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ADD no code instructions and FIX Tests (#45)
* Add no code instructions * FIX: End year in Debug (Test) mode * Reduce python version tests and reverse end year * FIX: Simplify and fix tests * HOTFIX: test_cli_cit_per_year_sorted * HOTFIX: citation values * UPDATE: Test once per month * REMOVE: Dependencies in GA tests * ADD: requirements.txt to setup.py * Add sponsor HOTFIX: Include explicit dependencies HOTFIX: Linebreak HOTFIX: Comma
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| buymeacoffee: fernandowip |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,91 +1,55 @@ | ||
| import unittest | ||
| from unittest.mock import patch | ||
| import sortgs | ||
| import os | ||
| import pandas as pd | ||
|
|
||
| class TestSortGS(unittest.TestCase): | ||
| @classmethod | ||
| def setUpClass(self): | ||
| '''run once before all tests''' | ||
| os.system("python sortgs.py --debug --kw 'machine learning' --nresults 10 --endyear 2022") | ||
| self.df_top_10=pd.read_csv('machine_learning.csv') | ||
|
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| os.system("python sortgs.py --debug --kw 'machine learning' --nresults 20 --endyear 2022") | ||
| self.df_top_20=pd.read_csv('machine_learning.csv') | ||
| def setUpClass(cls): | ||
| '''Run once before all tests''' | ||
| os.system("sortgs 'machine learning' --debug --nresults 10 --endyear 2022") | ||
| cls.df_top_10_cli = pd.read_csv('machine_learning.csv') | ||
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| os.system("python sortgs.py --debug --kw 'machine learning' --nresults 20 --endyear 2022 --sortby 'cit/year'") | ||
| self.df_top_sorted_cit_per_year=pd.read_csv('machine_learning.csv') | ||
| os.system("sortgs 'machine learning' --debug --nresults 10 --endyear 2022 --sortby 'cit/year'") | ||
| cls.df_top_sorted_cit_per_year_cli = pd.read_csv('machine_learning.csv') | ||
|
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| # Repeat the above, but testing the cli command | ||
| os.system("sortgs 'machine learning' --debug --nresults 10 --endyear 2022") | ||
| self.df_top_10_cli=pd.read_csv('machine_learning.csv') | ||
| def test_get_10_results_cli(self): | ||
| self.assertEqual(len(self.df_top_10_cli), 10) | ||
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||
| os.system("sortgs 'machine learning' --debug --nresults 20 --endyear 2022") | ||
| self.df_top_20_cli=pd.read_csv('machine_learning.csv') | ||
| def test_is_sorted_by_citations(self): | ||
| df = self.df_top_10_cli | ||
| top_citations = list(df.Citations.values[:5]) | ||
| self.assertEqual(top_citations, [3166, 2853, 2416, 948, 830]) | ||
|
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||
| os.system("sortgs 'machine learning' --debug --nresults 20 --endyear 2022 --sortby 'cit/year'") | ||
| self.df_top_sorted_cit_per_year_cli=pd.read_csv('machine_learning.csv') | ||
|
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||
| def test_get_10_results(self): | ||
| self.assertEqual(len(self.df_top_10), 10) | ||
|
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| def test_get_20_results(self): | ||
| self.assertEqual(len(self.df_top_20), 20) | ||
|
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| def test_is_sorted(self): | ||
| df=self.df_top_20 | ||
| top_citations=list(df.Citations.values[:5]) | ||
| self.assertEqual(top_citations, [49230, 8603, 3166, 3069, 2853]) | ||
|
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||
| def test_top_result(self): | ||
| df=self.df_top_20 | ||
| top_author = str(df.Author.values[0]) | ||
| def test_top_result_cli(self): | ||
| df = self.df_top_10_cli | ||
| top_author = str(df.Author.values[0]).strip() | ||
| top_citation = int(df.Citations.values[0]) | ||
| top_cit_per_year = int(df['cit/year'].values[0]) | ||
| top_results = [top_author, top_citation, top_cit_per_year] | ||
| self.assertEqual(top_results, [' Bishop', 49230, 2896]) | ||
| self.assertEqual(top_results, ['Shale', 3166, 352]) | ||
|
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||
| def test_cit_per_year_sorted(self): | ||
| df=self.df_top_sorted_cit_per_year | ||
| top_citations=list(df.Citations.values[:5]) | ||
| df = self.df_top_sorted_cit_per_year_cli | ||
| top_cit_per_year = list(df['cit/year'].values[:5]) | ||
| top_results = [top_citations, top_cit_per_year] | ||
| self.assertEqual(top_results, [[49230, 8603, 2853, 3166, 2416], | ||
| [2896, 782, 571, 352, 302]]) | ||
| self.assertEqual(top_cit_per_year, [571, 352, 302, 85, 79]) | ||
|
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||
| def test_csv_exists(self): | ||
| os.system("python sortgs.py --debug --kw 'machine learning' --nresults 10") | ||
| self.assertTrue(os.path.exists('machine_learning.csv')) | ||
|
|
||
| def test_cli_get_10_results(self): | ||
| self.assertEqual(len(self.df_top_10_cli), 10) | ||
|
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||
| def test_cli_get_20_results(self): | ||
| self.assertEqual(len(self.df_top_20_cli), 20) | ||
|
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||
| def test_cli_is_sorted(self): | ||
| df=self.df_top_20_cli | ||
| top_citations=list(df.Citations.values[:5]) | ||
| self.assertEqual(top_citations, [49230, 8603, 3166, 3069, 2853]) | ||
|
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||
| def test_cli_top_result(self): | ||
| df=self.df_top_20_cli | ||
| top_author = str(df.Author.values[0]) | ||
| top_citation = int(df.Citations.values[0]) | ||
| top_cit_per_year = int(df['cit/year'].values[0]) | ||
| top_results = [top_author, top_citation, top_cit_per_year] | ||
| self.assertEqual(top_results, [' Bishop', 49230, 2896]) | ||
|
|
||
| def test_cli_cit_per_year_sorted(self): | ||
| df=self.df_top_sorted_cit_per_year_cli | ||
| top_citations=list(df.Citations.values[:5]) | ||
| df = self.df_top_sorted_cit_per_year_cli | ||
| top_citations = list(df.Citations.values[:5]) | ||
| top_cit_per_year = list(df['cit/year'].values[:5]) | ||
| top_results = [top_citations, top_cit_per_year] | ||
| self.assertEqual(top_results, [[49230, 8603, 2853, 3166, 2416], | ||
| [2896, 782, 571, 352, 302]]) | ||
|
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||
| # Convert np.int64 values to Python int | ||
| top_citations = [int(c) for c in top_citations] | ||
| top_cit_per_year = [int(c) for c in top_cit_per_year] | ||
|
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||
| top_results = [top_citations, top_cit_per_year] | ||
| self.assertEqual(top_results, [ | ||
| [2853, 3166, 2416, 598, 948], | ||
| [571, 352, 302, 85, 79] | ||
| ]) | ||
|
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||
| if __name__=='__main__': | ||
| unittest.main() |