├── .coveragerc ├── .editorconfig ├── .gitignore ├── .travis.yml ├── CODE_OF_CONDUCT.md ├── CONTRIBUTING.md ├── HISTORY.md ├── LICENSE ├── MANIFEST.in ├── Makefile ├── README.md ├── camelot ├── __init__.py ├── __main__.py ├── __version__.py ├── cli.py ├── core.py ├── ext │ ├── __init__.py │ └── ghostscript │ │ ├── COPYING │ │ ├── __init__.py │ │ └── _gsprint.py ├── handlers.py ├── image_processing.py ├── io.py ├── parsers │ ├── __init__.py │ ├── base.py │ ├── lattice.py │ └── stream.py ├── plotting.py └── utils.py ├── docs ├── Makefile ├── _static │ ├── camelot.png │ ├── csv │ │ ├── background_lines.csv │ │ ├── foo.csv │ │ ├── table_areas.csv │ │ └── table_regions.csv │ ├── favicon.ico │ ├── pdf │ │ ├── background_lines.pdf │ │ ├── column_separators.pdf │ │ ├── copy_text.pdf │ │ ├── foo.pdf │ │ ├── group_rows.pdf │ │ ├── rotated.pdf │ │ ├── short_lines.pdf │ │ ├── superscript.pdf │ │ ├── table_areas.pdf │ │ ├── table_regions.pdf │ │ └── us-030.pdf │ └── png │ │ ├── background_lines.png │ │ ├── camelot-logo.png │ │ ├── edge_tol_1.png │ │ ├── edge_tol_2.png │ │ ├── plot_contour.png │ │ ├── plot_joint.png │ │ ├── plot_line.png │ │ ├── plot_table.png │ │ ├── plot_text.png │ │ ├── plot_textedge.png │ │ ├── short_lines.png │ │ ├── short_lines_1.png │ │ ├── short_lines_2.png │ │ ├── superscript.png │ │ └── table.png ├── _templates │ ├── hacks.html │ ├── sidebarintro.html │ └── sidebarlogo.html ├── _themes │ ├── .gitignore │ ├── LICENSE │ └── flask_theme_support.py ├── api.rst ├── benchmark │ ├── lattice │ │ ├── agstat │ │ │ ├── agstat-data-camelot-page-1-table-1.csv │ │ │ ├── agstat-data-pdf-table-extract-page-1-table-1.csv │ │ │ ├── agstat-data-pdfplumber.csv │ │ │ ├── agstat-data-pdftables-page-1-table-1.csv │ │ │ ├── agstat-data-tabula.csv │ │ │ ├── agstat-table-detection-camelot.png │ │ │ ├── agstat-table-detection-tabula.png │ │ │ └── agstat.pdf │ │ ├── background_lines_1 │ │ │ ├── background_lines_1-data-camelot-page-1-table-1.csv │ │ │ ├── background_lines_1-data-camelot-page-1-table-2.csv │ │ │ ├── background_lines_1-data-tabula.csv │ │ │ ├── background_lines_1-table-detection-camelot.png │ │ │ ├── background_lines_1-table-detection-tabula.png │ │ │ └── background_lines_1.pdf │ │ ├── background_lines_2 │ │ │ ├── background_lines_2-data-camelot-page-1-table-1.csv │ │ │ ├── background_lines_2-data-tabula.csv │ │ │ ├── background_lines_2-table-detection-camelot.png │ │ │ ├── background_lines_2-table-detection-tabula.png │ │ │ └── background_lines_2.pdf │ │ ├── column_span_1 │ │ │ ├── column_span_1-data-camelot-page-1-table-1.csv │ │ │ ├── column_span_1-data-pdf-table-extract-page-1-table-1.csv │ │ │ ├── column_span_1-data-pdfplumber.csv │ │ │ ├── column_span_1-data-pdftables-page-1-table-1.csv │ │ │ ├── column_span_1-data-tabula.csv │ │ │ ├── column_span_1-table-detection-camelot.png │ │ │ ├── column_span_1-table-detection-tabula.png │ │ │ └── column_span_1.pdf │ │ ├── column_span_2 │ │ │ ├── column_span_2-data-camelot-page-1-table-1.csv │ │ │ ├── column_span_2-data-tabula.csv │ │ │ ├── column_span_2-table-detection-camelot.png │ │ │ ├── column_span_2-table-detection-tabula.png │ │ │ └── column_span_2.pdf │ │ ├── electoral_roll │ │ │ ├── electoral_roll-data-camelot-page-1-table-1.csv │ │ │ ├── electoral_roll-data-tabula.csv │ │ │ ├── electoral_roll-table-detection-camelot.png │ │ │ ├── electoral_roll-table-detection-tabula.png │ │ │ └── electoral_roll.pdf │ │ ├── rotated │ │ │ ├── rotated-data-camelot-page-1-table-1.csv │ │ │ ├── rotated-data-pdf-table-extract-page-1-table-1.csv │ │ │ ├── rotated-data-pdfplumber.csv │ │ │ ├── rotated-data-pdftables-page-1-table-1.csv │ │ │ ├── rotated-data-tabula.csv │ │ │ ├── rotated-table-detection-camelot.png │ │ │ ├── rotated-table-detection-tabula.png │ │ │ └── rotated.pdf │ │ ├── row_span │ │ │ ├── row_span-data-camelot-page-1-table-1.csv │ │ │ ├── row_span-data-tabula.csv │ │ │ ├── row_span-table-detection-camelot.png │ │ │ ├── row_span-table-detection-tabula.png │ │ │ └── row_span.pdf │ │ ├── twotables_1 │ │ │ ├── twotables_1-data-camelot-page-1-table-1.csv │ │ │ ├── twotables_1-data-camelot-page-1-table-2.csv │ │ │ ├── twotables_1-data-pdf-table-extract-page-1-table-1.csv │ │ │ ├── twotables_1-data-pdfplumber.csv │ │ │ ├── twotables_1-data-pdftables-page-1-table-1.csv │ │ │ ├── twotables_1-data-tabula.csv │ │ │ ├── twotables_1-table-detection-camelot.png │ │ │ ├── twotables_1-table-detection-tabula.png │ │ │ └── twotables_1.pdf │ │ └── twotables_2 │ │ │ ├── twotables_2-data-camelot-page-1-table-1.csv │ │ │ ├── twotables_2-data-camelot-page-1-table-2.csv │ │ │ ├── twotables_2-data-pdf-table-extract-page-1-table-1.csv │ │ │ ├── twotables_2-data-pdfplumber.csv │ │ │ ├── twotables_2-data-pdftables-page-1-table-1.csv │ │ │ ├── twotables_2-table-detection-camelot.png │ │ │ ├── twotables_2-table-detection-tabula.png │ │ │ ├── twotables_2-tabula-0.csv │ │ │ ├── twotables_2-tabula-1.csv │ │ │ └── twotables_2.pdf │ └── stream │ │ ├── 12s0324 │ │ ├── 12s0324-data-camelot-page-1-table-1.csv │ │ ├── 12s0324-data-camelot-page-1-table-2.csv │ │ ├── 12s0324-data-tabula-0.csv │ │ ├── 12s0324-data-tabula-1.csv │ │ └── 12s0324.pdf │ │ ├── birdisland │ │ ├── birdisland-data-camelot-page-1-table-1.csv │ │ ├── birdisland-data-camelot-page-1-table-2.csv │ │ ├── birdisland-data-tabula.csv │ │ └── birdisland.pdf │ │ ├── budget │ │ ├── budget-data-camelot-page-1-table-1.csv │ │ ├── budget-data-pdf-table-extract-page-1-table-1.csv │ │ ├── budget-data-pdftables-page-1-table-1.csv │ │ ├── budget-data-tabula.csv │ │ └── budget.pdf │ │ ├── district_health │ │ ├── district_health-data-camelot-page-1-table-1.csv │ │ ├── district_health-data-pdf-table-extract-page-1-table-1.csv │ │ ├── district_health-data-pdfplumber.csv │ │ ├── district_health-data-pdftables-page-1-table-1.csv │ │ ├── district_health-data-tabula.csv │ │ └── district_health.pdf │ │ ├── health │ │ ├── health-data-camelot-page-1-table-1.csv │ │ ├── health-data-pdf-table-extract-page-1-table-1.csv │ │ ├── health-data-pdfplumber.csv │ │ ├── health-data-pdftables-page-1-table-1.csv │ │ ├── health-data-tabula.csv │ │ └── health.pdf │ │ ├── m27 │ │ ├── m27-data-camelot-page-1-table-1.csv │ │ ├── m27-data-tabula-0.csv │ │ └── m27.pdf │ │ ├── mexican_towns │ │ ├── mexican_towns-data-camelot-page-1-table-1.csv │ │ ├── mexican_towns-data-pdf-table-extract-page-1-table-1.csv │ │ ├── mexican_towns-data-pdftables-page-1-table-1.csv │ │ ├── mexican_towns-data-tabula.csv │ │ └── mexican_towns.pdf │ │ ├── missing_values │ │ ├── missing_values-data-camelot-page-1-table-1.csv │ │ ├── missing_values-data-pdf-table-extract-page-1-table-1.csv │ │ ├── missing_values-data-pdfplumber.csv │ │ ├── missing_values-data-pdftables-page-1-table-1.csv │ │ ├── missing_values-data-tabula.csv │ │ └── missing_values.pdf │ │ ├── population_growth │ │ ├── population_growth-data-camelot-page-1-table-1.csv │ │ ├── population_growth-data-tabula.csv │ │ └── population_growth.pdf │ │ ├── superscript │ │ ├── superscript-data-camelot-page-1-table-1.csv │ │ ├── superscript-data-tabula.csv │ │ └── superscript.pdf │ │ └── us-007 │ │ ├── us-007-data-camelot-page-1-table-1.csv │ │ ├── us-007-data-tabula.csv │ │ └── us-007.pdf ├── conf.py ├── dev │ └── contributing.rst ├── index.rst ├── make.bat └── user │ ├── advanced.rst │ ├── cli.rst │ ├── how-it-works.rst │ ├── install-deps.rst │ ├── install.rst │ ├── intro.rst │ └── quickstart.rst ├── requirements.txt ├── setup.cfg ├── setup.py └── tests ├── __init__.py ├── data.py ├── files ├── agstat.pdf ├── anticlockwise_table_1.pdf ├── anticlockwise_table_2.pdf ├── assam.pdf ├── background_lines_1.pdf ├── background_lines_2.pdf ├── baseline_plots │ ├── test_contour_plot.png │ ├── test_grid_plot.png │ ├── test_joint_plot.png │ ├── test_lattice_contour_plot.png │ ├── test_line_plot.png │ ├── test_stream_contour_plot.png │ ├── test_text_plot.png │ └── test_textedge_plot.png ├── blank.pdf ├── budget.pdf ├── budget_2014-15.pdf ├── clockwise_table_1.pdf ├── clockwise_table_2.pdf ├── column_span_1.pdf ├── column_span_2.pdf ├── detect_vertical_false.pdf ├── district_health.pdf ├── edge_tol.pdf ├── electoral_roll.pdf ├── foo.csv ├── foo.pdf ├── health.pdf ├── health_protected.pdf ├── image.pdf ├── medicine.pdf ├── mexican_towns.pdf ├── missing_values.pdf ├── population_growth.pdf ├── rainfall_distribution.pdf ├── row_span_1.pdf ├── row_span_2.pdf ├── row_span_3.pdf ├── superscript.pdf ├── table_region.pdf ├── tableception.pdf ├── tabula │ ├── 12s0324.pdf │ ├── 20.pdf │ ├── S2MNCEbirdisland.pdf │ ├── arabic.pdf │ ├── argentina_diputados_voting_record.pdf │ ├── campaign_donors.pdf │ ├── china.pdf │ ├── eu-002.pdf │ ├── eu-017.pdf │ ├── failing_sort.pdf │ ├── frx_2012_disclosure.pdf │ ├── icdar2013-dataset │ │ ├── competition-dataset-eu │ │ │ ├── eu-001-reg.xml │ │ │ ├── eu-001-str.xml │ │ │ ├── eu-001.json │ │ │ ├── eu-001.pdf │ │ │ ├── eu-002-reg.xml │ │ │ ├── eu-002-str.xml │ │ │ ├── eu-002.json │ │ │ ├── eu-002.pdf │ │ │ ├── eu-003-reg.xml │ │ │ ├── eu-003-str.xml │ │ │ ├── eu-003.json │ │ │ ├── eu-003.pdf │ │ │ ├── eu-004-reg.xml │ │ │ ├── eu-004-str.xml │ │ │ ├── eu-004.json │ │ │ ├── eu-004.pdf │ │ │ ├── eu-005-reg.xml │ │ │ ├── eu-005-str.xml │ │ │ ├── eu-005.json │ │ │ ├── eu-005.pdf │ │ │ ├── eu-006-reg.xml │ │ │ ├── eu-006-str.xml │ │ │ ├── eu-006.json │ │ │ ├── eu-006.pdf │ │ │ ├── eu-007-reg.xml │ │ │ ├── eu-007-str.xml │ │ │ ├── eu-007.json │ │ │ ├── eu-007.pdf │ │ │ ├── eu-008-reg.xml │ │ │ ├── eu-008-str.xml │ │ │ ├── eu-008.json │ │ │ ├── eu-008.pdf │ │ │ ├── eu-009a-reg.xml │ │ │ ├── eu-009a-str.xml │ │ │ ├── eu-009a.json │ │ │ ├── eu-009a.pdf │ │ │ ├── eu-009b-reg.xml │ │ │ ├── eu-009b-str.xml │ │ │ ├── eu-010-reg.xml │ │ │ ├── eu-010-str.xml │ │ │ ├── eu-010.json │ │ │ ├── eu-010.pdf │ │ │ ├── eu-011-reg.xml │ │ │ ├── eu-011-str.xml │ │ │ ├── eu-011.json │ │ │ ├── eu-011.pdf │ │ │ ├── eu-012-reg.xml │ │ │ ├── eu-012-str.xml │ │ │ ├── eu-012.json │ │ │ ├── eu-012.pdf │ │ │ ├── eu-013-reg.xml │ │ │ ├── eu-013-str.xml │ │ │ ├── eu-013.json │ │ │ ├── eu-013.pdf │ │ │ ├── eu-014-reg.xml │ │ │ ├── eu-014-str.xml │ │ │ ├── eu-014.json │ │ │ ├── eu-014.pdf │ │ │ ├── eu-015-reg.xml │ │ │ ├── eu-015-str.xml │ │ │ ├── eu-015.json │ │ │ ├── eu-015.pdf │ │ │ ├── eu-016-reg.xml │ │ │ ├── eu-016-str.xml │ │ │ ├── eu-016.json │ │ │ ├── eu-016.pdf │ │ │ ├── eu-017-reg.xml │ │ │ ├── eu-017-str.xml │ │ │ ├── eu-017.json │ │ │ ├── eu-017.pdf │ │ │ ├── eu-018-reg.xml │ │ │ ├── eu-018-str.xml │ │ │ ├── eu-018.json │ │ │ ├── eu-018.pdf │ │ │ ├── eu-019-reg.xml │ │ │ ├── eu-019-str.xml │ │ │ ├── eu-019.json │ │ │ ├── eu-019.pdf │ │ │ ├── eu-020-reg.xml │ │ │ ├── eu-020-str.xml │ │ │ ├── eu-020.json │ │ │ ├── eu-020.pdf │ │ │ ├── eu-021-reg.xml │ │ │ ├── eu-021-str.xml │ │ │ ├── eu-021.json │ │ │ ├── eu-021.pdf │ │ │ ├── eu-022-reg.xml │ │ │ ├── eu-022-str.xml │ │ │ ├── eu-022.json │ │ │ ├── eu-022.pdf │ │ │ ├── eu-023-reg.xml │ │ │ ├── eu-023-str.xml │ │ │ ├── eu-023.json │ │ │ ├── eu-023.pdf │ │ │ ├── eu-024-reg.xml │ │ │ ├── eu-024-str.xml │ │ │ ├── eu-024.json │ │ │ ├── eu-024.pdf │ │ │ ├── eu-025-reg.xml │ │ │ ├── eu-025-str.xml │ │ │ ├── eu-025.json │ │ │ ├── eu-025.pdf │ │ │ ├── eu-026-reg.xml │ │ │ ├── eu-026-str.xml │ │ │ ├── eu-026.json │ │ │ ├── eu-026.pdf │ │ │ ├── eu-027-reg.xml │ │ │ ├── eu-027-str.xml │ │ │ ├── eu-027.json │ │ │ └── eu-027.pdf │ │ └── competition-dataset-us │ │ │ ├── us-001-reg.xml │ │ │ ├── us-001-str.xml │ │ │ ├── us-001.json │ │ │ ├── us-001.pdf │ │ │ ├── us-002-reg.xml │ │ │ ├── us-002-str.xml │ │ │ ├── us-002.json │ │ │ ├── us-002.pdf │ │ │ ├── us-003-reg.xml │ │ │ ├── us-003-str.xml │ │ │ ├── us-003.json │ │ │ ├── us-003.pdf │ │ │ ├── us-004-reg.xml │ │ │ ├── us-004-str.xml │ │ │ ├── us-004.json │ │ │ ├── us-004.pdf │ │ │ ├── us-005-reg.xml │ │ │ ├── us-005-str.xml │ │ │ ├── us-005.json │ │ │ ├── us-005.pdf │ │ │ ├── us-006-reg.xml │ │ │ ├── us-006-str.xml │ │ │ ├── us-006.json │ │ │ ├── us-006.pdf │ │ │ ├── us-007-reg.xml │ │ │ ├── us-007-str.xml │ │ │ ├── us-007.json │ │ │ ├── us-007.pdf │ │ │ ├── us-008-reg.xml │ │ │ ├── us-008-str.xml │ │ │ ├── us-008.json │ │ │ ├── us-008.pdf │ │ │ ├── us-009-reg.xml │ │ │ ├── us-009-str.xml │ │ │ ├── us-009.json │ │ │ ├── us-009.pdf │ │ │ ├── us-010-reg.xml │ │ │ ├── us-010-str.xml │ │ │ ├── us-010.json │ │ │ ├── us-010.pdf │ │ │ ├── us-011a-reg.xml │ │ │ ├── us-011a-str.xml │ │ │ ├── us-011a.json │ │ │ ├── us-011a.pdf │ │ │ ├── us-011b-reg.xml │ │ │ ├── us-011b-str.xml │ │ │ ├── us-012-reg.xml │ │ │ ├── us-012-str.xml │ │ │ ├── us-012.json │ │ │ ├── us-012.pdf │ │ │ ├── us-013-reg.xml │ │ │ ├── us-013-str.xml │ │ │ ├── us-013.json │ │ │ ├── us-013.pdf │ │ │ ├── us-014-reg.xml │ │ │ ├── us-014-str.xml │ │ │ ├── us-014.json │ │ │ ├── us-014.pdf │ │ │ ├── us-015-reg.xml │ │ │ ├── us-015-str.xml │ │ │ ├── us-015.json │ │ │ ├── us-015.pdf │ │ │ ├── us-016-reg.xml │ │ │ ├── us-016-str.xml │ │ │ ├── us-016.json │ │ │ ├── us-016.pdf │ │ │ ├── us-017-reg.xml │ │ │ ├── us-017-str.xml │ │ │ ├── us-017.json │ │ │ ├── us-017.pdf │ │ │ ├── us-018-reg.xml │ │ │ ├── us-018-str.xml │ │ │ ├── us-018.json │ │ │ ├── us-018.pdf │ │ │ ├── us-019-reg.xml │ │ │ ├── us-019-str.xml │ │ │ ├── us-019.json │ │ │ ├── us-019.pdf │ │ │ ├── us-020-reg.xml │ │ │ ├── us-020-str.xml │ │ │ ├── us-020.json │ │ │ ├── us-020.pdf │ │ │ ├── us-021-reg.xml │ │ │ ├── us-021-str.xml │ │ │ ├── us-021.json │ │ │ ├── us-021.pdf │ │ │ ├── us-022-reg.xml │ │ │ ├── us-022-str.xml │ │ │ ├── us-022.json │ │ │ ├── us-022.pdf │ │ │ ├── us-023-reg.xml │ │ │ ├── us-023-str.xml │ │ │ ├── us-023.json │ │ │ ├── us-023.pdf │ │ │ ├── us-024-reg.xml │ │ │ ├── us-024-str.xml │ │ │ ├── us-024.json │ │ │ ├── us-024.pdf │ │ │ ├── us-025-reg.xml │ │ │ ├── us-025-str.xml │ │ │ ├── us-025.json │ │ │ ├── us-025.pdf │ │ │ ├── us-026-reg.xml │ │ │ ├── us-026-str.xml │ │ │ ├── us-026.json │ │ │ ├── us-026.pdf │ │ │ ├── us-027-reg.xml │ │ │ ├── us-027-str.xml │ │ │ ├── us-027.json │ │ │ ├── us-027.pdf │ │ │ ├── us-028-reg.xml │ │ │ ├── us-028-str.xml │ │ │ ├── us-028.json │ │ │ ├── us-028.pdf │ │ │ ├── us-029-reg.xml │ │ │ ├── us-029-str.xml │ │ │ ├── us-029.json │ │ │ ├── us-029.pdf │ │ │ ├── us-030-reg.xml │ │ │ ├── us-030-str.xml │ │ │ ├── us-030.json │ │ │ ├── us-030.pdf │ │ │ ├── us-031a-reg.xml │ │ │ ├── us-031a-str.xml │ │ │ ├── us-031a.json │ │ │ ├── us-031a.pdf │ │ │ ├── us-031b-reg.xml │ │ │ ├── us-031b-str.xml │ │ │ ├── us-032-reg.xml │ │ │ ├── us-032-str.xml │ │ │ ├── us-032.json │ │ │ ├── us-032.pdf │ │ │ ├── us-033-reg.xml │ │ │ ├── us-033-str.xml │ │ │ ├── us-033.json │ │ │ ├── us-033.pdf │ │ │ ├── us-034-reg.xml │ │ │ ├── us-034-str.xml │ │ │ ├── us-034.json │ │ │ ├── us-034.pdf │ │ │ ├── us-035a-reg.xml │ │ │ ├── us-035a-str.xml │ │ │ ├── us-035a.json │ │ │ ├── us-035a.pdf │ │ │ ├── us-035b-reg.xml │ │ │ ├── us-035b-str.xml │ │ │ ├── us-036-reg.xml │ │ │ ├── us-036-str.xml │ │ │ ├── us-036.json │ │ │ ├── us-036.pdf │ │ │ ├── us-037-reg.xml │ │ │ ├── us-037-str.xml │ │ │ ├── us-037.json │ │ │ ├── us-037.pdf │ │ │ ├── us-038-reg.xml │ │ │ ├── us-038-str.xml │ │ │ ├── us-038.json │ │ │ ├── us-038.pdf │ │ │ ├── us-039-reg.xml │ │ │ ├── us-039-str.xml │ │ │ ├── us-039.json │ │ │ ├── us-039.pdf │ │ │ ├── us-040-reg.xml │ │ │ ├── us-040-str.xml │ │ │ ├── us-040.json │ │ │ └── us-040.pdf │ ├── indictb1h_14.pdf │ ├── labor.pdf │ ├── m27.pdf │ ├── mednine.pdf │ ├── offense.pdf │ ├── puertos1.pdf │ ├── rotated_page.pdf │ ├── schools.pdf │ ├── should_detect_rulings.pdf │ ├── sort_exception.pdf │ ├── spanning_cells.pdf │ ├── spreadsheet_no_bounding_frame.pdf │ ├── sydney_disclosure_contract.pdf │ ├── twotables.pdf │ ├── us-007.pdf │ ├── us-017.pdf │ └── us-024.pdf ├── twotables_1.pdf └── twotables_2.pdf ├── test_cli.py ├── test_common.py ├── test_errors.py └── test_plotting.py /.coveragerc: -------------------------------------------------------------------------------- 1 | [run] 2 | branch = True 3 | omit = camelot/ext/* 4 | -------------------------------------------------------------------------------- /.editorconfig: -------------------------------------------------------------------------------- 1 | root = true 2 | 3 | [*] 4 | end_of_line = lf 5 | insert_final_newline = true 6 | 7 | [*.py] 8 | charset = utf-8 9 | indent_style = space 10 | indent_size = 4 11 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | __pycache__/ 2 | *.py[cod] 3 | *.so 4 | 5 | build/ 6 | dist/ 7 | *.egg-info/ 8 | .eggs/ 9 | .coverage 10 | coverage.xml 11 | 12 | .pytest_cache/ 13 | _build/ 14 | 15 | .venv/ 16 | htmlcov/ 17 | 18 | # vscode 19 | .vscode 20 | -------------------------------------------------------------------------------- /.travis.yml: -------------------------------------------------------------------------------- 1 | sudo: true 2 | language: python 3 | cache: pip 4 | addons: 5 | apt: 6 | update: true 7 | install: 8 | - make install 9 | jobs: 10 | include: 11 | - stage: test 12 | script: 13 | - make test 14 | python: '2.7' 15 | - stage: test 16 | script: 17 | - make test 18 | python: '3.5' 19 | - stage: test 20 | script: 21 | - make test 22 | python: '3.6' 23 | - stage: test 24 | script: 25 | - make test 26 | python: '3.7' 27 | dist: xenial 28 | - stage: coverage 29 | python: '3.6' 30 | script: 31 | - make test 32 | - codecov --verbose 33 | -------------------------------------------------------------------------------- /CODE_OF_CONDUCT.md: -------------------------------------------------------------------------------- 1 | Be cordial or be on your way. --Kenneth Reitz 2 | 3 | https://www.kennethreitz.org/essays/be-cordial-or-be-on-your-way 4 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Modifications: 4 | 5 | Copyright (c) 2019 Camelot Developers 6 | 7 | Original project: 8 | 9 | Copyright (c) 2018 Peeply Private Ltd (Singapore) 10 | 11 | Permission is hereby granted, free of charge, to any person obtaining a copy 12 | of this software and associated documentation files (the "Software"), to deal 13 | in the Software without restriction, including without limitation the rights 14 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 15 | copies of the Software, and to permit persons to whom the Software is 16 | furnished to do so, subject to the following conditions: 17 | 18 | The above copyright notice and this permission notice shall be included in all 19 | copies or substantial portions of the Software. 20 | 21 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 22 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 23 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 24 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 25 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 26 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 27 | SOFTWARE. 28 | -------------------------------------------------------------------------------- /MANIFEST.in: -------------------------------------------------------------------------------- 1 | include MANIFEST.in README.md HISTORY.md LICENSE setup.py setup.cfg 2 | -------------------------------------------------------------------------------- /Makefile: -------------------------------------------------------------------------------- 1 | .PHONY: docs 2 | INSTALL := 3 | UNAME_S := $(shell uname -s) 4 | ifeq ($(UNAME_S),Linux) 5 | INSTALL := @sudo apt install python-tk python3-tk ghostscript 6 | else ifeq ($(UNAME_S),Darwin) 7 | INSTALL := @brew install tcl-tk ghostscript 8 | else 9 | INSTALL := @echo "Please install tk and ghostscript" 10 | endif 11 | 12 | install: 13 | $(INSTALL) 14 | pip install --upgrade pip 15 | pip install ".[dev]" 16 | 17 | test: 18 | pytest --verbose --cov-config .coveragerc --cov-report term --cov-report xml --cov=camelot --mpl 19 | 20 | docs: 21 | cd docs && make html 22 | @echo "\033[95m\n\nBuild successful! View the docs homepage at docs/_build/html/index.html.\n\033[0m" 23 | 24 | publish: 25 | pip install twine 26 | python setup.py sdist 27 | twine upload dist/* 28 | rm -fr build dist .egg camelot_py.egg-info 29 | -------------------------------------------------------------------------------- /camelot/__init__.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | 3 | import logging 4 | 5 | from .__version__ import __version__ 6 | from .io import read_pdf 7 | from .plotting import PlotMethods 8 | 9 | 10 | # set up logging 11 | logger = logging.getLogger("camelot") 12 | 13 | format_string = "%(asctime)s - %(levelname)s - %(message)s" 14 | formatter = logging.Formatter(format_string, datefmt="%Y-%m-%dT%H:%M:%S") 15 | handler = logging.StreamHandler() 16 | handler.setFormatter(formatter) 17 | 18 | logger.addHandler(handler) 19 | 20 | # instantiate plot method 21 | plot = PlotMethods() 22 | -------------------------------------------------------------------------------- /camelot/__main__.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | 3 | from __future__ import absolute_import 4 | 5 | 6 | __all__ = ("main",) 7 | 8 | 9 | def main(): 10 | from camelot.cli import cli 11 | 12 | cli() 13 | 14 | 15 | if __name__ == "__main__": 16 | main() 17 | -------------------------------------------------------------------------------- /camelot/__version__.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | 3 | VERSION = (0, 7, 3) 4 | PRERELEASE = None # alpha, beta or rc 5 | REVISION = None 6 | 7 | 8 | def generate_version(version, prerelease=None, revision=None): 9 | version_parts = [".".join(map(str, version))] 10 | if prerelease is not None: 11 | version_parts.append("-{}".format(prerelease)) 12 | if revision is not None: 13 | version_parts.append(".{}".format(revision)) 14 | return "".join(version_parts) 15 | 16 | 17 | __title__ = "camelot-py" 18 | __description__ = "PDF Table Extraction for Humans." 19 | __url__ = "http://camelot-py.readthedocs.io/" 20 | __version__ = generate_version(VERSION, prerelease=PRERELEASE, revision=REVISION) 21 | __author__ = "Vinayak Mehta" 22 | __author_email__ = "vmehta94@gmail.com" 23 | __license__ = "MIT License" 24 | -------------------------------------------------------------------------------- /camelot/ext/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/camelot/ext/__init__.py -------------------------------------------------------------------------------- /camelot/parsers/__init__.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | 3 | from .stream import Stream 4 | from .lattice import Lattice 5 | -------------------------------------------------------------------------------- /camelot/parsers/base.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | 3 | import os 4 | 5 | from ..utils import get_page_layout, get_text_objects 6 | 7 | 8 | class BaseParser(object): 9 | """Defines a base parser. 10 | """ 11 | 12 | def _generate_layout(self, filename, layout_kwargs): 13 | self.filename = filename 14 | self.layout_kwargs = layout_kwargs 15 | self.layout, self.dimensions = get_page_layout(filename, **layout_kwargs) 16 | self.images = get_text_objects(self.layout, ltype="image") 17 | self.horizontal_text = get_text_objects(self.layout, ltype="horizontal_text") 18 | self.vertical_text = get_text_objects(self.layout, ltype="vertical_text") 19 | self.pdf_width, self.pdf_height = self.dimensions 20 | self.rootname, __ = os.path.splitext(self.filename) 21 | -------------------------------------------------------------------------------- /docs/_static/camelot.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/_static/camelot.png -------------------------------------------------------------------------------- /docs/_static/csv/background_lines.csv: -------------------------------------------------------------------------------- 1 | "State","Date","Halt stations","Halt days","Persons directly reached(in lakh)","Persons trained","Persons counseled","Persons testedfor HIV" 2 | "Delhi","1.12.2009","8","17","1.29","3,665","2,409","1,000" 3 | "Rajasthan","2.12.2009 to 19.12.2009","","","","","","" 4 | "Gujarat","20.12.2009 to 3.1.2010","6","13","6.03","3,810","2,317","1,453" 5 | "Maharashtra","4.01.2010 to 1.2.2010","13","26","1.27","5,680","9,027","4,153" 6 | "Karnataka","2.2.2010 to 22.2.2010","11","19","1.80","5,741","3,658","3,183" 7 | "Kerala","23.2.2010 to 11.3.2010","9","17","1.42","3,559","2,173","855" 8 | "Total","","47","92","11.81","22,455","19,584","10,644" 9 | -------------------------------------------------------------------------------- /docs/_static/csv/foo.csv: -------------------------------------------------------------------------------- 1 | "Cycle Name","KI (1/km)","Distance (mi)","Percent Fuel Savings","","","" 2 | "","","","Improved Speed","Decreased Accel","Eliminate Stops","Decreased Idle" 3 | "2012_2","3.30","1.3","5.9%","9.5%","29.2%","17.4%" 4 | "2145_1","0.68","11.2","2.4%","0.1%","9.5%","2.7%" 5 | "4234_1","0.59","58.7","8.5%","1.3%","8.5%","3.3%" 6 | "2032_2","0.17","57.8","21.7%","0.3%","2.7%","1.2%" 7 | "4171_1","0.07","173.9","58.1%","1.6%","2.1%","0.5%" -------------------------------------------------------------------------------- /docs/_static/csv/table_areas.csv: -------------------------------------------------------------------------------- 1 | "","One Withholding" 2 | "Payroll Period","Allowance" 3 | "Weekly","$71.15" 4 | "Biweekly","142.31" 5 | "Semimonthly","154.17" 6 | "Monthly","308.33" 7 | "Quarterly","925.00" 8 | "Semiannually","1,850.00" 9 | "Annually","3,700.00" 10 | "Daily or Miscellaneous","14.23" 11 | "(each day of the payroll period)","" 12 | -------------------------------------------------------------------------------- /docs/_static/csv/table_regions.csv: -------------------------------------------------------------------------------- 1 | "Età dell’Assicuratoall’epoca del decesso","Misura % dimaggiorazione" 2 | "18-75","1,00%" 3 | "76-80","0,50%" 4 | "81 in poi","0,10%" 5 | -------------------------------------------------------------------------------- /docs/_static/favicon.ico: -------------------------------------------------------------------------------- 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10 | -------------------------------------------------------------------------------- /docs/_themes/.gitignore: -------------------------------------------------------------------------------- 1 | *.pyc 2 | *.pyo -------------------------------------------------------------------------------- /docs/_themes/LICENSE: -------------------------------------------------------------------------------- 1 | Copyright (c) 2010 by Armin Ronacher. 2 | 3 | Some rights reserved. 4 | 5 | Redistribution and use in source and binary forms of the theme, with or 6 | without modification, are permitted provided that the following conditions 7 | are met: 8 | 9 | * Redistributions of source code must retain the above copyright 10 | notice, this list of conditions and the following disclaimer. 11 | 12 | * Redistributions in binary form must reproduce the above 13 | copyright notice, this list of conditions and the following 14 | disclaimer in the documentation and/or other materials provided 15 | with the distribution. 16 | 17 | * The names of the contributors may not be used to endorse or 18 | promote products derived from this software without specific 19 | prior written permission. 20 | 21 | We kindly ask you to only use these themes in an unmodified manner just 22 | for Flask and Flask-related products, not for unrelated projects. If you 23 | like the visual style and want to use it for your own projects, please 24 | consider making some larger changes to the themes (such as changing 25 | font faces, sizes, colors or margins). 26 | 27 | THIS THEME IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" 28 | AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE 29 | IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE 30 | ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE 31 | LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR 32 | CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF 33 | SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS 34 | INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN 35 | CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) 36 | ARISING IN ANY WAY OUT OF THE USE OF THIS THEME, EVEN IF ADVISED OF THE 37 | POSSIBILITY OF SUCH DAMAGE. -------------------------------------------------------------------------------- /docs/api.rst: -------------------------------------------------------------------------------- 1 | .. _api: 2 | 3 | API Reference 4 | ============= 5 | 6 | .. module:: camelot 7 | 8 | Main Interface 9 | -------------- 10 | .. autofunction:: camelot.read_pdf 11 | 12 | Lower-Level Classes 13 | ------------------- 14 | 15 | .. autoclass:: camelot.handlers.PDFHandler 16 | :inherited-members: 17 | 18 | .. autoclass:: camelot.parsers.Stream 19 | :inherited-members: 20 | 21 | .. autoclass:: camelot.parsers.Lattice 22 | :inherited-members: 23 | 24 | Lower-Lower-Level Classes 25 | ------------------------- 26 | 27 | .. autoclass:: camelot.core.TableList 28 | :inherited-members: 29 | 30 | .. autoclass:: camelot.core.Table 31 | :inherited-members: 32 | 33 | .. autoclass:: camelot.core.Cell -------------------------------------------------------------------------------- /docs/benchmark/lattice/agstat/agstat-data-camelot-page-1-table-1.csv: -------------------------------------------------------------------------------- 1 | "Sl.No.","District","(In lakhs)for 2012-13Projected Population","Adult (In lakhs)Equivalent to 88%","requirement(In Lakh tonnes)Total Consumption(@ 400gms/adult/day)","(In Lakh tonnes)(Including seeds, feeds & wastage)Total Requirement","Production (Rice)(In Lakh tonnes)","","","Surplus/Defi cit(In Lakh tonnes)","" 2 | "","","","","","","Kharif","Rabi","Total","Rice","Paddy" 3 | "1","Balasore","23.65","20.81","3.04","3.47","2.78","0.86","3.64","0.17","0.25" 4 | "2","Bhadrak","15.34","13.50","1.97","2.25","3.50","0.05","3.55","1.30","1.94" 5 | "3","Balangir","17.01","14.97","2.19","2.50","6.23","0.10","6.33","3.83","5.72" 6 | "4","Subarnapur","6.70","5.90","0.86","0.98","4.48","1.13","5.61","4.63","6.91" 7 | "5","Cuttack","26.63","23.43","3.42","3.91","3.75","0.06","3.81","-0.10","-0.15" 8 | "6","Jagatsingpur","11.49","10.11","1.48","1.69","2.10","0.02","2.12","0.43","0.64" 9 | "7","Jajpur","18.59","16.36","2.39","2.73","2.13","0.04","2.17","-0.56","-0.84" 10 | "8","Kendrapara","14.62","12.87","1.88","2.15","2.60","0.07","2.67","0.52","0.78" 11 | "9","Dhenkanal","12.13","10.67","1.56","1.78","2.26","0.02","2.28","0.50","0.75" 12 | "10","Angul","12.93","11.38","1.66","1.90","1.73","0.02","1.75","-0.15","-0.22" 13 | "11","Ganjam","35.77","31.48","4.60","5.26","4.57","0.00","4.57","-0.69","-1.03" 14 | "12","Gajapati","5.85","5.15","0.75","0.86","0.68","0.01","0.69","-0.17","-0.25" 15 | "13","Kalahandi","16.12","14.19","2.07","2.37","5.42","1.13","6.55","4.18","6.24" 16 | "14","Nuapada","6.18","5.44","0.79","0.90","1.98","0.08","2.06","1.16","1.73" 17 | "15","Keonjhar","18.42","16.21","2.37","2.71","2.76","0.08","2.84","0.13","0.19" 18 | "16","Koraput","14.09","12.40","1.81","2.07","2.08","0.34","2.42","0.35","0.52" 19 | "17","Malkangiri","6.31","5.55","0.81","0.93","1.78","0.04","1.82","0.89","1.33" 20 | "18","Nabarangpur","12.50","11.00","1.61","1.84","3.26","0.02","3.28","1.44","2.15" 21 | "19","Rayagada","9.83","8.65","1.26","1.44","1.15","0.03","1.18","-0.26","-0.39" 22 | "20","Mayurbhanj","25.61","22.54","3.29","3.76","4.90","0.06","4.96","1.20","1.79" 23 | "21","Kandhamal","7.45","6.56","0.96","1.10","0.70","0.01","0.71","-0.39","-0.58" 24 | "22","Boudh","4.51","3.97","0.58","0.66","1.73","0.03","1.76","1.10","1.64" 25 | "23","Puri","17.29","15.22","2.22","2.54","2.45","0.99","3.44","0.90","1.34" 26 | "24","Khordha","23.08","20.31","2.97","3.39","2.02","0.03","2.05","-1.34","-2.00" 27 | "25","Nayagarh","9.78","8.61","1.26","1.44","2.10","0.00","2.10","0.66","0.99" 28 | "26","Sambalpur","10.62","9.35","1.37","1.57","3.45","0.71","4.16","2.59","3.87" 29 | "27","Bargarh","15.00","13.20","1.93","2.21","6.87","2.65","9.52","7.31","10.91" 30 | "28","Deogarh","3.18","2.80","0.41","0.47","1.12","0.07","1.19","0.72","1.07" 31 | "29","Jharsuguda","5.91","5.20","0.76","0.87","0.99","0.01","1.00","0.13","0.19" 32 | "30","Sundargarh","21.21","18.66","2.72","3.11","4.72","0.02","4.74","1.63","2.43" 33 | "ODISHA","","427.80","376.49","54.99","62.86","86.29","8.68","94.97","32.11","47.92" 34 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/agstat/agstat-data-pdf-table-extract-page-1-table-1.csv: -------------------------------------------------------------------------------- 1 | "0","1","2","3","4","5","6","7","8","9","10" 2 | "DISTRICT WISE ESTIMATES OF MARKETABLE SURPLUS / DEFICIT OF RICE DURING 2012-13","","","","","","","","","","" 3 | "Sl. No.","District","Projected Population for 2012-13 (In lakhs)","Adult Equivalent to 88% (In lakhs)","Total Consumption requirement (@ 400gms/adult/day) (In Lakh tonnes)","Total Requirement (Including seeds, feeds & wastage) (In Lakh tonnes)","Production (Rice) (In Lakh tonnes)","","","Surplus/Deficit (In Lakh tonnes)","" 4 | "","","","","","","Kharif","Rabi","Total","Rice","Paddy" 5 | "1","Balasore","23.65","20.81","3.04","3.47","2.78","0.86","3.64","0.17","0.25" 6 | "2","Bhadrak","15.34","13.50","1.97","2.25","3.50","0.05","3.55","1.30","1.94" 7 | "3","Balangir","17.01","14.97","2.19","2.50","6.23","0.10","6.33","3.83","5.72" 8 | "4","Subarnapur","6.70","5.90","0.86","0.98","4.48","1.13","5.61","4.63","6.91" 9 | "5","Cuttack","26.63","23.43","3.42","3.91","3.75","0.06","3.81","-0.10","-0.15" 10 | "6","Jagatsingpur","11.49","10.11","1.48","1.69","2.10","0.02","2.12","0.43","0.64" 11 | "7","Jajpur","18.59","16.36","2.39","2.73","2.13","0.04","2.17","-0.56","-0.84" 12 | "8","Kendrapara","14.62","12.87","1.88","2.15","2.60","0.07","2.67","0.52","0.78" 13 | "9","Dhenkanal","12.13","10.67","1.56","1.78","2.26","0.02","2.28","0.50","0.75" 14 | "10","Angul","12.93","11.38","1.66","1.90","1.73","0.02","1.75","-0.15","-0.22" 15 | "11","Ganjam","35.77","31.48","4.60","5.26","4.57","0.00","4.57","-0.69","-1.03" 16 | "12","Gajapati","5.85","5.15","0.75","0.86","0.68","0.01","0.69","-0.17","-0.25" 17 | "13","Kalahandi","16.12","14.19","2.07","2.37","5.42","1.13","6.55","4.18","6.24" 18 | "14","Nuapada","6.18","5.44","0.79","0.90","1.98","0.08","2.06","1.16","1.73" 19 | "15","Keonjhar","18.42","16.21","2.37","2.71","2.76","0.08","2.84","0.13","0.19" 20 | "16","Koraput","14.09","12.40","1.81","2.07","2.08","0.34","2.42","0.35","0.52" 21 | "17","Malkangiri","6.31","5.55","0.81","0.93","1.78","0.04","1.82","0.89","1.33" 22 | "18","Nabarangpur","12.50","11.00","1.61","1.84","3.26","0.02","3.28","1.44","2.15" 23 | "19","Rayagada","9.83","8.65","1.26","1.44","1.15","0.03","1.18","-0.26","-0.39" 24 | "20","Mayurbhanj","25.61","22.54","3.29","3.76","4.90","0.06","4.96","1.20","1.79" 25 | "21","Kandhamal","7.45","6.56","0.96","1.10","0.70","0.01","0.71","-0.39","-0.58" 26 | "22","Boudh","4.51","3.97","0.58","0.66","1.73","0.03","1.76","1.10","1.64" 27 | "23","Puri","17.29","15.22","2.22","2.54","2.45","0.99","3.44","0.90","1.34" 28 | "24","Khordha","23.08","20.31","2.97","3.39","2.02","0.03","2.05","-1.34","-2.00" 29 | "25","Nayagarh","9.78","8.61","1.26","1.44","2.10","0.00","2.10","0.66","0.99" 30 | "26","Sambalpur","10.62","9.35","1.37","1.57","3.45","0.71","4.16","2.59","3.87" 31 | "27","Bargarh","15.00","13.20","1.93","2.21","6.87","2.65","9.52","7.31","10.91" 32 | "28","Deogarh","3.18","2.80","0.41","0.47","1.12","0.07","1.19","0.72","1.07" 33 | "29","Jharsuguda","5.91","5.20","0.76","0.87","0.99","0.01","1.00","0.13","0.19" 34 | "30","Sundargarh","21.21","18.66","2.72","3.11","4.72","0.02","4.74","1.63","2.43" 35 | "ODISHA","","427.80","376.49","54.99","62.86","86.29","8.68","94.97","32.11","47.92" 36 | "87","","","","","","","","","","" 37 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/agstat/agstat-data-pdfplumber.csv: -------------------------------------------------------------------------------- 1 | "0","1","2","3","4","5","6","7","8","9","10" 2 | "Sl. 3 | No.","District","n 4 | o 5 | i 6 | t 7 | a 8 | l3 9 | opu2-1hs) 10 | P1k 11 | d 20 la 12 | er n 13 | cto(I 14 | ef 15 | j 16 | o 17 | r 18 | P","% 19 | 8 20 | 8 21 | o ) 22 | s 23 | ult t tkh 24 | dna 25 | Aalen l 26 | v(I 27 | i 28 | u 29 | q 30 | E",") 31 | y 32 | n a 33 | umptiomentadult/donnes) 34 | nsres/h t 35 | ouimk 36 | Cqga 37 | al re00n L 38 | ot 4(I 39 | T @ 40 | (","menteds, age)nes) 41 | uireg sewastton 42 | qn h 43 | Reudis &ak 44 | al cld L 45 | tnen 46 | To(Ife(I","","","","","" 47 | "","","","","","","f 48 | i 49 | r 50 | a 51 | h 52 | K","i 53 | b 54 | a 55 | R","l 56 | a 57 | t 58 | o 59 | T","e 60 | c 61 | i 62 | R","y 63 | d 64 | d 65 | a 66 | P" 67 | "1","Balasore","23.65","20.81","3.04","3.47","2.78","0.86","3.64","0.17","0.25" 68 | "2","Bhadrak","15.34","13.50","1.97","2.25","3.50","0.05","3.55","1.30","1.94" 69 | "3","Balangir","17.01","14.97","2.19","2.50","6.23","0.10","6.33","3.83","5.72" 70 | "4","Subarnapur","6.70","5.90","0.86","0.98","4.48","1.13","5.61","4.63","6.91" 71 | "5","Cuttack","26.63","23.43","3.42","3.91","3.75","0.06","3.81","-0.10","-0.15" 72 | "6","Jagatsingpur","11.49","10.11","1.48","1.69","2.10","0.02","2.12","0.43","0.64" 73 | "7","Jajpur","18.59","16.36","2.39","2.73","2.13","0.04","2.17","-0.56","-0.84" 74 | "8","Kendrapara","14.62","12.87","1.88","2.15","2.60","0.07","2.67","0.52","0.78" 75 | "9","Dhenkanal","12.13","10.67","1.56","1.78","2.26","0.02","2.28","0.50","0.75" 76 | "10","Angul","12.93","11.38","1.66","1.90","1.73","0.02","1.75","-0.15","-0.22" 77 | "11","Ganjam","35.77","31.48","4.60","5.26","4.57","0.00","4.57","-0.69","-1.03" 78 | "12","Gajapati","5.85","5.15","0.75","0.86","0.68","0.01","0.69","-0.17","-0.25" 79 | "13","Kalahandi","16.12","14.19","2.07","2.37","5.42","1.13","6.55","4.18","6.24" 80 | "14","Nuapada","6.18","5.44","0.79","0.90","1.98","0.08","2.06","1.16","1.73" 81 | "15","Keonjhar","18.42","16.21","2.37","2.71","2.76","0.08","2.84","0.13","0.19" 82 | "16","Koraput","14.09","12.40","1.81","2.07","2.08","0.34","2.42","0.35","0.52" 83 | "17","Malkangiri","6.31","5.55","0.81","0.93","1.78","0.04","1.82","0.89","1.33" 84 | "18","Nabarangpur","12.50","11.00","1.61","1.84","3.26","0.02","3.28","1.44","2.15" 85 | "19","Rayagada","9.83","8.65","1.26","1.44","1.15","0.03","1.18","-0.26","-0.39" 86 | "20","Mayurbhanj","25.61","22.54","3.29","3.76","4.90","0.06","4.96","1.20","1.79" 87 | "21","Kandhamal","7.45","6.56","0.96","1.10","0.70","0.01","0.71","-0.39","-0.58" 88 | "22","Boudh","4.51","3.97","0.58","0.66","1.73","0.03","1.76","1.10","1.64" 89 | "23","Puri","17.29","15.22","2.22","2.54","2.45","0.99","3.44","0.90","1.34" 90 | "24","Khordha","23.08","20.31","2.97","3.39","2.02","0.03","2.05","-1.34","-2.00" 91 | "25","Nayagarh","9.78","8.61","1.26","1.44","2.10","0.00","2.10","0.66","0.99" 92 | "26","Sambalpur","10.62","9.35","1.37","1.57","3.45","0.71","4.16","2.59","3.87" 93 | "27","Bargarh","15.00","13.20","1.93","2.21","6.87","2.65","9.52","7.31","10.91" 94 | "28","Deogarh","3.18","2.80","0.41","0.47","1.12","0.07","1.19","0.72","1.07" 95 | "29","Jharsuguda","5.91","5.20","0.76","0.87","0.99","0.01","1.00","0.13","0.19" 96 | "30","","","18.66","2.72","3.11","4.72","0.02","4.74","1.63","2.43" 97 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/agstat/agstat-data-pdftables-page-1-table-1.csv: -------------------------------------------------------------------------------- 1 | "0","1","2","3" 2 | "","","","" 3 | "","","DISTRICTW","ISEESTIMATESOFMARKETABLESURPLUS/DEFICITOFRICE 4 | " 5 | "","","","DURING2012-13 6 | " 7 | "","","","PopulationSurplus/DeficitPopulation 8 | PopulationProduction(Rice) 9 | Population 10 | Population(InLakhPopulation2012-13(InLakhtonnes)Populationlakhs) 11 | Population2012-13lakhs)tonnes)2012-13" 12 | "","Sl. 13 | No.","DistrictPopulation","Population2012-13lakhs) 14 | 2012-13lakhs)EquivalentPopulationEquivalent2012-13lakhs) 15 | lakhs)Equivalent2012-13 16 | Equivalent 17 | Equivalent 18 | Equivalent 19 | Equivalent 20 | Equivalent" 21 | "","1","Balasore","Equivalent 22 | Equivalent 23 | 23.6520.813.043.472.780.863.640.170.25 24 | " 25 | "","2","Bhadrak","15.3413.501.972.253.500.053.551.301.94 26 | " 27 | "","3","Balangir","17.0114.972.192.506.230.106.333.835.72 28 | " 29 | "","4","Subarnapur","6.705.900.860.984.481.135.614.636.91 30 | " 31 | "","5","Cuttack","26.6323.433.423.913.750.063.81-0.10-0.15 32 | " 33 | "","6","Jagatsingpur","11.4910.111.481.692.100.022.120.430.64 34 | " 35 | "","7","Jajpur","18.5916.362.392.732.130.042.17-0.56-0.84 36 | " 37 | "","8","Kendrapara","14.6212.871.882.152.600.072.670.520.78 38 | " 39 | "","9","Dhenkanal","12.1310.671.561.782.260.022.280.500.75 40 | " 41 | "","10","Angul","12.9311.381.661.901.730.021.75-0.15-0.22 42 | " 43 | "","11","Ganjam","35.7731.484.605.264.570.004.57-0.69-1.03 44 | " 45 | "","12","Gajapati","5.855.150.750.860.680.010.69-0.17-0.25 46 | " 47 | "","13","Kalahandi","16.1214.192.072.375.421.136.554.186.24 48 | " 49 | "","14","Nuapada","6.185.440.790.901.980.082.061.161.73 50 | " 51 | "","15","Keonjhar","18.4216.212.372.712.760.082.840.130.19 52 | " 53 | "","16","Koraput","14.0912.401.812.072.080.342.420.350.52 54 | " 55 | "","17","Malkangiri","6.315.550.810.931.780.041.820.891.33" 56 | "","18","Nabarangpur","12.5011.001.611.843.260.023.281.442.15 57 | " 58 | "","19","Rayagada","9.838.651.261.441.150.031.18-0.26-0.39 59 | " 60 | "","20","Mayurbhanj","25.6122.543.293.764.900.064.961.201.79 61 | " 62 | "","21","Kandhamal","7.456.560.961.100.700.010.71-0.39-0.58 63 | " 64 | "","22","Boudh","4.513.970.580.661.730.031.761.101.64 65 | " 66 | "","23","Puri","17.2915.222.222.542.450.993.440.901.34 67 | " 68 | "","24","Khordha","23.0820.312.973.392.020.032.05-1.34-2.00 69 | " 70 | "","25","Nayagarh","9.788.611.261.442.100.002.100.660.99 71 | " 72 | "","26","Sambalpur","10.629.351.371.573.450.714.162.593.87 73 | " 74 | "","27","Bargarh","15.0013.201.932.216.872.659.527.3110.91 75 | " 76 | "","28","Deogarh","3.182.800.410.471.120.071.190.721.07 77 | " 78 | "","29","Jharsuguda","5.915.200.760.870.990.011.000.130.19 79 | " 80 | "","30","ndargarh 81 | 1 82 | 2 83 | 3 84 | 4 85 | 5 86 | 6 87 | 7 88 | 8 89 | 9 90 | 10 91 | 11 92 | 12 93 | 13 94 | 14 95 | 15 96 | 16 97 | 17 98 | 18 99 | 19 100 | 20 101 | 21 102 | 22 103 | 23 104 | 24 105 | 25 106 | 26 107 | 27 108 | 28 109 | 29 110 | 30Sundargarh","21.2118.662.723.114.720.024.741.632.43 111 | " 112 | "","","ODISHA 113 | ","427.80376.4954.9962.8686.298.6894.9732.1147.92 114 | 87" 115 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/agstat/agstat-data-tabula.csv: -------------------------------------------------------------------------------- 1 | "Sl. No.",District,,,,,"Production (Rice) (In Lakh tonnes)","Surplus/Defi cit (In Lakh tonnes)",,, 2 | "",,,,,,,,,, 3 | 1,Balasore,23.65,20.81,3.04,3.47,2.78,0.86,3.64,0.17,0.25 4 | 2,Bhadrak,15.34,13.50,1.97,2.25,3.50,0.05,3.55,1.30,1.94 5 | 3,Balangir,17.01,14.97,2.19,2.50,6.23,0.10,6.33,3.83,5.72 6 | 4,Subarnapur,6.70,5.90,0.86,0.98,4.48,1.13,5.61,4.63,6.91 7 | 5,Cuttack,26.63,23.43,3.42,3.91,3.75,0.06,3.81,-0.10,-0.15 8 | 6,Jagatsingpur,11.49,10.11,1.48,1.69,2.10,0.02,2.12,0.43,0.64 9 | 7,Jajpur,18.59,16.36,2.39,2.73,2.13,0.04,2.17,-0.56,-0.84 10 | 8,Kendrapara,14.62,12.87,1.88,2.15,2.60,0.07,2.67,0.52,0.78 11 | 9,Dhenkanal,12.13,10.67,1.56,1.78,2.26,0.02,2.28,0.50,0.75 12 | 10,Angul,12.93,11.38,1.66,1.90,1.73,0.02,1.75,-0.15,-0.22 13 | 11,Ganjam,35.77,31.48,4.60,5.26,4.57,0.00,4.57,-0.69,-1.03 14 | 12,Gajapati,5.85,5.15,0.75,0.86,0.68,0.01,0.69,-0.17,-0.25 15 | 13,Kalahandi,16.12,14.19,2.07,2.37,5.42,1.13,6.55,4.18,6.24 16 | 14,Nuapada,6.18,5.44,0.79,0.90,1.98,0.08,2.06,1.16,1.73 17 | 15,Keonjhar,18.42,16.21,2.37,2.71,2.76,0.08,2.84,0.13,0.19 18 | 16,Koraput,14.09,12.40,1.81,2.07,2.08,0.34,2.42,0.35,0.52 19 | 17,Malkangiri,6.31,5.55,0.81,0.93,1.78,0.04,1.82,0.89,1.33 20 | 18,Nabarangpur,12.50,11.00,1.61,1.84,3.26,0.02,3.28,1.44,2.15 21 | 19,Rayagada,9.83,8.65,1.26,1.44,1.15,0.03,1.18,-0.26,-0.39 22 | 20,Mayurbhanj,25.61,22.54,3.29,3.76,4.90,0.06,4.96,1.20,1.79 23 | 21,Kandhamal,7.45,6.56,0.96,1.10,0.70,0.01,0.71,-0.39,-0.58 24 | 22,Boudh,4.51,3.97,0.58,0.66,1.73,0.03,1.76,1.10,1.64 25 | 23,Puri,17.29,15.22,2.22,2.54,2.45,0.99,3.44,0.90,1.34 26 | 24,Khordha,23.08,20.31,2.97,3.39,2.02,0.03,2.05,-1.34,-2.00 27 | 25,Nayagarh,9.78,8.61,1.26,1.44,2.10,0.00,2.10,0.66,0.99 28 | 26,Sambalpur,10.62,9.35,1.37,1.57,3.45,0.71,4.16,2.59,3.87 29 | 27,Bargarh,15.00,13.20,1.93,2.21,6.87,2.65,9.52,7.31,10.91 30 | 28,Deogarh,3.18,2.80,0.41,0.47,1.12,0.07,1.19,0.72,1.07 31 | 29,Jharsuguda,5.91,5.20,0.76,0.87,0.99,0.01,1.00,0.13,0.19 32 | 30,Sundargarh,21.21,18.66,2.72,3.11,4.72,0.02,4.74,1.63,2.43 33 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/agstat/agstat-table-detection-camelot.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/agstat/agstat-table-detection-camelot.png -------------------------------------------------------------------------------- /docs/benchmark/lattice/agstat/agstat-table-detection-tabula.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/agstat/agstat-table-detection-tabula.png -------------------------------------------------------------------------------- /docs/benchmark/lattice/agstat/agstat.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/agstat/agstat.pdf -------------------------------------------------------------------------------- /docs/benchmark/lattice/background_lines_1/background_lines_1-data-camelot-page-1-table-1.csv: -------------------------------------------------------------------------------- 1 | "The Red Ribbon Express (RRE) is the world’s largest mass mobilisation drive on HIV/AIDS. The train will travel through 22 states, during its one year long journey, halting at 152 stations. Through the RRE, NACO, intends to break the silence surrounding the issue of HIV/AIDS, by taking the messages on prevention, care and support to people living in small towns and villages across the country. The aim is also to create an environment, free from stigma and discrimination faced by people living with HIV, so they can access the services, without fear and prejudice, and live a life of dignity. It has proved to be a successful multi- sectoral initiative, of the NACO and a powerful advocacy tool, both at the state and district level, besides enhancing local capacity to deal with HIV prevention.","","" 2 | "","","" 3 | "","","" 4 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/background_lines_1/background_lines_1-data-camelot-page-1-table-2.csv: -------------------------------------------------------------------------------- 1 | "State","Date","Halt stations","Halt days","Persons directly reached(in lakh)","Persons trained","Persons counseled","Persons testedfor HIV" 2 | "Delhi","1.12.2009","8","17","1.29","3,665","2,409","1,000" 3 | "Rajasthan","2.12.2009 to 19.12.2009","","","","","","" 4 | "Gujarat","20.12.2009 to 3.1.2010","6","13","6.03","3,810","2,317","1,453" 5 | "Maharashtra","4.01.2010 to 1.2.2010","13","26","1.27","5,680","9,027","4,153" 6 | "Karnataka","2.2.2010 to 22.2.2010","11","19","1.80","5,741","3,658","3,183" 7 | "Kerala","23.2.2010 to 11.3.2010","9","17","1.42","3,559","2,173","855" 8 | "Total","","47","92","11.81","22,455","19,584","10,644" 9 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/background_lines_1/background_lines_1-data-tabula.csv: -------------------------------------------------------------------------------- 1 | State,Date,"Halt stations","Halt days","Persons directly reached (in lakh)","Persons trained","Persons counseled","Persons tested for HIV" 2 | Delhi,1.12.2009,8,17,1.29,"3,665","2,409","1,000" 3 | Rajasthan,"2.12.2009 to 19.12.2009",,,,,, 4 | Gujarat,"20.12.2009 to 3.1.2010",6,13,6.03,"3,810","2,317","1,453" 5 | Maharashtra,"4.01.2010 to 1.2.2010",13,26,1.27,"5,680","9,027","4,153" 6 | Karnataka,"2.2.2010 to 22.2.2010",11,19,1.80,"5,741","3,658","3,183" 7 | Kerala,"23.2.2010 to 11.3.2010",9,17,1.42,"3,559","2,173",855 8 | Total,,47,92,11.81,"22,455","19,584","10,644" 9 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/background_lines_1/background_lines_1-table-detection-camelot.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/background_lines_1/background_lines_1-table-detection-camelot.png -------------------------------------------------------------------------------- /docs/benchmark/lattice/background_lines_1/background_lines_1-table-detection-tabula.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/background_lines_1/background_lines_1-table-detection-tabula.png -------------------------------------------------------------------------------- /docs/benchmark/lattice/background_lines_1/background_lines_1.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/background_lines_1/background_lines_1.pdf -------------------------------------------------------------------------------- /docs/benchmark/lattice/background_lines_2/background_lines_2-data-camelot-page-1-table-1.csv: -------------------------------------------------------------------------------- 1 | "Sl.No","SIZE GROUP(HA)","NO. OF HOLDINGS GROWING THE CROP","","AREA UNDER THE CROP","","","AREA UNDER THE CROP TREATED WITHTHE MANURE","","" 2 | "","","TOTAL NO.","NO. TREATED WITHTHE MANURE","HYV","OTHERS","TOTAL","HYV","OTHERS","TOTAL" 3 | "(1)","(2)","(3)","(4)","(5)","(6)","(7)","(8)","(9)","(10)" 4 | "1","MARGINAL (BELOW 1.0)","","","","","","","","" 5 | "","I","39053","0","12142","3322","15464","0","0","0" 6 | "","UI","7429","0","2088","1560","3648","0","0","0" 7 | "","T","46484","0","14230","4882","19112","0","0","0" 8 | "2","SMALL (1.0 - 1.99)","","","","","","","","" 9 | "","I","20341","0","16685","1631","18316","0","0","0" 10 | "","UI","6854","0","4594","1885","6479","0","0","0" 11 | "","T","27197","0","21279","3516","24795","0","0","0" 12 | "3","SEMI-MEDIUM (2.0 - 3.99)","","","","","","","","" 13 | "","I","20800","0","16991","7643","24634","0","0","0" 14 | "","UI","5856","0","1017","4819","5836","0","0","0" 15 | "","T","26555","0","18008","12462","30470","0","0","0" 16 | "4","MEDIUM (4.0 - 9.99)","","","","","","","","" 17 | "","I","11986","0","17576","4120","21696","0","0","0" 18 | "","UI","4615","0","1446","6227","7673","0","0","0" 19 | "","T","16312","0","19022","10347","29369","0","0","0" 20 | "5","LARGE (10 AND ABOVE)","","","","","","","","" 21 | "","I","2005","0","3671","639","4310","0","0","0" 22 | "","UI","521","0","611","831","1442","0","0","0" 23 | "","T","2485","0","4282","1470","5752","0","0","0" 24 | "6","ALL GROUPS","","","","","","","","" 25 | "","I","94185","0","67065","17355","84420","0","0","0" 26 | "","UI","25275","0","9756","15322","25078","0","0","0" 27 | "","T","119033","0","76821","32677","109498","0","0","0" 28 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/background_lines_2/background_lines_2-data-tabula.csv: -------------------------------------------------------------------------------- 1 | Sl.No,"SIZE GROUP (HA)","NO. OF HOLDINGS GROWING THE CROP TOTAL NO.NO. TREATED WITH THE MANURE",AREA UNDER THE CROP,"AREA UNDER THE CROP TREATED WITH THE MANURE",,,,, 2 | "",,"NO. TREATED WITH THE MANURE",HYV,OTHERS,TOTAL,HYV,OTHERS,TOTAL, 3 | "(1)",(2),(3),(4),(5),(6),(7),(8),(9),(10) 4 | 1,ARGINAL (BELOW 1.0),,,,,,,, 5 | "","I UI T",39053,0,12142,332,15464,0,0,0 6 | "",7429,0,2088,1560,3648,0,0,0, 7 | "",46484,0,14230,488,19112,0,0,0, 8 | 2,MALL (1.0 - 1.99),,,,,,,, 9 | "","I UI T",20341,0,16685,163,18316,0,0,0 10 | "",6854,0,4594,1885,6479,0,0,0, 11 | "",27197,0,21279,351,24795,0,0,0, 12 | 3,EMI-MEDIUM (2.0 - 3.99),,,,,,,, 13 | "","I UI T",20800,0,16991,764,24634,0,0,0 14 | "",5856,0,1017,4819,5836,0,0,0, 15 | "",26555,0,18008,1246,30470,0,0,0, 16 | 4,EDIUM (4.0 - 9.99),,,,,,,, 17 | "","I UI T",11986,0,17576,412,21696,0,0,0 18 | "",4615,0,1446,6227,7673,0,0,0, 19 | "",16312,0,19022,1034,29369,0,0,0, 20 | 5,ARGE (10 AND ABOVE),,,,,,,, 21 | "","I UI T",2005,0,3671,63,4310,0,0,0 22 | "",521,0,611,831,1442,0,0,0, 23 | "",2485,0,4282,147,5752,0,0,0, 24 | "",LL GROUPS,,,,,,,, 25 | "",94185,0,67065,1735,84420,0,0,0, 26 | 6,,,,,,,,, 27 | "NO. OF HOLDINGS GROWING THE CROP TOTAL NO.NO. TREATED WITH THE MANURE" 28 | "NO. TREATED WITH THE MANURE" 29 | 6 30 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/background_lines_2/background_lines_2-table-detection-camelot.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/background_lines_2/background_lines_2-table-detection-camelot.png -------------------------------------------------------------------------------- /docs/benchmark/lattice/background_lines_2/background_lines_2-table-detection-tabula.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/background_lines_2/background_lines_2-table-detection-tabula.png -------------------------------------------------------------------------------- /docs/benchmark/lattice/background_lines_2/background_lines_2.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/background_lines_2/background_lines_2.pdf -------------------------------------------------------------------------------- /docs/benchmark/lattice/column_span_1/column_span_1-data-camelot-page-1-table-1.csv: -------------------------------------------------------------------------------- 1 | "Sl. No.","Year","Population (in Lakh)","Accidental Deaths","","Suicides","","Percentage Population growth" 2 | "","","","Incidence","Rate","Incidence","Rate","" 3 | "(1)","(2)","(3)","(4)","(5)","(6)","(7)","(8)" 4 | "1.","1967","4999","126762","25.4","38829","7.8","2.2" 5 | "2.","1968","5111","126232","24.7","40688","8.0","2.2" 6 | "3.","1969","5225","130755","25.0","43633","8.4","2.2" 7 | "4.","1970","5343","139752","26.2","48428","9.1","2.3" 8 | "5.","1971","5512","105601","19.2","43675","7.9","3.2" 9 | "6.","1972","5635","106184","18.8","43601","7.7","2.2" 10 | "7.","1973","5759","130654","22.7","40807","7.1","2.2" 11 | "8.","1974","5883","110624","18.8","46008","7.8","2.2" 12 | "9.","1975","6008","113016","18.8","42890","7.1","2.1" 13 | "10.","1976","6136","111611","18.2","41415","6.7","2.1" 14 | "11.","1977","6258","117338","18.8","39718","6.3","2.0" 15 | "12.","1978","6384","118594","18.6","40207","6.3","2.0" 16 | "13.","1979","6510","108987","16.7","38217","5.9","2.0" 17 | "14.","1980","6636","116912","17.6","41663","6.3","1.9" 18 | "15.","1981","6840","122221","17.9","40245","5.9","3.1" 19 | "16.","1982","7052","125993","17.9","44732","6.3","3.1" 20 | "17.","1983","7204","128576","17.8","46579","6.5","2.2" 21 | "18.","1984","7356","134628","18.3","50571","6.9","2.1" 22 | "19.","1985","7509","139657","18.6","52811","7.0","2.1" 23 | "20.","1986","7661","147023","19.2","54357","7.1","2.0" 24 | "21.","1987","7814","152314","19.5","58568","7.5","2.0" 25 | "22.","1988","7966","163522","20.5","64270","8.1","1.9" 26 | "23.","1989","8118","169066","20.8","68744","8.5","1.9" 27 | "24.","1990","8270","174401","21.1","73911","8.9","1.9" 28 | "25.","1991","8496","188003","22.1","78450","9.2","2.7" 29 | "26.","1992","8677","194910","22.5","80149","9.2","2.1" 30 | "27.","1993","8838","192357","21.8","84244","9.5","1.9" 31 | "28.","1994","8997","190435","21.2","89195","9.9","1.8" 32 | "29.","1995","9160","222487","24.3","89178","9.7","1.8" 33 | "30.","1996","9319","220094","23.6","88241","9.5","1.7" 34 | "31.","1997","9552","233903","24.5","95829","10.0","2.5" 35 | "32.","1998","9709","258409","26.6","104713","10.8","1.6" 36 | "33.","1999","9866","271918","27.6","110587","11.2","1.6" 37 | "34.","2000","10021","255883","25.5","108593","10.8","1.6" 38 | "35.","2001","10270","271019","26.4","108506","10.6","2.5" 39 | "36.","2002","10506","260122","24.8","110417","10.5","2.3" 40 | "37.","2003","10682","259625","24.3","110851","10.4","1.7" 41 | "38.","2004","10856","277263","25.5","113697","10.5","1.6" 42 | "39.","2005","11028","294175","26.7","113914","10.3","1.6" 43 | "40.","2006","11198","314704","28.1","118112","10.5","1.5" 44 | "41.","2007","11366","340794","30.0","122637","10.8","1.5" 45 | "42.","2008","11531","342309","29.7","125017","10.8","1.4" 46 | "43.","2009","11694","357021","30.5","127151","10.9","1.4" 47 | "44.","2010","11858","384649","32.4","134599","11.4","1.4" 48 | "45.","2011","12102","390884","32.3","135585","11.2","2.1" 49 | "46.","2012","12134","394982","32.6","135445","11.2","1.0" 50 | "47.","2013","12288","400517","32.6","134799","11.0","1.0" 51 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/column_span_1/column_span_1-data-pdfplumber.csv: -------------------------------------------------------------------------------- 1 | "0","1","2","3","4","5","6","7" 2 | "Rate of Accidental Deaths & Suicides and Population Growth During 1967 to 2013","","","","","","","" 3 | "Sl. 4 | No.","Year","Population 5 | (in Lakh)","Accidental Deaths","","Suicides","","Percentage 6 | Population 7 | growth" 8 | "","","","Incidence","Rate","Incidence","Rate","" 9 | "(1)","(2)","(3)","(4)","(5)","(6)","(7)","(8)" 10 | "1.","1967","4999","126762","25.4","38829","7.8","2.2" 11 | "2.","1968","5111","126232","24.7","40688","8.0","2.2" 12 | "3.","1969","5225","130755","25.0","43633","8.4","2.2" 13 | "4.","1970","5343","139752","26.2","48428","9.1","2.3" 14 | "5.","1971","5512","105601","19.2","43675","7.9","3.2" 15 | "6.","1972","5635","106184","18.8","43601","7.7","2.2" 16 | "7.","1973","5759","130654","22.7","40807","7.1","2.2" 17 | "8.","1974","5883","110624","18.8","46008","7.8","2.2" 18 | "9.","1975","6008","113016","18.8","42890","7.1","2.1" 19 | "10.","1976","6136","111611","18.2","41415","6.7","2.1" 20 | "11.","1977","6258","117338","18.8","39718","6.3","2.0" 21 | "12.","1978","6384","118594","18.6","40207","6.3","2.0" 22 | "13.","1979","6510","108987","16.7","38217","5.9","2.0" 23 | "14.","1980","6636","116912","17.6","41663","6.3","1.9" 24 | "15.","1981","6840","122221","17.9","40245","5.9","3.1" 25 | "16.","1982","7052","125993","17.9","44732","6.3","3.1" 26 | "17.","1983","7204","128576","17.8","46579","6.5","2.2" 27 | "18.","1984","7356","134628","18.3","50571","6.9","2.1" 28 | "19.","1985","7509","139657","18.6","52811","7.0","2.1" 29 | "20.","1986","7661","147023","19.2","54357","7.1","2.0" 30 | "21.","1987","7814","152314","19.5","58568","7.5","2.0" 31 | "22.","1988","7966","163522","20.5","64270","8.1","1.9" 32 | "23.","1989","8118","169066","20.8","68744","8.5","1.9" 33 | "24.","1990","8270","174401","21.1","73911","8.9","1.9" 34 | "25.","1991","8496","188003","22.1","78450","9.2","2.7" 35 | "26.","1992","8677","194910","22.5","80149","9.2","2.1" 36 | "27.","1993","8838","192357","21.8","84244","9.5","1.9" 37 | "28.","1994","8997","190435","21.2","89195","9.9","1.8" 38 | "29.","1995","9160","222487","24.3","89178","9.7","1.8" 39 | "30.","1996","9319","220094","23.6","88241","9.5","1.7" 40 | "31.","1997","9552","233903","24.5","95829","10.0","2.5" 41 | "32.","1998","9709","258409","26.6","104713","10.8","1.6" 42 | "33.","1999","9866","271918","27.6","110587","11.2","1.6" 43 | "34.","2000","10021","255883","25.5","108593","10.8","1.6" 44 | "35.","2001","10270","271019","26.4","108506","10.6","2.5" 45 | "36.","2002","10506","260122","24.8","110417","10.5","2.3" 46 | "37.","2003","10682","259625","24.3","110851","10.4","1.7" 47 | "38.","2004","10856","277263","25.5","113697","10.5","1.6" 48 | "39.","2005","11028","294175","26.7","113914","10.3","1.6" 49 | "40.","2006","11198","314704","28.1","118112","10.5","1.5" 50 | "41.","2007","11366","340794","30.0","122637","10.8","1.5" 51 | "42.","2008","11531","342309","29.7","125017","10.8","1.4" 52 | "43.","2009","11694","357021","30.5","127151","10.9","1.4" 53 | "44.","2010","11858","384649","32.4","134599","11.4","1.4" 54 | "45.","2011","12102","390884","32.3","135585","11.2","2.1" 55 | "46.","2012","12134","394982","32.6","135445","11.2","1.0" 56 | "47.","2013","12288","400517","32.6","134799","11.0","1.0" 57 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/column_span_1/column_span_1-data-pdftables-page-1-table-1.csv: -------------------------------------------------------------------------------- 1 | "0","1" 2 | "","" 3 | "","RateofAccidentalDeaths&SuicidesandPopulationGrowthDuring1967to2013" 4 | ""," 5 | AccidentalDeathsSuicidesPercentageSl.Population 6 | Year 7 | Percentage 8 | Percentage 9 | Porcentage 10 | Popentage 11 | Popuntage 12 | Populntage 13 | Populatage 14 | Populatage 15 | Populatige 16 | Populatioe 17 | PopulationNo.(inLakh) 18 | Incidence 19 | Rate 20 | IncidenceRate 21 | growth" 22 | "","(1)(2) 23 | (3)(4)(5) 24 | (6) 25 | (7) 26 | (8)" 27 | "","1.1967499912676225.4388297.82.2" 28 | "","2. 29 | 1968511112623224.7406888.02.2" 30 | "","3.1969522513075525.0436338.42.2" 31 | "","4.1970534313975226.2484289.12.3" 32 | "","5.1971551210560119.2436757.93.2" 33 | "","6.1972563510618418.8436017.72.2" 34 | "","7.1973575913065422.7408077.12.2" 35 | "","8.1974588311062418.8460087.82.2" 36 | "","9.1975600811301618.8428907.12.1" 37 | "","10.1976613611161118.2414156.72.1" 38 | "","11.1977625811733818.8397186.32.0" 39 | "","12.1978638411859418.6402076.32.0" 40 | "","13.1979651010898716.7382175.92.0" 41 | "","14.1980663611691217.6416636.31.9" 42 | "","15.1981684012222117.9402455.93.1" 43 | "","16.1982705212599317.9447326.33.1" 44 | "","17.1983720412857617.8465796.52.2" 45 | "","18.1984735613462818.3505716.92.1" 46 | "","19.1985750913965718.6528117.02.1" 47 | "","20.1986766114702319.2543577.12.0" 48 | "","21.1987781415231419.5585687.52.0" 49 | "","22.1988796616352220.5642708.11.9" 50 | "","23.1989811816906620.8687448.51.9" 51 | "","24.1990827017440121.1739118.91.9" 52 | "","25.1991849618800322.1784509.22.7" 53 | "","26.1992867719491022.5801499.22.1" 54 | "","27.1993883819235721.8842449.51.9" 55 | "","28.1994899719043521.2891959.91.8" 56 | "","29.1995916022248724.3891789.71.8" 57 | "","30.1996931922009423.6882419.51.7" 58 | "","31.1997955223390324.59582910.02.5" 59 | "","32.1998970925840926.610471310.81.6" 60 | "","33.1999986627191827.611058711.21.6" 61 | "","34.20001002125588325.510859310.81.6" 62 | "","35.20011027027101926.410850610.62.5" 63 | "","36.20021050626012224.811041710.52.3" 64 | "","37.20031068225962524.311085110.41.7" 65 | "","38.20041085627726325.511369710.51.6" 66 | "","39.20051102829417526.711391410.31.6" 67 | "","40.20061119831470428.111811210.51.5" 68 | "","41.20071136634079430.012263710.81.5" 69 | "","42.20081153134230929.712501710.81.4" 70 | "","43.20091169435702130.512715110.91.4" 71 | "","44.20101185838464932.413459911.41.4" 72 | "","45.20111210239088432.313558511.22.1 73 | " 74 | "","46.20121213439498232.613544511.21.0 75 | " 76 | "","47.20131228840051732.613479911.01.0 77 | 78 | (xx) 79 | " 80 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/column_span_1/column_span_1-data-tabula.csv: -------------------------------------------------------------------------------- 1 | Rate of Accidental Deaths & Suicides and Population Growth During 1967 to 2013,,,,,,, 2 | "Sl. No.",Year,"Population (in Lakh)",Accidental Deaths,Suicides,"Percentage Population growth",, 3 | "",,,Incidence,Rate,Incidence,Rate, 4 | "(1)",(2),(3),(4),(5),(6),(7),(8) 5 | 1.,1967,4999,126762,25.4,38829,7.8,2.2 6 | 2.,1968,5111,126232,24.7,40688,8.0,2.2 7 | 3.,1969,5225,130755,25.0,43633,8.4,2.2 8 | 4.,1970,5343,139752,26.2,48428,9.1,2.3 9 | 5.,1971,5512,105601,19.2,43675,7.9,3.2 10 | 6.,1972,5635,106184,18.8,43601,7.7,2.2 11 | 7.,1973,5759,130654,22.7,40807,7.1,2.2 12 | 8.,1974,5883,110624,18.8,46008,7.8,2.2 13 | 9.,1975,6008,113016,18.8,42890,7.1,2.1 14 | 10.,1976,6136,111611,18.2,41415,6.7,2.1 15 | 11.,1977,6258,117338,18.8,39718,6.3,2.0 16 | 12.,1978,6384,118594,18.6,40207,6.3,2.0 17 | 13.,1979,6510,108987,16.7,38217,5.9,2.0 18 | 14.,1980,6636,116912,17.6,41663,6.3,1.9 19 | 15.,1981,6840,122221,17.9,40245,5.9,3.1 20 | 16.,1982,7052,125993,17.9,44732,6.3,3.1 21 | 17.,1983,7204,128576,17.8,46579,6.5,2.2 22 | 18.,1984,7356,134628,18.3,50571,6.9,2.1 23 | 19.,1985,7509,139657,18.6,52811,7.0,2.1 24 | 20.,1986,7661,147023,19.2,54357,7.1,2.0 25 | 21.,1987,7814,152314,19.5,58568,7.5,2.0 26 | 22.,1988,7966,163522,20.5,64270,8.1,1.9 27 | 23.,1989,8118,169066,20.8,68744,8.5,1.9 28 | 24.,1990,8270,174401,21.1,73911,8.9,1.9 29 | 25.,1991,8496,188003,22.1,78450,9.2,2.7 30 | 26.,1992,8677,194910,22.5,80149,9.2,2.1 31 | 27.,1993,8838,192357,21.8,84244,9.5,1.9 32 | 28.,1994,8997,190435,21.2,89195,9.9,1.8 33 | 29.,1995,9160,222487,24.3,89178,9.7,1.8 34 | 30.,1996,9319,220094,23.6,88241,9.5,1.7 35 | 31.,1997,9552,233903,24.5,95829,10.0,2.5 36 | 32.,1998,9709,258409,26.6,104713,10.8,1.6 37 | 33.,1999,9866,271918,27.6,110587,11.2,1.6 38 | 34.,2000,10021,255883,25.5,108593,10.8,1.6 39 | 35.,2001,10270,271019,26.4,108506,10.6,2.5 40 | 36.,2002,10506,260122,24.8,110417,10.5,2.3 41 | 37.,2003,10682,259625,24.3,110851,10.4,1.7 42 | 38.,2004,10856,277263,25.5,113697,10.5,1.6 43 | 39.,2005,11028,294175,26.7,113914,10.3,1.6 44 | 40.,2006,11198,314704,28.1,118112,10.5,1.5 45 | 41.,2007,11366,340794,30.0,122637,10.8,1.5 46 | 42.,2008,11531,342309,29.7,125017,10.8,1.4 47 | 43.,2009,11694,357021,30.5,127151,10.9,1.4 48 | 44.,2010,11858,384649,32.4,134599,11.4,1.4 49 | 45.,2011,12102,390884,32.3,135585,11.2,2.1 50 | 46.,2012,12134,394982,32.6,135445,11.2,1.0 51 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/column_span_1/column_span_1-table-detection-camelot.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/column_span_1/column_span_1-table-detection-camelot.png -------------------------------------------------------------------------------- /docs/benchmark/lattice/column_span_1/column_span_1-table-detection-tabula.png: -------------------------------------------------------------------------------- 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Examination","","","","","","" 4 | "History of morbidity","","","","","","" 5 | "Diet survey","1200","All the individuals partaking meals in the HH","","","","" 6 | "Blood Pressure #","2400","Men (≥ 18yrs)","10%","95%","20%","1728" 7 | "","","Women (≥ 18 yrs)","","","","1728" 8 | "Fasting blood glucose","2400","Men (≥ 18 yrs)","5%","95%","20%","1825" 9 | "","","Women (≥ 18 yrs)","","","","1825" 10 | "Knowledge &Practices on HTN &DM","2400","Men (≥ 18 yrs)","-","-","-","1728" 11 | "","2400","Women (≥ 18 yrs)","-","-","-","1728" 12 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/column_span_2/column_span_2-data-tabula.csv: -------------------------------------------------------------------------------- 1 | Investigations,"No. of HHs","Age/Sex/ Physiological Group","Preva- lence",C.I*,"Relative Precision","Sample size per State" 2 | Anthropometry,2400,All the available individuals,,,, 3 | Clinical Examination,,,,,, 4 | History of morbidity,,,,,, 5 | Diet survey,1200,All the individuals partaking meals in the HH,,,, 6 | Blood Pressure #,2400,Men (≥ 18yrs),10%,95%,20%,1728 7 | "",,Women (≥ 18 yrs),1728,,, 8 | Fasting blood glucose,2400,Men (≥ 18 yrs),5%,95%,20%,1825 9 | "",Women (≥ 18 yrs),1825,,,, 10 | 2400,Men (≥ 18 yrs),-,-,-,1728, 11 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/column_span_2/column_span_2-table-detection-camelot.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/column_span_2/column_span_2-table-detection-camelot.png -------------------------------------------------------------------------------- /docs/benchmark/lattice/column_span_2/column_span_2-table-detection-tabula.png: -------------------------------------------------------------------------------- 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| 18 33 | "" 34 | "" 35 | "" 36 | 19 37 | 20 38 | 21 39 | "" 40 | "" 41 | "" 42 | 22 43 | 23 44 | 24 45 | "" 46 | "" 47 | "" 48 | 25 49 | 26 50 | 27 51 | "" 52 | "" 53 | "" 54 | 28 55 | 29 56 | 30 57 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/electoral_roll/electoral_roll-table-detection-camelot.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/electoral_roll/electoral_roll-table-detection-camelot.png -------------------------------------------------------------------------------- /docs/benchmark/lattice/electoral_roll/electoral_roll-table-detection-tabula.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/electoral_roll/electoral_roll-table-detection-tabula.png -------------------------------------------------------------------------------- /docs/benchmark/lattice/electoral_roll/electoral_roll.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/electoral_roll/electoral_roll.pdf -------------------------------------------------------------------------------- /docs/benchmark/lattice/rotated/rotated-data-camelot-page-1-table-1.csv: -------------------------------------------------------------------------------- 1 | "State","Nutritional Assessment (No. of individuals)","","","","IYCF Practices (No. of mothers: 2011-12)","Blood Pressure (No. of adults: 2011-12)","","Fasting Blood Sugar (No. of adults:2011-12)","" 2 | "","1975-79","1988-90","1996-97","2011-12","","Men","Women","Men","Women" 3 | "Kerala","5738","6633","8864","8297","245","2161","3195","1645","2391" 4 | "Tamil Nadu","7387","10217","5813","7851","413","2134","2858","1119","1739" 5 | "Karnataka","6453","8138","12606","8958","428","2467","2894","1628","2028" 6 | "Andhra Pradesh","5844","9920","9545","8300","557","1899","2493","1111","1529" 7 | "Maharashtra","5161","7796","6883","9525","467","2368","2648","1417","1599" 8 | "Gujarat","4403","5374","4866","9645","477","2687","3021","2122","2503" 9 | "Madhya Pradesh","*","*","*","7942","470","1965","2150","1579","1709" 10 | "Orissa","3756","5540","12024","8473","398","2040","2624","1093","1628" 11 | "West Bengal","*","*","*","8047","423","2058","2743","1413","2027" 12 | "Uttar Pradesh","*","*","*","9860","581","2139","2415","1185","1366" 13 | "Pooled","38742","53618","60601","86898","4459","21918","27041","14312","18519" 14 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/rotated/rotated-data-pdf-table-extract-page-1-table-1.csv: -------------------------------------------------------------------------------- 1 | "0","1","2","3","4","5","6","7","8","9","10","11","12","13","14" 2 | "Table 1 : STATE WISE COVERAGE PARTICULARS BY PERIOD OF SURVEY (Contd...)","Fasting Blood Sugar (No. of adults: 2011-12)","Women","2391","1739","2028","1529","1599","2503","1709","1628","2027","1366","18519","* Data not available NNMB 72 Rural-Third Repeat Survey 2011-12" 3 | "","","Men","1645","1119","1628","1111","1417","2122","1579","1093","1413","1185","14312","" 4 | "","Blood Pressure (No. of adults: 2011-12)","Women","3195","2858","2894","2493","2648","3021","2150","2624","2743","2415","27041","" 5 | "","","Men","2161","2134","2467","1899","2368","2687","1965","2040","2058","2139","21918","" 6 | "","IYCF Practices (No. of mothers: 2011-12)","","245","413","428","557","467","477","470","398","423","581","4459","" 7 | "","Nutritional Assessment (No. of individuals)","2011-12","8297","7851","8958","8300","9525","9645","7942","8473","8047","9860","86898","" 8 | "","","1996-97","8864","5813","12606","9545","6883","4866","*","12024","*","*","60601","" 9 | "","","1988-90","6633","10217","8138","9920","7796","5374","*","5540","*","*","53618","" 10 | "","","1975-79","5738","7387","6453","5844","5161","4403","*","3756","*","*","38742","" 11 | "","State","","Kerala","Tamil Nadu","Karnataka","Andhra Pradesh","Maharashtra","Gujarat","Madhya Pradesh","Orissa","West Bengal","Uttar Pradesh","Pooled","" 12 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/rotated/rotated-data-pdfplumber.csv: -------------------------------------------------------------------------------- 1 | "0","1","2" 2 | "","e 3 | bl 4 | a 5 | ail 6 | v 7 | a 8 | 9 | t 10 | o 11 | n 12 | 13 | a 14 | t 15 | a 16 | D 17 | 18 | *","" 19 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/rotated/rotated-data-pdftables-page-1-table-1.csv: -------------------------------------------------------------------------------- 1 | "0","1","2","3","4","5","6","7","8" 2 | "","","","","","","","","" 3 | "","Sugar 4 | Sugar 5 | Sugar 6 | Sugar 7 | Sugar 8 | ","adults:adults: 9 | adults: 10 | adults: 11 | adults: 12 | adults: 13 | adults: 14 | ","2011-12)2011-12) 15 | 2011-12) 16 | 2011-12) 17 | 2011-12) 18 | 2011-12) 19 | 2011-12) 20 | 2011-12) 21 | ","1645 22 | 1645 23 | 1645 24 | 1645","2894 25 | 2894 26 | 2894 27 | 2894","2493 28 | 2493 29 | 2493 30 | 2493","2687 31 | 2687 32 | 2687 33 | 2687","581 34 | 581581" 35 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/rotated/rotated-data-tabula.csv: -------------------------------------------------------------------------------- 1 | "State la il Nadu",,,T,ble,"1 : Nut (","TA itio o.","E al f in","IS ss ivi","CO ss ual","ER ent )",G,PA 2 | "",,,"197 57 73","-79 8 7","1 1","88-9 633 21",,"996 88 58","97 4 3",,"011 829 785",12 3 | "ataka hra Prad arashtra rat hya Pra",sh,,"64 58","3 4",,"138 920",,"126 95","6 5",,"895 830", 4 | "",es,,"44 *",3,,"374 *",,"48 *",6,,"964 794", 5 | "sa t Bengal r Pradesh led * Data not",vail,"37 * * 38 ble","6 42",5,"540 * * 61",,"120 * * 606","4 1",,"847 804 986 68",8, 6 | MB,,,,,,,,,,,, 7 | "",,,,,,,,,,,, 8 | "",,,,,,,,,,,, 9 | "",,,,,,,,,,,, 10 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/rotated/rotated-table-detection-camelot.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/rotated/rotated-table-detection-camelot.png -------------------------------------------------------------------------------- /docs/benchmark/lattice/rotated/rotated-table-detection-tabula.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/rotated/rotated-table-detection-tabula.png -------------------------------------------------------------------------------- /docs/benchmark/lattice/rotated/rotated.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/rotated/rotated.pdf -------------------------------------------------------------------------------- /docs/benchmark/lattice/row_span/row_span-data-camelot-page-1-table-1.csv: -------------------------------------------------------------------------------- 1 | "Plan Type","County","Plan Name","Totals" 2 | "GMC","Sacramento","Anthem Blue Cross","164,380" 3 | "","","Health Net","126,547" 4 | "","","Kaiser Foundation","74,620" 5 | "","","Molina Healthcare","59,989" 6 | "","San Diego","Care 1st Health Plan","71,831" 7 | "","","Community Health Group","264,639" 8 | "","","Health Net","72,404" 9 | "","","Kaiser","50,415" 10 | "","","Molina Healthcare","206,430" 11 | "","Total GMC Enrollment","","1,091,255" 12 | "COHS","Marin","Partnership Health Plan of CA","36,006" 13 | "","Mendocino","","37,243" 14 | "","Napa","","28,398" 15 | "","Solano","","113,220" 16 | "","Sonoma","","112,271" 17 | "","Yolo","","52,674" 18 | "","Del Norte","","11,242" 19 | "","Humboldt","","49,911" 20 | "","Lake","","29,149" 21 | "","Lassen","","7,360" 22 | "","Modoc","","2,940" 23 | "","Shasta","","61,763" 24 | "","Siskiyou","","16,715" 25 | "","Trinity","","4,542" 26 | "","Merced","Central California Alliance for Health","123,907" 27 | "","Monterey","","147,397" 28 | "","Santa Cruz","","69,458" 29 | "","Santa Barbara","CenCal","117,609" 30 | "","San Luis Obispo","","55,761" 31 | "","Orange","CalOptima","783,079" 32 | "","San Mateo","Health Plan of San Mateo","113,202" 33 | "","Ventura","Gold Coast Health Plan","202,217" 34 | "","Total COHS Enrollment","","2,176,064" 35 | "Subtotal for Two-Plan, Regional Model, GMC and COHS","","","10,132,022" 36 | "PCCM","Los Angeles","AIDS Healthcare Foundation","828" 37 | "","San Francisco","Family Mosaic","25" 38 | "","Total PHP Enrollment","","853" 39 | "All Models Total Enrollments","","","10,132,875" 40 | "Source: Data Warehouse 12/14/15","","","" 41 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/row_span/row_span-data-tabula.csv: -------------------------------------------------------------------------------- 1 | Plan Type,County,Plan Name,Totals 2 | GMC,Sacramento,Anthem Blue Cross,"164,380" 3 | "",,Health Net,"126,547" 4 | "",,Kaiser Foundation,"74,620" 5 | "",,Molina Healthcare,"59,989" 6 | "",San Diego,Care 1st Health Plan,"71,831" 7 | "",,Community Health Group,"264,639" 8 | "",,Health Net,"72,404" 9 | "",,Kaiser,"50,415" 10 | "",,Molina Healthcare,"206,430" 11 | "",Total GMC Enrollment,"1,091,255", 12 | COHS,Marin,Partnership Health Plan of CA,"36,006" 13 | "",Mendocino,"37,243", 14 | "",Napa,"28,398", 15 | "",Solano,"113,220", 16 | "",Sonoma,"112,271", 17 | "",Yolo,"52,674", 18 | "",Del Norte,"11,242", 19 | "",Humboldt,"49,911", 20 | "",Lake,"29,149", 21 | "",Lassen,"7,360", 22 | "",Modoc,"2,940", 23 | "",Shasta,"61,763", 24 | "",Siskiyou,"16,715", 25 | "",Trinity,"4,542", 26 | "",Merced,Central California Alliance for Health,"123,907" 27 | "",Monterey,"147,397", 28 | "",Santa Cruz,"69,458", 29 | "",Santa Barbara,CenCal,"117,609" 30 | "",San Luis Obispo,"55,761", 31 | "",Orange,CalOptima,"783,079" 32 | "",San Mateo,Health Plan of San Mateo,"113,202" 33 | "",Ventura,Gold Coast Health Plan,"202,217" 34 | "",Total COHS Enrollment,"2,176,064", 35 | "Subtotal for Two-Plan, Regional Model, GMC and COHS","10,132,022",, 36 | PCCM,Los Angeles,AIDS Healthcare Foundation,828 37 | San Francisco,Family Mosaic,25, 38 | Total PHP Enrollment,853,, 39 | All Models Total Enrollments,"10,132,875",, 40 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/row_span/row_span-table-detection-camelot.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/row_span/row_span-table-detection-camelot.png -------------------------------------------------------------------------------- /docs/benchmark/lattice/row_span/row_span-table-detection-tabula.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/row_span/row_span-table-detection-tabula.png -------------------------------------------------------------------------------- /docs/benchmark/lattice/row_span/row_span.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/row_span/row_span.pdf -------------------------------------------------------------------------------- /docs/benchmark/lattice/twotables_1/twotables_1-data-camelot-page-1-table-1.csv: -------------------------------------------------------------------------------- 1 | "Sl. No.","Name of State/UT","Name of District","Disease/ Illness","No. of Cases","No. of Deaths","Date of start of outbreak","Date of reporting","Current Status","Comments/ Action taken" 2 | "","West Bengal","Bankura","xix. Acute Diarrhoeal Disease","46","0","10/11/13","15/11/13","Under Control","Cases of loose motion and vomiting reported from Village Daldali, SC Binodnagar, Block Onda, District Bankura. District RRT and Block health team investigated the outbreak. Active search for cases done. Cases treated at local health centre. 2 stool samples collected were negative for cholera culture. Out of 3 water samples collected 1 sample was non potable. Chlorination of water sources done. Health education given regarding safe drinking water and sanitation." 3 | "","","","xx. Acute Diarrhoeal Disease","34","0","10/11/13","14/11/13","Under Control","Cases of loose motion and vomiting reported from Village Icharia, SC Mankhamar, Block Onda, District Bankura. District RRT and Block health team investigated the outbreak. House to house survey done. All cases treated locally. 4 stool samples collected were negative for cholera culture. Out of 34 water samples collected, 8 samples were non potable. Chlorination of water sources done. Health education given regarding safe drinking water and sanitation." 4 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/twotables_1/twotables_1-data-camelot-page-1-table-2.csv: -------------------------------------------------------------------------------- 1 | "DISEASE OUTBREAKS OF PREVIOUS WEEKS REPORTED LATE","","","","","","","","" 2 | "Sl. No","Name of State/UT","Name of District","Disease/ Illness","Cases","Deaths","Date of start of outbreak","Current Status","Comments/ Action taken" 3 | "1","Bihar","Madhubani","xxi. Acute Diarrhoeal Disease","69","0","30/09/13","Under Control","Cases of diarrhoea and vomiting reported from Village Indra Mandal tola, SC Sugapatti, PHC Phulparas, District Madhubani. District RRT investigated the outbreak. House to house survey done. Medical camp organized. Symptomatic treatement given to cases. ORS packets and halogen tablets distributed in the community. Chlorination of water sources done. IEC done regarding safe drinking water and sanitation." 4 | "","","Madhubani","xxii. Acute Diarrhoeal Disease","30","1","28/10/13","Under Control","Cases of diarrhoea and vomiting reported from Village/SC Rupauli, PHC Jhanjharpur, District Madhubani. District RRT and Block health team investigated the outbreak. Active search for cases done. Medical camp organized. All cases treated. One death occurred in 14yr old female child. ORS packets and halogen tablets distributed. Chlorination of water sources done. IEC activity regarding safe drinking water done." 5 | "","","Katihar","xxiii. Acute Diarrhoeal Disease","13","3","24/10/13","Under control","Cases of diarrhoea reported from Village Ahuta, Alipur, SC Lachhor, PHC/Block Balrampur, District Katihar. District RRT investigated the outbreak. House to house survey done. Cases occurred in a Adiwasi community. 3 deaths occurred in 45yr, 35yr and 5yr old male. Temporary medical camps organized. All cases treated symptomatically. Chlorination of water sources done. Health education given." 6 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/twotables_1/twotables_1-data-pdf-table-extract-page-1-table-1.csv: -------------------------------------------------------------------------------- 1 | "0" 2 | "Sl. Name of Name of District Disease/ Illness No. No. of Date of Date of Current Comments/ Action taken No. State/UT of Deaths start of reporting Status Cases outbreak Cases of loose motion and vomiting reported from Village Under Daldali, SC Binodnagar, Block Onda, District Bankura. District xix. Acute Control RRT and Block health team investigated the outbreak. Active search for cases done. Cases treated at local health centre. 2 stool Diarrhoeal 46 0 10/11/13 15/11/13 samples collected were negative for cholera culture. Out of 3 Disease water samples collected 1 sample was non potable. Chlorination of water sources done. Health education given regarding safe Bankura West Bengal drinking water and sanitation. Cases of loose motion and vomiting reported from Village Under Icharia, SC Mankhamar, Block Onda, District Bankura. District xx. Acute Control RRT and Block health team investigated the outbreak. House to 34 0 10/11/13 14/11/13 house survey done. All cases treated locally. 4 stool samples Diarrhoeal collected were negative for cholera culture. Out of 34 water Disease samples collected, 8 samples were non potable. Chlorination of water sources done. Health education given regarding safe drinking water and sanitation. DISEASE OUTBREAKS OF PREVIOUS WEEKS REPORTED LATE Sl. Name of Name of District Disease/ Illness Cases Deaths Date of Current Comments/ Action taken No State/UT start of Status outbreak Cases of diarrhoea and vomiting reported from Village Indra Mandal tola, SC Sugapatti, PHC Phulparas, District Madhubani. District RRT investigated the xxi. Acute Under outbreak. House to house survey done. Medical camp organized. Madhubani Diarrhoeal 69 0 30/09/13 Control Symptomatic treatement given to cases. ORS packets and halogen tablets Disease distributed in the community. Chlorination of water sources done. IEC done regarding safe drinking water and sanitation. Cases of diarrhoea and vomiting reported from Village/SC Rupauli, PHC Jhanjharpur, District Madhubani. District RRT and Block health team xxii. Acute Under investigated the outbreak. Active search for cases done. Medical camp 1 Bihar Madhubani Diarrhoeal 30 1 28/10/13 Control organized. All cases treated. One death occurred in 14yr old female child. Disease ORS packets and halogen tablets distributed. Chlorination of water sources done. IEC activity regarding safe drinking water done. Cases of diarrhoea reported from Village Ahuta, Alipur, SC Lachhor, PHC/Block Balrampur, District Katihar. District RRT investigated the xxiii. Acute Under outbreak. House to house survey done. Cases occurred in a Adiwasi Katihar Diarrhoeal 13 3 24/10/13 control community. 3 deaths occurred in 45yr, 35yr and 5yr old male. Temporary Disease medical camps organized. All cases treated symptomatically. Chlorination of water sources done. Health education given." 3 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/twotables_1/twotables_1-data-pdfplumber.csv: -------------------------------------------------------------------------------- 1 | "0" 2 | "Sl." 3 | "No." 4 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/twotables_1/twotables_1-table-detection-camelot.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/twotables_1/twotables_1-table-detection-camelot.png -------------------------------------------------------------------------------- /docs/benchmark/lattice/twotables_1/twotables_1-table-detection-tabula.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/twotables_1/twotables_1-table-detection-tabula.png -------------------------------------------------------------------------------- /docs/benchmark/lattice/twotables_1/twotables_1.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/twotables_1/twotables_1.pdf -------------------------------------------------------------------------------- /docs/benchmark/lattice/twotables_2/twotables_2-data-camelot-page-1-table-1.csv: -------------------------------------------------------------------------------- 1 | "State","n","Literacy Status","","","","","" 2 | "","","Illiterate","Read & Write","1-4 std.","5-8 std.","9-12 std.","College" 3 | "Kerala","2400","7.2","0.5","25.3","20.1","41.5","5.5" 4 | "Tamil Nadu","2400","21.4","2.3","8.8","35.5","25.8","6.2" 5 | "Karnataka","2399","37.4","2.8","12.5","18.3","23.1","5.8" 6 | "Andhra Pradesh","2400","54.0","1.7","8.4","13.2","18.8","3.9" 7 | "Maharashtra","2400","22.0","0.9","17.3","20.3","32.6","7.0" 8 | "Gujarat","2390","28.6","0.1","14.4","23.1","26.9","6.8" 9 | "Madhya Pradesh","2402","29.1","3.4","8.5","35.1","13.3","10.6" 10 | "Orissa","2405","33.2","1.0","10.4","25.7","21.2","8.5" 11 | "West Bengal","2293","41.7","4.4","13.2","17.1","21.2","2.4" 12 | "Uttar Pradesh","2400","35.3","2.1","4.5","23.3","27.1","7.6" 13 | "Pooled","23889","30.9","1.9","12.3","23.2","25.2","6.4" 14 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/twotables_2/twotables_2-data-camelot-page-1-table-2.csv: -------------------------------------------------------------------------------- 1 | "State","n","Literacy Status","","","","","" 2 | "","","Illiterate","Read & Write","1-4 std.","5-8 std.","9-12 std.","College" 3 | "Kerala","2400","8.8","0.3","20.1","17.0","45.6","8.2" 4 | "Tamil Nadu","2400","29.9","1.5","8.5","33.1","22.3","4.8" 5 | "Karnataka","2399","47.9","2.5","10.2","18.8","18.4","2.3" 6 | "Andhra Pradesh","2400","66.4","0.7","6.8","12.9","11.4","1.8" 7 | "Maharashtra","2400","41.3","0.6","14.1","20.1","21.6","2.2" 8 | "Gujarat","2390","57.6","0.1","10.3","16.5","12.9","2.7" 9 | "Madhya Pradesh","2402","58.7","2.2","6.6","24.1","5.3","3.0" 10 | "Orissa","2405","50.0","0.9","8.1","21.9","15.1","4.0" 11 | "West Bengal","2293","49.1","4.8","11.2","16.8","17.1","1.1" 12 | "Uttar Pradesh","2400","67.3","2.0","3.1","17.2","7.7","2.7" 13 | "Pooled","23889","47.7","1.5","9.9","19.9","17.8","3.3" 14 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/twotables_2/twotables_2-data-pdf-table-extract-page-1-table-1.csv: -------------------------------------------------------------------------------- 1 | "0","1","2","3","4","5","6","7","8","9" 2 | "Table 6 : DISTRIBUTION (%) OF HOUSEHOLDS BY LITERACY STATUS OF MALE HEAD OF THE HOUSEHOLD","","","","","","","","","" 3 | "NN","State","n","Literacy Status","","","","","","2" 4 | "","","","Illiterate","Read & Write 0.5","1-4 std. 25.3","5-8 std. 20.1","9-12 std. 41.5","College 5.5","" 5 | "","Kerala","2400","7.2","","","","","","" 6 | "","Tamil Nadu","2400","21.4","2.3","8.8","35.5","25.8","6.2","" 7 | "","Karnataka","2399","37.4","2.8","12.5","18.3","23.1","5.8","" 8 | "","Andhra Pradesh","2400","54.0","1.7","8.4","13.2","18.8","3.9","" 9 | "","Maharashtra","2400","22.0","0.9","17.3","20.3","32.6","7.0","" 10 | "","Gujarat","2390","28.6","0.1","14.4","23.1","26.9","6.8","" 11 | "","Madhya Pradesh","2402","29.1","3.4","8.5","35.1","13.3","10.6","" 12 | "","Orissa","2405","33.2","1.0","10.4","25.7","21.2","8.5","" 13 | "","West Bengal","2293","41.7","4.4","13.2","17.1","21.2","2.4","" 14 | "","Uttar Pradesh","2400","35.3","2.1","4.5","23.3","27.1","7.6","" 15 | "","Pooled","23889","30.9","1.9","12.3","23.2","25.2","6.4","" 16 | "","Table 7 : DISTRIBUTION (%) OF HOUSEHOLDS BY LITERACY STATUS OF ADULT WOMEN","","","","","","","","" 17 | "","State","n","Literacy Status","","","","","","" 18 | "","","","Illiterate","Read & Write 0.3","1-4 std. 20.1","5-8 std. 17.0","9-12 std. 45.6","College 8.2","" 19 | "","Kerala","2400","8.8","","","","","","" 20 | "","Tamil Nadu","2400","29.9","1.5","8.5","33.1","22.3","4.8","" 21 | "","Karnataka","2399","47.9","2.5","10.2","18.8","18.4","2.3","" 22 | "","Andhra Pradesh","2400","66.4","0.7","6.8","12.9","11.4","1.8","" 23 | "","Maharashtra","2400","41.3","0.6","14.1","20.1","21.6","2.2","" 24 | "","Gujarat","2390","57.6","0.1","10.3","16.5","12.9","2.7","" 25 | "","Madhya Pradesh","2402","58.7","2.2","6.6","24.1","5.3","3.0","" 26 | "","Orissa","2405","50.0","0.9","8.1","21.9","15.1","4.0","" 27 | "","West Bengal","2293","49.1","4.8","11.2","16.8","17.1","1.1","" 28 | "","Uttar Pradesh","2400","67.3","2.0","3.1","17.2","7.7","2.7","" 29 | "","Pooled","23889","47.7","1.5","9.9","19.9","17.8","3.3","" 30 | "","NMB 75 Rural-Third Repeat Survey 2011-12","","","","","","","","" 31 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/twotables_2/twotables_2-data-pdfplumber.csv: -------------------------------------------------------------------------------- 1 | "0" 2 | "Table 6 : DISTRIBUTION (%) OF HOUSEHOLDS BY LITERACY STATUS OF" 3 | "MALE HEAD OF THE HOUSEHOLD" 4 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/twotables_2/twotables_2-data-pdftables-page-1-table-1.csv: -------------------------------------------------------------------------------- 1 | "0","1" 2 | "","" 3 | "","Table6:DISTRIBUTION(%)OFHOUSEHOLDSBYLITERACYSTATUSOF 4 | " 5 | "","MALEHEADOFTHEHOUSEHOLD 6 | " 7 | "","LiteracyStatus 8 | " 9 | "","State 10 | nRead&IlliterateRead &1-4std.5-8std.9-12std.CollegeWrite" 11 | "","Kerala24007.20.525.320.141.55.5 12 | " 13 | "","TamilNadu240021.42.38.835.525.86.2" 14 | "","Karnataka239937.42.812.518.323.15.8" 15 | "","AndhraPradesh240054.01.78.413.218.83.9" 16 | "","Maharashtra240022.00.917.320.332.67.0" 17 | "","Gujarat239028.60.114.423.126.96.8" 18 | "","MadhyaPradesh240229.13.48.535.113.310.6" 19 | "","Orissa240533.21.010.425.721.28.5" 20 | "","WestBengal229341.74.413.217.121.22.4" 21 | "","UttarPradesh240035.32.14.523.327.17.6" 22 | "","Pooled2388930.91.912.323.225.26.4" 23 | "","Table7:DISTRIBUTION(%)OFHOUSEHOLDSBYLITERACYSTATUSOF" 24 | "","ADULTWOMEN" 25 | "","LiteracyStatus" 26 | "","StatenRead&IlliterateRead &1-4std.5-8std.9-12std.CollegeWrite" 27 | "","Kerala24008.80.320.117.045.68.2" 28 | "","TamilNadu240029.91.58.533.122.34.8" 29 | "","Karnataka239947.92.510.218.818.42.3" 30 | "","AndhraPradesh240066.40.76.812.911.41.8" 31 | "","Maharashtra240041.30.614.120.121.62.2" 32 | "","Gujarat239057.60.110.316.512.92.7" 33 | "","MadhyaPradesh240258.72.26.624.15.33.0" 34 | "","Orissa240550.00.98.121.915.14.0" 35 | "","WestBengal229349.14.811.216.817.11.1" 36 | "","UttarPradesh240067.32.03.117.27.72.7" 37 | "","Pooled2388947.71.59.919.917.83.3" 38 | ""," 39 | NNMB75Rural-ThirdRepeatSurvey2011-12" 40 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/twotables_2/twotables_2-table-detection-camelot.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/twotables_2/twotables_2-table-detection-camelot.png -------------------------------------------------------------------------------- /docs/benchmark/lattice/twotables_2/twotables_2-table-detection-tabula.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/twotables_2/twotables_2-table-detection-tabula.png -------------------------------------------------------------------------------- /docs/benchmark/lattice/twotables_2/twotables_2-tabula-0.csv: -------------------------------------------------------------------------------- 1 | "",,,Literacy Status, 2 | State,n,Read & Illiterate CollegeWrite,1-4 std. 5-8 std. 9-12 std., 3 | Kerala,2400,7.2 0.5,25.3 20.1 41.5,5.5 4 | Tamil Nadu,2400,21.4 2.3,8.8 35.5 25.8,6.2 5 | Karnataka,2399,37.4 2.8,12.5 18.3 23.1,5.8 6 | Andhra Pradesh,2400,54.0 1.7,8.4 13.2 18.8,3.9 7 | Maharashtra,2400,22.0 0.9,17.3 20.3 32.6,7.0 8 | Gujarat,2390,28.6 0.1,14.4 23.1 26.9,6.8 9 | Madhya Pradesh,2402,29.1 3.4,8.5 35.1 13.3,10.6 10 | Orissa,2405,33.2 1.0,10.4 25.7 21.2,8.5 11 | West Bengal,2293,41.7 4.4,13.2 17.1 21.2,2.4 12 | Uttar Pradesh,2400,35.3 2.1,4.5 23.3 27.1,7.6 13 | Pooled,23889,30.9 1.9,12.3 23.2 25.2,6.4 14 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/twotables_2/twotables_2-tabula-1.csv: -------------------------------------------------------------------------------- 1 | "",,,Literacy Status, 2 | State,n,Read & Illiterate CollegeWrite,1-4 std. 5-8 std. 9-12 std., 3 | Kerala,2400,8.8 0.3,20.1 17.0 45.6,8.2 4 | Tamil Nadu,2400,29.9 1.5,8.5 33.1 22.3,4.8 5 | Karnataka,2399,47.9 2.5,10.2 18.8 18.4,2.3 6 | Andhra Pradesh,2400,66.4 0.7,6.8 12.9 11.4,1.8 7 | Maharashtra,2400,41.3 0.6,14.1 20.1 21.6,2.2 8 | Gujarat,2390,57.6 0.1,10.3 16.5 12.9,2.7 9 | Madhya Pradesh,2402,58.7 2.2,6.6 24.1 5.3,3.0 10 | Orissa,2405,50.0 0.9,8.1 21.9 15.1,4.0 11 | West Bengal,2293,49.1 4.8,11.2 16.8 17.1,1.1 12 | Uttar Pradesh,2400,67.3 2.0,3.1 17.2 7.7,2.7 13 | Pooled,23889,47.7 1.5,9.9 19.9 17.8,3.3 14 | -------------------------------------------------------------------------------- /docs/benchmark/lattice/twotables_2/twotables_2.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/lattice/twotables_2/twotables_2.pdf -------------------------------------------------------------------------------- /docs/benchmark/stream/12s0324/12s0324.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/stream/12s0324/12s0324.pdf -------------------------------------------------------------------------------- /docs/benchmark/stream/birdisland/birdisland-data-tabula.csv: -------------------------------------------------------------------------------- 1 | Kruger,K2-1901,RR2Y,1.9,R,"Ac,PV",56.4,7.6,0,126.3,$846 2 | Stine,19RA02 §,RR2Y,1.9,R,CMB,55.3,7.6,0,120.0,$830 3 | Wensman,W 3190NR2,RR2Y,1.9,R,Ac,54.5,7.6,0,119.5,$818 4 | Hefty,H17Y12,RR2Y,1.7,MR,I,53.7,7.7,0,124.4,$806 5 | Dyna-Gro,S15RY53,RR2Y,1.5,R,Ac,53.6,7.7,0,126.8,$804 6 | LG Seeds,C2050R2,RR2Y,2.1,R,Ac,53.6,7.7,0,123.9,$804 7 | Titan Pro,19M42,RR2Y,1.9,R,CMB,53.6,7.7,0,121.0,$804 8 | Stine,19RA02 (2) §,RR2Y,1.9,R,CMB,53.4,7.7,0,123.9,$801 9 | Asgrow,AG1832 §,RR2Y,1.8,MR,"Ac,PV",52.9,7.7,0,122.0,$794 10 | Prairie Brand,PB-1566R2,RR2Y,1.5,R,CMB,52.8,7.7,0,122.9,$792 11 | Channel,1901R2,RR2Y,1.9,R,"Ac,PV",52.8,7.6,0,123.4,$791 12 | Titan Pro,20M1,RR2Y,2.0,R,Am,52.5,7.5,0,124.4,$788 13 | Kruger,K2-2002,RR2Y,2.0,R,"Ac,PV",52.4,7.9,0,125.4,$786 14 | Channel,1700R2,RR2Y,1.7,R,"Ac,PV",52.3,7.9,0,123.9,$784 15 | Hefty,H16Y11,RR2Y,1.6,MR,I,51.4,7.6,0,123.9,$771 16 | Anderson,162R2Y,RR2Y,1.6,R,None,51.3,7.5,0,119.5,$770 17 | Titan Pro,15M22,RR2Y,1.5,R,CMB,51.3,7.8,0,125.4,$769 18 | Dairyland,DSR-1710R2Y,RR2Y,1.7,R,CMB,51.3,7.7,0,122.0,$769 19 | Hefty,H20R3,RR2Y,2.0,MR,I,50.5,8.2,0,121.0,$757 20 | Prairie Brand,PB-1743R2,RR2Y,1.7,R,CMB,50.2,7.7,0,125.8,$752 21 | Gold Country,1741,RR2Y,1.7,R,Ac,50.1,7.8,0,123.9,$751 22 | Trelay,20RR43,RR2Y,2.0,R,"Ac,Ex",49.9,7.6,0,127.8,$749 23 | Hefty,H14R3,RR2Y,1.4,MR,I,49.7,7.7,0,122.9,$746 24 | Prairie Brand,PB-2099NRR2,RR2Y,2.0,R,CMB,49.6,7.8,0,126.3,$743 25 | Wensman,W 3174NR2,RR2Y,1.7,R,Ac,49.3,7.6,0,122.5,$740 26 | Kruger,K2-1602,RR2Y,1.6,R,"Ac,PV",48.7,7.6,0,125.4,$731 27 | NK Brand,S18-C2 §,RR2Y,1.8,R,CMB,48.7,7.7,0,126.8,$731 28 | Kruger,K2-1902,RR2Y,1.9,R,"Ac,PV",48.7,7.5,0,124.4,$730 29 | Prairie Brand,PB-1823R2,RR2Y,1.8,R,None,48.5,7.6,0,121.0,$727 30 | Gold Country,1541,RR2Y,1.5,R,Ac,48.4,7.6,0,110.4,$726 31 | -------------------------------------------------------------------------------- /docs/benchmark/stream/birdisland/birdisland.pdf: -------------------------------------------------------------------------------- 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-------------------------------------------------------------------------------- 1 | "","Table: 5 Public Health Outlay 2012-13 (Budget Estimates) (Rs. in 000)","","","","","","" 2 | "States-A","Revenue","","Capital","","Total","Others(1)","Total" 3 | "","","","","","Revenue &","","" 4 | "","Medical &","Family","Medical &","Family","","","" 5 | "","","","","","Capital","","" 6 | "","Public","Welfare","Public","Welfare","","","" 7 | "","Health","","Health","","","","" 8 | "Andhra Pradesh","47,824,589","9,967,837","1,275,000","15,000","59,082,426","14,898,243","73,980,669" 9 | "Arunachal Pradesh","2,241,609","107,549","23,000","0","2,372,158","86,336","2,458,494" 10 | "Assam","14,874,821","2,554,197","161,600","0","17,590,618","4,408,505","21,999,123" 11 | "Bihar","21,016,708","4,332,141","5,329,000","0","30,677,849","2,251,571","32,929,420" 12 | "Chhattisgarh","11,427,311","1,415,660","2,366,592","0","15,209,563","311,163","15,520,726" 13 | "Delhi","28,084,780","411,700","4,550,000","0","33,046,480","5,000","33,051,480" 14 | "Goa","4,055,567","110,000","330,053","0","4,495,620","12,560","4,508,180" 15 | "Gujarat","26,328,400","6,922,900","12,664,000","42,000","45,957,300","455,860","46,413,160" 16 | "Haryana","15,156,681","1,333,527","40,100","0","16,530,308","1,222,698","17,753,006" 17 | "Himachal Pradesh","8,647,229","1,331,529","580,800","0","10,559,558","725,315","11,284,873" 18 | "Jammu & Kashmir","14,411,984","270,840","3,188,550","0","17,871,374","166,229","18,037,603" 19 | "Jharkhand","8,185,079","3,008,077","3,525,558","0","14,718,714","745,139","15,463,853" 20 | "Karnataka","34,939,843","4,317,801","3,669,700","0","42,927,344","631,088","43,558,432" 21 | "Kerala","27,923,965","3,985,473","929,503","0","32,838,941","334,640","33,173,581" 22 | "Madhya Pradesh","28,459,540","4,072,016","3,432,711","0","35,964,267","472,139","36,436,406" 23 | "Maharashtra","55,011,100","6,680,721","5,038,576","0","66,730,397","313,762","67,044,159" 24 | "Manipur","2,494,600","187,700","897,400","0","3,579,700","0","3,579,700" 25 | "Meghalaya","2,894,093","342,893","705,500","5,000","3,947,486","24,128","3,971,614" 26 | "Mizoram","1,743,501","84,185","10,250","0","1,837,936","17,060","1,854,996" 27 | "Nagaland","2,368,724","204,329","226,400","0","2,799,453","783,054","3,582,507" 28 | "Odisha","14,317,179","2,552,292","1,107,250","0","17,976,721","451,438","18,428,159" 29 | "Puducherry","4,191,757","52,249","192,400","0","4,436,406","2,173","4,438,579" 30 | "Punjab","19,775,485","2,208,343","2,470,882","0","24,454,710","1,436,522","25,891,232" 31 | "","Health Sector Financing by Centre and States/UTs in India [2009-10 to 2012-13](Revised) P a g e |23","","","","","","" 32 | -------------------------------------------------------------------------------- /docs/benchmark/stream/health/health-data-pdf-table-extract-page-1-table-1.csv: -------------------------------------------------------------------------------- 1 | "0" 2 | "(1) States-A Revenue Capital Total Others Total Revenue & Medical & Family Medical & Family Capital Public Welfare Public Welfare Health Health Andhra Pradesh 47,824,589 9,967,837 1,275,000 15,000 59,082,426 14,898,243 73,980,669 Arunachal Pradesh 2,241,609 107,549 23,000 0 2,372,158 86,336 2,458,494 Assam 14,874,821 2,554,197 161,600 0 17,590,618 4,408,505 21,999,123 Bihar 21,016,708 4,332,141 5,329,000 0 30,677,849 2,251,571 32,929,420 Chhattisgarh 11,427,311 1,415,660 2,366,592 0 15,209,563 311,163 15,520,726 Delhi 28,084,780 411,700 4,550,000 0 33,046,480 5,000 33,051,480 Goa 4,055,567 110,000 330,053 0 4,495,620 12,560 4,508,180 Gujarat 26,328,400 6,922,900 12,664,000 42,000 45,957,300 455,860 46,413,160 Haryana 15,156,681 1,333,527 40,100 0 16,530,308 1,222,698 17,753,006 Himachal Pradesh 8,647,229 1,331,529 580,800 0 10,559,558 725,315 11,284,873 Jammu & Kashmir 14,411,984 270,840 3,188,550 0 17,871,374 166,229 18,037,603 Jharkhand 8,185,079 3,008,077 3,525,558 0 14,718,714 745,139 15,463,853 Karnataka 34,939,843 4,317,801 3,669,700 0 42,927,344 631,088 43,558,432 Kerala 27,923,965 3,985,473 929,503 0 32,838,941 334,640 33,173,581 Madhya Pradesh 28,459,540 4,072,016 3,432,711 0 35,964,267 472,139 36,436,406 Maharashtra 55,011,100 6,680,721 5,038,576 0 66,730,397 313,762 67,044,159 Manipur 2,494,600 187,700 897,400 0 3,579,700 0 3,579,700 Meghalaya 2,894,093 342,893 705,500 5,000 3,947,486 24,128 3,971,614 Mizoram 1,743,501 84,185 10,250 0 1,837,936 17,060 1,854,996 Nagaland 2,368,724 204,329 226,400 0 2,799,453 783,054 3,582,507 Odisha 14,317,179 2,552,292 1,107,250 0 17,976,721 451,438 18,428,159 Puducherry 4,191,757 52,249 192,400 0 4,436,406 2,173 4,438,579 Punjab 19,775,485 2,208,343 2,470,882 0 24,454,710 1,436,522 25,891,232 Health Sector Financing by Centre and States/UTs in India [2009-10 to 2012-13](Revised) P a g e |23" 3 | -------------------------------------------------------------------------------- /docs/benchmark/stream/health/health-data-pdftables-page-1-table-1.csv: -------------------------------------------------------------------------------- 1 | "0","1" 2 | "","" 3 | "","Table:5 4 | PublicHealthOutlay2012-13(BudgetEstimates) 5 | (Rs.in000) 6 | " 7 | "","States-A 8 | Revenue 9 | Capital 10 | Total 11 | Others 12 | (1) 13 | Total 14 | " 15 | "","Revenue&Medical&FamilyMedical&Family 16 | 17 | 18 | 19 | CapitalPublic 20 | WelfareMedical &Public 21 | Welfare" 22 | "","HealthFamily 23 | Welfare Medical & 24 | Public 25 | Health Family 26 | Welfare 47,824,589 9HealthFamily 27 | Welfare 47,824,589 9,967,837 1,275,000" 28 | "","AndhraPradesh 29 | 47,824,5899,967,8371,275,00015,00059,082,42614,898,24373,980,669" 30 | "","ArunachalPradesh 31 | 2,241,609107,54923,00002,372,15886,3362,458,494" 32 | "","Assam14,874,8212,554,197161,600017,590,6184,408,50521,999,123" 33 | "","Bihar21,016,7084,332,1415,329,000030,677,8492,251,57132,929,420" 34 | "","Chhattisgarh11,427,3111,415,6602,366,592015,209,563311,16315,520,726" 35 | "","Delhi28,084,780411,7004,550,000033,046,4805,00033,051,480" 36 | "","Goa4,055,567110,000330,05304,495,62012,5604,508,180" 37 | "","Gujarat26,328,4006,922,90012,664,00042,00045,957,300455,86046,413,160" 38 | "","Haryana15,156,6811,333,52740,100016,530,3081,222,69817,753,006" 39 | "","HimachalPradesh8,647,2291,331,529580,800010,559,558725,31511,284,873" 40 | "","Jammu&Kashmir14,411,984270,8403,188,550017,871,374166,22918,037,603" 41 | "","Jharkhand8,185,0793,008,0773,525,558014,718,714745,13915,463,853" 42 | "","Karnataka34,939,8434,317,8013,669,700042,927,344631,08843,558,432" 43 | "","Kerala27,923,9653,985,473929,503032,838,941334,64033,173,581" 44 | "","MadhyaPradesh28,459,5404,072,0163,432,711035,964,267472,13936,436,406" 45 | "","Maharashtra55,011,1006,680,7215,038,576066,730,397313,76267,044,159" 46 | "","Manipur2,494,600187,700897,40003,579,70003,579,700" 47 | "","Meghalaya2,894,093342,893705,5005,0003,947,48624,1283,971,614" 48 | "","Mizoram1,743,50184,18510,25001,837,93617,0601,854,996" 49 | "","Nagaland2,368,724204,329226,40002,799,453783,0543,582,507" 50 | "","Odisha 51 | 14,317,1792,552,2921,107,250017,976,721451,43818,428,159" 52 | "","Puducherry4,191,75752,249192,40004,436,4062,1734,438,579" 53 | "","Punjab 54 | 19,775,4852,208,3432,470,882024,454,7101,436,52225,891,232" 55 | "","HealthSectorFinancingbyCentreandStates/UTsinIndia[2009-10to2012-13](Revised)Page|23" 56 | -------------------------------------------------------------------------------- /docs/benchmark/stream/health/health-data-tabula.csv: -------------------------------------------------------------------------------- 1 | Table: 5,Public Health Outlay 2012-13 (Budget Estimates)(Rs. in 000), 2 | States-A,Revenue Capital Total Others(1),Total 3 | "",Medical & Family Medical & Family Revenue &, 4 | "",Public Welfare Public Welfare Capital, 5 | "",Health Health, 6 | Andhra Pradesh,"47,824,589 9,967,837 1,275,000 15,000 59,082,426 14,898,243","73,980,669" 7 | Arunachal Pradesh,"2,241,609 107,549 23,000 0 2,372,158 86,336","2,458,494" 8 | Assam,"14,874,821 2,554,197 161,600 0 17,590,618 4,408,505","21,999,123" 9 | Bihar,"21,016,708 4,332,141 5,329,000 0 30,677,849 2,251,571","32,929,420" 10 | Chhattisgarh,"11,427,311 1,415,660 2,366,592 0 15,209,563 311,163","15,520,726" 11 | Delhi,"28,084,780 411,700 4,550,000 0 33,046,480 5,000","33,051,480" 12 | Goa,"4,055,567 110,000 330,053 0 4,495,620 12,560","4,508,180" 13 | Gujarat,"26,328,400 6,922,900 12,664,000 42,000 45,957,300 455,860","46,413,160" 14 | Haryana,"15,156,681 1,333,527 40,100 0 16,530,308 1,222,698","17,753,006" 15 | Himachal Pradesh,"8,647,229 1,331,529 580,800 0 10,559,558 725,315","11,284,873" 16 | Jammu & Kashmir,"14,411,984 270,840 3,188,550 0 17,871,374 166,229","18,037,603" 17 | Jharkhand,"8,185,079 3,008,077 3,525,558 0 14,718,714 745,139","15,463,853" 18 | Karnataka,"34,939,843 4,317,801 3,669,700 0 42,927,344 631,088","43,558,432" 19 | Kerala,"27,923,965 3,985,473 929,503 0 32,838,941 334,640","33,173,581" 20 | Madhya Pradesh,"28,459,540 4,072,016 3,432,711 0 35,964,267 472,139","36,436,406" 21 | Maharashtra,"55,011,100 6,680,721 5,038,576 0 66,730,397 313,762","67,044,159" 22 | Manipur,"2,494,600 187,700 897,400 0 3,579,700 0","3,579,700" 23 | Meghalaya,"2,894,093 342,893 705,500 5,000 3,947,486 24,128","3,971,614" 24 | Mizoram,"1,743,501 84,185 10,250 0 1,837,936 17,060","1,854,996" 25 | Nagaland,"2,368,724 204,329 226,400 0 2,799,453 783,054","3,582,507" 26 | Odisha,"14,317,179 2,552,292 1,107,250 0 17,976,721 451,438","18,428,159" 27 | Puducherry,"4,191,757 52,249 192,400 0 4,436,406 2,173","4,438,579" 28 | Punjab,"19,775,485 2,208,343 2,470,882 0 24,454,710 1,436,522","25,891,232" 29 | -------------------------------------------------------------------------------- /docs/benchmark/stream/health/health.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/stream/health/health.pdf -------------------------------------------------------------------------------- /docs/benchmark/stream/m27/m27.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/stream/m27/m27.pdf -------------------------------------------------------------------------------- /docs/benchmark/stream/mexican_towns/mexican_towns-data-pdf-table-extract-page-1-table-1.csv: -------------------------------------------------------------------------------- 1 | "0" 2 | "Clave Clave Clave Nombre Entidad Nombre Municipio Nombre Localidad Entidad Municipio Localidad 01 Aguascalientes 001 Aguascalientes 0094 Granja Adelita 01 Aguascalientes 001 Aguascalientes 0096 Agua Azul 01 Aguascalientes 001 Aguascalientes 0100 Rancho Alegre 01 Aguascalientes 001 Aguascalientes 0102 Los Arbolitos [Rancho] 01 Aguascalientes 001 Aguascalientes 0104 Ardillas de Abajo (Las Ardillas) 01 Aguascalientes 001 Aguascalientes 0106 Arellano 01 Aguascalientes 001 Aguascalientes 0112 Bajío los Vázquez 01 Aguascalientes 001 Aguascalientes 0113 Bajío de Montoro 01 Aguascalientes 001 Aguascalientes 0114 Residencial San Nicolás [Baños la Cantera] 01 Aguascalientes 001 Aguascalientes 0120 Buenavista de Peñuelas 01 Aguascalientes 001 Aguascalientes 0121 Cabecita 3 Marías (Rancho Nuevo) 01 Aguascalientes 001 Aguascalientes 0125 Cañada Grande de Cotorina 01 Aguascalientes 001 Aguascalientes 0126 Cañada Honda [Estación] 01 Aguascalientes 001 Aguascalientes 0127 Los Caños 01 Aguascalientes 001 Aguascalientes 0128 El Cariñán 01 Aguascalientes 001 Aguascalientes 0129 El Carmen [Granja] 01 Aguascalientes 001 Aguascalientes 0135 El Cedazo (Cedazo de San Antonio) 01 Aguascalientes 001 Aguascalientes 0138 Centro de Arriba (El Taray) 01 Aguascalientes 001 Aguascalientes 0139 Cieneguilla (La Lumbrera) 01 Aguascalientes 001 Aguascalientes 0141 Cobos 01 Aguascalientes 001 Aguascalientes 0144 El Colorado (El Soyatal) 01 Aguascalientes 001 Aguascalientes 0146 El Conejal 01 Aguascalientes 001 Aguascalientes 0157 Cotorina de Abajo 01 Aguascalientes 001 Aguascalientes 0162 Coyotes 01 Aguascalientes 001 Aguascalientes 0166 La Huerta (La Cruz) 01 Aguascalientes 001 Aguascalientes 0170 Cuauhtémoc (Las Palomas) 01 Aguascalientes 001 Aguascalientes 0171 Los Cuervos (Los Ojos de Agua) 01 Aguascalientes 001 Aguascalientes 0172 San José [Granja] 01 Aguascalientes 001 Aguascalientes 0176 La Chiripa 01 Aguascalientes 001 Aguascalientes 0182 Dolores 01 Aguascalientes 001 Aguascalientes 0183 Los Dolores 01 Aguascalientes 001 Aguascalientes 0190 El Duraznillo 01 Aguascalientes 001 Aguascalientes 0191 Los Durón 01 Aguascalientes 001 Aguascalientes 0197 La Escondida 01 Aguascalientes 001 Aguascalientes 0201 Brande Vin [Bodegas] 01 Aguascalientes 001 Aguascalientes 0207 Valle Redondo 01 Aguascalientes 001 Aguascalientes 0209 La Fortuna 01 Aguascalientes 001 Aguascalientes 0212 Lomas del Gachupín 01 Aguascalientes 001 Aguascalientes 0213 El Carmen (Gallinas Güeras) [Rancho] 01 Aguascalientes 001 Aguascalientes 0216 La Gloria 01 Aguascalientes 001 Aguascalientes 0226 Hacienda Nueva" 3 | -------------------------------------------------------------------------------- /docs/benchmark/stream/mexican_towns/mexican_towns-data-tabula.csv: -------------------------------------------------------------------------------- 1 | 01,Aguascalientes,001,Aguascalientes,0094,Granja Adelita 2 | 01,Aguascalientes,001,Aguascalientes,0096,Agua Azul 3 | 01,Aguascalientes,001,Aguascalientes,0100,Rancho Alegre 4 | 01,Aguascalientes,001,Aguascalientes,0102,Los Arbolitos [Rancho] 5 | 01,Aguascalientes,001,Aguascalientes,0104,Ardillas de Abajo (Las Ardillas) 6 | 01,Aguascalientes,001,Aguascalientes,0106,Arellano 7 | 01,Aguascalientes,001,Aguascalientes,0112,Bajío los Vázquez 8 | 01,Aguascalientes,001,Aguascalientes,0113,Bajío de Montoro 9 | 01,Aguascalientes,001,Aguascalientes,0114,Residencial San Nicolás [Baños la Cantera] 10 | 01,Aguascalientes,001,Aguascalientes,0120,Buenavista de Peñuelas 11 | 01,Aguascalientes,001,Aguascalientes,0121,Cabecita 3 Marías (Rancho Nuevo) 12 | 01,Aguascalientes,001,Aguascalientes,0125,Cañada Grande de Cotorina 13 | 01,Aguascalientes,001,Aguascalientes,0126,Cañada Honda [Estación] 14 | 01,Aguascalientes,001,Aguascalientes,0127,Los Caños 15 | 01,Aguascalientes,001,Aguascalientes,0128,El Cariñán 16 | 01,Aguascalientes,001,Aguascalientes,0129,El Carmen [Granja] 17 | 01,Aguascalientes,001,Aguascalientes,0135,El Cedazo (Cedazo de San Antonio) 18 | 01,Aguascalientes,001,Aguascalientes,0138,Centro de Arriba (El Taray) 19 | 01,Aguascalientes,001,Aguascalientes,0139,Cieneguilla (La Lumbrera) 20 | 01,Aguascalientes,001,Aguascalientes,0141,Cobos 21 | 01,Aguascalientes,001,Aguascalientes,0144,El Colorado (El Soyatal) 22 | 01,Aguascalientes,001,Aguascalientes,0146,El Conejal 23 | 01,Aguascalientes,001,Aguascalientes,0157,Cotorina de Abajo 24 | 01,Aguascalientes,001,Aguascalientes,0162,Coyotes 25 | 01,Aguascalientes,001,Aguascalientes,0166,La Huerta (La Cruz) 26 | 01,Aguascalientes,001,Aguascalientes,0170,Cuauhtémoc (Las Palomas) 27 | 01,Aguascalientes,001,Aguascalientes,0171,Los Cuervos (Los Ojos de Agua) 28 | 01,Aguascalientes,001,Aguascalientes,0172,San José [Granja] 29 | 01,Aguascalientes,001,Aguascalientes,0176,La Chiripa 30 | 01,Aguascalientes,001,Aguascalientes,0182,Dolores 31 | 01,Aguascalientes,001,Aguascalientes,0183,Los Dolores 32 | 01,Aguascalientes,001,Aguascalientes,0190,El Duraznillo 33 | 01,Aguascalientes,001,Aguascalientes,0191,Los Durón 34 | 01,Aguascalientes,001,Aguascalientes,0197,La Escondida 35 | 01,Aguascalientes,001,Aguascalientes,0201,Brande Vin [Bodegas] 36 | 01,Aguascalientes,001,Aguascalientes,0207,Valle Redondo 37 | 01,Aguascalientes,001,Aguascalientes,0209,La Fortuna 38 | 01,Aguascalientes,001,Aguascalientes,0212,Lomas del Gachupín 39 | 01,Aguascalientes,001,Aguascalientes,0213,El Carmen (Gallinas Güeras) [Rancho] 40 | 01,Aguascalientes,001,Aguascalientes,0216,La Gloria 41 | 01,Aguascalientes,001,Aguascalientes,0226,Hacienda Nueva 42 | -------------------------------------------------------------------------------- /docs/benchmark/stream/mexican_towns/mexican_towns.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/stream/mexican_towns/mexican_towns.pdf -------------------------------------------------------------------------------- /docs/benchmark/stream/missing_values/missing_values.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/stream/missing_values/missing_values.pdf -------------------------------------------------------------------------------- /docs/benchmark/stream/population_growth/population_growth-data-camelot-page-1-table-1.csv: -------------------------------------------------------------------------------- 1 | "","TABLE 4: STATE-WISE DECADAL GROWTH RATE OF POPULATION","","","","","" 2 | "","","","","","","(Per cent)" 3 | "States/Union Territories","1951-1961","1961-1971","1971-1981","1981-1991","1991-2001","2001-2011" 4 | "Andaman and Nicobar Islands","105.19","81.17","63.93","48.70","26.90","6.68" 5 | "Andhra Pradesh","15.65","20.90","23.10","24.20","14.59","11.10" 6 | "Arunachal Pradesh","-","38.91","35.15","36.83","27.00","25.92" 7 | "Assam","34.98","34.95","23.36","24.24","18.92","16.93" 8 | "Bihar","19.79","20.91","24.16","23.38","28.62","25.07" 9 | "Chandigarh","394.13","114.59","75.55","42.16","40.28","17.10" 10 | "Chhattisgarh","22.77","27.12","20.39","25.73","18.27","22.59" 11 | "Dadra and Nagar Haveli","39.56","27.96","39.78","33.57","59.22","55.50" 12 | "Daman and Diu","-24.56","70.85","26.07","28.62","55.73","53.54" 13 | "NCT of Delhi","52.44","52.93","53.00","51.45","47.02","20.96" 14 | "Goa","7.77","34.77","26.74","16.08","15.21","8.17" 15 | "Gujarat","26.88","29.39","27.67","21.19","22.66","19.17" 16 | "Haryana","33.79","32.22","28.75","27.41","28.43","19.90" 17 | "Himachal Pradesh","17.87","23.04","23.71","20.79","17.54","12.81" 18 | "Jammu and Kashmir","9.44","29.65","29.69","30.89","29.43","23.71" 19 | "Jharkhand","19.69","22.58","23.79","24.03","23.36","22.34" 20 | "Karnataka","21.57","24.22","26.75","21.12","17.51","15.67" 21 | "Kerala","24.76","26.29","19.24","14.32","9.43","4.86" 22 | "Lakshadweep","14.61","31.95","26.53","28.47","17.30","6.23" 23 | "Madhya Pradesh","24.73","29.28","27.16","27.24","24.26","20.30" 24 | "Maharashtra","23.60","27.45","24.54","25.73","22.73","15.99" 25 | "Manipur","35.04","37.53","32.46","29.29","24.86","18.65" 26 | "Meghalaya","27.03","31.50","32.04","32.86","30.65","27.82" 27 | "Mizoram","35.61","24.93","48.55","39.70","28.82","22.78" 28 | "Nagaland","14.07","39.88","50.05","56.08","64.53","-0.47" 29 | "Odisha","19.82","25.05","20.17","20.06","16.25","13.97" 30 | "Puducherry","16.34","27.81","28.15","33.64","20.62","27.72" 31 | "Punjab","21.56","21.70","23.89","20.81","20.10","13.73" 32 | "Rajasthan","26.20","27.83","32.97","28.44","28.41","21.44" 33 | "Sikkim","17.76","29.38","50.77","28.47","33.06","12.36" 34 | "Tamil Nadu","11.85","22.30","17.50","15.39","11.72","15.60" 35 | "Tripura","78.71","36.28","31.92","34.30","16.03","14.75" 36 | "Uttar Pradesh","16.38","19.54","25.39","25.61","25.85","20.09" 37 | "Uttarakhand","22.57","24.42","27.45","23.13","20.41","19.17" 38 | "West Bengal","32.80","26.87","23.17","24.73","17.77","13.93" 39 | "ALL INDIA","21.51","24.80","24.66","23.87","21.54","17.64" 40 | "‘-’: Not Available.","","","","","","" 41 | "Source : Registrar General of India, Ministry of Home Affairs, Government of India.","","","","","","" 42 | "","","6","","","","" 43 | -------------------------------------------------------------------------------- /docs/benchmark/stream/population_growth/population_growth-data-tabula.csv: -------------------------------------------------------------------------------- 1 | States/Union Territories,1951-1961,1961-1971,1971-1981,1981-1991,1991-2001,2001-2011 2 | Andaman and Nicobar Islands,105.19,81.17,63.93,48.70,26.90,6.68 3 | Andhra Pradesh,15.65,20.90,23.10,24.20,14.59,11.10 4 | Arunachal Pradesh,-,38.91,35.15,36.83,27.00,25.92 5 | Assam,34.98,34.95,23.36,24.24,18.92,16.93 6 | Bihar,19.79,20.91,24.16,23.38,28.62,25.07 7 | Chandigarh,394.13,114.59,75.55,42.16,40.28,17.10 8 | Chhattisgarh,22.77,27.12,20.39,25.73,18.27,22.59 9 | Dadra and Nagar Haveli,39.56,27.96,39.78,33.57,59.22,55.50 10 | Daman and Diu,-24.56,70.85,26.07,28.62,55.73,53.54 11 | NCT of Delhi,52.44,52.93,53.00,51.45,47.02,20.96 12 | Goa,7.77,34.77,26.74,16.08,15.21,8.17 13 | Gujarat,26.88,29.39,27.67,21.19,22.66,19.17 14 | Haryana,33.79,32.22,28.75,27.41,28.43,19.90 15 | Himachal Pradesh,17.87,23.04,23.71,20.79,17.54,12.81 16 | Jammu and Kashmir,9.44,29.65,29.69,30.89,29.43,23.71 17 | Jharkhand,19.69,22.58,23.79,24.03,23.36,22.34 18 | Karnataka,21.57,24.22,26.75,21.12,17.51,15.67 19 | Kerala,24.76,26.29,19.24,14.32,9.43,4.86 20 | Lakshadweep,14.61,31.95,26.53,28.47,17.30,6.23 21 | Madhya Pradesh,24.73,29.28,27.16,27.24,24.26,20.30 22 | Maharashtra,23.60,27.45,24.54,25.73,22.73,15.99 23 | Manipur,35.04,37.53,32.46,29.29,24.86,18.65 24 | Meghalaya,27.03,31.50,32.04,32.86,30.65,27.82 25 | Mizoram,35.61,24.93,48.55,39.70,28.82,22.78 26 | Nagaland,14.07,39.88,50.05,56.08,64.53,-0.47 27 | Odisha,19.82,25.05,20.17,20.06,16.25,13.97 28 | Puducherry,16.34,27.81,28.15,33.64,20.62,27.72 29 | Punjab,21.56,21.70,23.89,20.81,20.10,13.73 30 | Rajasthan,26.20,27.83,32.97,28.44,28.41,21.44 31 | Sikkim,17.76,29.38,50.77,28.47,33.06,12.36 32 | Tamil Nadu,11.85,22.30,17.50,15.39,11.72,15.60 33 | Tripura,78.71,36.28,31.92,34.30,16.03,14.75 34 | Uttar Pradesh,16.38,19.54,25.39,25.61,25.85,20.09 35 | Uttarakhand,22.57,24.42,27.45,23.13,20.41,19.17 36 | West Bengal,32.80,26.87,23.17,24.73,17.77,13.93 37 | ALL INDIA,21.51,24.80,24.66,23.87,21.54,17.64 38 | -------------------------------------------------------------------------------- /docs/benchmark/stream/population_growth/population_growth.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/stream/population_growth/population_growth.pdf -------------------------------------------------------------------------------- /docs/benchmark/stream/superscript/superscript-data-camelot-page-1-table-1.csv: -------------------------------------------------------------------------------- 1 | "","TABLE 125: STATE-WISE COMPOSITION OF OUTSTANDING LIABILITIES - 1997 (Contd.)","","","","","","","","","" 2 | "","","","","(As at end-March)","","","","","","" 3 | "","","","","","","","","","","(` Billion)" 4 | "States","Total","Market","NSSF","WMA","Loans","Loans","Loans","Loans","Loans","Loans" 5 | "","Internal","Loans","","from","from","from","from","from","from SBI","from" 6 | "","Debt","","","RBI","Banks","LIC","GIC","NABARD","& Other","NCDC" 7 | "","","","","","& FIs","","","","Banks","" 8 | "1","2=","3","4","5","6=","7","8","9","10","11" 9 | "","(3 to 6)+14","","","","(7 to13)","","","","","" 10 | "Andhra Pradesh","48.11","40.45","-","3.26","4.4","2.62","-","0.91","-","0.25" 11 | "Arunachal Pradesh","1.23","1.1","-","-","0.13","-","-","-","-","-" 12 | "Assam","12.69","10.02","-","2.41","0.26","0.08","-","-0.06","0.01","0.24" 13 | "Bihar","40.75","41.54","-","-","-1.42","0.19","-","-1.01","-0.36","0.2" 14 | "Chhattisgarh","-","-","-","-","-","-","-","-","-","-" 15 | "Goa","1.4","1.02","-","-","0.38","0.31","-","0.07","-","-" 16 | "Gujarat","19.75","17.1","-","-","2.64","1.17","-","1.11","-","0.44" 17 | "Haryana","11.53","9.67","-","0.06","1.8","0.55","-","0.64","-","0.49" 18 | "Himachal Pradesh","8.02","2.94","-","4.55","0.53","0.13","-","0.05","-","0.25" 19 | "Jammu and Kashmir","11.72","4.49","-","-","7.23","0.66","-","0.02","6.08","-" 20 | "Jharkhand","-","-","-","-","-","-","-","-","-","-" 21 | "Karnataka","22.44","19.59","-","-","2.86","1.22","-","0.89","-","0.69" 22 | "Kerala","29.03","24.912","-","-","4.11","1.77","-","0.48","-","1.45" 23 | "Madhya Pradesh","27.13","23.57","-","-","3.56","0.38","-","1.86","-","1.28" 24 | "Maharashtra","30.47","26.07","-","-","4.39","0.21","-","-0.12","0.02","2.89" 25 | "Manipur","2.17","1.61","-","0.26","0.29","0.08","-","-","-","0.09" 26 | "Meghalaya","1.36","1.38","-","-","-0.02","0.04","-","-0.05","-","0.03" 27 | "Mizoram","1.17","0.46","-","0.27","0.43","0.11","-","-","-","0.03" 28 | "Nagaland","2.99","2.6","-","-","0.39","0.24","-","-","-","0.04" 29 | "Odisha","34.04","27.58","-","4.4","2.06","0.56","-","0.66","-","0.2" 30 | "Punjab","19.18","10.93","-","1.03","7.23","0.17","-","0.71","5.9","0.46" 31 | "Rajasthan","36.77","28.63","-","4.99","3.16","0.57","-","1.64","-","0.81" 32 | "Sikkim","0.16","-","-","-","0.16","0.03","-","-","-","0.01" 33 | "Tamil Nadu","34.11","31.41","-","-","2.7","1.3","-","0.6","-","0.68" 34 | "Tripura","2.3","1.89","-","-","0.41","0.41","-","-0.05","-","0.02" 35 | "Uttaranchal","-","-","-","-","-","-","-","-","-","-" 36 | "Uttar Pradesh","80.62","74.89","-","4.34","1.34","0.6","-","-0.21","0.18","0.03" 37 | "West Bengal","34.23","32.19","-","-","2.04","0.77","-","0.06","-","0.51" 38 | "NCT Delhi","-","-","-","-","-","-","-","-","-","-" 39 | "ALL STATES","513.38","436.02","-","25.57","51.06","14.18","-","8.21","11.83","11.08" 40 | "2 Includes `2.45 crore outstanding under “Market Loan Suspense”.","","","","","","","","","","" 41 | "","","","","445","","","","","","" 42 | -------------------------------------------------------------------------------- /docs/benchmark/stream/superscript/superscript-data-tabula.csv: -------------------------------------------------------------------------------- 1 | States,Total,Market,NSSF,WMA,Loans,Loans,Loans,Loans,Loans,Loans 2 | "",Internal,Loans,,from,from,from,from,from,from SBI,from 3 | "",Debt,,,RBI,Banks,LIC,GIC,NABARD,& Other,NCDC 4 | "",,,,,& FIs,,,,Banks, 5 | 1,2=,3,4,5,6=,7,8,9,10,11 6 | "",(3 to 6)+14,,,,(7 to13),,,,, 7 | Andhra Pradesh,48.11,40.45,-,3.26,4.4,2.62,-,0.91,-,0.25 8 | Arunachal Pradesh,1.23,1.1,-,-,0.13,-,-,-,-,- 9 | Assam,12.69,10.02,-,2.41,0.26,0.08,-,-0.06,0.01,0.24 10 | Bihar,40.75,41.54,-,-,-1.42,0.19,-,-1.01,-0.36,0.2 11 | Chhattisgarh,-,-,-,-,-,-,-,-,-,- 12 | Goa,1.4,1.02,-,-,0.38,0.31,-,0.07,-,- 13 | Gujarat,19.75,17.1,-,-,2.64,1.17,-,1.11,-,0.44 14 | Haryana,11.53,9.67,-,0.06,1.8,0.55,-,0.64,-,0.49 15 | Himachal Pradesh,8.02,2.94,-,4.55,0.53,0.13,-,0.05,-,0.25 16 | Jammu and Kashmir,11.72,4.49,-,-,7.23,0.66,-,0.02,6.08,- 17 | Jharkhand,-,-,-,-,-,-,-,-,-,- 18 | Karnataka,22.44,19.59,-,-,2.86,1.22,-,0.89,-,0.69 19 | Kerala,29.03,24.912,-,-,4.11,1.77,-,0.48,-,1.45 20 | Madhya Pradesh,27.13,23.57,-,-,3.56,0.38,-,1.86,-,1.28 21 | Maharashtra,30.47,26.07,-,-,4.39,0.21,-,-0.12,0.02,2.89 22 | Manipur,2.17,1.61,-,0.26,0.29,0.08,-,-,-,0.09 23 | Meghalaya,1.36,1.38,-,-,-0.02,0.04,-,-0.05,-,0.03 24 | Mizoram,1.17,0.46,-,0.27,0.43,0.11,-,-,-,0.03 25 | Nagaland,2.99,2.6,-,-,0.39,0.24,-,-,-,0.04 26 | Odisha,34.04,27.58,-,4.4,2.06,0.56,-,0.66,-,0.2 27 | Punjab,19.18,10.93,-,1.03,7.23,0.17,-,0.71,5.9,0.46 28 | Rajasthan,36.77,28.63,-,4.99,3.16,0.57,-,1.64,-,0.81 29 | Sikkim,0.16,-,-,-,0.16,0.03,-,-,-,0.01 30 | Tamil Nadu,34.11,31.41,-,-,2.7,1.3,-,0.6,-,0.68 31 | Tripura,2.3,1.89,-,-,0.41,0.41,-,-0.05,-,0.02 32 | Uttaranchal,-,-,-,-,-,-,-,-,-,- 33 | Uttar Pradesh,80.62,74.89,-,4.34,1.34,0.6,-,-0.21,0.18,0.03 34 | West Bengal,34.23,32.19,-,-,2.04,0.77,-,0.06,-,0.51 35 | NCT Delhi,-,-,-,-,-,-,-,-,-,- 36 | ALL STATES,513.38,436.02,-,25.57,51.06,14.18,-,8.21,11.83,11.08 37 | -------------------------------------------------------------------------------- /docs/benchmark/stream/superscript/superscript.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/stream/superscript/superscript.pdf -------------------------------------------------------------------------------- /docs/benchmark/stream/us-007/us-007-data-camelot-page-1-table-1.csv: -------------------------------------------------------------------------------- 1 | "","One Withholding" 2 | "Payroll Period","Allowance" 3 | "Weekly","$71.15" 4 | "Biweekly","142.31" 5 | "Semimonthly","154.17" 6 | "Monthly","308.33" 7 | "Quarterly","925.00" 8 | "Semiannually","1,850.00" 9 | "Annually","3,700.00" 10 | "Daily or Miscellaneous","14.23" 11 | "(each day of the payroll period)","" 12 | -------------------------------------------------------------------------------- /docs/benchmark/stream/us-007/us-007-data-tabula.csv: -------------------------------------------------------------------------------- 1 | "",One Withholding 2 | Payroll Period,Allowance 3 | Weekly,$ 71.15 4 | Biweekly,142.31 5 | Semimonthly,154.17 6 | Monthly,308.33 7 | Quarterly,925.00 8 | Semiannually,"1,850.00" 9 | Annually,"3,700.00" 10 | Daily or Miscellaneous,14.23 11 | "(each day of the payroll period)", 12 | -------------------------------------------------------------------------------- /docs/benchmark/stream/us-007/us-007.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/docs/benchmark/stream/us-007/us-007.pdf -------------------------------------------------------------------------------- /docs/user/cli.rst: -------------------------------------------------------------------------------- 1 | .. _cli: 2 | 3 | Command-Line Interface 4 | ====================== 5 | 6 | Camelot comes with a command-line interface. 7 | 8 | You can print the help for the interface by typing ``camelot --help`` in your favorite terminal program, as shown below. Furthermore, you can print the help for each command by typing ``camelot --help``. Try it out! 9 | 10 | :: 11 | 12 | Usage: camelot [OPTIONS] COMMAND [ARGS]... 13 | 14 | Camelot: PDF Table Extraction for Humans 15 | 16 | Options: 17 | --version Show the version and exit. 18 | -q, --quiet TEXT Suppress logs and warnings. 19 | -p, --pages TEXT Comma-separated page numbers. Example: 1,3,4 20 | or 1,4-end. 21 | -pw, --password TEXT Password for decryption. 22 | -o, --output TEXT Output file path. 23 | -f, --format [csv|json|excel|html] 24 | Output file format. 25 | -z, --zip Create ZIP archive. 26 | -split, --split_text Split text that spans across multiple cells. 27 | -flag, --flag_size Flag text based on font size. Useful to 28 | detect super/subscripts. 29 | -strip, --strip_text Characters that should be stripped from a 30 | string before assigning it to a cell. 31 | -M, --margins ... 32 | PDFMiner char_margin, line_margin and 33 | word_margin. 34 | --help Show this message and exit. 35 | 36 | Commands: 37 | lattice Use lines between text to parse the table. 38 | stream Use spaces between text to parse the table. 39 | -------------------------------------------------------------------------------- /docs/user/install-deps.rst: -------------------------------------------------------------------------------- 1 | .. _install_deps: 2 | 3 | Installation of dependencies 4 | ============================ 5 | 6 | The dependencies `Tkinter`_ and `ghostscript`_ can be installed using your system's package manager. You can run one of the following, based on your OS. 7 | 8 | .. _Tkinter: https://wiki.python.org/moin/TkInter 9 | .. _ghostscript: https://www.ghostscript.com 10 | 11 | OS-specific instructions 12 | ------------------------ 13 | 14 | For Ubuntu 15 | ^^^^^^^^^^ 16 | :: 17 | 18 | $ apt install python-tk ghostscript 19 | 20 | Or for Python 3:: 21 | 22 | $ apt install python3-tk ghostscript 23 | 24 | For macOS 25 | ^^^^^^^^^ 26 | :: 27 | 28 | $ brew install tcl-tk ghostscript 29 | 30 | For Windows 31 | ^^^^^^^^^^^ 32 | 33 | For Tkinter, you can download the `ActiveTcl Community Edition`_ from ActiveState. For ghostscript, you can get the installer at the `ghostscript downloads page`_. 34 | 35 | .. _ActiveTcl Community Edition: https://www.activestate.com/activetcl/downloads 36 | .. _ghostscript downloads page: https://www.ghostscript.com/download/gsdnld.html 37 | .. _as shown here: https://java.com/en/download/help/path.xml 38 | 39 | Checks to see if dependencies were installed correctly 40 | ------------------------------------------------------ 41 | 42 | You can do the following checks to see if the dependencies were installed correctly. 43 | 44 | For Tkinter 45 | ^^^^^^^^^^^ 46 | 47 | Launch Python, and then at the prompt, type:: 48 | 49 | >>> import Tkinter 50 | 51 | Or in Python 3:: 52 | 53 | >>> import tkinter 54 | 55 | If you have Tkinter, Python will not print an error message, and if not, you will see an ``ImportError``. 56 | 57 | For ghostscript 58 | ^^^^^^^^^^^^^^^ 59 | 60 | Run the following to check the ghostscript version. 61 | 62 | For Ubuntu/macOS:: 63 | 64 | $ gs -version 65 | 66 | For Windows:: 67 | 68 | C:\> gswin64c.exe -version 69 | 70 | Or for Windows 32-bit:: 71 | 72 | C:\> gswin32c.exe -version 73 | 74 | If you have ghostscript, you should see the ghostscript version and copyright information. 75 | -------------------------------------------------------------------------------- /docs/user/install.rst: -------------------------------------------------------------------------------- 1 | .. _install: 2 | 3 | Installation of Camelot 4 | ======================= 5 | 6 | This part of the documentation covers the steps to install Camelot. 7 | 8 | Using conda 9 | ----------- 10 | 11 | The easiest way to install Camelot is to install it with `conda`_, which is a package manager and environment management system for the `Anaconda`_ distribution. 12 | :: 13 | 14 | $ conda install -c conda-forge camelot-py 15 | 16 | .. note:: Camelot is available for Python 2.7, 3.5 and 3.6 on Linux, macOS and Windows. For Windows, you will need to install ghostscript which you can get from their `downloads page`_. 17 | 18 | .. _conda: https://conda.io/docs/ 19 | .. _Anaconda: http://docs.continuum.io/anaconda/ 20 | .. _downloads page: https://www.ghostscript.com/download/gsdnld.html 21 | .. _conda-forge: https://conda-forge.org/ 22 | 23 | Using pip 24 | --------- 25 | 26 | After :ref:`installing the dependencies `, which include `Tkinter`_ and `ghostscript`_, you can simply use pip to install Camelot:: 27 | 28 | $ pip install camelot-py[cv] 29 | 30 | .. _Tkinter: https://wiki.python.org/moin/TkInter 31 | .. _ghostscript: https://www.ghostscript.com 32 | 33 | From the source code 34 | -------------------- 35 | 36 | After :ref:`installing the dependencies `, you can install from the source by: 37 | 38 | 1. Cloning the GitHub repository. 39 | :: 40 | 41 | $ git clone https://www.github.com/camelot-dev/camelot 42 | 43 | 2. Then simply using pip again. 44 | :: 45 | 46 | $ cd camelot 47 | $ pip install ".[cv]" 48 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | click>=6.7 2 | matplotlib>=2.2.3 3 | numpy>=1.13.3 4 | opencv-python>=3.4.2.17 5 | openpyxl>=2.5.8 6 | pandas>=0.23.4 7 | pdfminer.six>=20170720 8 | PyPDF2>=1.26.0 9 | -------------------------------------------------------------------------------- /setup.cfg: -------------------------------------------------------------------------------- 1 | [aliases] 2 | test=pytest 3 | 4 | [tool:pytest] 5 | addopts = --verbose --cov-config .coveragerc --cov-report term --cov-report xml --cov=camelot --mpl 6 | python_files = tests/test_*.py 7 | -------------------------------------------------------------------------------- /setup.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | 3 | import os 4 | from setuptools import find_packages 5 | 6 | 7 | here = os.path.abspath(os.path.dirname(__file__)) 8 | about = {} 9 | with open(os.path.join(here, 'camelot', '__version__.py'), 'r') as f: 10 | exec(f.read(), about) 11 | 12 | with open('README.md', 'r') as f: 13 | readme = f.read() 14 | 15 | 16 | requires = [ 17 | 'chardet>=3.0.4', 18 | 'click>=6.7', 19 | 'numpy>=1.13.3', 20 | 'openpyxl>=2.5.8', 21 | 'pandas>=0.23.4', 22 | 'pdfminer.six>=20170720', 23 | 'PyPDF2>=1.26.0' 24 | ] 25 | 26 | cv_requires = [ 27 | 'opencv-python>=3.4.2.17' 28 | ] 29 | 30 | plot_requires = [ 31 | 'matplotlib>=2.2.3', 32 | ] 33 | 34 | dev_requires = [ 35 | 'codecov>=2.0.15', 36 | 'pytest>=3.8.0', 37 | 'pytest-cov>=2.6.0', 38 | 'pytest-mpl>=0.10', 39 | 'pytest-runner>=4.2', 40 | 'Sphinx>=1.7.9' 41 | ] 42 | 43 | all_requires = cv_requires + plot_requires 44 | dev_requires = dev_requires + all_requires 45 | 46 | 47 | def setup_package(): 48 | metadata = dict(name=about['__title__'], 49 | version=about['__version__'], 50 | description=about['__description__'], 51 | long_description=readme, 52 | long_description_content_type="text/markdown", 53 | url=about['__url__'], 54 | author=about['__author__'], 55 | author_email=about['__author_email__'], 56 | license=about['__license__'], 57 | packages=find_packages(exclude=('tests',)), 58 | install_requires=requires, 59 | extras_require={ 60 | 'all': all_requires, 61 | 'cv': cv_requires, 62 | 'dev': dev_requires, 63 | 'plot': plot_requires 64 | }, 65 | entry_points={ 66 | 'console_scripts': [ 67 | 'camelot = camelot.cli:cli', 68 | ], 69 | }, 70 | classifiers=[ 71 | # Trove classifiers 72 | # Full list: https://pypi.python.org/pypi?%3Aaction=list_classifiers 73 | 'License :: OSI Approved :: MIT License', 74 | 'Programming Language :: Python :: 2.7', 75 | 'Programming Language :: Python :: 3.5', 76 | 'Programming Language :: Python :: 3.6', 77 | 'Programming Language :: Python :: 3.7' 78 | ]) 79 | 80 | try: 81 | from setuptools import setup 82 | except ImportError: 83 | from distutils.core import setup 84 | 85 | setup(**metadata) 86 | 87 | 88 | if __name__ == '__main__': 89 | setup_package() 90 | -------------------------------------------------------------------------------- /tests/__init__.py: -------------------------------------------------------------------------------- 1 | import matplotlib 2 | matplotlib.use('agg') 3 | -------------------------------------------------------------------------------- /tests/files/agstat.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/atlanhq/camelot/cd8ac7979fe3631866fe439f07e9d6aaa5b1e5c6/tests/files/agstat.pdf -------------------------------------------------------------------------------- /tests/files/anticlockwise_table_1.pdf: -------------------------------------------------------------------------------- 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| filename = os.path.join(testdir, "foo.pdf") 26 | tables = camelot.read_pdf(filename) 27 | return camelot.plot(tables[0], kind='grid') 28 | 29 | 30 | @pytest.mark.mpl_image_compare( 31 | baseline_dir="files/baseline_plots", remove_text=True) 32 | def test_lattice_contour_plot(): 33 | filename = os.path.join(testdir, "foo.pdf") 34 | tables = camelot.read_pdf(filename) 35 | return camelot.plot(tables[0], kind='contour') 36 | 37 | 38 | @pytest.mark.mpl_image_compare( 39 | baseline_dir="files/baseline_plots", remove_text=True) 40 | def test_stream_contour_plot(): 41 | filename = os.path.join(testdir, "tabula/12s0324.pdf") 42 | tables = camelot.read_pdf(filename, flavor='stream') 43 | return camelot.plot(tables[0], kind='contour') 44 | 45 | 46 | @pytest.mark.mpl_image_compare( 47 | baseline_dir="files/baseline_plots", remove_text=True) 48 | def test_line_plot(): 49 | filename = os.path.join(testdir, "foo.pdf") 50 | tables = camelot.read_pdf(filename) 51 | return camelot.plot(tables[0], kind='line') 52 | 53 | 54 | @pytest.mark.mpl_image_compare( 55 | baseline_dir="files/baseline_plots", remove_text=True) 56 | def test_joint_plot(): 57 | filename = os.path.join(testdir, "foo.pdf") 58 | tables = camelot.read_pdf(filename) 59 | return camelot.plot(tables[0], kind='joint') 60 | 61 | 62 | @pytest.mark.mpl_image_compare( 63 | baseline_dir="files/baseline_plots", remove_text=True) 64 | def test_textedge_plot(): 65 | filename = os.path.join(testdir, "tabula/12s0324.pdf") 66 | tables = camelot.read_pdf(filename, flavor='stream') 67 | return camelot.plot(tables[0], kind='textedge') 68 | --------------------------------------------------------------------------------