def test_parse_with_custom_parser(self):
"""
Parses a subclass of DataFrame with a custom converter.
:return:
"""
from typing import Type
from parsyfiles.converting_core import T
from logging import Logger
from xml.etree.ElementTree import ElementTree, parse, tostring
def read_xml(desired_type: Type[T], file_path: str, encoding: str,
logger: Logger, **kwargs):
"""
Opens an XML file and returns the tree parsed from it as an ElementTree.
:param desired_type:
:param file_path:
:param encoding:
:param logger:
:param kwargs:
:return:
"""
return parse(file_path)
my_parser = SingleFileParserFunction(parser_function=read_xml,
streaming_mode=False,
supported_exts={'.xml'},
supported_types={ElementTree})
parser = RootParser('parsyfiles with timeseries')
parser.register_parser(my_parser)
xmls = parser.parse_collection(fix_path('./xml_collection'),
ElementTree)
pprint({name: tostring(x.getroot()) for name, x in xmls.items()})
def test_union_recursive_1(root_parser: RootParser):
""" Tests that you can parse infinitely-nested dictionaries from a folder using forward references """
class A:
def __init__(self, foo: str):
self.foo = foo
# First (preferred) way
InfiniteRecursiveDictOfA = Dict[str, Union[A, 'InfiniteRecursiveDictOfA']]
items = root_parser.parse_item(get_path('test2'), InfiniteRecursiveDictOfA)
assert type(items['a']['a']['a']) == A
assert type(items['a']['a']['b']) == A
assert type(items['a']['b']) == A
assert type(items['b']) == A
# Less preferred way, but check that it works too
InfiniteRecursiveDictOfA2 = Union[A, Dict[str,
'InfiniteRecursiveDictOfA2']]
items = root_parser.parse_collection(get_path('test2'),
InfiniteRecursiveDictOfA2)
assert type(items['a']['a']['a']) == A
assert type(items['a']['a']['b']) == A
assert type(items['a']['b']) == A
assert type(items['b']) == A
# This is a forward reference that is equivalent to 'A'.
# It should be handled correctly by parsyfiles so as not to lead to infinite recursiong
InfiniteRecursiveDictOfA3 = Union[A, 'InfiniteRecursiveDictOfA3']
item = root_parser.parse_item(get_path('test2', 'b'),
InfiniteRecursiveDictOfA3)
assert type(item) == A
def test_print_and_get_capabilities_by_type(root_parser: RootParser):
""" Tests that the declared capabilities by type are correct """
c = root_parser.get_capabilities_by_type(strict_type_matching=False)
print('\n' + str(len(c)) + ' Root parser capabilities by type:')
assert len(c) == 15
cdict = to_str_coll(c)
# dump(cdict, 'reference_capabilities_by_type.json')
assert cdict == load('reference_capabilities_by_type.json')
root_parser.print_capabilities_by_type(strict_type_matching=False)
def test_root_parser_any():
"""
Tests that we can ask the rootparser for its capabilities to parse a given type
:return:
"""
root_parser = RootParser()
# print
root_parser.print_capabilities_for_type(typ=Any)
# details
res = root_parser.find_all_matching_parsers(strict=False,
desired_type=AnyObject,
required_ext='.cfg')
match_generic, match_approx, match_exact = res[0]
assert len(match_generic) == 0
assert len(match_approx) == 0
def test_get_all_supported_types_pretty_str(root_parser: RootParser):
""" Tests that the declared supported types are there and that their number is correct """
t = root_parser.get_all_supported_types_pretty_str()
print('\n' + str(len(t)) + ' Root parser supported types:')
pprint(t)
assert len(t) == 15
# dump(list(t), 'reference_supported_types.json')
assert t == set(load('reference_supported_types.json'))
def test_get_all_supported_exts(root_parser: RootParser):
""" Tests that the declared supported extensions are there and that their number is correct """
e = root_parser.get_all_supported_exts()
print('\n' + str(len(e)) + ' Root parser supported extensions:')
pprint(e)
assert len(e) == 13
# dump(list(e), 'reference_supported_exts.json')
assert e == set(load('reference_supported_exts.json'))
def test_get_all_parsers(root_parser: RootParser):
""" Tests that the default parsers are there and that their number is correct """
parsers = root_parser.get_all_parsers(strict_type_matching=False)
print('\n' + str(len(parsers)) + ' Root parser parsers:')
pprint(parsers)
assert len(parsers) == 127
parsers_str = to_str_coll(parsers)
# dump(parsers_str, 'reference_parsers.json')
assert parsers_str == load('reference_parsers.json')
def test_pass_parser_options(self):
"""
Passes options to the pandas parser
:return:
"""
from pandas import DataFrame
from parsyfiles import RootParser
# create a root parser
parser = RootParser()
# retrieve the parsers of interest
parsers = parser.get_capabilities_for_type(DataFrame,
strict_type_matching=False)
df_csv_parser = parsers['.csv']['1_exact_match'][0]
p_id_csv = df_csv_parser.get_id_for_options()
print('Parser id for csv is : ' + p_id_csv +
', implementing function is ' + repr(df_csv_parser._parser_func))
print('option hints : ' + df_csv_parser.options_hints())
df_xls_parser = parsers['.xls']['1_exact_match'][0]
p_id_xls = df_xls_parser.get_id_for_options()
print('Parser id for csv is : ' + p_id_xls +
', implementing function is ' + repr(df_xls_parser._parser_func))
print('option hints : ' + df_xls_parser.options_hints())
from parsyfiles import create_parser_options, add_parser_options
# configure the DataFrame parsers to automatically parse dates and use the first column as index
opts = create_parser_options()
opts = add_parser_options(opts, 'read_df_or_series_from_csv', {
'parse_dates': True,
'index_col': 0
})
opts = add_parser_options(opts, 'read_dataframe_from_xls',
{'index_col': 0})
dfs = parser.parse_collection(
fix_path('./test_data/demo/ts_collection'),
DataFrame,
options=opts)
print(dfs)
def test_union_1(root_parser: RootParser):
""" Tests that parsing a Union works """
class A:
def __init__(self, foo: str):
self.foo = foo
class B:
def __init__(self, bar: float):
self.bar = bar
item = root_parser.parse_item(get_path('test1', 'a'), Union[A, B])
assert type(item) == A
def test_simple_collection(self):
"""
Parsing a collection of dataframes as a dictionary
:return:
"""
from pandas import DataFrame
dfs = parse_collection(fix_path('./simple_collection'), DataFrame)
pprint(dfs)
df = parse_item(fix_path('./simple_collection/c'), DataFrame)
pprint(df)
RootParser().print_capabilities_for_type(typ=DataFrame)
def test_typevars_3(root_parser: RootParser):
""" Tests that a TypeVar with 'constraints' may be used as a desired Type -> it will be a Union """
class A:
def __init__(self, foo: str):
self.foo = foo
class B:
def __init__(self, bar: float):
self.bar = bar
TV = TypeVar('TV', A, B)
item = root_parser.parse_item(get_path('test2', 'a'), TV)
assert type(item) == A
item = root_parser.parse_item(get_path('test2', 'b'), TV)
assert type(item) == B
items = root_parser.parse_collection(get_path('test2'), TV)
assert len(items) == 2
assert type(items['a']) == A
assert type(items['b']) == B
def test_union_2(root_parser: RootParser):
""" Tests that parsing a collection of Union works """
class A:
def __init__(self, foo: str):
self.foo = foo
class B:
def __init__(self, bar: float):
self.bar = bar
items = root_parser.parse_collection(get_path('test1'), Union[A, B])
assert len(items) == 2
assert type(items['a']) == A
assert type(items['b']) == B
def test_typevars_2(root_parser: RootParser):
""" Tests that a TypeVar with 'bound' may be used as a desired Type directly -> it will be replaced with the bound
type """
class A:
def __init__(self, foo: str):
self.foo = foo
class B(A):
def __init__(self, bar: float):
super(B, self).__init__(foo=str(bar))
TV = TypeVar('TV', bound=A)
item = root_parser.parse_item(get_path('test2', 'a'), TV)
assert type(item) == A
item = root_parser.parse_item(get_path('test2', 'b'), TV)
assert type(item) == B
items = root_parser.parse_collection(get_path('test2'), TV)
assert len(items) == 2
assert type(items['a']) == A
assert type(items['b']) == B
def test_simple_objects(self):
"""
Parsing a collection of simple objects_data
:return:
"""
# First define the function that we want to test
# (not useful, but just to show a complete story in the readme...)
def exec_op(x: float, y: float, op: str) -> float:
if op is '+':
return x + y
elif op is '-':
return x - y
else:
raise ValueError('Unsupported operation : \'' + op + '\'')
# Then define the simple class representing your test case
class ExecOpTest(object):
def __init__(self, x: float, y: float, op: str,
expected_result: float):
self.x = x
self.y = y
self.op = op
self.expected_result = expected_result
def __str__(self):
return self.__repr__()
def __repr__(self):
return str(self.x) + ' ' + self.op + ' ' + str(
self.y) + ' =? ' + str(self.expected_result)
# Create the parser and parse a single file
# e = parse_item('./test_data/objects_data/test_diff_1', ExecOpTest)
# pprint(e)
# parse all of them as dicts
sf_tests_dct = parse_collection(fix_path('./simple_objects'), Dict)
# assert that they are sorted
assert list(sf_tests_dct.keys()) == list(sorted(sf_tests_dct.keys()))
# parse all of them as objects_data
sf_tests = parse_collection(fix_path('./simple_objects'), ExecOpTest)
pprint(sf_tests)
#
RootParser().print_capabilities_for_type(typ=ExecOpTest)
def test_parse_subtypes(root_parser: RootParser):
""" Tests that subclasses can be parsed """
class A:
pass
class B(A):
def __init__(self, foo: str):
self.foo = foo
class C(B):
def __init__(self, bar: str):
super(C, self).__init__(foo=bar)
items = root_parser.parse_collection(get_path('test2'), A)
assert type(items['b']) == B
assert type(items['c']) == C
def test_custom_parser_ok_for_subclasses():
"""
Tests that if you register a custom parser for a subclass of A, it gets correctly used to parse A (in non-strict
mode, which is the default)
:return:
"""
root_parser = RootParser()
class A:
def __init__(self, txt):
self.txt = txt
class B(A):
""" a subclass of A """
pass
def read_B_from_txt(desired_type: Type[dict], file_object: TextIOBase,
logger: Logger, *args, **kwargs) -> str:
# read the entire stream into a string
str_io = StringIO()
shutil.copyfileobj(file_object, str_io)
# only return the first character
return B(str_io.getvalue()[0])
# before registering a parser for B, only generic parsers are able to parse a A
before_capa = root_parser.get_capabilities_for_type(A)['.txt']
assert list(before_capa.keys()) == ['3_generic']
# register a parser for B
root_parser.register_parser(
SingleFileParserFunction(parser_function=read_B_from_txt,
streaming_mode=True,
supported_exts={'.txt'},
supported_types={B}))
# after registering the new parser appears in the list able to parse A
after_capa = root_parser.get_capabilities_for_type(A)['.txt']
assert str(after_capa['2_approx_match'][0]) == '<read_B_from_txt>'
a = root_parser.parse_item(get_path('b64pickle-float-1.0=True'), A)
# check that the custom parser was used, not the generic 'construct from string'
assert len(a.txt) == 1
assert a.txt == 'g'
def test_typevars_1(root_parser: RootParser):
""" Tests that a constructor containing TypeVars is correctly handled """
class A:
def __init__(self, foo: str):
self.foo = foo
class B(A):
def __init__(self, bar: float):
super(B, self).__init__(foo=bar)
TV = TypeVar('TV', bound=A)
class Test(Generic[TV]):
def __init__(self, obj: TV):
self.obj = obj
items = root_parser.parse_collection(get_path('test1'), Test)
assert len(items) == 2
assert type(items['a'].obj) == A
assert type(items['b'].obj) == B
def test_get_all_conversion_chains(root_parser: RootParser):
""" Tests that the default conversion chains are there and that their number is correct """
chains = root_parser.get_all_conversion_chains()
print('\n' + str(len(chains[0])) + '(generic) + ' + str(len(chains[2])) +
'(specific) Root parser converters:')
pprint(chains)
assert len(chains[0]) == 22
assert len(chains[1]) == 0
assert len(chains[2]) == 200
generic_chains_str = to_str_coll(chains[0])
specific_chains_str = to_str_coll(chains[2])
# dump(generic_chains_str, 'reference_generic_conversion_chains.json')
assert generic_chains_str == load(
'reference_generic_conversion_chains.json')
# dump(specific_chains_str, 'reference_specific_conversion_chains.json')
assert specific_chains_str == load(
'reference_specific_conversion_chains.json')
def test_multifile_objects(self):
"""
Parsing a list of multifile objects_data
:return:
"""
from pandas import Series, DataFrame
class AlgoConf(object):
def __init__(self, foo_param: str, bar_param: int):
self.foo_param = foo_param
self.bar_param = bar_param
class AlgoResults(object):
def __init__(self, score: float, perf: float):
self.score = score
self.perf = perf
def exec_op_series(x: Series, y: AlgoConf) -> AlgoResults:
pass
class ExecOpSeriesTest(object):
def __init__(self, x: Series, y: AlgoConf,
expected_results: AlgoResults):
self.x = x
self.y = y
self.expected_results = expected_results
# parse all of them
mf_tests = parse_collection(fix_path('./complex_objects'),
ExecOpSeriesTest)
pprint(mf_tests)
RootParser().print_capabilities_for_type(typ=ExecOpSeriesTest)
from parsyfiles import FlatFileMappingConfiguration
dfs = parse_collection(
fix_path('./complex_objects_flat'),
DataFrame,
file_mapping_conf=FlatFileMappingConfiguration())
pprint(dfs)
class AllTests(TestCase):
def setUp(self):
"""
Creates the root parser to be used in most tests
:return:
"""
self.root_parser = RootParser()
def test_a_root_parser_capabilities(self):
"""
Tests that we can print the capabilities of the root parser: registered parsers and converters, supported
extensions and types, etc.
:return:
"""
p = self.root_parser.get_all_parsers(strict_type_matching=False)
print('\n' + str(len(p)) + ' Root parser parsers:')
pprint(p)
print('Testing option hints for parsing chain')
print(p[0].options_hints())
c = self.root_parser.get_all_conversion_chains()
print('\n' + str(len(c[0]) + len(c[2])) + ' Root parser converters:')
pprint(c)
e = self.root_parser.get_all_supported_exts()
print('\n' + str(len(e)) + ' Root parser supported extensions:')
pprint(e)
t = self.root_parser.get_all_supported_types_pretty_str()
print('\n' + str(len(t)) + ' Root parser supported types:')
pprint(t)
print('\nRoot parser parsers by extensions:')
self.root_parser.print_capabilities_by_ext(strict_type_matching=False)
print('\nRoot parser parsers by types:')
self.root_parser.print_capabilities_by_type(strict_type_matching=False)
return
def test_b_root_parser_any(self):
"""
Tests that we can ask the rootparser for its capabilities to parse a given type
:return:
"""
# print
self.root_parser.print_capabilities_for_type(typ=Any)
# details
res = self.root_parser.find_all_matching_parsers(
strict=False, desired_type=AnyObject, required_ext='.cfg')
match_generic, match_approx, match_exact = res[0]
self.assertEquals(len(match_generic), 0)
self.assertEquals(len(match_approx), 0)
def test_objects_support(self):
"""
Tests all the supported ways to parse a simple object
:return:
"""
# Then define the simple class representing your test case
class ExecOpTest(object):
def __init__(self, x: float, y: float, op: str,
expected_result: float):
self.x = x
self.y = y
self.op = op
self.expected_result = expected_result
def __str__(self):
return self.__repr__()
def __repr__(self):
return str(self.x) + ' ' + self.op + ' ' + str(
self.y) + ' =? ' + str(self.expected_result)
# create the parser and parse a single file
e = parse_item(fix_path('./test_data/objects/test_diff_1'), ExecOpTest)
pprint(e)
# parse all of them
e = parse_collection(fix_path('./test_data/objects'), ExecOpTest)
pprint(e)
def test_collections(self):
"""
Tests all the supported ways to parse collections
:return:
"""
l = parse_item(
fix_path('./test_data/collections'),
Tuple[Dict[str, int], List[int], Set[int], Tuple[str, int, str]])
print(l)
def test_parse_subclass_of_known_with_custom_converter(self):
"""
Parses a subclass of DataFrame with a custom converter.
:return:
"""
# define your class
from pandas import DataFrame, DatetimeIndex
class TimeSeries(DataFrame):
"""
A basic timeseries class that extends DataFrame
"""
def __init__(self, df: DataFrame):
"""
Constructor from a DataFrame. The DataFrame index should be an instance of DatetimeIndex
:param df:
"""
if isinstance(df, DataFrame) and isinstance(
df.index, DatetimeIndex):
if df.index.tz is None:
df.index = df.index.tz_localize(
tz='UTC'
) # use the UTC hypothesis in absence of other hints
self._df = df
else:
raise ValueError(
'Error creating TimeSeries from DataFrame: provided DataFrame does not have a '
'valid DatetimeIndex')
def __getattr__(self, item):
# Redirects anything that is not implemented here to the base dataframe.
# this is called only if the attribute was not found the usual way
# easy version of the dynamic proxy just to save time :)
# see http://code.activestate.com/recipes/496741-object-proxying/ for "the answer"
df = object.__getattribute__(self, '_df')
if hasattr(df, item):
return getattr(df, item)
else:
raise AttributeError('\'' + self.__class__.__name__ +
'\' object has no attribute \'' +
item + '\'')
def update(self,
other,
join='left',
overwrite=True,
filter_func=None,
raise_conflict=False):
""" For some reason this method was abstract in DataFrame so we have to implement it """
return self._df.update(other,
join=join,
overwrite=overwrite,
filter_func=filter_func,
raise_conflict=raise_conflict)
# -- create your converter
from typing import Type
from logging import Logger
from parsyfiles.converting_core import ConverterFunction
def df_to_ts(desired_type: Type[TimeSeries], df: DataFrame,
logger: Logger) -> TimeSeries:
""" Converter from DataFrame to TimeSeries """
return TimeSeries(df)
my_converter = ConverterFunction(from_type=DataFrame,
to_type=TimeSeries,
conversion_method=df_to_ts)
# -- create a parser and register your converter
from parsyfiles import RootParser, create_parser_options, add_parser_options
parser = RootParser('parsyfiles with timeseries')
parser.register_converter(my_converter)
# -- you might wish to configure the DataFrame parser, though:
opts = create_parser_options()
opts = add_parser_options(opts, 'read_df_or_series_from_csv', {
'parse_dates': True,
'index_col': 0
})
opts = add_parser_options(opts, 'read_dataframe_from_xls',
{'index_col': 0})
dfs = parser.parse_collection(fix_path('./ts_collection'),
TimeSeries,
options=opts)
def parse_with_new_instance():
rp = RootParser()
result = rp.parse_item(
os.path.join(THIS_DIR, 'test_data/b64pickle-float-1.0=True'), bool)
assert result == True
def root_parser():
l = getLogger('parsyfiles')
l.setLevel(DEBUG)
return RootParser()
def setUp(self):
"""
Creates the root parser to be used in most tests
:return:
"""
self.root_parser = RootParser()
def test_option_hints(root_parser: RootParser):
""" Tests the option_hints method on the first parser available """
print('Testing option hints for parsing chain')
p = root_parser.get_all_parsers(strict_type_matching=False)
print(p[0].options_hints())
