diff --git a/input/test/__init__.py b/input/test/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..897ddc50ea7451bdc6c43afc4411348c40654099
--- /dev/null
+++ b/input/test/__init__.py
@@ -0,0 +1,2 @@
+from input.test.test_input import *
+from input.publication import Publication
\ No newline at end of file
diff --git a/input/test/test_acs.py b/input/test/test_acs.py
new file mode 100755
index 0000000000000000000000000000000000000000..b1871403e991caf4ebc518bb5f9c4d5a030e80cf
--- /dev/null
+++ b/input/test/test_acs.py
@@ -0,0 +1,300 @@
+#!/usr/bin/env python
+
+from input.get.acs import Fetcher as Acs
+from input.publication import Publication, Citation
+from input.test.test_input import FetcherTestCase
+
+
+class AcsTestCase(FetcherTestCase):
+ """
+ Methods with test_* will be detected by unittest and run.
+ """
+
+ def test_url(self):
+ # Positive Testing
+ self.can_use_url_test(Acs, "https://doi.org/10.1021/acs.jcim.1c00203", True)
+ self.can_use_url_test(Acs, "doi.org/10.1021/acs.jcim.1c00203", True)
+ self.can_use_url_test(Acs, "10.1021/acs.jcim.1c00203", True)
+ self.can_use_url_test(Acs, " 10.1021/acs.jcim.1c00203", True)
+ self.can_use_url_test(Acs, "10.1021/acs.jcim.1c00203 ", True)
+ self.can_use_url_test(Acs, "\t 10.1021/acs.jcim.1c00203 \t\n", True)
+ self.can_use_url_test(Acs, "https://pubs.acs.org/doi/10.1021/acs.jcim.1c00203", True)
+
+ # Negative Testing
+ self.can_use_url_test(Acs, "", False)
+ self.can_use_url_test(Acs, "https://doi.org/10.1038/219021a0", False)
+ self.can_use_url_test(Acs, "https://www.nature.com/articles/219021a0", False)
+ self.can_use_url_test(Acs, "https://pubs.acs.org/doi/doi.org/10.1021/acs.jcim.1c00203", False)
+
+
+
+ def test_publication(self):
+ url = "https://doi.org/10.1021/acs.jcim.1c00203"
+ self.get_publication_test(Acs, url, self.expectedPubs[url])
+
+
+ # Dictionary of Expected Results, with url
+ expectedPubs = {
+ "https://doi.org/10.1021/acs.jcim.1c00203":
+ Publication(
+ doi_url = "https://doi.org/10.1021/acs.jcim.1c00203",
+ title = "AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings",
+ contributors = ["Jerome Eberhardt","Diogo Santos-Martins", "Andreas F. Tillack", "Stefano Forli"],
+ journal="J. Chem. Inf. Model.",
+ publication_date = "July 19, 2021",
+ subjects = ["Algorithms","Ligands","Molecules","Receptors","Macrocycles"],
+ references = [
+ Citation(doi_url = "https://doi.org/10.1002/jcc.21334"
+ , title ="AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading"
+ , journal="J. Comput. Chem."
+ , contributors=["Trott, O.", "Olson, A. J."]
+ , cit_type="Reference")
+ , Citation(doi_url = "https://doi.org/10.1038/nprot.2016.051"
+ , title ="Computational protein-ligand docking and virtual drug screening with the AutoDock suite"
+ , journal="Nat. Protoc."
+ , contributors=["Forli, S.","Huey, R.","Pique, M. E.","Sanner, M. F.","Goodsell, D. S.","Olson, A. J."]
+ , cit_type="Reference")
+ , Citation(title = "A semiempirical free energy force field with charge-based desolvation"
+ , doi_url = "https://doi.org/10.1002/jcc.20634"
+ , journal="J. Comput. Chem."
+ , contributors=["Huey, R.","Morris, G. M.","Olson, A. J.","Goodsell, D. S."]
+ , cit_type="Reference")
+ , Citation(title="Accelerating autodock4 with gpus and gradient-based local search"
+ , doi_url="https://doi.org/10.1021/acs.jctc.0c01006"
+ , journal="J. Chem. Theory Comput."
+ , contributors=["Santos-Martins, D.","Solis-Vasquez, L.","Tillack, A. F.","Sanner, M. F.","Koch, A.","Forli, S."]
+ , cit_type="Reference")
+ , Citation(title="AutoDockFR: Advances in Protein-Ligand Docking with Explicitly Specified Binding Site Flexibility"
+ , doi_url="https://doi.org/10.1371/journal.pcbi.1004586"
+ , journal="PLoS Comput. Biol."
+ , contributors=["Ravindranath, P. A.","Forli, S.","Goodsell, D. S.","Olson, A. J.","Sanner, M. F."]
+ , cit_type="Reference")
+ , Citation(title="Docking flexible cyclic peptides with AutoDock CrankPep"
+ , doi_url="https://doi.org/10.1021/acs.jctc.9b00557"
+ , journal="J. Chem. Theory Comput."
+ , contributors=["Zhang, Y.","Sanner, M. F."]
+ , cit_type="Reference")
+ , Citation(title="Fast, accurate, and reliable molecular docking with QuickVina 2"
+ , doi_url="https://doi.org/10.1093/bioinformatics/btv082"
+ , journal="Bioinformatics"
+ , contributors=["Alhossary, A.","Handoko, S. D.","Mu, Y.","Kwoh, C.-K."]
+ , cit_type="Reference")
+ , Citation(title="Lessons learned in empirical scoring with smina from the CSAR 2011 benchmarking exercise"
+ , doi_url="https://doi.org/10.1021/ci300604z"
+ , journal="J. Chem. Inf. Model."
+ , contributors=["Koes, D. R.","Baumgartner, M. P.","Camacho, C. J."]
+ , cit_type="Reference")
+ , Citation(title="Vina-Carb: Improving Glycosidic Angles during Carbohydrate Docking"
+ , doi_url="https://doi.org/10.1021/acs.jctc.5b00834"
+ , journal="J. Chem. Theory Comput."
+ , contributors=["Nivedha, A. K.","Thieker, D. F.","Makeneni, S.","Hu, H.","Woods, R. J."]
+ , cit_type="Reference")
+ , Citation(title="AutoDock VinaXB: implementation of XBSF, new empirical halogen bond scoring function, into AutoDock Vina"
+ , doi_url="https://doi.org/10.1186/s13321-016-0139-1"
+ , journal="J. Cheminf."
+ , contributors=["Koebel, M. R.","Schmadeke, G.","Posner, R. G.","Sirimulla, S."]
+ , cit_type="Reference")
+ , Citation(title="Vinardo: A Scoring Function Based on Autodock Vina Improves Scoring, Docking, and Virtual Screening"
+ , doi_url="https://doi.org/10.1371/journal.pone.0155183"
+ , journal="PLoS One"
+ , contributors=["Quiroga, R.","Villarreal, M. A."]
+ , cit_type="Reference")
+ , Citation(title="Lennard-Jones potential and dummy atom settings to overcome the AUTODOCK limitation in treating flexible ring systems"
+ , doi_url="https://doi.org/10.1021/ci700036j"
+ , journal="J. Chem. Inf. Model."
+ , contributors=["Forli, S.","Botta, M."]
+ , cit_type="Reference")
+ , Citation(title="AutoDock4Zn: an improved AutoDock force field for small-molecule docking to zinc metalloproteins"
+ , doi_url="https://doi.org/10.1021/ci500209e"
+ , journal="J. Chem. Inf. Model."
+ , contributors=["Santos-Martins, D.","Forli, S.","Ramos, M. J.","Olson, A. J."]
+ , cit_type="Reference")
+ , Citation(title="A force field with discrete displaceable waters and desolvation entropy for hydrated ligand docking"
+ , doi_url="https://doi.org/10.1021/jm2005145"
+ , journal="J. Med. Chem."
+ , contributors=["Forli, S.","Olson, A. J."]
+ , cit_type="Reference")
+ , Citation(title="Directional phosphorylation and nuclear transport of the splicing factor SRSF1 is regulated by an RNA recognition motif"
+ , doi_url="https://doi.org/10.1016/j.jmb.2016.04.009"
+ , journal="J. Mol. Biol."
+ , contributors=["Serrano, P.","Aubol, B. E.","Keshwani, M. M.","Forli, S.","Ma, C.-T.","Dutta, S. K.","Geralt, M.","Wüthrich, K.","Adams, J. A."]
+ , cit_type="Reference")
+ , Citation(title="Covalent docking using autodock: Two-point attractor and flexible side chain methods"
+ , doi_url="https://doi.org/10.1002/pro.2733"
+ , journal="Protein Sci."
+ , contributors=["Bianco, G.","Forli, S.","Goodsell, D. S.","Olson, A. J."]
+ , cit_type="Reference")
+ , Citation(title="Consensus docking: improving the reliability of docking in a virtual screening context"
+ , doi_url="https://doi.org/10.1021/ci300399w"
+ , journal="J. Chem. Inf. Model."
+ , contributors=["Houston, D. R.","Walkinshaw, M. D."]
+ , cit_type="Reference")
+ , Citation(title="DockBench: an integrated informatic platform bridging the gap between the robust validation of docking protocols and virtual screening simulations"
+ , doi_url="https://doi.org/10.3390/molecules20069977"
+ , journal="Molecules"
+ , contributors=["Cuzzolin, A.","Sturlese, M.","Malvacio, I.","Ciancetta, A.","Moro, S."]
+ , cit_type="Reference")
+ , Citation(title="A new force field for molecular mechanical simulation of nucleic acids and proteins"
+ , doi_url="https://doi.org/10.1021/ja00315a051"
+ , journal="J. Am. Chem. Soc."
+ , contributors=["Weiner, S. J.","Kollman, P. A.","Case, D. A.","Singh, U. C.","Ghio, C.","Alagona, G.","Profeta, S.","Weiner, P."]
+ , cit_type="Reference")
+ , Citation(title="AutoDock Bias: improving binding mode prediction and virtual screening using known protein-ligand interactions"
+ , doi_url="https://doi.org/10.1093/bioinformatics/btz152"
+ , journal="Bioinformatics"
+ , contributors=["Arcon, J. P.","Modenutti, C. P.","Avendaño, D.","Lopez, E. D.","Defelipe, L. A.","Ambrosio, F. A.","Turjanski, A. G.","Forli, S.","Marti, M. A."]
+ , cit_type="Reference")
+ , Citation(title="Inhomogeneous Fluid Approach to Solvation Thermodynamics. 1. Theory"
+ , doi_url="https://doi.org/10.1021/jp9723574"
+ , journal="J. Phys. Chem. B"
+ , contributors=["Lazaridis, T."]
+ , cit_type="Reference")
+ , Citation(title="Inhomogeneous fluid approach to solvation thermodynamics. 2. Applications to simple fluids"
+ , doi_url="https://doi.org/10.1021/jp972358w"
+ , journal="J. Phys. Chem. B"
+ , contributors=["Lazaridis, T."]
+ , cit_type="Reference")
+ , Citation(title="Grid inhomogeneous solvation theory: Hydration structure and thermodynamics of the miniature receptor cucurbit[7]uril"
+ , doi_url="https://doi.org/10.1063/1.4733951"
+ , journal="J. Chem. Phys."
+ , contributors=["Nguyen, C. N.","Young, T. K.","Gilson, M. K."]
+ , cit_type="Reference")
+ , Citation(title="AutoDock-GIST: Incorporating Thermodynamics of Active-Site Water into Scoring Function for Accurate Protein-Ligand Docking"
+ , doi_url="https://doi.org/10.3390/molecules21111604"
+ , journal="Molecules"
+ , contributors=["Uehara, S.","Tanaka, S."]
+ , cit_type="Reference")
+ , Citation(title="ZINC20—A Free Ultralarge-Scale Chemical Database for Ligand Discovery"
+ , doi_url="https://doi.org/10.1021/acs.jcim.0c00675"
+ , journal="J. Chem. Inf. Model."
+ , contributors=["Irwin, J. J.","Tang, K. G.","Young, J.","Dandarchuluun, C.","Wong, B. R.","Khurelbaatar, M.","Moroz, Y. S.","Mayfield, J.","Sayle, R. A."]
+ , cit_type="Reference")
+ , Citation(title="Structural biology-inspired discovery of novel KRAS–PDEδ inhibitors"
+ , doi_url="https://doi.org/10.1021/acs.jmedchem.7b01243"
+ , journal="J. Med. Chem."
+ , contributors=["Jiang, Y.","Zhuang, C.","Chen, L.","Lu, J.","Dong, G.","Miao, Z.","Zhang, W.","Li, J.","Sheng, C."]
+ , cit_type="Reference")
+ , Citation(title="D3R grand challenge 2015: evaluation of protein–ligand pose and affinity predictions"
+ , doi_url="https://doi.org/10.1007/s10822-016-9946-8"
+ , journal="J. Comput.-Aided Mol. Des."
+ , contributors=["Gathiaka, S.","Liu, S.","Chiu, M.","Yang, H.","Stuckey, J. A.","Kang, Y. N.","Delproposto, J.","Kubish, G.","Dunbar, J. B.","Carlson, H. A.","Burley, S. K.","Walters, W. P.","Amaro, R. E.","Feher, V. A.","Gilson, M. K."]
+ , cit_type="Reference")
+ , Citation(title="D3R grand challenge 4: blind prediction of protein–ligand poses, affinity rankings, and relative binding free energies"
+ , doi_url="https://doi.org/10.1007/s10822-020-00289-y"
+ , journal="J. Comput.-Aided Mol. Des."
+ , contributors=["Parks, C. D.","Gaieb, Z.","Chiu, M.","Yang, H.","Shao, C.","Walters, W. P.","Jansen, J. M.","McGaughey, G.","Lewis, R. A.","Bembenek, S. D.","Ameriks, M. K.","Mirzadegan, T.","Burley, S. K.","Amaro, R. E.","Gilson, M. K."]
+ , cit_type="Reference")
+ , Citation(title="D3R Grand Challenge 4: prospective pose prediction of BACE1 ligands with AutoDock-GPU"
+ , doi_url="https://doi.org/10.1007/s10822-019-00241-9"
+ , journal="J. Comput.-Aided Mol. Des."
+ , contributors=["Santos-Martins, D.","Eberhardt, J.","Bianco, G.","Solis-Vasquez, L.","Ambrosio, F. A.","Koch, A.","Forli, S."]
+ , cit_type="Reference")
+ , Citation(title="Comparison of affinity ranking using AutoDock-GPU and MM-GBSA scores for BACE-1 inhibitors in the D3R Grand Challenge 4"
+ , doi_url="https://doi.org/10.1007/s10822-019-00240-w"
+ , journal="J. Comput.-Aided Mol. Des."
+ , contributors=["El Khoury, L.","Santos-Martins, D.","Sasmal, S.","Eberhardt, J.","Bianco, G.","Ambrosio, F. A.","Solis-Vasquez, L.","Koch, A.","Forli, S.","Mobley, D. L."]
+ , cit_type="Reference")
+ , Citation(title="Macrocycle modeling in ICM: benchmarking and evaluation in D3R Grand Challenge 4"
+ , doi_url="https://doi.org/10.1007/s10822-019-00225-9"
+ , journal="J. Comput.-Aided Mol. Des."
+ , contributors=["Lam, P. C.-H.","Abagyan, R.","Totrov, M."]
+ , cit_type="Reference")
+ , Citation(title="Directory of useful decoys, enhanced (DUD-E): better ligands and decoys for better benchmarking"
+ , doi_url="https://doi.org/10.1021/jm300687e"
+ , journal="J. Med. Chem."
+ , contributors=["Mysinger, M. M.","Carchia, M.","Irwin, J. J.","Shoichet, B. K."]
+ , cit_type="Reference")
+ , Citation(title="Evaluation of AutoDock and AutoDock Vina on the CASF-2013 benchmark"
+ , doi_url="https://doi.org/10.1021/acs.jcim.8b00312"
+ , journal="J. Chem. Inf. Model."
+ , contributors=["Gaillard, T."]
+ , cit_type="Reference")
+ , Citation(title="Autodock vina adopts more accurate binding poses but autodock4 forms better binding affinity"
+ , doi_url="https://doi.org/10.1021/acs.jcim.9b00778"
+ , journal="J. Chem. Inf. Model."
+ , contributors=["Nguyen, N. T.","Nguyen, T. H.","Pham, T. N. H.","Huy, N. T.","Bay, M. V.","Pham, M. Q.","Nam, P. C.","Vu, V. V.","Ngo, S. T."]
+ , cit_type="Reference")
+ , Citation(title="Development and validation of a genetic algorithm for flexible docking"
+ , doi_url="https://doi.org/10.1006/jmbi.1996.0897"
+ , journal="J. Mol. Biol."
+ , contributors=["Jones, G.","Willett, P.","Glen, R. C.","Leach, A. R.","Taylor, R."]
+ , cit_type="Reference")
+ , Citation(title="Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy"
+ , doi_url="https://doi.org/10.1021/jm0306430"
+ , journal="J. Med. Chem."
+ , contributors=["Friesner, R. A.","Banks, J. L.","Murphy, R. B.","Halgren, T. A.","Klicic, J. J.","Mainz, D. T.","Repasky, M. P.","Knoll, E. H.","Shelley, M.","Perry, J. K."]
+ , cit_type="Reference")
+ , Citation(title="Surflex: fully automatic flexible molecular docking using a molecular similarity-based search engine"
+ , doi_url="https://doi.org/10.1021/jm020406h"
+ , journal="J. Med. Chem."
+ , contributors=["Jain, A. N."]
+ , cit_type="Reference")
+ , Citation(title="A fast flexible docking method using an incremental construction algorithm"
+ , doi_url="https://doi.org/10.1006/jmbi.1996.0477"
+ , journal="J. Mol. Biol."
+ , contributors=["Rarey, M.","Kramer, B.","Lengauer, T.","Klebe, G."]
+ , cit_type="Reference")
+ , Citation(title="EDock: blind protein–ligand docking by replica-exchange monte carlo simulation"
+ , doi_url="https://doi.org/10.1186/s13321-020-00440-9"
+ , journal="J. Cheminf."
+ , contributors=["Zhang, W.","Bell, E. W.","Yin, M.","Zhang, Y."]
+ , cit_type="Reference")
+ , Citation(title="DOCK 6: Impact of new features and current docking performance"
+ , doi_url="https://doi.org/10.1002/jcc.23905"
+ , journal="J. Comput. Chem."
+ , contributors=["Allen, W. J.","Balius, T. E.","Mukherjee, S.","Brozell, S. R.","Moustakas, D. T.","Lang, P. T.","Case, D. A.","Kuntz, I. D.","Rizzo, R. C."]
+ , cit_type="Reference")
+ , Citation(title="Improving scoring-docking-screening powers of protein–ligand scoring functions using random forest"
+ , doi_url="https://doi.org/10.1002/jcc.24667"
+ , journal="J. Comput. Chem."
+ , contributors=["Wang, C.","Zhang, Y."]
+ , cit_type="Reference")
+ , Citation(title="ID-Score: a new empirical scoring function based on a comprehensive set of descriptors related to protein–ligand interactions"
+ , doi_url="https://doi.org/10.1021/ci300493w"
+ , journal="J. Chem. Inf. Model."
+ , contributors=["Li, G.-B.","Yang, L.-L.","Wang, W.-J.","Li, L.-L.","Yang, S.-Y."]
+ , cit_type="Reference")
+ , Citation(title="Further development and validation of empirical scoring functions for structure-based binding affinity prediction"
+ , doi_url="https://doi.org/10.1023/a:1016357811882"
+ , journal="J. Comput.-Aided Mol. Des."
+ , contributors=["Wang, R.","Lai, L.","Wang, S."]
+ , cit_type="Reference")
+ , Citation(title="A knowledge-based energy function for protein- ligand, protein- protein, and protein- DNA complexes"
+ , doi_url="https://doi.org/10.1021/jm049314d"
+ , journal="J. Med. Chem."
+ , contributors=["Zhang, C.","Liu, S.","Zhu, Q.","Zhou, Y."]
+ , cit_type="Reference")
+ , Citation(title="DLIGAND2: an improved knowledge-based energy function for protein–ligand interactions using the distance-scaled, finite, ideal-gas reference state"
+ , doi_url="https://doi.org/10.1186/s13321-019-0373-4"
+ , journal="J. Cheminf."
+ , contributors=["Chen, P.","Ke, Y.","Lu, Y.","Du, Y.","Li, J.","Yan, H.","Zhao, H.","Zhou, Y.","Yang, Y."]
+ , cit_type="Reference")
+ , Citation(title="Comparing AutoDock and Vina in ligand/decoy discrimination for virtual screening"
+ , doi_url="https://doi.org/10.3390/app9214538"
+ , journal="Appl. Sci."
+ , contributors=["Vieira, T. F.","Sousa, S. F."]
+ , cit_type="Reference")
+ , Citation(title="Benchmark of four popular virtual screening programs: construction of the active/decoy dataset remains a major determinant of measured performance"
+ , doi_url="https://doi.org/10.1186/s13321-016-0167-x"
+ , journal="J. Cheminf."
+ , contributors=["Chaput, L.","Martinez-Sanz, J.","Quiniou, E.","Rigolet, P.","Saettel, N.","Mouawad, L."]
+ , cit_type="Reference")
+ , Citation(title="Array programming with NumPy"
+ , doi_url="https://doi.org/10.1038/s41586-020-2649-2"
+ , journal="Nature"
+ , contributors=["Harris, C. R."]
+ , cit_type="Reference")
+ , Citation(title="Matplotlib: A 2D graphics environment"
+ , doi_url="https://doi.org/10.1109/mcse.2007.55"
+ , journal="Comput. Sci. Eng."
+ , contributors=["Hunter, J. D."]
+ , cit_type="Reference")
+ ], citations = [
+ Citation(doi_url = "https://doi.org/10.1021/acsomega.1c04320"
+ , title ="Novel Anti-Hepatitis B Virus Activity of Euphorbia schimperi and Its Quercetin and Kaempferol Derivatives"
+ , journal="ACS Omega"
+ , contributors=["Mohammad K. Parvez","Sarfaraz Ahmed","Mohammed S. Al-Dosari","Mazin A. S. Abdelwahid","Ahmed H. Arbab","Adnan J. Al-Rehaily","Mai M. Al-Oqail"],cit_type="Citation"),
+
+ ]
+ )
+ }
\ No newline at end of file
diff --git a/input/test/test_input.py b/input/test/test_input.py
new file mode 100755
index 0000000000000000000000000000000000000000..86fe6aea1521090e916e81266bfc97cda75b82b7
--- /dev/null
+++ b/input/test/test_input.py
@@ -0,0 +1,72 @@
+import unittest
+from input.get.journal_fetcher import JournalFetcher
+
+from input.publication import Publication
+
+"""
+Testing the Publication fetcher
+
+Publication 1: 'https://doi.org/10.1021/acs.jcim.1c00203'
+Publication 2: 'doi.org/10.1021/acs.jcim.1c00917'
+Publication 3: '10.1038/nchem.1781'
+Publication 4: '11.12/jaj'
+Publication 5: '11.12/'
+Publication 6: 'https://doi.org/10.1021/acs.jmedchem.0c01332' # Paper is a PDF
+"""
+# TODO: Testcases for:
+# - Specific Journals: Inherit from FetcherTestCase
+# - interface module-importer (test case)
+# - Error detection
+# - wrong/no Journal_fetchers
+# - wrong urls
+# - correct Types in publication
+# - Edgecases (i.e. paper as pdf, no connection, etc)
+
+
+class InterfaceTestCase(unittest.TestCase):
+ pass
+
+class FetcherTestCase(unittest.TestCase):
+
+
+ def can_use_url_test(self, fetcher : JournalFetcher, test_url: str, expected_res: bool):
+ # Tests the 'can_use_url'-method
+ self.assertEqual(fetcher.can_use_url(test_url), expected_res)
+
+
+ def get_publication_test(self, fetcher : JournalFetcher, test_url: str, expected_res: Publication):
+ """
+ this test asserts that every variable is equals to the expected result
+ """
+ actual_res = fetcher.get_publication(test_url)
+ self.assertEqual(actual_res.doi_url, expected_res.doi_url)
+ self.assertEqual(actual_res.title, expected_res.title)
+ self.assertEqual(actual_res.contributors, expected_res.contributors)
+ self.assertEqual(actual_res.journal, expected_res.journal)
+ self.assertEqual(actual_res.publication_date, expected_res.publication_date)
+ self.assertEqual(actual_res.subjects, expected_res.subjects)
+ # self.assertEqual(actual_res.num_citations, expected_res.num_citations)
+
+ # Checking for all references
+ self.assertEquals(len(actual_res.references), len(expected_res.references))
+ num_references = len(expected_res.references)
+ for i in range(num_references):
+ self.assertEqual(actual_res.references[i].doi_url, expected_res.references[i].doi_url)
+ self.assertEqual(actual_res.references[i].journal, expected_res.references[i].journal)
+ self.assertEqual(actual_res.references[i].contributors, expected_res.references[i].contributors)
+ self.assertEqual(actual_res.references[i].cit_type, expected_res.references[i].cit_type)
+
+ # Checking for all citations
+ self.assertEquals(len(actual_res.citations), len(expected_res.citations))
+ num_citations = len(expected_res.citations)
+ for i in range(num_citations):
+ self.assertEqual(actual_res.citations[i].doi_url, expected_res.citations[i].doi_url)
+ self.assertEqual(actual_res.citations[i].journal, expected_res.citations[i].journal)
+ self.assertEqual(actual_res.citations[i].contributors, expected_res.citations[i].contributors)
+ self.assertEqual(actual_res.citations[i].cit_type, expected_res.citations[i].cit_type)
+
+
+
+if __name__=="__main__":
+ print("test")
+ unittest.main()
\ No newline at end of file