Jakob Runge - RankMe

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Structural Causal Bottleneck Models. CoRR Simon Bing, Jonas Wahl, Jakob Runge
2025	J	`jnl`	Context-Specific Causal Graph Discovery with Unobserved Contexts: Non-Stationarity, Regimes and Spatio-Temporal Patterns. CoRR Martin Rabel, Jakob Runge
2025	J	`jnl`	Internal Incoherency Scores for Constraint-based Causal Discovery Algorithms. CoRR Sofia Faltenbacher, Jonas Wahl, Rebecca Herman, Jakob Runge
2025	J	`jnl`	Multidata Causal Discovery for Statistical Hurricane Intensity Forecasting. CoRR Saranya Ganesh S., Frederick Iat-Hin Tam, Milton S. Gomez, Marie McGraw, Mark DeMaria, Kate D. Musgrave, Jakob Runge, Tom Beucler
2025	—	`conf`	Non-parametric Conditional Independence Testing for Mixed Continuous-Categorical Variables: A Novel Method and Numerical Evaluation. CLeaR Oana-Iuliana Popescu, Andreas Gerhardus, Martin Rabel, Jakob Runge
2025	A*	`conf`	Sanity Checking Causal Representation Learning on a Simple Real-World System. ICML Juan L. Gamella, Simon Bing, Jakob Runge
2025	J	`jnl`	Sanity Checking Causal Representation Learning on a Simple Real-World System. CoRR Juan L. Gamella, Simon Bing, Jakob Runge
2025	A	`conf`	Separation-Based Distance Measures for Causal Graphs. AISTATS Jonas Wahl, Jakob Runge
2025	—	`conf`	Unitless Unrestricted Markov-Consistent SCM Generation: Better Benchmark Datasets for Causal Discovery. CLeaR Rebecca Herman, Jonas Wahl, Urmi Ninad, Jakob Runge
2025	J	`jnl`	Unitless Unrestricted Markov-Consistent SCM Generation: Better Benchmark Datasets for Causal Discovery. CoRR Rebecca Herman, Jonas Wahl, Urmi Ninad, Jakob Runge
2025	J	`jnl`	Using Time Structure to Estimate Causal Effects. CoRR Tom Hochsprung, Jakob Runge, Andreas Gerhardus
2024	A	`conf`	A Global Markov Property for Solutions of Stochastic Difference Equations and the corresponding Full Time Graphs. UAI Tom Hochsprung, Jakob Runge, Andreas Gerhardus
2024	—	`conf`	Bootstrap aggregation and confidence measures to improve time series causal discovery. CLeaR Kevin Debeire, Andreas Gerhardus, Jakob Runge, Veronika Eyring
2024	J	`jnl`	Causal Modeling in Multi-Context Systems: Distinguishing Multiple Context-Specific Causal Graphs which Account for Observational Support. CoRR Martin Rabel, Wiebke Günther, Jakob Runge, Andreas Gerhardus
2024	J	`jnl`	Causal Representation Learning in Temporal Data via Single-Parent Decoding. CoRR Philippe Brouillard, Sébastien Lachapelle, Julia Kaltenborn, Yaniv Gurwicz, Dhanya Sridhar, Alexandre Drouin, Peer Nowack, Jakob Runge, David Rolnick
2024	A*	`conf`	Causal discovery with endogenous context variables. NeurIPS Wiebke Günther, Oana-Iuliana Popescu, Martin Rabel, Urmi Ninad, Andreas Gerhardus, Jakob Runge
2024	J	`jnl`	Causal discovery with endogenous context variables. CoRR Wiebke Günther, Oana-Iuliana Popescu, Martin Rabel, Urmi Ninad, Andreas Gerhardus, Jakob Runge
2024	—	`conf`	Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions. CLeaR Simon Bing, Urmi Ninad, Jonas Wahl, Jakob Runge
2024	J	`jnl`	Invariance & Causal Representation Learning: Prospects and Limitations. Trans. Mach. Learn. Res. Simon Bing, Tom Hochsprung, Jonas Wahl, Urmi Ninad, Jakob Runge
2023	J	`jnl`	A Causal Discovery Approach To Learn How Urban Form Shapes Sustainable Mobility Across Continents. CoRR Felix Wagner, Florian Nachtigall, Lukas Franken, Nikola Milojevic-Dupont, Rafael H. M. Pereira, Nicolas Koch, Jakob Runge, Marta Gonzalez, Felix Creutzig
2023	A	`conf`	Causal Discovery for time series from multiple datasets with latent contexts. UAI Wiebke Günther, Urmi Ninad, Jakob Runge
2023	A*	`conf`	ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning. NeurIPS Julia Kaltenborn, Charlotte E. E. Lange, Venkatesh Ramesh, Philippe Brouillard, Yaniv Gurwicz, Chandni Nagda, Jakob Runge, Peer Nowack, David Rolnick
2023	J	`jnl`	ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning. CoRR Julia Kaltenborn, Charlotte E. E. Lange, Venkatesh Ramesh, Philippe Brouillard, Yaniv Gurwicz, Chandni Nagda, Jakob Runge, Peer Nowack, David Rolnick
2023	J	`jnl`	Discovering Causal Relations and Equations from Data. CoRR Gustau Camps-Valls, Andreas Gerhardus, Urmi Ninad, Gherardo Varando, Georg Martius, Emili Balaguer-Ballester, Ricardo Vinuesa, Emiliano Diaz, Laure Zanna, Jakob Runge
2023	J	`jnl`	Distinguishing Cause and Effect in Bivariate Structural Causal Models: A Systematic Investigation. J. Mach. Learn. Res. Christoph Käding, Jakob Runge
2023	J	`jnl`	Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions. CoRR Simon Bing, Urmi Ninad, Jonas Wahl, Jakob Runge
2023	A	`conf`	Increasing effect sizes of pairwise conditional independence tests between random vectors. UAI Tom Hochsprung, Jonas Wahl, Andreas Gerhardus, Urmi Ninad, Jakob Runge
2023	J	`jnl`	Invariance & Causal Representation Learning: Prospects and Limitations. CoRR Simon Bing, Jonas Wahl, Urmi Ninad, Jakob Runge
2023	J	`jnl`	Non-parametric Conditional Independence Testing for Mixed Continuous-Categorical Variables: A Novel Method and Numerical Evaluation. CoRR Oana-Iuliana Popescu, Andreas Gerhardus, Jakob Runge
2023	J	`jnl`	Projecting infinite time series graphs to finite marginal graphs using number theory. CoRR Andreas Gerhardus, Jonas Wahl, Sofia Faltenbacher, Urmi Ninad, Jakob Runge
2023	J	`jnl`	Selecting Robust Features for Machine Learning Applications using Multidata Causal Discovery. CoRR Saranya Ganesh S., Tom Beucler, Frederick Iat-Hin Tam, Milton S. Gomez, Jakob Runge, Andreas Gerhardus
2023	A*	`conf`	Vector Causal Inference between Two Groups of Variables. AAAI Jonas Wahl, Urmi Ninad, Jakob Runge
2022	A*	`conf`	Conditional Independence Testing with Heteroskedastic Data and Applications to Causal Discovery. NeurIPS Wiebke Günther, Urmi Ninad, Jonas Wahl, Jakob Runge
2021	J	`jnl`	A Data-Driven Approach to Partitioning Net Ecosystem Exchange Using a Deep State Space Model. IEEE Access Violeta Teodora Trifunov, Maha Shadaydeh, Jakob Runge, Markus Reichstein, Joachim Denzler
2021	—	`conf`	Conditional Adversarial Debiasing: Towards Learning Unbiased Classifiers from Biased Data. GCPR Christian Reimers, Paul Bodesheim, Jakob Runge, Joachim Denzler
2021	—	`conf`	Conditional Dependence Tests Reveal the Usage of ABCD Rule Features and Bias Variables in Automatic Skin Lesion Classification. CVPR Workshops Christian Reimers, Niklas Penzel, Paul Bodesheim, Jakob Runge, Joachim Denzler
2021	—	`conf`	EarthNet2021: A Large-Scale Dataset and Challenge for Earth Surface Forecasting as a Guided Video Prediction Task. CVPR Workshops Christian Requena-Mesa, Vitus Benson, Markus Reichstein, Jakob Runge, Joachim Denzler
2021	J	`jnl`	EarthNet2021: A large-scale dataset and challenge for Earth surface forecasting as a guided video prediction task. CoRR Christian Requena-Mesa, Vitus Benson, Markus Reichstein, Jakob Runge, Joachim Denzler
2021	J	`jnl`	Necessary and sufficient conditions for optimal adjustment sets in causal graphical models with hidden variables. CoRR Jakob Runge
2021	A*	`conf`	Necessary and sufficient graphical conditions for optimal adjustment sets in causal graphical models with hidden variables. NeurIPS Jakob Runge
2021	J	`jnl`	Towards Learning an Unbiased Classifier from Biased Data via Conditional Adversarial Debiasing. CoRR Christian Reimers, Paul Bodesheim, Jakob Runge, Joachim Denzler
2020	J	`jnl`	A Perspective on Gaussian Processes for Earth Observation. CoRR Gustau Camps-Valls, Dino Sejdinovic, Jakob Runge, Markus Reichstein
2020	—	`conf`	Determining the Relevance of Features for Deep Neural Networks. ECCV (26) Christian Reimers, Jakob Runge, Joachim Denzler
2020	A	`conf`	Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets. UAI Jakob Runge
2020	J	`jnl`	Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets. CoRR Jakob Runge
2020	J	`jnl`	EarthNet2021: A novel large-scale dataset and challenge for forecasting localized climate impacts. CoRR Christian Requena-Mesa, Vitus Benson, Joachim Denzler, Jakob Runge, Markus Reichstein
2020	A*	`conf`	High-recall causal discovery for autocorrelated time series with latent confounders. NeurIPS Andreas Gerhardus, Jakob Runge
2020	J	`jnl`	High-recall causal discovery for autocorrelated time series with latent confounders. CoRR Andreas Gerhardus, Jakob Runge
2019	—	`conf`	Nonlinear Causal Link Estimation Under Hidden Confounding with an Application to Time Series Anomaly Detection. GCPR Violeta Teodora Trifunov, Maha Shadaydeh, Jakob Runge, Veronika Eyring, Markus Reichstein, Joachim Denzler
2019	—	`conf`	The Causality for Climate Competition. NeurIPS (Competition and Demos) Jakob Runge, Xavier-Andoni Tibau, Matthias Bruhns, Jordi Muñoz-Marí, Gustau Camps-Valls
2018	A	`conf`	Conditional independence testing based on a nearest-neighbor estimator of conditional mutual information. AISTATS Jakob Runge
2017	J	`jnl`	Conditional independence testing based on a nearest-neighbor estimator of conditional mutual information. CoRR Jakob Runge
2013	J	`jnl`	Reliability of Inference of Directed Climate Networks Using Conditional Mutual Information. Entropy Jaroslav Hlinka, David Hartman, Martin Vejmelka, Jakob Runge, Norbert Marwan, Jürgen Kurths, Milan Palus
2013	J	`jnl`	Statistical Mechanics and Information-Theoretic Perspectives on Complexity in the Earth System. Entropy Georgios Balasis, Reik V. Donner, Stelios M. Potirakis, Jakob Runge, Constantinos Papadimitriou, Ioannis A. Daglis, Konstantinos Eftaxias, Jürgen Kurths
2012	J	`jnl`	Quantifying Causal Coupling Strength: A Lag-specific Measure For Multivariate Time Series Related To Transfer Entropy CoRR Jakob Runge, Jobst Heitzig, Norbert Marwan, Jürgen Kurths

"""
Integration tests for the HashExtractor class.
"""
import pytest
import hashlib
from unittest.mock import Mock, patch, MagicMock

pytestmark = [pytest.mark.integration]


class TestHashExtractorInitialization:
    """Tests for HashExtractor initialization."""

    def test_initialization_elf(self, elf_binary_path, mock_logger):
        """Test initialization with ELF file."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)

            assert extractor.filepath == elf_binary_path
            assert extractor.hashes is None
            assert extractor.filetype == "elf"
            assert extractor.macho is None

    def test_initialization_with_macho_object(self, elf_binary_path, mock_logger):
        """Test initialization with pre-parsed macho object."""
        from redb.extractors.hashes import HashExtractor

        mock_macho = MagicMock()
        mock_macho.get_architectures.return_value = ["x86_64"]

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger, macho=mock_macho)

            assert extractor.macho is mock_macho

    def test_initialization_pe(self, pe_binary_path, mock_logger):
        """Test initialization with PE file."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(pe_binary_path, mock_logger)

            assert extractor.filepath == pe_binary_path
            assert extractor.filetype == "pebin"
            # PE object should be created
            assert extractor.pe is not None

    def test_elastic_index_suffix(self, elf_binary_path, mock_logger):
        """Test that elastic_index has correct suffix."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)

            assert "-hashes" in extractor.elastic_index


class TestHashExtractorTag:
    """Tests for tag method."""

    def test_tag_value(self, elf_binary_path, mock_logger):
        """Test that tag returns correct value."""
        from redb.extractors.hashes import HashExtractor
        from redb.extractors.enum import Tag

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)

            assert extractor.tag() == Tag.HASH.value
            assert extractor.tag() == "hash"


class TestHashExtractorBasicHashes:
    """Tests for basic hash extraction."""

    def test_extract_md5(self, elf_binary_path, mock_logger, known_hashes):
        """Test MD5 hash extraction."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)

            result = extractor.extract()

            assert result is not None
            assert result.md5 == known_hashes['md5']

    def test_extract_sha1(self, elf_binary_path, mock_logger, known_hashes):
        """Test SHA1 hash extraction."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)

            result = extractor.extract()

            assert result is not None
            assert result.sha1 == known_hashes['sha1']

    def test_extract_sha256(self, elf_binary_path, mock_logger, known_hashes):
        """Test SHA256 hash extraction."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)

            result = extractor.extract()

            assert result is not None
            assert result.sha256 == known_hashes['sha256']

    def test_extract_ssdeep(self, elf_binary_path, mock_logger):
        """Test ssdeep hash extraction."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)

            result = extractor.extract()

            assert result is not None
            # ssdeep should be a string
            assert isinstance(result.ssdeep_hash, str)

    def test_extract_tlsh(self, elf_binary_path, mock_logger):
        """Test TLSH hash extraction."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)

            result = extractor.extract()

            assert result is not None
            # TLSH should be a string
            assert isinstance(result.tlsh_hash, str)


class TestHashExtractorPEHashes:
    """Tests for PE-specific hash extraction."""

    def test_extract_imphash(self, pe_binary_path, mock_logger):
        """Test imphash extraction for PE file."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(pe_binary_path, mock_logger)

            result = extractor.extract()

            assert result is not None
            # Imphash should be set for PE files
            if extractor.pe is not None:
                assert result.imphash is not None or result.imphash is None  # May or may not have imports

    def test_extract_authentihash(self, pe_binary_path, mock_logger):
        """Test authentihash extraction for PE file."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(pe_binary_path, mock_logger)

            result = extractor.extract()

            assert result is not None
            # Authentihash should be set for PE files
            if extractor.pe is not None:
                assert result.authentihash is not None

    def test_pe_hashes_not_set_for_elf(self, elf_binary_path, mock_logger):
        """Test that PE-specific hashes are not set for ELF files."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)

            result = extractor.extract()

            assert result is not None
            # PE-specific hashes should be None for ELF
            assert result.imphash is None
            assert result.authentihash is None
            assert result.richhash is None


class TestHashExtractorRichHeaderHashes:
    """Tests for Rich header hash extraction."""

    def test_compute_richhash(self, pe_binary_path, mock_logger):
        """Test Rich header hash computation."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(pe_binary_path, mock_logger)

            result = extractor.extract()

            assert result is not None
            # Rich hash may or may not be present depending on the PE
            if result.richhash is not None:
                assert isinstance(result.richhash, str)
                assert len(result.richhash) == 32  # MD5 hex length

    def test_compute_richpe_hash(self, pe_binary_path, mock_logger):
        """Test RichPE hash computation."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(pe_binary_path, mock_logger)

            result = extractor.extract()

            assert result is not None
            # RichPE hash may or may not be present
            if result.richpe_hash is not None:
                assert isinstance(result.richpe_hash, str)
                assert len(result.richpe_hash) == 32  # MD5 hex length

    def test_compute_richpv_hash(self, pe_binary_path, mock_logger):
        """Test RichPV hash computation."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(pe_binary_path, mock_logger)

            result = extractor.extract()

            assert result is not None
            # RichPV hashes may or may not be present
            if result.richpv_hash is not None:
                assert isinstance(result.richpv_hash, str)
            if result.richpv_hash_sorted is not None:
                assert isinstance(result.richpv_hash_sorted, str)


class TestHashExtractorELFHashes:
    """Tests for ELF-specific hash extraction."""

    def test_extract_elf_import_hash(self, elf_binary_path, mock_logger):
        """Test ELF import hash extraction."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)

            result = extractor.extract()

            assert result is not None
            # Import hash may or may not be present
            if result.import_hash is not None:
                assert isinstance(result.import_hash, str)
                assert len(result.import_hash) == 32

    def test_extract_elf_export_hash(self, elf_binary_path, mock_logger):
        """Test ELF export hash extraction."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)

            result = extractor.extract()

            assert result is not None
            # Export hash may or may not be present
            if result.export_hash is not None:
                assert isinstance(result.export_hash, str)

    def test_extract_elf_section_hash(self, elf_binary_path, mock_logger):
        """Test ELF section hash extraction."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)

            result = extractor.extract()

            assert result is not None
            # Section hash should be present for valid ELF
            if result.section_hash is not None:
                assert isinstance(result.section_hash, str)

    def test_extract_elf_symbol_hash(self, elf_binary_path, mock_logger):
        """Test ELF symbol hash extraction."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)

            result = extractor.extract()

            assert result is not None
            # Symbol hash (symhash) may or may not be present
            if result.symbol_hash is not None:
                assert isinstance(result.symbol_hash, str)

    def test_extract_elf_dynamic_hash(self, elf_binary_path, mock_logger):
        """Test ELF dynamic hash extraction."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)

            result = extractor.extract()

            assert result is not None
            # Dynamic hash may or may not be present
            if result.dynamic_hash is not None:
                assert isinstance(result.dynamic_hash, str)


class TestHashExtractorPrepareExportData:
    """Tests for prepare_export_data method."""

    def test_prepare_export_elasticsearch(self, elf_binary_path, mock_logger):
        """Test prepare_export_data for Elasticsearch."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)
            extractor.extract()

            result = extractor.prepare_export_data("ElasticsearchExporter")

            assert result is extractor.hashes

    def test_prepare_export_clickhouse(self, elf_binary_path, mock_logger):
        """Test prepare_export_data for ClickHouse."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)
            extractor.extract()

            result = extractor.prepare_export_data("ClickHouseExporter")

            # Should return tuple of (data, column_names, column_type_names)
            assert isinstance(result, tuple)
            assert len(result) == 3

            data, column_names, column_type_names = result

            assert isinstance(data, list)
            assert isinstance(column_names, list)
            assert isinstance(column_type_names, list)

            # Check expected columns
            assert 'sha256' in column_names
            assert 'md5' in column_names
            assert 'sha1' in column_names
            assert 'ssdeep_hash' in column_names
            assert 'tlsh_hash' in column_names

    def test_prepare_export_clickhouse_pe(self, pe_binary_path, mock_logger):
        """Test prepare_export_data for ClickHouse with PE file."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(pe_binary_path, mock_logger)
            extractor.extract()

            result = extractor.prepare_export_data("ClickHouseExporter")

            data, column_names, column_type_names = result

            # PE-specific columns should be present
            assert 'authentihash' in column_names
            assert 'imphash' in column_names
            assert 'richhash' in column_names

    def test_prepare_export_clickhouse_has_macho_columns(self, elf_binary_path, mock_logger):
        """Test prepare_export_data for ClickHouse includes Mach-O hash columns."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)
            extractor.extract()

            result = extractor.prepare_export_data("ClickHouseExporter")

            data, column_names, column_type_names = result

            # Mach-O hash columns should be present
            assert 'macho_dylib_hash' in column_names
            assert 'macho_import_hash' in column_names
            assert 'macho_export_hash' in column_names
            assert 'macho_entitlement_hash' in column_names
            assert 'macho_symhash' in column_names


class TestHashExtractorClickHouseTable:
    """Tests for get_clickhouse_table method."""

    def test_clickhouse_table_name(self, elf_binary_path, mock_logger):
        """Test correct ClickHouse table name."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)

            assert extractor.get_clickhouse_table() == "redb_hashes"


@pytest.mark.unit
@pytest.mark.dataclass
class TestHashExtractorHashesDataclass:
    """Tests for Hashes dataclass structure."""

    def test_hashes_dataclass_structure(self, elf_binary_path, mock_logger):
        """Test that Hashes dataclass has expected structure."""
        from redb.extractors.hashes import HashExtractor
        from redb.models.dataclasses import Hashes

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)

            result = extractor.extract()

            assert isinstance(result, Hashes)
            # Required fields
            assert hasattr(result, 'md5')
            assert hasattr(result, 'sha1')
            assert hasattr(result, 'sha256')
            assert hasattr(result, 'ssdeep_hash')
            assert hasattr(result, 'tlsh_hash')
            # Optional fields
            assert hasattr(result, 'authentihash')
            assert hasattr(result, 'imphash')
            assert hasattr(result, 'richhash')

    def test_hashes_dataclass_has_macho_fields(self):
        """Test that Hashes dataclass has Mach-O hash fields."""
        from redb.models.dataclasses import Hashes

        # Create instance with default values
        hashes = Hashes(
            md5="d41d8cd98f00b204e9800998ecf8427e",
            sha1="da39a3ee5e6b4b0d3255bfef95601890afd80709",
            sha256="e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855",
            ssdeep_hash="",
            tlsh_hash=""
        )

        # Verify Mach-O hash fields exist and default to None
        assert hasattr(hashes, 'macho_dylib_hash')
        assert hasattr(hashes, 'macho_import_hash')
        assert hasattr(hashes, 'macho_export_hash')
        assert hasattr(hashes, 'macho_entitlement_hash')
        assert hasattr(hashes, 'macho_symhash')

        assert hashes.macho_dylib_hash is None
        assert hashes.macho_import_hash is None
        assert hashes.macho_export_hash is None
        assert hashes.macho_entitlement_hash is None
        assert hashes.macho_symhash is None

    def test_hashes_dataclass_with_macho_values(self):
        """Test that Hashes dataclass can be created with Mach-O hash values."""
        from redb.models.dataclasses import Hashes

        hashes = Hashes(
            md5="d41d8cd98f00b204e9800998ecf8427e",
            sha1="da39a3ee5e6b4b0d3255bfef95601890afd80709",
            sha256="e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855",
            ssdeep_hash="",
            tlsh_hash="",
            macho_dylib_hash="abc123def456789012345678901234567",
            macho_import_hash="def456abc123789012345678901234567",
            macho_export_hash="789012abc123def456345678901234567",
            macho_entitlement_hash="345678abc123def456789012901234567",
            macho_symhash="901234abc123def456789012345678567"
        )

        assert hashes.macho_dylib_hash == "abc123def456789012345678901234567"
        assert hashes.macho_import_hash == "def456abc123789012345678901234567"
        assert hashes.macho_export_hash == "789012abc123def456345678901234567"
        assert hashes.macho_entitlement_hash == "345678abc123def456789012901234567"
        assert hashes.macho_symhash == "901234abc123def456789012345678567"


class TestHashExtractorErrorHandling:
    """Tests for error handling in HashExtractor."""

    def test_extract_handles_hash_errors(self, elf_binary_path, mock_logger):
        """Test that extract handles hash computation errors gracefully."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)

            # Even if some hashes fail, we should get a result
            result = extractor.extract()

            assert result is not None

    def test_extract_with_invalid_pe(self, elf_binary_path, mock_logger):
        """Test extraction when PE parsing fails."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            # Force filetype to be 'pebin' but use ELF file
            with patch.object(HashExtractor, '__init__', lambda self, *args, **kwargs: None):
                extractor = HashExtractor.__new__(HashExtractor)
                extractor.filepath = elf_binary_path
                extractor.log = mock_logger
                extractor.hashes = None
                extractor.pe = None
                extractor.filetype = 'pebin'

                with open(elf_binary_path, 'rb') as f:
                    extractor.binary = f.read()

                # Should not crash
                result = extractor._extract_hashes()
                assert result is not None


class TestHashExtractorMachoHashes:
    """Tests for Mach-O specific hash extraction."""

    def test_macho_hashes_not_set_for_elf(self, elf_binary_path, mock_logger):
        """Test that Mach-O hashes are not set for ELF files."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)

            result = extractor.extract()

            assert result is not None
            assert result.macho_dylib_hash is None
            assert result.macho_import_hash is None
            assert result.macho_export_hash is None
            assert result.macho_entitlement_hash is None
            assert result.macho_symhash is None

    def test_macho_hashes_not_set_for_pe(self, pe_binary_path, mock_logger):
        """Test that Mach-O hashes are not set for PE files."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(pe_binary_path, mock_logger)

            result = extractor.extract()

            assert result is not None
            assert result.macho_dylib_hash is None
            assert result.macho_import_hash is None
            assert result.macho_export_hash is None
            assert result.macho_entitlement_hash is None
            assert result.macho_symhash is None

    def test_extract_macho_hashes_with_mock(self, elf_binary_path, mock_logger):
        """Test Mach-O hash extraction with mocked macho object."""
        from redb.extractors.hashes import HashExtractor

        # Create mock macho object
        mock_macho = MagicMock()
        mock_macho.get_architectures.return_value = ["x86_64"]
        mock_macho.get_similarity_hashes.return_value = {
            'dylib_hash': 'abc123def456789012345678901234ab',
            'import_hash': 'def456abc789012345678901234567cd',
            'export_hash': '789012abc456def345678901234567ef',
            'entitlement_hash': '345678abc123def789012901234567gh',
            'symhash': '901234abc123def456789012345678ij'
        }

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger, macho=mock_macho)
            # Override filetype to trigger macho hash extraction
            extractor.filetype = 'macho'

            result = extractor.extract()

            assert result is not None
            assert result.macho_dylib_hash == 'abc123def456789012345678901234ab'
            assert result.macho_import_hash == 'def456abc789012345678901234567cd'
            assert result.macho_export_hash == '789012abc456def345678901234567ef'
            assert result.macho_entitlement_hash == '345678abc123def789012901234567gh'
            assert result.macho_symhash == '901234abc123def456789012345678ij'

    def test_extract_macho_hashes_fat_binary_mock(self, elf_binary_path, mock_logger):
        """Test Mach-O hash extraction for FAT binary with mocked macho object."""
        from redb.extractors.hashes import HashExtractor

        # Create mock macho object for FAT binary
        mock_macho = MagicMock()
        mock_macho.get_architectures.return_value = ["x86_64", "arm64"]  # Multiple archs = FAT
        mock_macho.get_similarity_hashes.return_value = {
            'fat': {
                'dylib_hash': 'fat_dylib_hash_12345678901234567',
                'import_hash': 'fat_import_hash_12345678901234567',
            },
            'combined': {
                'dylib_hash': 'combined_dylib_hash_1234567890123',
            }
        }

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger, macho=mock_macho)
            extractor.filetype = 'macho'

            result = extractor.extract()

            assert result is not None
            # Should use 'fat' key for FAT binaries
            assert result.macho_dylib_hash == 'fat_dylib_hash_12345678901234567'
            assert result.macho_import_hash == 'fat_import_hash_12345678901234567'

    def test_extract_macho_hashes_handles_empty(self, elf_binary_path, mock_logger):
        """Test Mach-O hash extraction handles empty hash dict."""
        from redb.extractors.hashes import HashExtractor

        mock_macho = MagicMock()
        mock_macho.get_architectures.return_value = ["x86_64"]
        mock_macho.get_similarity_hashes.return_value = {}

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger, macho=mock_macho)
            extractor.filetype = 'macho'

            result = extractor.extract()

            # Should not crash, hashes should be None
            assert result is not None
            assert result.macho_dylib_hash is None

    def test_extract_macho_hashes_handles_none(self, elf_binary_path, mock_logger):
        """Test Mach-O hash extraction handles None return."""
        from redb.extractors.hashes import HashExtractor

        mock_macho = MagicMock()
        mock_macho.get_architectures.return_value = ["x86_64"]
        mock_macho.get_similarity_hashes.return_value = None

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger, macho=mock_macho)
            extractor.filetype = 'macho'

            result = extractor.extract()

            # Should not crash
            assert result is not None


class TestHashExtractorConsistency:
    """Tests for hash consistency."""

    def test_hash_consistency_across_extractions(self, elf_binary_path, mock_logger):
        """Test that hashes are consistent across multiple extractions."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor1 = HashExtractor(elf_binary_path, mock_logger)
            result1 = extractor1.extract()

            extractor2 = HashExtractor(elf_binary_path, mock_logger)
            result2 = extractor2.extract()

            assert result1.md5 == result2.md5
            assert result1.sha1 == result2.sha1
            assert result1.sha256 == result2.sha256

    def test_hash_values_are_lowercase(self, elf_binary_path, mock_logger):
        """Test that hash values are lowercase hex strings."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)

            result = extractor.extract()

            assert result.md5 == result.md5.lower()
            assert result.sha1 == result.sha1.lower()
            assert result.sha256 == result.sha256.lower()

    def test_hash_lengths_correct(self, elf_binary_path, mock_logger):
        """Test that hash lengths are correct."""
        from redb.extractors.hashes import HashExtractor

        with patch('redb.settings.ELASTIC_BINARIES_COLLECTION', 'test'):
            extractor = HashExtractor(elf_binary_path, mock_logger)

            result = extractor.extract()

            assert len(result.md5) == 32  # MD5 = 128 bits = 32 hex chars
            assert len(result.sha1) == 40  # SHA1 = 160 bits = 40 hex chars
            assert len(result.sha256) == 64  # SHA256 = 256 bits = 64 hex chars