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Initial package for python-nested-lookup

OBS-URL: https://build.opensuse.org/request/show/912776
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python/python-nested-lookup?expand=0&rev=1
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Markéta Machová 2021-08-20 07:23:54 +00:00 committed by Git OBS Bridge
commit 74cb1eb798
7 changed files with 1156 additions and 0 deletions
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.osc

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version https://git-lfs.github.com/spec/v1
oid sha256:23789e328bd1d0b3f9db93cf51b7103a978dd0d8a834770d2c19b365e934ab96
size 7837

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-------------------------------------------------------------------
Fri Jul 24 01:13:13 PM UTC 2020 - John Vandenberg <jayvdb@gmail.com>
- Initial spec for v0.2.21

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#
# spec file for package python-nested-lookup
#
# Copyright (c) 2021, Martin Hauke <mardnh@gmx.de>
#
# All modifications and additions to the file contributed by third parties
# remain the property of their copyright owners, unless otherwise agreed
# upon. The license for this file, and modifications and additions to the
# file, is the same license as for the pristine package itself (unless the
# license for the pristine package is not an Open Source License, in which
# case the license is the MIT License). An "Open Source License" is a
# license that conforms to the Open Source Definition (Version 1.9)
# published by the Open Source Initiative.
# Please submit bugfixes or comments via http://bugs.opensuse.org/
%{?!python_module:%define python_module() python-%{**} python3-%{**}}
Name: python-nested-lookup
Version: 0.2.21
Release: 0
License: SUSE-Public-Domain
Summary: Python functions for working with deeply nested documents (lists and dicts)
Url: https://github.com/russellballestrini/nested-lookup
Group: Development/Languages/Python
Source: https://files.pythonhosted.org/packages/source/n/nested-lookup/nested-lookup-%{version}.tar.gz
Source1: https://raw.githubusercontent.com/russellballestrini/nested-lookup/307983caa591bfd08a1f414109f640671a4dea51/test_lookup_api.py
Source2: https://raw.githubusercontent.com/russellballestrini/nested-lookup/master/test_nested_lookup.py
BuildRequires: python-rpm-macros
BuildRequires: %{python_module setuptools}
# SECTION test requirements
BuildRequires: %{python_module six}
# /SECTION
BuildRequires: fdupes
Requires: python-six
BuildArch: noarch
%python_subpackages
%description
Python functions for working with deeply nested documents (lists and dicts)
%prep
%setup -q -n nested-lookup-%{version}
cp %{SOURCE1} %{SOURCE2} .
%build
%python_build
%install
%python_install
%python_expand %fdupes %{buildroot}%{$python_sitelib}
%check
%pyunittest -v
%files %{python_files}
%doc README.rst
%{python_sitelib}/nested_lookup*
%changelog

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from unittest import TestCase
from nested_lookup import nested_lookup, nested_update
from nested_lookup import nested_delete, nested_alter
class BaseLookUpApi(TestCase):
def setUp(self):
self.sample_data1 = {
"build_version": {
"model_name": "MacBook Pro",
"build_version": {
"processor_name": "Intel Core i7",
"processor_speed": "2.7 GHz",
"core_details": {
"build_version": "4",
"l2_cache(per_core)": "256 KB",
},
},
"number_of_cores": "4",
"memory": "256 KB",
},
"os_details": {"product_version": "10.13.6", "build_version": "17G65"},
"name": "Test",
"date": "YYYY-MM-DD HH:MM:SS",
}
self.sample_data2 = {
"hardware_details": {
"model_name": "MacBook Pro",
"processor_details": [
{"processor_name": "Intel Core i7", "processor_speed": "2.7 GHz"},
{"total_number_of_cores": "4", "l2_cache(per_core)": "256 KB"},
],
"total_number_of_cores": "5",
"memory": "16 GB",
}
}
self.sample_data3 = {
"values": [
{
"checks": [
{
"monitoring_zones": [
"mzdfw",
"mzfra",
"mzhkg",
"mziad",
"mzlon",
"mzord",
"mzsyd",
]
}
]
}
]
}
self.sample_data4 = {
"modelversion": "1.1.0",
"vorgangsID": "1",
"versorgungsvorschlagDatum": 1510558834978,
"eingangsdatum": 1510558834978,
"plz": 82269,
"vertragsteile": [
{
"typ": "1",
"beitragsDaten": {
"endalter": 85,
"brutto": 58.76,
"netto": 58.76,
"zahlungsrhythmus": "MONATLICH",
"plz": 86899,
},
"beginn": 1512082800000,
"lebenslang": "True",
"ueberschussverwendung": {
"ueberschussverwendung": "2",
"indexoption": "3",
},
"deckung": [
{
"typ": "2",
"art": "1",
"leistung": {"value": 7500242424.0, "einheit": "2"},
"leistungsRhythmus": "1",
}
],
"zuschlagNachlass": [],
},
{
"typ": "1",
"beitragsDaten": {
"endalter": 85,
"brutto": 0.6,
"netto": 0.6,
"zahlungsrhythmus": "1",
},
"zuschlagNachlass": [],
},
],
}
class TestNestedDelete(BaseLookUpApi):
def test_sample_data1(self):
result = {
"os_details": {"product_version": "10.13.6"},
"name": "Test",
"date": "YYYY-MM-DD HH:MM:SS",
}
self.assertEqual(result, nested_delete(self.sample_data1, "build_version"))
def test_sample_data2(self):
result = {
"hardware_details": {
"model_name": "MacBook Pro",
"total_number_of_cores": "5",
"memory": "16 GB",
}
}
self.assertEqual(result, nested_delete(self.sample_data2, "processor_details"))
def test_sample_data3(self):
result = {"values": [{"checks": [{}]}]}
self.assertEqual(result, nested_delete(self.sample_data3, "monitoring_zones"))
class TestNestedUpdate(BaseLookUpApi):
def test_sample_data1(self):
result = {
"build_version": "Test1",
"os_details": {"product_version": "10.13.6", "build_version": "Test1"},
"name": "Test",
"date": "YYYY-MM-DD HH:MM:SS",
}
self.assertEqual(
result, nested_update(self.sample_data1, "build_version", "Test1")
)
def test_sample_data1_list_input_treat_list_as_element_true(self):
result = {
"build_version": ["Test5", "Test6", "Test7"],
"os_details": {
"product_version": "10.13.6",
"build_version": ["Test5", "Test6", "Test7"],
},
"name": "Test",
"date": "YYYY-MM-DD HH:MM:SS",
}
self.assertEqual(
result,
nested_update(
self.sample_data1,
"build_version",
["Test5", "Test6", "Test7"],
treat_as_element=True,
),
)
def test_nested_update_in_place_false(self):
"""
ested_update should mutate and return a copy of the original document
"""
before_id = id(self.sample_data1)
result = nested_update(
self.sample_data1, "build_version", "Test2", in_place=False
)
after_id = id(result)
# the object ids should _not_ match.
self.assertNotEqual(before_id, after_id)
def test_nested_update_in_place_true(self):
"""
nested_update should mutate and return the original document
"""
before_id = id(self.sample_data1)
result = nested_update(
self.sample_data1, "build_version", "Test2", in_place=True
)
after_id = id(result)
# the object ids should match.
self.assertEqual(before_id, after_id)
def test_nested_update_in_place_true_list_input(self):
doc = self.sample_data4
# get all instances of the given element
findings = nested_lookup("plz", doc, False, True)
# alter those instances
updated_findings = list()
for key, val in findings.items():
for elem in val:
updated_findings.append(elem + 300)
# update those instances with the altered results
doc_updated = nested_update(
doc, "plz", updated_findings, treat_as_element=False
)
elem1 = doc_updated["plz"] # 85269
# 87199
elem2 = doc_updated["vertragsteile"][0]["beitragsDaten"]["plz"]
self.assertEqual(elem1, 82569)
self.assertEqual(elem2, 87199)
def test_nested_update_in_place_false_list_input(self):
doc = self.sample_data4
# get all instances of the given element
findings = nested_lookup("plz", doc, False, True)
# alter those instances
updated_findings = list()
for key, val in findings.items():
for elem in val:
updated_findings.append(elem + 300)
# update those instances with the altered results
doc_updated = nested_update(
doc, "plz", updated_findings, in_place=False, treat_as_element=False
)
elem1 = doc_updated["plz"]
elem2 = doc_updated["vertragsteile"][0]["beitragsDaten"]["plz"]
self.assertEqual(elem1, 82569)
self.assertEqual(elem2, 87199)
def test_nested_update_in_place_false_list_input_as_element_false(self):
doc = self.sample_data4
# get all instances of the given element
list_input = [1, 2, 3, 4, 5]
# update those instances with the altered results
doc_updated = nested_update(
doc, "plz", list_input, in_place=False, treat_as_element=False
)
elem1 = doc_updated["plz"]
elem2 = doc_updated["vertragsteile"][0]["beitragsDaten"]["plz"]
# should not work without specifying "treat_list_as_element = True"
# in nested_update
self.assertNotEqual(elem1, list_input)
self.assertNotEqual(elem2, list_input)
def test_nested_update_in_place_false_list_input_as_element_true(self):
doc = self.sample_data4
# get all instances of the given element
list_input = [1, 2, 3, 4, 5]
# update those instances with the altered results
doc_updated = nested_update(
doc, "plz", list_input, in_place=False, treat_as_element=True
)
elem1 = doc_updated["plz"]
elem2 = doc_updated["vertragsteile"][0]["beitragsDaten"]["plz"]
# should not work without specifying "treat_list_as_element = True"
# in nested_update
self.assertEqual(elem1, list_input)
self.assertEqual(elem2, list_input)
def test_nested_update_in_place_true_list_input_as_element_false(self):
doc = self.sample_data4
# get all instances of the given element
list_input = [1, 2, 3, 4, 5]
# update those instances with the altered results
doc_updated = nested_update(
doc, "plz", list_input, in_place=True, treat_as_element=False
)
elem1 = doc_updated["plz"]
elem2 = doc_updated["vertragsteile"][0]["beitragsDaten"]["plz"]
# should not work without specifying "treat_list_as_element = True"
# in nested_update
self.assertNotEqual(elem1, list_input)
self.assertNotEqual(elem2, list_input)
def test_nested_update_in_place_true_list_input_as_element_true(self):
doc = self.sample_data4
# get all instances of the given element
list_input = [1, 2, 3, 4, 5]
# update those instances with the altered results
doc_updated = nested_update(
doc, "plz", list_input, in_place=True, treat_as_element=True
)
elem1 = doc_updated["plz"]
elem2 = doc_updated["vertragsteile"][0]["beitragsDaten"]["plz"]
# should not work without specifying "treat_list_as_element = True"
# in nested_update
self.assertEqual(elem1, list_input)
self.assertEqual(elem2, list_input)
def test_nested_delete_in_place_false(self):
"""
nested_delete should mutate and return a copy of the original document
"""
before_id = id(self.sample_data1)
result = nested_delete(self.sample_data1, "build_version", in_place=False)
after_id = id(result)
# the object ids should _not_ match.
self.assertNotEqual(before_id, after_id)
def test_nested_delete_in_place_true(self):
"""nested_delete should mutate and return the original document"""
before_id = id(self.sample_data1)
result = nested_delete(self.sample_data1, "build_version", in_place=True)
after_id = id(result)
# the object ids should match.
self.assertEqual(before_id, after_id)
def test_nested_update_taco_for_example(self):
document = [{"taco": 42}, {"salsa": [{"burrito": {"taco": 69}}]}]
updated_document = nested_update(
document, "taco", [100, 200], treat_as_element=False
)
self.assertEqual(updated_document[0]["taco"], 100)
# The multi-update version only works for scalar input,
# if you need to adress a list of dicts, you have to
# manually iterate over those and pass them to nested_update
# one by one
self.assertEqual(updated_document[1]["salsa"][0]["burrito"]["taco"], 200)
def test_nested_update_raise_error(self):
doc = self.sample_data4
# get all instances of the given element
list_input = 1
# update those instances with the altered results
self.assertRaises(
Exception,
nested_update,
doc,
"plz",
list_input,
in_place=True,
treat_as_element=False,
)
def test_sample_data2(self):
result = {
"hardware_details": {
"model_name": "MacBook Pro",
"processor_details": {"test_key1": "test_value1"},
"total_number_of_cores": "5",
"memory": "16 GB",
}
}
self.assertEqual(
result,
nested_update(
self.sample_data2, "processor_details", {"test_key1": "test_value1"}
),
)
def test_sample_data3(self):
result = {"values": [{"checks": {"key1": ["value1"], "key2": "value2"}}]}
self.assertEqual(
result,
nested_update(
self.sample_data3, "checks", {"key1": ["value1"], "key2": "value2"}
),
)
def test_sample_data4(self):
result = {
"modelversion": {"key1": ["value1"], "key2": "value2"},
"vorgangsID": "1",
"versorgungsvorschlagDatum": 1510558834978,
"eingangsdatum": 1510558834978,
"plz": 82269,
"vertragsteile": [
{
"typ": "1",
"beitragsDaten": {
"endalter": 85,
"brutto": 58.76,
"netto": 58.76,
"zahlungsrhythmus": "MONATLICH",
"plz": 86899,
},
"beginn": 1512082800000,
"lebenslang": "True",
"ueberschussverwendung": {
"ueberschussverwendung": "2",
"indexoption": "3",
},
"deckung": [
{
"typ": "2",
"art": "1",
"leistung": {"value": 7500242424.0, "einheit": "2"},
"leistungsRhythmus": "1",
}
],
"zuschlagNachlass": [],
},
{
"typ": "1",
"beitragsDaten": {
"endalter": 85,
"brutto": 0.6,
"netto": 0.6,
"zahlungsrhythmus": "1",
},
"zuschlagNachlass": [],
},
],
}
self.assertEqual(
result,
nested_update(
self.sample_data4,
"modelversion",
{"key1": ["value1"], "key2": "value2"},
),
)
class TestNestedAlter(BaseLookUpApi):
def test_nested_alter_in_place_true(self):
# callback functions
def callback(data):
return str(data) + "###"
doc_updated = nested_alter(
self.sample_data4, "vorgangsID", callback, in_place=True
)
vorgangsid = doc_updated["vorgangsID"]
self.assertEqual(vorgangsid, "1###")
def test_nested_alter_in_place_false(self):
# callback functions
def callback(data):
return str(data) + "###"
doc_updated = nested_alter(
self.sample_data4, "vorgangsID", callback, in_place=False
)
vorgangsid = doc_updated["vorgangsID"]
# should not work without specifying
# "treat_list_as_element = True" in nested_update
self.assertEqual(vorgangsid, "1###")
def test_nested_alter_list_input_in_place_true(self):
# callback functions
def callback(data):
return str(data) + "###"
doc_updated = nested_alter(
self.sample_data4, ["plz", "vorgangsID"], callback, in_place=True
)
plz1 = doc_updated["plz"]
plz2 = doc_updated["vertragsteile"][0]["beitragsDaten"]["plz"]
vorgangsid = doc_updated["vorgangsID"]
# should not work without specifying
# "treat_list_as_element = True" in nested_update
self.assertEqual(plz1, "82269###")
self.assertEqual(plz2, "86899###")
self.assertEqual(vorgangsid, "1###")
def test_nested_alter_list_input_with_args_in_place_true(self):
# callback functions
def callback(data, str1, str2):
return str(data) + str1 + str2
doc_updated = nested_alter(
self.sample_data4,
["plz", "vorgangsID"],
callback,
function_parameters=["abc", "def"],
in_place=True,
)
plz1 = doc_updated["plz"]
plz2 = doc_updated["vertragsteile"][0]["beitragsDaten"]["plz"]
vorgangsid = doc_updated["vorgangsID"]
# should not work without specifying
# "treat_list_as_element = True" in nested_update
self.assertEqual(plz1, "82269abcdef")
self.assertEqual(plz2, "86899abcdef")
self.assertEqual(vorgangsid, "1abcdef")
def test_nested_alter_list_input_with_args_in_place_false(self):
# callback functions
def callback(data, str1, str2):
return str(data) + str1 + str2
doc_updated = nested_alter(
self.sample_data4,
["plz", "vorgangsID"],
callback,
function_parameters=["abc", "def"],
in_place=False,
)
plz1 = doc_updated["plz"]
plz2 = doc_updated["vertragsteile"][0]["beitragsDaten"]["plz"]
vorgangsid = doc_updated["vorgangsID"]
# should not work without specifying
# "treat_list_as_element = True" in nested_update
self.assertEqual(plz1, "82269abcdef")
self.assertEqual(plz2, "86899abcdef")
self.assertEqual(vorgangsid, "1abcdef")
def test_nested_alter_list_input_in_place_false(self):
# callback functions
def callback(data):
return str(data) + "###"
doc_updated = nested_alter(
self.sample_data4, ["plz", "vorgangsID"], callback, in_place=False
)
plz1 = doc_updated["plz"]
plz2 = doc_updated["vertragsteile"][0]["beitragsDaten"]["plz"]
vorgangsid = doc_updated["vorgangsID"]
# should not work without specifying
# "treat_list_as_element = True" in nested_update
self.assertEqual(plz1, "82269###")
self.assertEqual(plz2, "86899###")
self.assertEqual(vorgangsid, "1###")
def test_nested_alter_taco_for_example(self):
documents = [{"taco": 42}, {"salsa": [{"burrito": {"taco": 69}}]}]
# write a callback function which processes a scalar value.
# Be aware about the possible types which can be passed to
# the callback functions.
# In this example we can be sure that only int will be passed,
# in production you should check the type because it could be
# anything.
def callback(data):
return data + 10 # (data/100*10)
# The alter-version only works for scalar input (one dict),
# if you need to adress a list of dicts, you have to
# manually iterate over those and pass them to
# nested_update one by one
out = []
for elem in documents:
altered_document = nested_alter(elem, "taco", callback)
out.append(altered_document)
self.maxDiff = None
self.assertEqual(out[0]["taco"], 52)
self.assertEqual(out[1]["salsa"][0]["burrito"]["taco"], 79)
def test_nested_alter_work_with_right_order(self):
document = {"taco": 42, "salsa": [{"burrito":{"key":20}}], "key":50}
def callback(data):
return data + 100
altered_document = nested_alter(document, "key", callback, in_place=True)
self.assertEqual(altered_document["salsa"][0]["burrito"]["key"], 120)
self.assertEqual(altered_document["key"], 150)
def test_sample_data4(self):
result = {
"modelversion": "1.1.0",
"vorgangsID": "1",
"versorgungsvorschlagDatum": 1510558834978,
"eingangsdatum": 1510558834978,
"plz": 82270,
"vertragsteile": [
{
"typ": "1",
"beitragsDaten": {
"endalter": 85,
"brutto": 58.76,
"netto": 58.76,
"zahlungsrhythmus": "MONATLICH",
"plz": 86900,
},
"beginn": 1512082800000,
"lebenslang": "True",
"ueberschussverwendung": {
"ueberschussverwendung": "2",
"indexoption": "3",
},
"deckung": [
{
"typ": "2",
"art": "1",
"leistung": {"value": 7500242424.0, "einheit": "2"},
"leistungsRhythmus": "1",
}
],
"zuschlagNachlass": [],
},
{
"typ": "1",
"beitragsDaten": {
"endalter": 85,
"brutto": 0.6,
"netto": 0.6,
"zahlungsrhythmus": "1",
},
"zuschlagNachlass": [],
},
],
}
# add +1 to all plz
def callback(data):
return data + 1
self.maxDiff = None
self.assertEqual(result, nested_alter(self.sample_data4, "plz", callback))

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from unittest import TestCase
from nested_lookup import (
nested_lookup,
get_all_keys,
get_occurrence_of_key,
get_occurrence_of_value,
get_occurrences_and_values
)
class TestNestedLookup(TestCase):
def setUp(self):
self.subject_dict = {"a": 1, "b": {"d": 100}, "c": {"d": 200}}
self.subject_dict2 = {
"name": "Russell Ballestrini",
"email_address": "test1@example.com",
"other": {
"secondary_email": "test2@example.com",
"EMAIL_RECOVERY": "test3@example.com",
"email_address": "test4@example.com",
},
}
self.subject_dict3 = {
"build_version": {
"model_name": "MacBook Pro",
"build_version": {
"processor_name": "Intel Core i7",
"processor_speed": "2.7 GHz",
"core_details": {
"build_version": "4",
"l2_cache(per_core)": "256 KB",
},
},
"number_of_cores": "4",
"memory": "256 KB",
},
"os_details": {"product_version": "10.13.6", "build_version": "17G65"},
"name": "Test",
"date": "YYYY-MM-DD HH:MM:SS",
}
self.subject_dict4 = {1: "a", 2: {"b": 44, "C": 55}, 3: "d", 4: "e", "6776": "works"}
def test_nested_lookup(self):
results = nested_lookup("d", self.subject_dict)
self.assertEqual(2, len(results))
self.assertIn(100, results)
self.assertIn(200, results)
self.assertSetEqual({100, 200}, set(results))
def test_nested_lookup_wrapped_in_list(self):
results = nested_lookup("d", [{}, self.subject_dict, {}])
self.assertEqual(2, len(results))
self.assertIn(100, results)
self.assertIn(200, results)
self.assertSetEqual({100, 200}, set(results))
def test_nested_lookup_wrapped_in_list_in_dict_in_list(self):
results = nested_lookup("d", [{}, {"H": [self.subject_dict]}])
self.assertEqual(2, len(results))
self.assertIn(100, results)
self.assertIn(200, results)
self.assertSetEqual({100, 200}, set(results))
def test_nested_lookup_wrapped_in_list_in_list(self):
results = nested_lookup("d", [{}, [self.subject_dict, {}]])
self.assertEqual(2, len(results))
self.assertIn(100, results)
self.assertIn(200, results)
self.assertSetEqual({100, 200}, set(results))
def test_nested_lookup_key_is_non_str(self):
results = nested_lookup(key=4, document=self.subject_dict4)
self.assertIn("e", results)
def test_wild_nested_lookup(self):
results = nested_lookup(key="mail", document=self.subject_dict2, wild=True)
self.assertEqual(4, len(results))
self.assertIn("test1@example.com", results)
self.assertIn("test2@example.com", results)
self.assertIn("test3@example.com", results)
def test_wild_nested_lookup_integer_keys_in_document(self):
results = nested_lookup(key="c", document=self.subject_dict4, wild=True)
self.assertIn(55, results)
def test_wild_nested_lookup_integer_key_as_substring(self):
# test that wild works converts integers into strings before substring matching.
results = nested_lookup(key=77, document=self.subject_dict4, wild=True)
self.assertIn("works", results)
def test_wild_with_keys_nested_lookup(self):
matches = nested_lookup(
key="mail", document=self.subject_dict2, wild=True, with_keys=True
)
self.assertEqual(3, len(matches))
self.assertIn("email_address", matches)
self.assertIn("secondary_email", matches)
self.assertIn("EMAIL_RECOVERY", matches)
self.assertSetEqual(
{"test1@example.com", "test4@example.com"}, set(matches["email_address"])
)
self.assertIn("test2@example.com", matches["secondary_email"])
def test_nested_lookup_with_keys(self):
matches = nested_lookup("d", self.subject_dict, with_keys=True)
self.assertIn("d", matches)
self.assertEqual(2, len(matches["d"]))
self.assertSetEqual({100, 200}, set(matches["d"]))
def test_after_key_is_found(self):
result = nested_lookup(key="build_version", document=self.subject_dict3)
self.assertEqual(4, len(result))
self.assertIn("4", result)
self.assertIn("17G65", result)
match1 = {
"processor_name": "Intel Core i7",
"processor_speed": "2.7 GHz",
"core_details": {"build_version": "4", "l2_cache(per_core)": "256 KB"},
}
self.assertIn(match1, result)
match2 = {
"build_version": {
"processor_name": "Intel Core i7",
"processor_speed": "2.7 GHz",
"core_details": {"build_version": "4", "l2_cache(per_core)": "256 KB"},
},
"memory": "256 KB",
"model_name": "MacBook Pro",
"number_of_cores": "4",
}
self.assertIn(match2, result)
class TestGetAllKeys(TestCase):
def setUp(self):
self.sample1 = {
"hardware_details": {
"model_name": "MacBook Pro",
"processor_details": {
"processor_name": "Intel Core i7",
"processor_speed": "2.7 GHz",
"core_details": {
"total_numberof_cores": "4",
"l2_cache(per_core)": "256 KB",
},
},
"total_number_of_cores": "4",
"memory": "16 GB",
},
"os_details": {"product_version": "10.13.6", "build_version": "17G65"},
"name": "Test",
"date": "YYYY-MM-DD HH:MM:SS",
}
self.sample2 = {
"hardware_details": {
"model_name": "MacBook Pro",
"processor_details": [
{
"processor_name": "Intel Core i7",
"processor_speed": "2.7 GHz",
"core_details": {
"total_numberof_cores": "4",
"l2_cache(per_core)": "256 KB",
},
}
],
"total_number_of_cores": "4",
"memory": "16 GB",
}
}
self.sample3 = {
"hardware_details": {
"model_name": "MacBook Pro",
"processor_details": [
{"processor_name": "Intel Core i7", "processor_speed": "2.7 GHz"},
{"total_numberof_cores": "4", "l2_cache(per_core)": "256 KB"},
],
"total_number_of_cores": "4",
"memory": "16 GB",
}
}
self.sample4 = {
"values": [
{
"checks": [
{
"monitoring_zones": [
"mzdfw",
"mzfra",
"mzhkg",
"mziad",
"mzlon",
"mzord",
"mzsyd",
]
}
]
}
]
}
self.sample5 = [
{
"listings": [
{
"name": "title",
"postcode": "postcode",
"full_address": "fulladdress",
"city": "city",
"lat": "latitude",
"lng": "longitude",
}
]
}
]
def test_sample_data1(self):
result = get_all_keys(self.sample1)
self.assertEqual(15, len(result))
keys_to_verify = [
"model_name",
"core_details",
"l2_cache(per_core)",
"build_version",
"date",
]
for key in keys_to_verify:
self.assertIn(key, result)
def test_sample_data2(self):
result = get_all_keys(self.sample2)
self.assertEqual(10, len(result))
keys_to_verify = [
"hardware_details",
"processor_speed",
"total_numberof_cores",
"memory",
]
for key in keys_to_verify:
self.assertIn(key, result)
def test_sample_data3(self):
result = get_all_keys(self.sample3)
self.assertEqual(9, len(result))
keys_to_verify = [
"processor_details",
"processor_name",
"l2_cache(per_core)",
"total_number_of_cores",
]
for key in keys_to_verify:
self.assertIn(key, result)
def test_sample_data4(self):
result = get_all_keys(self.sample4)
self.assertEqual(3, len(result))
keys_to_verify = ["values", "checks", "monitoring_zones"]
for key in keys_to_verify:
self.assertIn(key, result)
def test_sample_data5(self):
result = get_all_keys(self.sample5)
self.assertEqual(7, len(result))
keys_to_verify = [
"listings",
"name",
"postcode",
"full_address",
"city",
"lat",
"lng",
]
for key in keys_to_verify:
self.assertIn(key, result)
class TestGetOccurrence(TestCase):
def setUp(self):
self.sample1 = {
"build_version": {
"model_name": "MacBook Pro",
"build_version": {
"processor_name": "Intel Core i7",
"processor_speed": "2.7 GHz",
"core_details": {
"build_version": "4",
"l2_cache(per_core)": "256 KB",
},
},
"number_of_cores": "4",
"memory": "256 KB",
},
"os_details": {"product_version": "10.13.6", "build_version": "17G65"},
"name": "Test",
"date": "YYYY-MM-DD HH:MM:SS",
}
self.sample2 = {
"hardware_details": {
"model_name": "MacBook Pro",
"processor_details": [
{
"processor_name": "4",
"processor_speed": "2.7 GHz",
"core_details": {
"total_numberof_cores": "4",
"l2_cache(per_core)": "256 KB",
},
}
],
"total_number_of_cores": "4",
"memory": "16 GB",
}
}
self.sample3 = {
"hardware_details": {
"model_name": "MacBook Pro",
"processor_details": [
{"total_number_of_cores": "4", "processor_speed": "2.7 GHz"},
{"total_number_of_cores": "4", "l2_cache(per_core)": "256 KB"},
],
"total_number_of_cores": "4",
"memory": "16 GB",
}
}
self.sample4 = {
"values": [
{
"checks": [
{
"monitoring_zones": [
"mzdfw",
"mzfra",
"mzhkg",
"mziad",
"mzlon",
"mzord",
"mzsyd",
]
}
]
}
]
}
self.sample5 = {
"hardware_details": {
"model_name": "MacBook Pro",
"total_number_of_cores": 0,
"memory": False,
}
}
self.sample6 = [
{
"processor_name": "4",
"processor_speed": "2.7 GHz",
"core_details": {
"total_numberof_cores": "4",
"l2_cache(per_core)": "256 KB",
}
}
]
self.sample7 = [
{
"processor_name": "4",
"processor_speed": "2.7 GHz",
"core_details": {
"total_numberof_cores": "4",
"l2_cache(per_core)": "256 KB",
}
},
{
"processor_name": "4",
"processor_speed": "2.7 GHz",
"core_details": {
"total_numberof_cores": "4",
"l2_cache(per_core)": "256 KB",
}
}
]
def test_sample_data1(self):
result = get_occurrence_of_key(self.sample1, "build_version")
self.assertEqual(4, result)
result = get_occurrence_of_value(self.sample1, "256 KB")
self.assertEqual(2, result)
def test_sample_data2(self):
result = get_occurrence_of_key(self.sample2, "core_details")
self.assertEqual(1, result)
result = get_occurrence_of_value(self.sample2, "4")
self.assertEqual(3, result)
def test_sample_data3(self):
result = get_occurrence_of_key(self.sample3, "total_number_of_cores")
self.assertEqual(3, result)
result = get_occurrence_of_value(self.sample3, "4")
self.assertEqual(3, result)
def test_sample_data4(self):
result = get_occurrence_of_key(self.sample4, "checks")
self.assertEqual(1, result)
result = get_occurrence_of_value(self.sample4, "mziad")
self.assertEqual(1, result)
# Add one more value in key "monitoring_zones" and verify
self.sample4["values"][0]["checks"][0]["monitoring_zones"].append("mziad")
self.assertEqual(2, get_occurrence_of_value(self.sample4, "mziad"))
def test_sample_data5(self):
self.assertEqual(
1, get_occurrence_of_key(self.sample5, "total_number_of_cores")
)
self.assertEqual(1, get_occurrence_of_key(self.sample5, "memory"))
# Add key 'memory' and verify
self.sample5["memory"] = 0
self.assertEqual(2, get_occurrence_of_key(self.sample5, "memory"))
def test_sample_data6(self):
value = '4'
result = get_occurrences_and_values(self.sample6, value)
self.assertEqual(2, result[value]['occurrences'])
self.assertEqual(2, len(result[value]['values']))
def test_sample_data7(self):
value = '2.7 GHz'
result = get_occurrences_and_values(self.sample6, value)
self.assertEqual(1, result[value]['occurrences'])
self.assertEqual(1, len(result[value]['values']))
def test_sample_data8(self):
value = '4'
result = get_occurrences_and_values(self.sample7, value)
self.assertEqual(4, result[value]['occurrences'])
self.assertEqual(4, len(result[value]['values']))
def test_sample_data9(self):
value = '5'
result = get_occurrences_and_values(self.sample7, value)
self.assertEqual(0, result[value]['occurrences'])
self.assertEqual(0, len(result[value]['values']))
if __name__ == "__main__":
pass