def test_bool():
col = {"name": "test", "type": "boolean"}
pontiless_meta = {"columns": [col]}
mf = MetaFaker(pontiless_meta)
test_bool = mf.fake_bool()
assert isinstance(test_bool, bool)
assert test_bool in [True, False]
# Check row generator
row = mf.generate_row()
assert isinstance(row["test"], bool)
def test_dates(col, exp_fmt):
meta = {"columns": [col]}
mf = MetaFaker(meta)
# Check datetime creation
test_date = mf.fake_datetime(col)
assert isinstance(test_date, str)
datetime.strptime(test_date, exp_fmt)
# Check row generator
row = mf.generate_row()
assert isinstance(row["test"], str)
datetime.strptime(row["test"], exp_fmt)
def test_seed():
meta = {
"columns": [
{
"name": "my_int",
"type": "int",
"minimum": 10,
"maximum": 20,
"nullable": True,
},
{
"name": "my_character_enum",
"type": "character",
"enum": ["a", "b", "c"]
},
{
"name": "my_email",
"type": "character",
},
{
"name": "my_datetime",
"type": "datetime",
},
{
"name": "my_address",
"type": "character",
},
]
}
sc = {"my_email": "email", "my_address": "address"}
mf = MetaFaker(meta=meta, special_cols=sc, locale="en_GB")
mf.seed = 888
with tempfile.TemporaryDirectory() as d:
mf.write_data_to_csv(f"{d}/test.csv", total_rows=10)
with open(f"{d}/test.csv",
"r") as t1, open("tests/data/output/seed_test.csv",
"r") as t2:
fileone = t1.readlines()
filetwo = t2.readlines()
assert fileone == filetwo, "Problem with seed"
def test_number(t):
col = {"name": "test", "type": t}
pontiless_meta = {"columns": [col]}
mf = MetaFaker(pontiless_meta)
test_double = mf.fake_double(col)
assert isinstance(test_double, float)
assert test_double >= mf.default_min and test_double <= mf.default_max
# Check row generator
row = mf.generate_row()
assert isinstance(row["test"], float)
assert row["test"] >= mf.default_min and row["test"] <= mf.default_max
# Check limits work
meta = {
"columns": [{
"name": "test",
"type": t,
"minimum": 0,
"maximum": 2
}]
}
mf = MetaFaker(meta)
row = mf.generate_row()
assert isinstance(row["test"], float)
assert row["test"] >= 0.0
assert row["test"] <= 2.0
def test_int():
col = {"name": "test", "type": "int"}
pontiless_meta = {"columns": [col]}
mf = MetaFaker(pontiless_meta)
test_int = mf.fake_int(col)
assert isinstance(test_int, int)
assert test_int >= mf.default_min and test_int <= mf.default_max
# Check row generator
row = mf.generate_row()
assert isinstance(row["test"], int)
assert row["test"] >= mf.default_min and row["test"] <= mf.default_max
# Check limits work
meta = {
"columns": [{
"name": "test",
"type": "int",
"minimum": 0,
"maximum": 2
}]
}
mf = MetaFaker(meta)
row = mf.generate_row()
assert isinstance(row["test"], int)
assert row["test"] in [0, 1, 2]
def test_nulling():
meta = {
"columns": [
{
"name": "my_int",
"type": "int",
"nullable": True
},
{
"name": "my_character",
"type": "character",
"nullable": True
},
]
}
mf = MetaFaker(meta=meta, null_probability=1.0)
row = mf.generate_row()
for k, v in row.items():
assert v is None
def test_readme():
meta = {
"columns": [
{
"name": "my_int",
"type": "int",
"minimum": 10,
"maximum": 20,
"nullable": True,
},
{
"name": "my_character_enum",
"type": "character",
"enum": ["a", "b", "c"]
},
{
"name": "my_email",
"type": "character",
},
{
"name": "my_datetime",
"type": "datetime",
},
]
}
sc = {"my_email": "email"}
mf = MetaFaker(meta=meta, special_cols=sc)
row = mf.generate_row()
# Make checks against row
if row["my_int"] is not None:
assert row["my_int"] >= 10
assert row["my_int"] <= 20
assert row["my_character_enum"] in ["a", "b", "c"]
assert "@" in row["my_email"]
# Check for no errors
dt = datetime.strptime(row["my_datetime"], "%Y-%m-%d %H:%M:%S")
mf.write_data_to_csv(StringIO(), total_rows=10)
mf.write_data_to_jsonl(StringIO(), 10)
def test_character():
pontiless_meta = {"columns": [{"name": "test", "type": "character"}]}
mf = MetaFaker(pontiless_meta)
assert isinstance(mf.fake_character(), str)
assert isinstance(mf.fake_character("email"), str)
assert "@" in mf.fake_character("email")
assert isinstance(mf.fake_character("address"), str)
assert isinstance(mf.fake_character("street_address"), str)
assert isinstance(mf.fake_character("first_name"), str)
assert isinstance(mf.fake_character("first_name_female"), str)
assert isinstance(mf.fake_character("first_name_male"), str)
# Check row generator
row = mf.generate_row()
assert isinstance(row["test"], str)
# Check special rows work
mf.special_cols = {"test": "email"}
row = mf.generate_row()
assert "@" in row["test"]