from datetime import date as Date import json import os import io import re import shutil import pydantic import pytest import time_machine import ruamel.yaml from rendercv import data_models as dm from .conftest import update_testdata @pytest.mark.parametrize( "date, expected_date_object, expected_error", [ ("2020-01-01", Date(2020, 1, 1), None), ("2020-01", Date(2020, 1, 1), None), ("2020", Date(2020, 1, 1), None), (2020, Date(2020, 1, 1), None), ("present", Date(2024, 1, 1), None), ("invalid", None, ValueError), ("20222", None, ValueError), ("202222-20200", None, ValueError), ("202222-12-20", None, ValueError), ("2022-20-20", None, ValueError), ], ) @time_machine.travel("2024-01-01") def test_get_date_object(date, expected_date_object, expected_error): if expected_error: with pytest.raises(expected_error): dm.get_date_object(date) else: assert dm.get_date_object(date) == expected_date_object @pytest.mark.parametrize( "date, expected_date_string", [ (Date(2020, 1, 1), "Jan 2020"), (Date(2020, 2, 1), "Feb 2020"), (Date(2020, 3, 1), "Mar 2020"), (Date(2020, 4, 1), "Apr 2020"), (Date(2020, 5, 1), "May 2020"), (Date(2020, 6, 1), "June 2020"), (Date(2020, 7, 1), "July 2020"), (Date(2020, 8, 1), "Aug 2020"), (Date(2020, 9, 1), "Sept 2020"), (Date(2020, 10, 1), "Oct 2020"), (Date(2020, 11, 1), "Nov 2020"), (Date(2020, 12, 1), "Dec 2020"), ], ) def test_format_date(date, expected_date_string): assert dm.format_date(date) == expected_date_string @pytest.mark.parametrize( "key, value", [ ("cv.phone", "+905555555555"), ("cv.email", "test@example.com"), ("cv.sections.education.0.degree", "PhD"), ("cv.sections.education.0.highlights.0", "Did this."), ("cv.sections.this_is_a_new_section", '["This is a text entry."]'), ("design.page_size", "a4paper"), ("design", '{"theme": "engineeringresumes"}'), ], ) def test_set_or_update_a_value(rendercv_data_model, key, value): dm.set_or_update_a_value(rendercv_data_model, key, value) # replace with regex pattern: key = re.sub(r"sections\.([^\.]*)", 'sections_input["\\1"]', key) key = re.sub(r"\.(\d+)", "[\\1]", key) if value.startswith("{") and value.endswith("}"): value = eval(value) elif value.startswith("[") and value.endswith("]"): value = eval(value) assert eval(f"rendercv_data_model.{key}") == value @pytest.mark.parametrize( "key, value", [ ("cv.phones", "+905555555555"), ("cv.emssdsail", ""), ("cv.sections.education.99.degree", "PhD"), ("dessssign.page_size", "a4paper"), ], ) def test_set_or_update_a_value_invalid_keys(rendercv_data_model, key, value): with pytest.raises((ValueError, KeyError, IndexError, AttributeError)): dm.set_or_update_a_value(rendercv_data_model, key, value) @pytest.mark.parametrize( "key, value", [ ("cv.phone", "+9999995555555555"), ("cv.email", "notanemail***"), ("cv.sections.education.0.highlights", "this is not a list"), ("design.page_size", "invalid_page_size"), ], ) def test_set_or_update_a_value_invalid_values(rendercv_data_model, key, value): with pytest.raises(pydantic.ValidationError): dm.set_or_update_a_value(rendercv_data_model, key, value) def test_read_input_file(input_file_path): # Update the auxiliary files if update_testdata is True if update_testdata: # create testdata directory if it doesn't exist if not input_file_path.parent.exists(): input_file_path.parent.mkdir() input_dictionary = { "cv": { "name": "John Doe", }, "design": { "theme": "classic", }, } # dump the dictionary to a yaml file yaml_object = ruamel.yaml.YAML() yaml_object.dump(input_dictionary, input_file_path) data_model = dm.read_input_file(input_file_path) assert isinstance(data_model, dm.RenderCVDataModel) def test_read_input_file_directly_with_contents(input_file_path): input_dictionary = { "cv": { "name": "John Doe", }, "design": { "theme": "classic", }, } # dump the dictionary to a yaml file yaml_object = ruamel.yaml.YAML() yaml_object.width = 60 yaml_object.indent(mapping=2, sequence=4, offset=2) with io.StringIO() as string_stream: yaml_object.dump(input_dictionary, string_stream) yaml_string = string_stream.getvalue() data_model = dm.read_input_file(yaml_string) assert isinstance(data_model, dm.RenderCVDataModel) def test_read_input_file_invalid_file(tmp_path): invalid_file_path = tmp_path / "invalid.extension" invalid_file_path.write_text("dummy content", encoding="utf-8") with pytest.raises(ValueError): dm.read_input_file(invalid_file_path) def test_read_input_file_that_doesnt_exist(tmp_path): non_existent_file_path = tmp_path / "non_existent_file.yaml" with pytest.raises(FileNotFoundError): dm.read_input_file(non_existent_file_path) @pytest.mark.parametrize( "theme", dm.available_themes, ) def test_get_a_sample_data_model(theme): data_model = dm.get_a_sample_data_model("John Doe", theme) assert isinstance(data_model, dm.RenderCVDataModel) def test_get_a_sample_data_model_invalid_theme(): with pytest.raises(ValueError): dm.get_a_sample_data_model("John Doe", "invalid") def test_generate_json_schema(): schema = dm.generate_json_schema() assert isinstance(schema, dict) def test_generate_json_schema_file(tmp_path): schema_file_path = tmp_path / "schema.json" dm.generate_json_schema_file(schema_file_path) assert schema_file_path.exists() schema_text = schema_file_path.read_text(encoding="utf-8") schema = json.loads(schema_text) assert isinstance(schema, dict) # def test_if_the_schema_is_the_latest(root_directory_path): # original_schema_file_path = root_directory_path / "schema.json" # original_schema_text = original_schema_file_path.read_text() # original_schema = json.loads(original_schema_text) # new_schema = dm.generate_json_schema() # assert original_schema == new_schema @pytest.mark.parametrize( "start_date, end_date, date, expected_date_string, expected_date_string_only_years," " expected_time_span", [ ( "2020-01-01", "2021-01-01", None, "Jan 2020 -- Jan 2021", "2020 -- 2021", "1 year 1 month", ), ( Date(2020, 1, 1), Date(2021, 1, 1), None, "Jan 2020 -- Jan 2021", "2020 -- 2021", "1 year 1 month", ), ( "2020-01", "2021-01", None, "Jan 2020 -- Jan 2021", "2020 -- 2021", "1 year 1 month", ), ( "2020-01", "2021-01-01", None, "Jan 2020 -- Jan 2021", "2020 -- 2021", "1 year 1 month", ), ( "2020-01-01", "2021-01", None, "Jan 2020 -- Jan 2021", "2020 -- 2021", "1 year 1 month", ), ( "2020-01-01", None, None, "Jan 2020 -- present", "2020 -- present", "4 years 1 month", ), ( "2020-02-01", "present", None, "Feb 2020 -- present", "2020 -- present", "3 years 11 months", ), ("2020-01-01", "2021-01-01", "2023-02-01", "Feb 2023", "2023", ""), ("2020", "2021", None, "2020 -- 2021", "2020 -- 2021", "1 year"), ("2020", None, None, "2020 -- present", "2020 -- present", "4 years"), ("2020-10-10", "2022", None, "Oct 2020 -- 2022", "2020 -- 2022", "2 years"), ( "2020-10-10", "2020-11-05", None, "Oct 2020 -- Nov 2020", "2020 -- 2020", "1 month", ), ("2022", "2023-10-10", None, "2022 -- Oct 2023", "2022 -- 2023", "1 year"), ( "2020-01-01", "present", "My Custom Date", "My Custom Date", "My Custom Date", "", ), ( "2020-01-01", None, "My Custom Date", "My Custom Date", "My Custom Date", "", ), ( None, None, "My Custom Date", "My Custom Date", "My Custom Date", "", ), ( None, "2020-01-01", "My Custom Date", "My Custom Date", "My Custom Date", "", ), (None, None, "2020-01-01", "Jan 2020", "2020", ""), (None, None, "2020-09", "Sept 2020", "2020", ""), (None, None, Date(2020, 1, 1), "Jan 2020", "2020", ""), (None, None, None, "", "", ""), (None, "2020-01-01", None, "Jan 2020", "2020", ""), (None, "present", None, "Jan 2024", "2024", ""), ("2002", "2020", "2024", "2024", "2024", ""), ], ) @time_machine.travel("2024-01-01") def test_dates( start_date, end_date, date, expected_date_string, expected_date_string_only_years, expected_time_span, ): entry_base = dm.EntryBase(start_date=start_date, end_date=end_date, date=date) assert entry_base.date_string == expected_date_string assert entry_base.date_string_only_years == expected_date_string_only_years assert entry_base.time_span_string == expected_time_span @pytest.mark.parametrize( "date, expected_date_string", [ ("2020-01-01", "Jan 2020"), ("2020-01", "Jan 2020"), ("2020", "2020"), ], ) def test_publication_dates(publication_entry, date, expected_date_string): publication_entry["date"] = date publication_entry = dm.PublicationEntry(**publication_entry) assert publication_entry.date_string == expected_date_string @pytest.mark.parametrize("date", ["2025-23-23"]) def test_invalid_publication_dates(publication_entry, date): with pytest.raises(pydantic.ValidationError): publication_entry["date"] = date dm.PublicationEntry(**publication_entry) @pytest.mark.parametrize( "start_date, end_date, date", [ ("aaa", "2021-01-01", None), ("2020-01-01", "aaa", None), ("2023-01-01", "2021-01-01", None), ("2022", "2021", None), ("2025", "2021", None), ("2020-01-01", "invalid_end_date", None), ("invalid_start_date", "2021-01-01", None), ("2020-99-99", "2021-01-01", None), ("2020-10-12", "2020-99-99", None), (None, None, "2020-20-20"), ], ) def test_invalid_dates(start_date, end_date, date): with pytest.raises(pydantic.ValidationError): dm.EntryBase(start_date=start_date, end_date=end_date, date=date) @pytest.mark.parametrize( "doi, expected_doi_url", [ ("10.1109/TASC.2023.3340648", "https://doi.org/10.1109/TASC.2023.3340648"), ], ) def test_doi_url(publication_entry, doi, expected_doi_url): publication_entry["doi"] = doi publication_entry = dm.PublicationEntry(**publication_entry) assert publication_entry.doi_url == expected_doi_url @pytest.mark.parametrize( "network, username", [ ("Mastodon", "invalidmastodon"), ("Mastodon", "@inva@l@id"), ("Mastodon", "@invalid@ne<>twork.com"), ("StackOverflow", "invalidusername"), ("StackOverflow", "invalidusername//"), ("StackOverflow", "invalidusername/invalid"), ("YouTube", "@invalidusername"), ], ) def test_invalid_social_networks(network, username): with pytest.raises(pydantic.ValidationError): dm.SocialNetwork(network=network, username=username) @pytest.mark.parametrize( "network, username, expected_url", [ ("LinkedIn", "myusername", "https://linkedin.com/in/myusername"), ("GitHub", "myusername", "https://github.com/myusername"), ("Instagram", "myusername", "https://instagram.com/myusername"), ("ORCID", "myusername", "https://orcid.org/myusername"), ("Twitter", "myusername", "https://twitter.com/myusername"), ("Mastodon", "@myusername@test.org", "https://test.org/@myusername"), ( "StackOverflow", "4567/myusername", "https://stackoverflow.com/users/4567/myusername", ), ( "GitLab", "myusername", "https://gitlab.com/myusername", ), ( "ResearchGate", "myusername", "https://researchgate.net/profile/myusername", ), ( "YouTube", "myusername", "https://youtube.com/@myusername", ), ( "Google Scholar", "myusername", "https://scholar.google.com/citations?user=myusername", ), ], ) def test_social_network_url(network, username, expected_url): social_network = dm.SocialNetwork(network=network, username=username) assert str(social_network.url) == expected_url @pytest.mark.parametrize( "entry, expected_entry_type, expected_section_type", [ ( "publication_entry", "PublicationEntry", "SectionWithPublicationEntries", ), ( "experience_entry", "ExperienceEntry", "SectionWithExperienceEntries", ), ( "education_entry", "EducationEntry", "SectionWithEducationEntries", ), ( "normal_entry", "NormalEntry", "SectionWithNormalEntries", ), ("one_line_entry", "OneLineEntry", "SectionWithOneLineEntries"), ("text_entry", "TextEntry", "SectionWithTextEntries"), ("bullet_entry", "BulletEntry", "SectionWithBulletEntries"), ], ) def test_get_entry_and_section_type( entry, expected_entry_type, expected_section_type, request: pytest.FixtureRequest ): entry = request.getfixturevalue(entry) entry_type, section_type = dm.get_entry_and_section_type(entry) assert entry_type == expected_entry_type assert section_type.__name__ == expected_section_type # initialize the entry with the entry type if entry_type != "TextEntry": entry = eval(f"dm.{entry_type}(**entry)") entry_type, section_type = dm.get_entry_and_section_type(entry) assert entry_type == expected_entry_type assert section_type.__name__ == expected_section_type def test_sections( education_entry, experience_entry, publication_entry, normal_entry, one_line_entry, text_entry, ): input = { "name": "John Doe", "sections": { "arbitrary_title": [ education_entry, education_entry, ], "arbitrary_title_2": [ experience_entry, experience_entry, ], "arbitrary_title_3": [ publication_entry, publication_entry, ], "arbitrary_title_4": [ normal_entry, normal_entry, ], "arbitrary_title_5": [ one_line_entry, one_line_entry, ], "arbitrary_title_6": [ text_entry, text_entry, ], }, } cv = dm.CurriculumVitae(**input) assert len(cv.sections) == 6 for section in cv.sections: assert len(section.entries) == 2 def test_sections_with_invalid_entries(): input = {"name": "John Doe", "sections": dict()} input["sections"]["section_title"] = [ { "this": "is", "an": "invalid", "entry": 10, } ] with pytest.raises(pydantic.ValidationError): dm.CurriculumVitae(**input) @pytest.mark.parametrize( "invalid_custom_theme_name", [ "pathdoesntexist", "invalid_theme_name", ], ) def test_invalid_custom_theme(invalid_custom_theme_name): with pytest.raises(pydantic.ValidationError): dm.RenderCVDataModel( **{ "cv": {"name": "John Doe"}, "design": {"theme": invalid_custom_theme_name}, } ) def test_custom_theme_with_missing_files(tmp_path): custom_theme_path = tmp_path / "customtheme" custom_theme_path.mkdir() with pytest.raises(pydantic.ValidationError): os.chdir(tmp_path) dm.RenderCVDataModel( **{ # type: ignore "cv": {"name": "John Doe"}, "design": {"theme": "customtheme"}, } ) def test_custom_theme(testdata_directory_path): os.chdir( testdata_directory_path / "test_copy_theme_files_to_output_directory_custom_theme" ) data_model = dm.RenderCVDataModel( **{ # type: ignore "cv": {"name": "John Doe"}, "design": {"theme": "dummytheme"}, } ) assert data_model.design.theme == "dummytheme" def test_custom_theme_without_init_file(tmp_path, testdata_directory_path): reference_custom_theme_path = ( testdata_directory_path / "test_copy_theme_files_to_output_directory_custom_theme" / "dummytheme" ) # copy the directory to tmp_path: custom_theme_path = tmp_path / "dummytheme" shutil.copytree(reference_custom_theme_path, custom_theme_path, dirs_exist_ok=True) # remove the __init__.py file: init_file = custom_theme_path / "__init__.py" init_file.unlink() os.chdir(tmp_path) data_model = dm.RenderCVDataModel( **{ # type: ignore "cv": {"name": "John Doe"}, "design": {"theme": "dummytheme"}, } ) assert data_model.design.theme == "dummytheme" def test_custom_theme_with_broken_init_file(tmp_path, testdata_directory_path): reference_custom_theme_path = ( testdata_directory_path / "test_copy_theme_files_to_output_directory_custom_theme" / "dummytheme" ) # copy the directory to tmp_path: custom_theme_path = tmp_path / "dummytheme" shutil.copytree(reference_custom_theme_path, custom_theme_path, dirs_exist_ok=True) # overwrite the __init__.py file (syntax error) init_file = custom_theme_path / "__init__.py" init_file.write_text("invalid python code", encoding="utf-8") os.chdir(tmp_path) with pytest.raises(pydantic.ValidationError): dm.RenderCVDataModel( **{ # type: ignore "cv": {"name": "John Doe"}, "design": {"theme": "dummytheme"}, } ) # overwrite the __init__.py file (import error) init_file = custom_theme_path / "__init__.py" init_file.write_text("from ... import test", encoding="utf-8") os.chdir(tmp_path) with pytest.raises(pydantic.ValidationError): dm.RenderCVDataModel( **{ # type: ignore "cv": {"name": "John Doe"}, "design": {"theme": "dummytheme"}, } ) def test_locale_catalog(): data_model = dm.get_a_sample_data_model("John Doe") data_model.locale_catalog = dm.LocaleCatalog( month="a", months="b", year="c", years="d", present="e", to="f", abbreviations_for_months=[ "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", ], ) assert dm.locale_catalog == data_model.locale_catalog.model_dump() def test_if_local_catalog_resets(): data_model = dm.get_a_sample_data_model("John Doe") data_model.locale_catalog = dm.LocaleCatalog( month="a", ) assert dm.locale_catalog["month"] == "a" data_model = dm.get_a_sample_data_model("John Doe") assert dm.locale_catalog["month"] == "month" def test_dictionary_to_yaml(): input_dictionary = { "test_list": [ "a", "b", "c", ], "test_dict": { "a": 1, "b": 2, }, } yaml_string = dm.dictionary_to_yaml(input_dictionary) # load the yaml string yaml_object = ruamel.yaml.YAML() output_dictionary = yaml_object.load(yaml_string) assert input_dictionary == output_dictionary def test_create_a_sample_yaml_input_file(tmp_path): input_file_path = tmp_path / "input.yaml" yaml_contents = dm.create_a_sample_yaml_input_file(input_file_path) assert input_file_path.exists() assert yaml_contents == input_file_path.read_text(encoding="utf-8") def test_default_input_file_doesnt_have_local_catalog(): yaml_contents = dm.create_a_sample_yaml_input_file() assert "locale_catalog" not in yaml_contents @pytest.mark.parametrize( "key, expected_section_title", [ ("this_is_a_test", "This Is A Test"), ("welcome_to_RenderCV!", "Welcome To RenderCV!"), ("\\faGraduationCap_education", "\\faGraduationCap Education"), ("Hello_World", "Hello World"), ("Hello World", "Hello World"), ], ) def test_dictionary_key_to_proper_section_title(key, expected_section_title): assert dm.dictionary_key_to_proper_section_title(key) == expected_section_title