in convert(self, value, context)
34 def convert(self, value, context=None):
35 context = context or get_import_context()
---> 36 return self._convert(value, context)
37
38 def _convert(self, value, context):
/home/user/anaconda2/lib/python2.7/site-packages/schematics/types/compound.pyc in _convert(self, value, context)
131 "Input must be a mapping or '%s' instance" % self.model_class.__name__)
132 if context.convert and context.oo:
--> 133 return model_class(value, context=context)
134 else:
135 return model_class.convert(value, context=context)
TypeError: __init__() takes exactly 1 argument (3 given)
Somewhat weirder, a request like:
client.list_market_catalogue(MarketFilter(market_ids=['1.135391020']))
Works fine.
python 2.7.13, Anaconda 4.4.0, Ubuntu 16.04.2
Any idea what could be causing this?
From the trace it looks to me like the schematics library is your issue. Checking the open issues on the betfair github there is, as of this writing, an open ticket regarding schematics breaking the api. It would appear that the author has left schematics out of the requirements and that version 1.1.1 is required. My guess is you have schematics 2.0 installed on the computer causing the issue.
One way to find this in the future would be to pip freeze the working environment and diff the broken environment. Moreover, when moving to a new machine you can use the output of pip freeze to duplicate the environment and avoid messy version issues like this.