def test_write_conceptscheme():
with specimen("common-structure.xml") as f:
msg = sdmx.read_sdmx(f)
data = sdmx.to_pandas(msg)
cdc = data["concept_scheme"]["CROSS_DOMAIN_CONCEPTS"]
assert cdc.loc["UNIT_MEASURE", "name"] == "Unit of Measure"
def test_freq_in_series_attribute(self, req):
# Test that we don't have regression on Issues #39 and #41
# INSEE time series provide the FREQ value as attribute on the series
# instead of a dimension. This caused a runtime error when writing as
# pandas dataframe.
data_response = sdmx.read_sdmx(SERIES["UNEMPLOYMENT_CAT_A_B_C"]["data-fp"])
sdmx.to_pandas(data_response)
def test_gh_75(self, req):
"""Test of https://github.com/dr-leo/pandaSDMX/pull/75."""
df_id = "47_850"
# # Reported Dataflow query works
# df = req.dataflow(df_id).dataflow[df_id]
with specimen("47_850-structure") as f:
df = sdmx.read_sdmx(f).dataflow[df_id]
# dict() key for the query
data_key = dict(
FREQ=["A"],
ITTER107=["001001"],
SETTITOLARE=["1"],
TIPO_DATO=["AUTP"],
TIPO_GESTIONE=["ALL"],
TIPSERVSOC=["ALL"],
)
# Dimension components are in the correct order
assert [dim.id for dim in df.structure.dimensions.components
] == list(data_key.keys()) + ["TIME_PERIOD"]
# Reported data query works
req.data(df_id, key="A.001001+001002.1.AUTP.ALL.ALL")
# Use a dict() key to force Request to make a sub-query for the DSD
req.data(df_id, key=data_key)
def test_message_repr(specimen, pattern, expected):
with specimen(pattern) as f:
msg = sdmx.read_sdmx(f)
if isinstance(expected, re.Pattern):
assert expected.fullmatch(repr(msg))
else:
# __repr__() and __str__() give the same, expected result
assert expected == repr(msg) == str(msg)
def test_load_dataset(self, base_path):
dataset_code = "IPI-2010-A21"
# Load all dataflows
dataflows_response = sdmx.read_sdmx(base_path / DATAFLOW_FP)
dataflows = dataflows_response.dataflow
assert len(dataflows) == 663
assert dataset_code in dataflows
# Load datastructure for current dataset_code
fp_datastructure = base_path / DATASETS[dataset_code]["datastructure-fp"]
datastructure_response = sdmx.read_sdmx(fp_datastructure)
assert dataset_code in datastructure_response.dataflow
dsd = datastructure_response.dataflow[dataset_code].structure
# Verify dimensions list
dimensions = OrderedDict(
[dim.id, dim]
for dim in dsd.dimensions
if dim.id not in ["TIME", "TIME_PERIOD"]
)
dim_keys = list(dimensions.keys())
assert dim_keys == ["FREQ", "PRODUIT", "NATURE"]
# Load datas for the current dataset
fp_data = base_path / DATASETS[dataset_code]["data-fp"]
data = sdmx.read_sdmx(fp_data)
# Verify series count and values
series = data.data[0].series
series_count = len(series)
assert series_count == DATASETS[dataset_code]["series_count"]
first_series = series[0]
observations = first_series
first_obs = observations[0]
last_obs = observations[-1]
assert first_obs.dim == "2015-10"
assert first_obs.value == "105.61"
assert last_obs.dim == "1990-01"
assert last_obs.value == "139.22"
def test_structure_roundtrip(pytestconfig, specimen_id, strict, tmp_path):
"""Test that SDMX-ML StructureMessages can be 'round-tripped'."""
# Read a specimen file
with specimen(specimen_id) as f:
msg0 = sdmx.read_sdmx(f)
# Write to file
path = tmp_path / "output.xml"
path.write_bytes(sdmx.to_xml(msg0, pretty_print=True))
# Read again
msg1 = sdmx.read_sdmx(path)
# Contents are identical
assert msg0.compare(msg1, strict), (
path.read_text() if pytestconfig.getoption("verbose") else path
)
def test_write_data_arguments():
msg = sdmx.read_sdmx(test_files(kind="data")["argvalues"][0])
# Attributes must be a string
with raises(TypeError):
sdmx.to_pandas(msg, attributes=2)
# Attributes must contain only 'dgso'
with raises(ValueError):
sdmx.to_pandas(msg, attributes="foobarbaz")
def test_write_categoryscheme(specimen):
with specimen("IPI-2010-A21-structure.xml") as f:
msg = sdmx.read_sdmx(f)
data = sdmx.to_pandas(msg)
cs = data["category_scheme"]["CLASSEMENT_DATAFLOWS"]
assert cs.loc["COMPTA-NAT", "name"] == "National accounts (GDP, consumption...)"
# Children appear
assert cs.loc["CNA-PIB-2005", "parent"] == "CNA-PIB"
def test_read_xml_structure_insee(specimen):
with specimen("IPI-2010-A21-structure.xml") as f:
msg = sdmx.read_sdmx(f)
# Same objects referenced
assert id(msg.dataflow["IPI-2010-A21"].structure) == id(
msg.structure["IPI-2010-A21"])
# Number of dimensions loaded correctly
dsd = msg.structure["IPI-2010-A21"]
assert len(dsd.dimensions) == 4
def test_fixe_key_names(self, base_path):
"""Verify key or attribute contains '-' in name."""
dataset_code = "CNA-2010-CONSO-SI-A17"
fp_datastructure = base_path / DATASETS[dataset_code]["datastructure-fp"]
datastructure_response = sdmx.read_sdmx(fp_datastructure)
assert dataset_code in datastructure_response.dataflow
dsd = datastructure_response.dataflow[dataset_code].structure
dimensions = OrderedDict(
[dim.id, dim]
for dim in dsd.dimensions
if dim.id not in ["TIME", "TIME_PERIOD"]
)
dim_keys = list(dimensions.keys())
assert dim_keys == ["SECT-INST", "OPERATION", "PRODUIT", "PRIX"]
fp_data = base_path / DATASETS[dataset_code]["data-fp"]
data = sdmx.read_sdmx(fp_data)
series = data.data[0].series
series_key = list(series.keys())[0]
assert list(series_key.values.keys()) == [
"SECT-INST",
"OPERATION",
"PRODUIT",
"PRIX",
]
assert list(series_key.attrib.keys()) == [
"FREQ",
"IDBANK",
"TITLE",
"LAST_UPDATE",
"UNIT_MEASURE",
"UNIT_MULT",
"REF_AREA",
"DECIMALS",
"BASE_PER",
"TIME_PER_COLLECT",
]
def test_write_data(specimen, path):
msg = sdmx.read_sdmx(path)
result = sdmx.to_pandas(msg)
expected = specimen.expected_data(path)
if expected is not None:
print(expected, result, sep="\n")
assert_pd_equal(expected, result)
# TODO incomplete
assert isinstance(result, (pd.Series, pd.DataFrame, list)), type(result)
def test_write_data_arguments(specimen):
# The identity here is not important; any non-empty DataMessage will work
with specimen("INSEE/CNA-2010-CONSO-SI-A17.xml") as f:
msg = sdmx.read_sdmx(f)
# Attributes must be a string
with raises(TypeError):
sdmx.to_pandas(msg, attributes=2)
# Attributes must contain only 'dgso'
with raises(ValueError):
sdmx.to_pandas(msg, attributes="foobarbaz")
def test_exr_constraints():
with specimen("1/structure-full.xml") as f:
m = sdmx.read_sdmx(f)
ECB_EXR1 = m.structure["ECB_EXR1"]
# Test DimensionDescriptor
dd = ECB_EXR1.dimensions
# Correct order
assert dd[0].id == "FREQ"
# Correct number of dimensions
assert len(dd.components) == 6
# Dimensions can be retrieved by name; membership can be tested
assert "W" in dd.get("FREQ")
# Similar tests for AttributeDescriptor
ad = ECB_EXR1.attributes
assert len(ad.components) == 24
assert ad[-1].id == "UNIT_MULT"
assert "5" in ad.get("UNIT_MULT")
pytest.xfail("constrained codes not implemented")
assert len(m._constrained_codes), 14
assert "W" not in m._constrained_codes.FREQ
key = {"FREQ": ["W"]}
assert m.in_codes(key)
assert not m.in_constraints(key, raise_error=False)
with pytest.raises(ValueError):
m.in_constraints(key)
assert m.in_constraints({"CURRENCY": ["CHF"]})
# test with invalid key
with pytest.raises(TypeError):
m._in_constraints({"FREQ": "A"})
# structure writer with constraints
out = sdmx.to_pandas(m)
cl = out.codelist
assert cl.shape == (3555, 2)
# unconstrained codelists
out = sdmx.to_pandas(m, constraint=False)
cl = out.codelist
assert cl.shape, (4177, 2)
def test_write_codelist(specimen):
# Retrieve codelists from a test specimen and convert to pandas
with specimen("common-structure.xml") as f:
dsd_common = sdmx.read_sdmx(f)
codelists = sdmx.to_pandas(dsd_common)["codelist"]
# File contains 5 code lists
assert len(codelists) == 5
# Code lists have expected number of items
assert len(codelists["CL_FREQ"]) == 8
# Items names can be retrieved by ID
freq = codelists["CL_FREQ"]
assert freq["A"] == "Annual"
# Non-hierarchical code list has a string name
assert freq.name == "Code list for Frequency (FREQ)"
# Hierarchical code list
with specimen("codelist_partial.xml") as f:
msg = sdmx.read_sdmx(f)
# Convert single codelist
CL_AREA = sdmx.to_pandas(msg.codelist["CL_AREA"])
# Hierichical list has a 'parent' column; parent of Africa is the World
assert CL_AREA.loc["002", "parent"] == "001"
# Pandas features can be used to merge parent names
area_hierarchy = pd.merge(
CL_AREA,
CL_AREA,
how="left",
left_on="parent",
right_index=True,
suffixes=("", "_parent"),
)
assert area_hierarchy.loc["002", "name_parent"] == "World"
def test_data_roundtrip(pytestconfig, data_id, structure_id, tmp_path):
"""Test that SDMX-ML DataMessages can be 'round-tripped'."""
# Read structure from file
with specimen(structure_id) as f:
dsd = sdmx.read_sdmx(f).structure[0]
# Read data from file, using the DSD
with specimen(data_id) as f:
msg0 = sdmx.read_sdmx(f, dsd=dsd)
# Write to file
path = tmp_path / "output.xml"
path.write_bytes(sdmx.to_xml(msg0, pretty_print=True))
# Read again, using the same DSD
msg1 = sdmx.read_sdmx(path, dsd=dsd)
# Contents are identical
assert msg0.compare(msg1, strict=True), (
path.read_text() if pytestconfig.getoption("verbose") else path
)
def test_flat():
# Create a bare Message
msg = DataMessage()
# Recreate the content from exr-flat.json
header = Header(
id="62b5f19d-f1c9-495d-8446-a3661ed24753",
prepared="2012-11-29T08:40:26Z",
sender=model.Agency(id="ECB"),
)
msg.header = header
ds = DataSet()
# Create a Key and attributes
key = Key(
FREQ="D",
CURRENCY="NZD",
CURRENCY_DENOM="EUR",
EXR_TYPE="SP00",
EXR_SUFFIX="A",
TIME_PERIOD="2013-01-18",
)
obs_status = DataAttribute(id="OBS_STATUS")
attr = {"OBS_STATUS": AttributeValue(value_for=obs_status, value="A")}
ds.obs.append(
Observation(dimension=key, value=1.5931, attached_attribute=attr))
key = key.copy(TIME_PERIOD="2013-01-21")
ds.obs.append(
Observation(dimension=key, value=1.5925, attached_attribute=attr))
key = key.copy(CURRENCY="RUB", TIME_PERIOD="2013-01-18")
ds.obs.append(
Observation(dimension=key, value=40.3426, attached_attribute=attr))
key = key.copy(TIME_PERIOD="2013-01-21")
ds.obs.append(
Observation(dimension=key, value=40.3000, attached_attribute=attr))
msg.data.append(ds)
# Write to pd.Dataframe
df1 = sdmx.to_pandas(msg)
with specimen("flat.json") as f:
ref = sdmx.read_sdmx(f)
df2 = sdmx.to_pandas(ref)
assert_pd_equal(df1, df2)
def test_read_ss_xml(specimen):
with specimen("M.USD.EUR.SP00.A.xml", opened=False) as f:
msg_path = f
dsd_path = f.parent / "structure.xml"
# Read the DSD
dsd = sdmx.read_sdmx(dsd_path).structure["ECB_EXR1"]
# Read a data message
msg = sdmx.read_sdmx(msg_path, dsd=dsd)
ds = msg.data[0]
# The dataset in the message is structured by the DSD
assert ds.structured_by is dsd
# Structures referenced in the dataset are from the dsd
s0_key = list(ds.series.keys())[0]
# AttributeValue.value_for
assert s0_key.attrib["DECIMALS"].value_for is dsd.attributes.get(
"DECIMALS")
# SeriesKey.described_by
assert s0_key.described_by is dsd.dimensions
# Key.described_by
assert ds.obs[0].key.described_by is dsd.dimensions
# KeyValue.value_for
assert ds.obs[0].key.values[0].value_for is dsd.dimensions.get("FREQ")
# DSD information that is not in the data message can be looked up through
# navigating object relationships
TIME_FORMAT = s0_key.attrib["TIME_FORMAT"].value_for
assert len(TIME_FORMAT.related_to.dimensions) == 5
def test_structuremessage(tmp_path, structuremessage):
result = sdmx.to_xml(structuremessage, pretty_print=True)
print(result.decode())
# Message can be round-tripped to/from file
path = tmp_path / "output.xml"
path.write_bytes(result)
msg = sdmx.read_sdmx(path)
# Contents match the original object
assert (msg.codelist["CL_COLLECTION"]["A"].name["en"] ==
structuremessage.codelist["CL_COLLECTION"]["A"].name["en"])
# False because `structuremessage` lacks URNs, which are constructed automatically
# by `to_xml`
assert not msg.compare(structuremessage, strict=True)
# Compares equal when allowing this difference
assert msg.compare(structuremessage, strict=False)
def test_sdmx_roundtrip(tmp_path):
path = tmp_path / "structure.xml"
# Structure can be written
with open(path, "wb") as f:
f.write(sdmx.to_xml(generate(), pretty_print=True))
# Structure can be read
sm = sdmx.read_sdmx(path)
# One CubeRegion
assert 1 == len(sm.constraint["PRICE_FUEL"].data_content_region)
# One dimension with a MemberSelection
cr = sm.constraint["PRICE_FUEL"].data_content_region[0]
assert {"FUEL"} == set(d.id for d in cr.member.keys())
# 3 values in the MemberSelection
assert 3 == len(cr.member["FUEL"].values)
def test_write_agencyscheme(specimen):
# Convert an agency scheme
with specimen("ECB/orgscheme.xml") as f:
msg = sdmx.read_sdmx(f)
data = sdmx.to_pandas(msg)
assert data["organisation_scheme"]["AGENCIES"]["ESTAT"] == "Eurostat"
# to_pandas only returns keys for non-empty attributes of StructureMessage
# https://github.com/dr-leo/pandaSDMX/issues/90
assert set(data.keys()) == {"organisation_scheme"}
# Attribute access works
assert data.organisation_scheme.AGENCIES.ESTAT == "Eurostat"
with pytest.raises(AttributeError):
data.codelist
with pytest.raises(AttributeError):
data.dataflow
with pytest.raises(AttributeError):
data.structure
def test_read_sdmx(tmp_path, specimen):
# Copy the file to a temporary file with an urecognizable suffix
target = tmp_path / "foo.badsuffix"
with specimen("flat.json", opened=False) as original:
target.open("w").write(original.read_text())
# With unknown file extension, read_sdmx() peeks at the file content
sdmx.read_sdmx(target)
# Format can be inferred from an already-open file without extension
with specimen("flat.json") as f:
sdmx.read_sdmx(f)
# Exception raised when the file contents don't allow to guess the format
bad_file = BytesIO(b"#! neither XML nor JSON")
exc = (
"cannot infer SDMX message format from path None, format={}, or content "
"'#! ne..'")
with pytest.raises(RuntimeError, match=exc.format("None")):
sdmx.read_sdmx(bad_file)
# Using the format= argument forces a certain reader to be used
with pytest.raises(json.JSONDecodeError):
sdmx.read_sdmx(bad_file, format="JSON")
def test_write_dataflow(specimen):
# Read the INSEE dataflow definition
with specimen("INSEE/dataflow") as f:
msg = sdmx.read_sdmx(f)
# Convert to pandas
result = sdmx.to_pandas(msg, include="dataflow")
# Number of Dataflows described in the file
assert len(result["dataflow"]) == 663
# ID and names of first Dataflows
mbop = "Monthly Balance of Payments - "
expected = pd.Series(
{
"ACT-TRIM-ANC": "Activity by sex and age - Quarterly series",
"BPM6-CCAPITAL": "{}Capital account".format(mbop),
"BPM6-CFINANCIER": "{}Financial account".format(mbop),
"BPM6-CTRANSACTION": "{}Current transactions account".format(mbop),
"BPM6-TOTAL": "{}Overall total and main headings".format(mbop),
}
)
assert_pd_equal(result["dataflow"].head(), expected)
def test_msg(self, path, dsd):
# The message can be parsed
sdmx.read_sdmx(path / self.filename, dsd=dsd)
def msg(self, path, dsd):
yield sdmx.read_sdmx(path / self.filename, dsd=dsd)
def dsd(self, path):
yield sdmx.read_sdmx(path / self.dsd_filename).structure[0]
def test_bare_series(specimen):
with specimen("ng-ts.xml") as f:
sdmx.read_sdmx(f)
def get_dsd():
dsd_file = 'SDG_DSD.xml'
msg = sdmx.read_sdmx(dsd_file)
return msg.structure[0]
def retrieve_dsd(self, dsd):
if dsd.startswith('http'):
urlretrieve(dsd, 'SDG_DSD.xml')
dsd = 'SDG_DSD.xml'
msg = sdmx.read_sdmx(dsd)
return msg.structure[0]
def test_writer_structure(path):
msg = sdmx.read_sdmx(path)
sdmx.to_pandas(msg)
def test_write_data_attributes(path):
msg = sdmx.read_sdmx(path)
result = sdmx.to_pandas(msg, attributes="osgd")
# TODO incomplete
assert isinstance(result, (pd.Series, pd.DataFrame, list)), type(result)
