from reportlab.lib.pagesizes import A4
from reportlab.lib import colors
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from reportlab.lib.units import cm, mm
from reportlab.platypus import (
    SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle,
    HRFlowable, KeepTogether, PageBreak
)
from reportlab.lib.enums import TA_CENTER, TA_LEFT, TA_RIGHT
from reportlab.platypus import BaseDocTemplate, PageTemplate, Frame
from reportlab.pdfgen import canvas
from reportlab.lib.colors import HexColor
import datetime

# ── Color Palette ──────────────────────────────────────────────────────────────
DARK_NAVY    = HexColor('#1a2e4a')
MED_BLUE     = HexColor('#2563eb')
LIGHT_BLUE   = HexColor('#dbeafe')
ACCENT_TEAL  = HexColor('#0d9488')
TEAL_LIGHT   = HexColor('#ccfbf1')
ACCENT_RED   = HexColor('#dc2626')
RED_LIGHT    = HexColor('#fee2e2')
ACCENT_AMBER = HexColor('#d97706')
AMBER_LIGHT  = HexColor('#fef3c7')
ACCENT_GREEN = HexColor('#16a34a')
GREEN_LIGHT  = HexColor('#dcfce7')
ACCENT_PURPLE= HexColor('#7c3aed')
PURPLE_LIGHT = HexColor('#ede9fe')
HEADER_BG    = HexColor('#0f172a')
ROW_ALT      = HexColor('#f8fafc')
ROW_NORM     = HexColor('#ffffff')
BORDER_GREY  = HexColor('#cbd5e1')
TEXT_DARK    = HexColor('#1e293b')
TEXT_MED     = HexColor('#475569')
TEXT_LIGHT   = HexColor('#94a3b8')
ORANGE_LIGHT = HexColor('#ffedd5')
ACCENT_ORANGE= HexColor('#ea580c')

W, H = A4

# ── Page numbering canvas ──────────────────────────────────────────────────────
class NumberedCanvas(canvas.Canvas):
    def __init__(self, *args, **kwargs):
        canvas.Canvas.__init__(self, *args, **kwargs)
        self._saved_page_states = []

    def showPage(self):
        self._saved_page_states.append(dict(self.__dict__))
        self._startPage()

    def save(self):
        num_pages = len(self._saved_page_states)
        for state in self._saved_page_states:
            self.__dict__.update(state)
            self.draw_page_footer(num_pages)
            canvas.Canvas.showPage(self)
        canvas.Canvas.save(self)

    def draw_page_footer(self, page_count):
        page_num = self._pageNumber
        self.setFillColor(HEADER_BG)
        self.rect(0, 0, W, 22, fill=1, stroke=0)
        self.setFillColor(colors.white)
        self.setFont('Helvetica', 7.5)
        self.drawString(20, 7, 'Antibiotic Quick Reference Guide – India General Practice')
        self.drawRightString(W - 20, 7, f'Page {page_num} of {page_count}')
        self.setStrokeColor(MED_BLUE)
        self.setLineWidth(2)
        self.line(0, 22, W, 22)


def make_header(canvas_obj, doc):
    """Draw the branded page header."""
    canvas_obj.saveState()
    # Header background
    canvas_obj.setFillColor(HEADER_BG)
    canvas_obj.rect(0, H - 52, W, 52, fill=1, stroke=0)
    # Accent stripe
    canvas_obj.setFillColor(MED_BLUE)
    canvas_obj.rect(0, H - 55, W, 3, fill=1, stroke=0)
    # Title
    canvas_obj.setFillColor(colors.white)
    canvas_obj.setFont('Helvetica-Bold', 16)
    canvas_obj.drawString(20, H - 32, 'ANTIBIOTIC QUICK REFERENCE GUIDE')
    canvas_obj.setFont('Helvetica', 9)
    canvas_obj.setFillColor(HexColor('#94a3b8'))
    canvas_obj.drawString(20, H - 47, 'India General Practice  |  Selection by Infection Type  |  2025–26')
    canvas_obj.restoreState()


def build_styles():
    styles = getSampleStyleSheet()
    base = dict(fontName='Helvetica', textColor=TEXT_DARK, leading=12)

    section_title = ParagraphStyle('SectionTitle',
        fontName='Helvetica-Bold', fontSize=11,
        textColor=colors.white, leading=14,
        spaceAfter=0, spaceBefore=4)

    sub_note = ParagraphStyle('SubNote',
        fontName='Helvetica-Oblique', fontSize=7.5,
        textColor=TEXT_MED, leading=10)

    cell_body = ParagraphStyle('CellBody',
        fontName='Helvetica', fontSize=8,
        textColor=TEXT_DARK, leading=11, spaceAfter=1)

    cell_bold = ParagraphStyle('CellBold',
        fontName='Helvetica-Bold', fontSize=8.5,
        textColor=DARK_NAVY, leading=11)

    drug_first = ParagraphStyle('DrugFirst',
        fontName='Helvetica-Bold', fontSize=8.5,
        textColor=ACCENT_GREEN, leading=11)

    drug_alt = ParagraphStyle('DrugAlt',
        fontName='Helvetica', fontSize=8,
        textColor=ACCENT_TEAL, leading=11)

    drug_third = ParagraphStyle('DrugThird',
        fontName='Helvetica-Oblique', fontSize=7.5,
        textColor=TEXT_MED, leading=10)

    warn = ParagraphStyle('Warn',
        fontName='Helvetica-Bold', fontSize=7.5,
        textColor=ACCENT_RED, leading=10)

    toc_title = ParagraphStyle('TOCTitle',
        fontName='Helvetica-Bold', fontSize=18,
        textColor=DARK_NAVY, leading=22, alignment=TA_CENTER)

    big_title = ParagraphStyle('BigTitle',
        fontName='Helvetica-Bold', fontSize=28,
        textColor=colors.white, leading=32, alignment=TA_CENTER)

    return {
        'section_title': section_title, 'sub_note': sub_note,
        'cell_body': cell_body, 'cell_bold': cell_bold,
        'drug_first': drug_first, 'drug_alt': drug_alt,
        'drug_third': drug_third, 'warn': warn,
        'toc_title': toc_title, 'big_title': big_title
    }


# ── DATA ───────────────────────────────────────────────────────────────────────
# Format per row:
#  (Infection, First-Line, Alternative, Notes, Duration)

RESPIRATORY_DATA = [
    ('Strep Pharyngitis\n(Group A Strep)',
     'Amoxicillin 500mg TDS\n(Mox, Novamox)',
     'Azithromycin 500mg OD x3d\n(Azithral, Azee)',
     'Penicillin-allergic: Cephalexin\nor Clindamycin',
     '10 days\n(Amox)'),
    ('Acute Otitis Media',
     'Amoxicillin 500mg TDS\n(Mox, Novamox)',
     'Amoxiclav 625mg BD\n(Augmentin, Clavam)',
     'If failed 48–72h or recurrent;\nPenicillin allergic: Cefuroxime',
     '5–7 days'),
    ('Acute Bacterial Sinusitis',
     'Amoxicillin 500mg TDS\n(Novamox, Mox)',
     'Amoxiclav 625mg BD\n(Augmentin)',
     'Levofloxacin 500mg OD if\nfailed first-line',
     '5–7 days'),
    ('Community-Acquired\nPneumonia (mild, OPD)',
     'Amoxicillin 1g TDS\n(Novamox)\n+ Azithromycin 500mg OD\n(Azithral)',
     'Levofloxacin 500mg OD\n(Glevo, Lox)',
     'Atypicals: Doxycycline 100mg BD\n(Doxicip) as alternative',
     '5–7 days'),
    ('AECB (Chronic Bronchitis)',
     'Amoxiclav 625mg BD\n(Augmentin)',
     'Levofloxacin 500mg OD\n(Lox, Glevo)',
     'Mild: Azithromycin 500mg OD\nx5d acceptable',
     '5–7 days'),
    ('Atypical Pneumonia\n(Mycoplasma/Chlamydophila)',
     'Azithromycin 500mg OD\n(Azithral, Azee)',
     'Doxycycline 100mg BD\n(Doxicip, Doxt)',
     'Clarithromycin 500mg BD\n(Claribid) if Azithro unavail.',
     '5–7 days'),
]

UTI_DATA = [
    ('Uncomplicated Cystitis\n(Non-pregnant women)',
     'Nitrofurantoin 100mg BD\n(Niftran, Macrobid)',
     'Cefixime 200mg BD\n(Taxim-O, Zifi)',
     'Avoid FQ empirically (high\nresistance in India)',
     '5–7 days\n(Nitrofurantoin)'),
    ('Uncomplicated Cystitis\n(Pregnancy – 2nd trimester)',
     'Nitrofurantoin 100mg BD\n(Niftran)',
     'Cephalexin 500mg QID\n(Sporidex)',
     'Avoid in 1st/3rd trimester;\nAvoid TMP-SMX in 1st trimester',
     '7 days'),
    ('Complicated UTI /\nPyelonephritis (Oral)',
     'Levofloxacin 500mg OD\n(Glevo, Lox)',
     'Ciprofloxacin 500mg BD\n(Cifran, Ciplox)',
     'Start IV if severely ill;\nCefuroxime if FQ-resistant',
     '10–14 days'),
    ('Recurrent UTI\n(Prophylaxis)',
     'Nitrofurantoin 50mg OD\n(Niftran) – post-coital or\nnightly',
     'Cotrimoxazole 480mg OD\n(Septran)',
     'Based on culture sensitivity;\nassess after 6 months',
     '3–6 months'),
    ('Asymptomatic Bacteriuria\n(Pregnancy)',
     'Based on culture sensitivity\n(Cephalexin/Nitrofurantoin)',
     'Amoxicillin 500mg TDS\n(Mox)',
     'Always treat in pregnancy;\nrepeat culture after treatment',
     '7 days'),
]

GI_DATA = [
    ('Typhoid / Enteric Fever\n(Outpatient)',
     'Cefixime 200mg BD\n(Taxim-O, Mahacef)',
     'Azithromycin 500mg OD\n(Azithral)',
     'Avoid FQ – high resistance\nin India; treat 14 days with Cefixime',
     'Cefixime: 14d\nAzithro: 7–10d'),
    ('Acute Bacterial Diarrhea\n(Shigella/Salmonella)',
     'Cefixime 200mg BD\n(Taxim-O, Zifi)',
     'Azithromycin 500mg OD\n(Azithral)',
     'Ciprofloxacin 500mg BD if\nsensitivity confirmed',
     '5 days'),
    ('Amoebic Dysentery /\nLiver Abscess',
     'Metronidazole 400mg TDS\n(Flagyl, Metrogyl)',
     'Tinidazole 2g OD\n(Fasigyn, Tiniba)',
     'Follow with Diloxanide furoate\nfor luminal cysts',
     '7–10 days\n(Metro)'),
    ('Giardiasis',
     'Tinidazole 2g single dose\n(Fasigyn)',
     'Metronidazole 400mg TDS\n(Flagyl)',
     'Secnidazole 2g single dose\n(Secnil) – convenience option',
     'Single dose\n(Tinidazole)'),
    ('Cholera',
     'Azithromycin 1g single dose\n(Azithral) – pregnant/children',
     'Doxycycline 300mg stat\n(Doxicip) – adults',
     'ORS/IV rehydration is primary\ntreatment; antibiotics adjunctive',
     'Single dose'),
    ('H. pylori Eradication\n(Triple Therapy)',
     'Amoxicillin 1g BD +\nClarithromycin 500mg BD +\nPPI (Omeprazole 20mg BD)',
     'Amoxicillin 1g BD +\nMetronidazole 400mg BD +\nPPI',
     'Quadruple if clarithromycin\nresistance suspected (add Bismuth)',
     '14 days\n(preferred)'),
    ('Traveler\'s Diarrhea\n(Campylobacter)',
     'Azithromycin 500mg OD\n(Azithral)',
     'Ciprofloxacin 500mg BD\n(Cifran)',
     'Rifaximin 200mg TDS (Rcifax)\nfor non-invasive E.coli',
     '3 days'),
]

STI_DATA = [
    ('Chlamydia\n(Uncomplicated genital)',
     'Azithromycin 1g single dose\n(Azithral 1g)',
     'Doxycycline 100mg BD\n(Doxicip)',
     'Notify and treat partner;\ntest for other STIs',
     'Single dose\n(Azithro); 7d Doxy'),
    ('Gonorrhea\n(Uncomplicated urogenital)',
     'Cefixime 400mg single dose\n(Taxim-O 400mg)',
     'Cefpodoxime 200mg\nsingle dose (Cepodem)',
     'Add Azithromycin 1g for\nco-treatment of Chlamydia',
     'Single dose'),
    ('Bacterial Vaginosis',
     'Metronidazole 400mg BD\n(Metrogyl)',
     'Clindamycin 300mg BD\n(Dalacin C)',
     'Secnidazole 2g single dose\n(Secnil) – good compliance',
     '7 days\n(Metro oral)'),
    ('Trichomoniasis',
     'Metronidazole 2g single dose\n(Metrogyl)',
     'Tinidazole 2g single dose\n(Fasigyn)',
     'Treat partner simultaneously;\navoid alcohol during treatment',
     'Single dose'),
    ('Pelvic Inflammatory\nDisease (PID) – Oral',
     'Ofloxacin 400mg BD +\nMetronidazole 400mg TDS\n(Zanocin + Flagyl)',
     'Doxycycline 100mg BD +\nMetronidazole 400mg TDS',
     'Admit if severe; Ceftriaxone\nIM + oral follow-up',
     '14 days'),
]

SKIN_DATA = [
    ('Impetigo\n(Non-bullous)',
     'Amoxiclav 625mg BD\n(Augmentin)',
     'Cephalexin 500mg QID\n(Sporidex)',
     'Topical Mupirocin 2% for\nlimited lesions; oral for extensive',
     '7 days'),
    ('Cellulitis\n(Non-purulent)',
     'Amoxiclav 625mg BD\n(Augmentin)',
     'Cephalexin 500mg QID\n(Sporidex, Ibilex)',
     'Severe: IV Cloxacillin;\nMark borders to track progression',
     '5–7 days'),
    ('Furuncle / Carbuncle\n(Staphylococcal)',
     'Cloxacillin 500mg QID\n(Clox, Bioclox)',
     'Amoxiclav 625mg BD\n(Augmentin)',
     'I&D is primary; antibiotics\nfor surrounding cellulitis',
     '5–7 days'),
    ('Community-Acquired MRSA\nSSTI (CA-MRSA)',
     'Cotrimoxazole 960mg BD\n(Septran) ± Doxycycline',
     'Clindamycin 300mg TDS\n(Dalacin C, Clinmycin)',
     'Linezolid 600mg BD (Linox)\nif severe; always I&D abscesses',
     '5–7 days'),
    ('Diabetic Foot\n(Mild-Moderate)',
     'Amoxiclav 625–1000mg BD\n(Augmentin)',
     'Clindamycin 300mg TDS +\nCiprofloxacin 500mg BD',
     'Severe/MRSA risk: Linezolid;\nWound care + glucose control',
     '7–14 days'),
    ('Bite Wounds\n(Human/Animal)',
     'Amoxiclav 625mg BD\n(Augmentin)',
     'Doxycycline 100mg BD +\nMetronidazole 400mg TDS',
     'Augmentin = drug of choice;\nRabies/tetanus prophylaxis',
     '5–7 days\n(prophylaxis)'),
    ('Acne Vulgaris\n(Moderate-Severe)',
     'Doxycycline 100mg BD\n(Doxicip, Doxt)',
     'Minocycline 100mg BD\n(Minoz, Minolox)',
     'Combine with topical retinoid;\nUsually 3–6 months course',
     '3–6 months'),
]

BONE_DATA = [
    ('Osteomyelitis\n(MSSA, oral step-down)',
     'Cloxacillin 500mg QID\n(Clox)',
     'Cephalexin 1g QID\n(Sporidex)',
     'After initial IV; continue\n4–6 weeks total',
     '4–6 weeks\ntotal'),
    ('Osteomyelitis\n(MRSA, oral)',
     'Linezolid 600mg BD\n(Linox, Zyvox)',
     'Cotrimoxazole 960mg BD\n(Septran)',
     'Monitor CBC weekly\n(Linezolid); bone biopsy ideal',
     '6 weeks\ntotal'),
    ('Septic Arthritis\n(Oral step-down)',
     'Based on culture\n(commonly Cephalexin/Cloxacillin)',
     'Ciprofloxacin 500mg BD\n(Cifran) if Gram-neg',
     'Start IV; oral only after\nclinical improvement',
     '4–6 weeks'),
]

TROPICAL_DATA = [
    ('Scrub Typhus\n(Rickettsia)',
     'Doxycycline 100mg BD\n(Doxicip, Doxt)',
     'Azithromycin 500mg OD\n(Azithral) – pregnancy/children',
     'Start empirically in\nendemic areas; do not wait for serology',
     '7 days'),
    ('Leptospirosis (Mild)',
     'Doxycycline 100mg BD\n(Doxicip)',
     'Amoxicillin 500mg TDS\n(Novamox)',
     'Severe: IV Penicillin or\nCeftriaxone (hospital admission)',
     '7 days'),
    ('Brucellosis',
     'Doxycycline 100mg BD +\nRifampicin 600mg OD\n(Doxicip + Rifampicin)',
     'Doxycycline + Streptomycin IM\n(1g/day IM x 21 days)',
     'Combination mandatory;\nRifampicin for 6 weeks (with Doxy)',
     '6 weeks'),
    ('Malaria Prophylaxis\n(Chloroquine-resistant zones)',
     'Doxycycline 100mg OD\n(Doxicip)',
     'Atovaquone-Proguanil\n(Malanil)',
     'Start 1–2 days before travel;\ncontinue 4 weeks after return',
     'Duration of\nexposure + 4 wks'),
    ('Dengue / Chikungunya',
     'Supportive only\n(No antibiotics needed)',
     '—',
     'Antibiotics NOT indicated;\nAvoid NSAIDs in dengue (bleeding risk)',
     'N/A'),
]

MISC_DATA = [
    ('Dental Abscess /\nOral Infections',
     'Amoxiclav 625mg BD\n(Augmentin)',
     'Metronidazole 400mg TDS +\nAmoxicillin 500mg TDS',
     'Penicillin-allergic:\nClindamycin 300mg TDS',
     '5–7 days'),
    ('Dental Prophylaxis\n(Before procedures)',
     'Amoxicillin 2g single dose\n1h before procedure',
     'Clindamycin 600mg\n(Dalacin C) if Pen-allergic',
     'For high-risk cardiac patients\n(prosthetic valves, previous IE)',
     'Single dose'),
    ('Hepatic Encephalopathy\n(Prevention)',
     'Rifaximin 550mg BD\n(Rcifax, Rifagut)',
     'Lactulose + Rifaximin\ncombination',
     'Rifaximin: poorly absorbed;\nlong-term use acceptable',
     'Long-term'),
    ('SIBO (Small Intestinal\nBacterial Overgrowth)',
     'Rifaximin 200mg TDS x14d\n(Rcifax)',
     'Metronidazole 400mg TDS\n(Flagyl)',
     'Breath test to confirm;\naddress underlying cause',
     '14 days'),
    ('Pneumocystis (PCP)\nProphylaxis – HIV',
     'Cotrimoxazole 960mg OD\n(Septran)',
     'Dapsone 100mg OD',
     'Start when CD4 < 200;\nalso covers Toxoplasma prophylaxis',
     'Until CD4 > 200\nfor 3 months'),
]

WARNING_NOTES = [
    ('⚠ Fluoroquinolone Resistance', 'E. coli FQ resistance >60–70% in many Indian cities. Avoid empirical FQ for uncomplicated UTI.'),
    ('⚠ Typhoid Resistance', 'Nalidixic acid-resistant S. Typhi common. Cefixime or Azithromycin preferred over Ciprofloxacin for enteric fever.'),
    ('⚠ FDC Combinations', 'Fixed-dose combinations (e.g. Ofloxacin+Ornidazole) are popular in India but often irrational. Use only when both components are genuinely indicated.'),
    ('⚠ Duration Matters', 'Complete full antibiotic course. Stopping early causes resistance. Monitor for C. difficile with prolonged broad-spectrum use.'),
    ('⚠ Pregnancy Caution', 'Avoid: Fluoroquinolones, Tetracyclines, TMP-SMX (1st trimester), Nitrofurantoin (3rd trimester), Metronidazole (1st trimester).'),
    ('⚠ Culture First', 'Send swab/urine/blood culture before starting antibiotics whenever feasible. Adjust therapy based on sensitivity reports.'),
]


def section_header(text, bg_color, styles):
    data = [[Paragraph(text, styles['section_title'])]]
    t = Table(data, colWidths=[W - 3*cm])
    t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), bg_color),
        ('LEFTPADDING', (0,0), (-1,-1), 10),
        ('RIGHTPADDING', (0,0), (-1,-1), 10),
        ('TOPPADDING', (0,0), (-1,-1), 6),
        ('BOTTOMPADDING', (0,0), (-1,-1), 6),
        ('ROUNDEDCORNERS', [4,4,4,4]),
    ]))
    return t


def make_table(data_rows, styles, col_widths=None):
    S = styles
    if col_widths is None:
        col_widths = [4.5*cm, 4.8*cm, 4.8*cm, 5.2*cm, 2.1*cm]

    header_row = [
        Paragraph('<b>Infection</b>', S['cell_bold']),
        Paragraph('<b>First-Line Drug(s)</b>', S['cell_bold']),
        Paragraph('<b>Alternative</b>', S['cell_bold']),
        Paragraph('<b>Notes / Special Populations</b>', S['cell_bold']),
        Paragraph('<b>Duration</b>', S['cell_bold']),
    ]
    rows = [header_row]

    for i, (inf, first, alt, notes, dur) in enumerate(data_rows):
        row = [
            Paragraph(inf, S['cell_bold']),
            Paragraph(first.replace('\n', '<br/>'), S['drug_first']),
            Paragraph(alt.replace('\n', '<br/>'), S['drug_alt']),
            Paragraph(notes.replace('\n', '<br/>'), S['cell_body']),
            Paragraph(dur.replace('\n', '<br/>'), S['cell_body']),
        ]
        rows.append(row)

    t = Table(rows, colWidths=col_widths, repeatRows=1)

    style_cmds = [
        ('BACKGROUND', (0,0), (-1,0), DARK_NAVY),
        ('TEXTCOLOR', (0,0), (-1,0), colors.white),
        ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
        ('FONTSIZE', (0,0), (-1,0), 8.5),
        ('TOPPADDING', (0,0), (-1,0), 6),
        ('BOTTOMPADDING', (0,0), (-1,0), 6),
        ('GRID', (0,0), (-1,-1), 0.4, BORDER_GREY),
        ('VALIGN', (0,0), (-1,-1), 'TOP'),
        ('TOPPADDING', (0,1), (-1,-1), 5),
        ('BOTTOMPADDING', (0,1), (-1,-1), 5),
        ('LEFTPADDING', (0,0), (-1,-1), 6),
        ('RIGHTPADDING', (0,0), (-1,-1), 6),
        ('ROWBACKGROUNDS', (0,1), (-1,-1), [ROW_NORM, ROW_ALT]),
        ('LINEBELOW', (0,0), (-1,0), 1.5, MED_BLUE),
    ]
    t.setStyle(TableStyle(style_cmds))
    return t


def make_warning_table(styles):
    S = styles
    header = [Paragraph('<b>⚠  IMPORTANT WARNINGS &amp; INDIA-SPECIFIC NOTES</b>', S['section_title'])]
    header_row = [header]

    rows_data = []
    for title, note in WARNING_NOTES:
        rows_data.append([
            Paragraph(f'<b>{title}</b>', ParagraphStyle('wt', fontName='Helvetica-Bold', fontSize=8, textColor=ACCENT_RED, leading=11)),
            Paragraph(note, ParagraphStyle('wn', fontName='Helvetica', fontSize=8, textColor=TEXT_DARK, leading=11)),
        ])

    header_t = Table(header_row, colWidths=[W - 3*cm])
    header_t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), ACCENT_RED),
        ('LEFTPADDING', (0,0), (-1,-1), 10),
        ('TOPPADDING', (0,0), (-1,-1), 6),
        ('BOTTOMPADDING', (0,0), (-1,-1), 6),
    ]))

    warn_t = Table(rows_data, colWidths=[5.2*cm, 16.0*cm])
    warn_t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), RED_LIGHT),
        ('GRID', (0,0), (-1,-1), 0.4, HexColor('#fca5a5')),
        ('VALIGN', (0,0), (-1,-1), 'TOP'),
        ('TOPPADDING', (0,0), (-1,-1), 5),
        ('BOTTOMPADDING', (0,0), (-1,-1), 5),
        ('LEFTPADDING', (0,0), (-1,-1), 8),
        ('RIGHTPADDING', (0,0), (-1,-1), 8),
    ]))
    return header_t, warn_t


def make_legend_table(styles):
    S = styles
    legend_items = [
        (ACCENT_GREEN, 'First-Line Drug', 'Preferred empirical choice per Indian treatment guidelines'),
        (ACCENT_TEAL, 'Alternative Drug', 'Used when first-line is contraindicated, fails, or causes allergy'),
        (TEXT_MED, 'Third-Line / Note', 'Reserve for specific indications; check sensitivity'),
    ]
    rows = []
    for color, label, desc in legend_items:
        swatch = Table([['']], colWidths=[1*cm], rowHeights=[0.5*cm])
        swatch.setStyle(TableStyle([('BACKGROUND', (0,0), (0,0), color), ('BOX', (0,0), (0,0), 0.5, colors.white)]))
        rows.append([
            swatch,
            Paragraph(f'<b>{label}</b>', ParagraphStyle('ll', fontName='Helvetica-Bold', fontSize=8, textColor=color, leading=11)),
            Paragraph(desc, ParagraphStyle('ld', fontName='Helvetica', fontSize=7.5, textColor=TEXT_MED, leading=10)),
        ])

    t = Table(rows, colWidths=[1.2*cm, 4*cm, 12*cm])
    t.setStyle(TableStyle([
        ('VALIGN', (0,0), (-1,-1), 'MIDDLE'),
        ('TOPPADDING', (0,0), (-1,-1), 3),
        ('BOTTOMPADDING', (0,0), (-1,-1), 3),
        ('LEFTPADDING', (0,0), (-1,-1), 4),
    ]))
    return t


# ── COVER PAGE ─────────────────────────────────────────────────────────────────
def make_cover(styles):
    elements = []
    # Big spacing for visual balance
    elements.append(Spacer(1, 3*cm))

    # Main title block
    cover_title_data = [[
        Paragraph('ANTIBIOTIC', ParagraphStyle('ct1', fontName='Helvetica-Bold', fontSize=38, textColor=colors.white, leading=42, alignment=TA_CENTER)),
    ]]
    cover_title_data2 = [[
        Paragraph('QUICK REFERENCE GUIDE', ParagraphStyle('ct2', fontName='Helvetica-Bold', fontSize=22, textColor=HexColor('#93c5fd'), leading=26, alignment=TA_CENTER)),
    ]]

    t1 = Table(cover_title_data, colWidths=[W - 3*cm])
    t1.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), DARK_NAVY),
        ('TOPPADDING', (0,0), (-1,-1), 18),
        ('BOTTOMPADDING', (0,0), (-1,-1), 0),
        ('LEFTPADDING', (0,0), (-1,-1), 20),
    ]))
    t2 = Table(cover_title_data2, colWidths=[W - 3*cm])
    t2.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), DARK_NAVY),
        ('TOPPADDING', (0,0), (-1,-1), 0),
        ('BOTTOMPADDING', (0,0), (-1,-1), 18),
        ('LEFTPADDING', (0,0), (-1,-1), 20),
    ]))
    elements.append(t1)
    elements.append(t2)
    elements.append(Spacer(1, 0.5*cm))

    # Subtitle bar
    sub_data = [[Paragraph('India General Practice  |  Selection by Infection Type  |  Edition 2025–26',
        ParagraphStyle('csub', fontName='Helvetica', fontSize=12, textColor=DARK_NAVY, leading=16, alignment=TA_CENTER))]]
    sub_t = Table(sub_data, colWidths=[W - 3*cm])
    sub_t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), LIGHT_BLUE),
        ('TOPPADDING', (0,0), (-1,-1), 10),
        ('BOTTOMPADDING', (0,0), (-1,-1), 10),
    ]))
    elements.append(sub_t)
    elements.append(Spacer(1, 1*cm))

    # Contents list
    sections = [
        ('🫁', 'Respiratory Tract Infections', 'URTI, pharyngitis, sinusitis, CAP, AECB, atypical pneumonia'),
        ('🔬', 'Urinary Tract Infections', 'Cystitis, pyelonephritis, UTI in pregnancy, prophylaxis'),
        ('🍽', 'Gastrointestinal Infections', 'Typhoid, amoebiasis, H. pylori, diarrhea, cholera'),
        ('🩺', 'Sexually Transmitted Infections', 'Chlamydia, gonorrhea, BV, trichomoniasis, PID'),
        ('🩹', 'Skin & Soft Tissue Infections', 'Cellulitis, MRSA, impetigo, diabetic foot, acne, bites'),
        ('🦴', 'Bone & Joint Infections', 'Osteomyelitis (MSSA/MRSA), septic arthritis'),
        ('🌡', 'Tropical & Endemic Diseases', 'Scrub typhus, leptospirosis, brucellosis, malaria'),
        ('📋', 'Miscellaneous', 'Dental, HE prophylaxis, SIBO, PCP prophylaxis'),
    ]

    toc_rows = []
    for icon, section, detail in sections:
        toc_rows.append([
            Paragraph(icon, ParagraphStyle('icon', fontName='Helvetica-Bold', fontSize=14, leading=18, alignment=TA_CENTER)),
            Paragraph(f'<b>{section}</b><br/><font size="8" color="#64748b">{detail}</font>',
                ParagraphStyle('toc_item', fontName='Helvetica', fontSize=10, leading=15, textColor=DARK_NAVY)),
        ])

    toc_t = Table(toc_rows, colWidths=[1.2*cm, W - 3*cm - 1.2*cm])
    toc_t.setStyle(TableStyle([
        ('VALIGN', (0,0), (-1,-1), 'MIDDLE'),
        ('TOPPADDING', (0,0), (-1,-1), 6),
        ('BOTTOMPADDING', (0,0), (-1,-1), 6),
        ('LEFTPADDING', (0,0), (-1,-1), 8),
        ('ROWBACKGROUNDS', (0,0), (-1,-1), [LIGHT_BLUE, colors.white]),
        ('BOX', (0,0), (-1,-1), 0.5, BORDER_GREY),
        ('LINEBELOW', (0,0), (-1,-1), 0.3, BORDER_GREY),
    ]))
    elements.append(toc_t)
    elements.append(Spacer(1, 1*cm))

    # Disclaimer
    disc = Paragraph(
        '<b>Disclaimer:</b> This guide is for educational reference only. Always prescribe antibiotics based on clinical '
        'assessment, local resistance patterns, allergy history, and culture/sensitivity reports where available. '
        'Drug doses may vary by weight, renal/hepatic function, and patient age. Refer to current NCDC/WHO/institutional '
        'guidelines for definitive treatment protocols.',
        ParagraphStyle('disc', fontName='Helvetica-Oblique', fontSize=7.5, textColor=TEXT_MED, leading=11)
    )
    disc_t = Table([[disc]], colWidths=[W - 3*cm])
    disc_t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), AMBER_LIGHT),
        ('BOX', (0,0), (-1,-1), 0.8, ACCENT_AMBER),
        ('TOPPADDING', (0,0), (-1,-1), 8),
        ('BOTTOMPADDING', (0,0), (-1,-1), 8),
        ('LEFTPADDING', (0,0), (-1,-1), 10),
        ('RIGHTPADDING', (0,0), (-1,-1), 10),
    ]))
    elements.append(disc_t)
    elements.append(PageBreak())
    return elements


# ── MAIN BUILD ─────────────────────────────────────────────────────────────────
def build_pdf():
    outpath = '/tmp/workspace/antibiotic-guide/Antibiotic_Quick_Reference_India.pdf'

    doc = BaseDocTemplate(
        outpath, pagesize=A4,
        leftMargin=1.5*cm, rightMargin=1.5*cm,
        topMargin=2.2*cm, bottomMargin=1.5*cm,
        title='Antibiotic Quick Reference Guide – India',
        author='General Practice Reference',
        subject='Antibiotic selection by infection type',
    )

    # COVER page (no header/footer) – using a blank template
    cover_frame = Frame(0, 0, W, H, leftPadding=1.5*cm, rightPadding=1.5*cm,
                        topPadding=1.5*cm, bottomPadding=1.5*cm)
    cover_template = PageTemplate(id='Cover', frames=[cover_frame])
    cover_template.beforeDrawPage = lambda c, d: (
        c.setFillColor(HEADER_BG),
        c.rect(0, 0, W, H, fill=1, stroke=0),
        c.setFillColor(MED_BLUE),
        c.rect(0, 0, W, 8, fill=1, stroke=0),
        c.rect(0, H - 8, W, 8, fill=1, stroke=0),
    )

    # Content pages
    content_frame = Frame(
        1.5*cm, 1.5*cm,
        W - 3*cm, H - 3.8*cm,   # leave room for header + footer
        leftPadding=0, rightPadding=0,
        topPadding=0, bottomPadding=0
    )
    content_template = PageTemplate(id='Content', frames=[content_frame], onPage=make_header)

    doc.addPageTemplates([cover_template, content_template])

    styles = build_styles()
    elems = []

    # Cover
    elems.extend(make_cover(styles))

    # Switch to content template
    from reportlab.platypus import NextPageTemplate
    elems.append(NextPageTemplate('Content'))

    def section(title, bg, data, extra_space=True):
        block = []
        block.append(section_header(title, bg, styles))
        block.append(make_table(data, styles))
        if extra_space:
            block.append(Spacer(1, 0.4*cm))
        return KeepTogether(block[:2]) if len(data) <= 3 else block

    # LEGEND
    legend_title_data = [[Paragraph('<b>COLOR LEGEND</b>', styles['section_title'])]]
    legend_header_t = Table(legend_title_data, colWidths=[W - 3*cm])
    legend_header_t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), DARK_NAVY),
        ('LEFTPADDING', (0,0), (-1,-1), 10),
        ('TOPPADDING', (0,0), (-1,-1), 5),
        ('BOTTOMPADDING', (0,0), (-1,-1), 5),
    ]))
    legend_content_t = make_legend_table(styles)
    legend_wrap = Table([[legend_content_t]], colWidths=[W - 3*cm])
    legend_wrap.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), HexColor('#f1f5f9')),
        ('BOX', (0,0), (-1,-1), 0.5, BORDER_GREY),
        ('TOPPADDING', (0,0), (-1,-1), 4),
        ('BOTTOMPADDING', (0,0), (-1,-1), 4),
    ]))
    elems.append(KeepTogether([legend_header_t, legend_wrap]))
    elems.append(Spacer(1, 0.4*cm))

    # 1. Respiratory
    s = section('🫁  RESPIRATORY TRACT INFECTIONS', MED_BLUE, RESPIRATORY_DATA)
    if isinstance(s, list): elems.extend(s)
    else: elems.append(s)

    # 2. UTI
    s = section('🔬  URINARY TRACT INFECTIONS', ACCENT_TEAL, UTI_DATA)
    if isinstance(s, list): elems.extend(s)
    else: elems.append(s)

    # 3. GI
    s = section('🍽  GASTROINTESTINAL INFECTIONS', ACCENT_AMBER, GI_DATA)
    if isinstance(s, list): elems.extend(s)
    else: elems.append(s)

    # 4. STI
    s = section('🩺  SEXUALLY TRANSMITTED INFECTIONS', ACCENT_PURPLE, STI_DATA)
    if isinstance(s, list): elems.extend(s)
    else: elems.append(s)

    # 5. Skin
    s = section('🩹  SKIN &amp; SOFT TISSUE INFECTIONS', ACCENT_ORANGE, SKIN_DATA)
    if isinstance(s, list): elems.extend(s)
    else: elems.append(s)

    # 6. Bone
    s = section('🦴  BONE &amp; JOINT INFECTIONS', HexColor('#b45309'), BONE_DATA)
    if isinstance(s, list): elems.extend(s)
    else: elems.append(s)

    # 7. Tropical
    s = section('🌡  TROPICAL &amp; ENDEMIC DISEASES (India)', HexColor('#0e7490'), TROPICAL_DATA)
    if isinstance(s, list): elems.extend(s)
    else: elems.append(s)

    # 8. Misc
    s = section('📋  MISCELLANEOUS', HexColor('#4338ca'), MISC_DATA)
    if isinstance(s, list): elems.extend(s)
    else: elems.append(s)

    # Warnings
    w_header, w_body = make_warning_table(styles)
    elems.append(Spacer(1, 0.2*cm))
    elems.append(w_header)
    elems.append(w_body)
    elems.append(Spacer(1, 0.4*cm))

    # Final note
    final_note = Paragraph(
        '<b>Key References:</b> NCDC National Treatment Guidelines for Antimicrobial Use in Infectious Diseases (India) | '
        'WHO AWaRe Classification 2023 | KD Tripathi Essentials of Medical Pharmacology 9th Ed. | '
        'Harrison\'s Principles of Internal Medicine 22E (2025)',
        ParagraphStyle('fnote', fontName='Helvetica-Oblique', fontSize=7, textColor=TEXT_LIGHT, leading=10)
    )
    final_t = Table([[final_note]], colWidths=[W - 3*cm])
    final_t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), HexColor('#f8fafc')),
        ('BOX', (0,0), (-1,-1), 0.4, BORDER_GREY),
        ('TOPPADDING', (0,0), (-1,-1), 6),
        ('BOTTOMPADDING', (0,0), (-1,-1), 6),
        ('LEFTPADDING', (0,0), (-1,-1), 8),
        ('RIGHTPADDING', (0,0), (-1,-1), 8),
    ]))
    elems.append(final_t)

    doc.build(elems, canvasmaker=NumberedCanvas)
    print(f'PDF saved to: {outpath}')
    return outpath


if __name__ == '__main__':
    path = build_pdf()
    print(f'SUCCESS: {path}')

from reportlab.lib.pagesizes import A4
from reportlab.lib import colors
from reportlab.lib.styles import ParagraphStyle
from reportlab.lib.units import cm
from reportlab.platypus import (
    SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle,
    KeepTogether, PageBreak, NextPageTemplate, BaseDocTemplate,
    PageTemplate, Frame
)
from reportlab.lib.enums import TA_CENTER, TA_LEFT
from reportlab.lib.colors import HexColor
from reportlab.pdfgen import canvas

# ── Palette ────────────────────────────────────────────────────────────────────
DARK_NAVY     = HexColor('#0f172a')
NAVY2         = HexColor('#1e3a5f')
MED_BLUE      = HexColor('#1d4ed8')
LIGHT_BLUE    = HexColor('#dbeafe')
ACCENT_TEAL   = HexColor('#0f766e')
TEAL_LIGHT    = HexColor('#ccfbf1')
ACCENT_RED    = HexColor('#b91c1c')
RED_LIGHT     = HexColor('#fee2e2')
ACCENT_AMBER  = HexColor('#b45309')
AMBER_LIGHT   = HexColor('#fef3c7')
ACCENT_GREEN  = HexColor('#15803d')
GREEN_LIGHT   = HexColor('#dcfce7')
ACCENT_PURPLE = HexColor('#6d28d9')
PURPLE_LIGHT  = HexColor('#ede9fe')
ACCENT_ORANGE = HexColor('#c2410c')
ORANGE_LIGHT  = HexColor('#ffedd5')
ACCENT_ROSE   = HexColor('#be123c')
ROSE_LIGHT    = HexColor('#ffe4e6')
ACCENT_CYAN   = HexColor('#0e7490')
CYAN_LIGHT    = HexColor('#cffafe')
ACCENT_LIME   = HexColor('#4d7c0f')
LIME_LIGHT    = HexColor('#ecfccb')
HEADER_BG     = HexColor('#0f172a')
ROW_ALT       = HexColor('#f8fafc')
ROW_NORM      = HexColor('#ffffff')
BORDER_GREY   = HexColor('#cbd5e1')
TEXT_DARK     = HexColor('#1e293b')
TEXT_MED      = HexColor('#475569')
TEXT_LIGHT    = HexColor('#94a3b8')
W, H = A4


# ── Numbered Canvas ────────────────────────────────────────────────────────────
class NumberedCanvas(canvas.Canvas):
    def __init__(self, *args, **kwargs):
        canvas.Canvas.__init__(self, *args, **kwargs)
        self._saved_page_states = []

    def showPage(self):
        self._saved_page_states.append(dict(self.__dict__))
        self._startPage()

    def save(self):
        num_pages = len(self._saved_page_states)
        for state in self._saved_page_states:
            self.__dict__.update(state)
            self.draw_footer(num_pages)
            canvas.Canvas.showPage(self)
        canvas.Canvas.save(self)

    def draw_footer(self, page_count):
        self.setFillColor(HEADER_BG)
        self.rect(0, 0, W, 22, fill=1, stroke=0)
        self.setFillColor(colors.white)
        self.setFont('Helvetica', 7.5)
        self.drawString(20, 7, 'Parenteral Antibiotic Quick Reference Guide – India Hospital Practice')
        self.drawRightString(W - 20, 7, f'Page {self._pageNumber} of {page_count}')
        self.setStrokeColor(ACCENT_RED)
        self.setLineWidth(2)
        self.line(0, 22, W, 22)


def make_header(c, doc):
    c.saveState()
    c.setFillColor(HEADER_BG)
    c.rect(0, H - 54, W, 54, fill=1, stroke=0)
    c.setFillColor(ACCENT_RED)
    c.rect(0, H - 57, W, 3, fill=1, stroke=0)
    c.setFillColor(colors.white)
    c.setFont('Helvetica-Bold', 15)
    c.drawString(20, H - 33, 'PARENTERAL ANTIBIOTIC QUICK REFERENCE GUIDE')
    c.setFont('Helvetica', 8.5)
    c.setFillColor(HexColor('#94a3b8'))
    c.drawString(20, H - 48, 'India Hospital / ICU Practice  |  IV/IM Selection by Infection Type  |  2025–26')
    c.restoreState()


# ── Styles ─────────────────────────────────────────────────────────────────────
def build_styles():
    S = {}
    S['sec_title'] = ParagraphStyle('SecTitle', fontName='Helvetica-Bold',
        fontSize=10.5, textColor=colors.white, leading=14)
    S['cell_bold'] = ParagraphStyle('CellBold', fontName='Helvetica-Bold',
        fontSize=8, textColor=DARK_NAVY, leading=11)
    S['cell_body'] = ParagraphStyle('CellBody', fontName='Helvetica',
        fontSize=7.5, textColor=TEXT_DARK, leading=11, spaceAfter=1)
    S['drug_first'] = ParagraphStyle('DrugFirst', fontName='Helvetica-Bold',
        fontSize=8, textColor=ACCENT_GREEN, leading=11)
    S['drug_alt'] = ParagraphStyle('DrugAlt', fontName='Helvetica',
        fontSize=7.5, textColor=ACCENT_TEAL, leading=11)
    S['warn_title'] = ParagraphStyle('WarnTitle', fontName='Helvetica-Bold',
        fontSize=7.5, textColor=ACCENT_RED, leading=10)
    S['warn_body'] = ParagraphStyle('WarnBody', fontName='Helvetica',
        fontSize=7.5, textColor=TEXT_DARK, leading=10)
    S['dose_tag'] = ParagraphStyle('DoseTag', fontName='Helvetica-Bold',
        fontSize=7, textColor=ACCENT_AMBER, leading=10)
    return S


# ── DATA ───────────────────────────────────────────────────────────────────────
# Columns: Infection | First-Line IV/IM + Dose + Brand | Alternative | Notes | Route/Freq/Duration

RESP_DATA = [
    ('Severe CAP\n(Hospitalized, non-ICU)',
     'Co-amoxiclav 1.2g IV 8-hrly\n(Augmentin IV, Amoxyclav IV)\n+ Azithromycin 500mg IV OD\n(Azithral IV)',
     'Ceftriaxone 1–2g IV OD\n(Monocef, Oframax)\n+ Azithromycin 500mg IV OD',
     'Atypical coverage mandatory;\nswitch to oral after 48–72h\nclinical improvement',
     'IV → Oral step-down\nat 48–72 h\n5–7 days total'),
    ('Severe CAP\n(ICU / Ventilated)',
     'Piperacillin-Tazobactam 4.5g\nIV 6-hrly (Tazact, Pipcin-TZ)\n+ Levofloxacin 500mg IV OD\n(Glevo IV)',
     'Meropenem 1g IV 8-hrly\n(Meromer, Meronem)\n+ Azithromycin 500mg IV',
     'Add Vancomycin if MRSA\npneumonia suspected;\ncheck PCT/CRP to guide duration',
     '7–10 days IV\n(reassess at 72h)'),
    ('Hospital-Acquired\nPneumonia (HAP)',
     'Piperacillin-Tazobactam 4.5g\nIV 6-hrly (Tazact)',
     'Meropenem 1g IV 8-hrly\n(Meromer)\n± Vancomycin 15mg/kg IV\n8-hrly (Vancorid)',
     'Anti-pseudomonal cover\nmandatory; de-escalate based\non culture in 48–72h',
     '7–8 days\n(avoid prolonging)'),
    ('Aspiration Pneumonia',
     'Piperacillin-Tazobactam 4.5g\nIV 6-hrly (Tazact)',
     'Ceftriaxone 1g IV OD +\nMetronidazole 500mg IV 8-hrly\n(Metrogyl IV)',
     'Anaerobic cover essential;\nnot all aspiration episodes\nneed antibiotics',
     '5–7 days'),
    ('Lung Abscess',
     'Amoxiclav 1.2g IV 8-hrly\n(Augmentin IV)',
     'Piperacillin-Tazobactam 4.5g\nIV 6-hrly + Metronidazole\n500mg IV 8-hrly',
     'Long course needed;\nswitch to oral Amoxiclav\nafter initial IV response',
     'IV 2–3 wks then\noral 4–6 wks total'),
    ('Pleural Empyema',
     'Piperacillin-Tazobactam 4.5g\nIV 6-hrly (Tazact)',
     'Ceftriaxone 2g IV OD +\nMetronidazole 500mg IV 8-hrly',
     'Drainage (ICD/VATS) mandatory;\nantibiotics adjunctive',
     '4–6 weeks total'),
]

UTI_DATA = [
    ('Acute Pyelonephritis\n(Moderate)',
     'Ceftriaxone 1–2g IV OD\n(Monocef, Oframax)',
     'Ciprofloxacin 400mg IV BD\n(Ciplox IV)\n[if sensitivity confirmed]',
     'E. coli FQ resistance\n>60% empirically in India;\nstep down to oral after 48–72h',
     'IV 3–5 days then\noral 7–14 days total'),
    ('Complicated UTI /\nUrosepsis',
     'Piperacillin-Tazobactam 4.5g\nIV 6-hrly (Tazact)',
     'Meropenem 1g IV 8-hrly\n(Meromer) if ESBL suspected',
     'ESBL common in India;\nAvoid Cephalosporins for\nESBL-producing organisms',
     '10–14 days\n(IV until afebrile)'),
    ('Catheter-Associated\nUTI (CA-UTI)',
     'Based on culture/sensitivity\n(Ceftriaxone empirically\nif Gram-neg)',
     'Meropenem 1g IV 8-hrly if\nESBL/Carbapenem-sensitive',
     'Remove/change catheter first;\ndon\'t treat asymptomatic\nbacteriuria in catheterised pts',
     '7 days\n(symptomatic)'),
    ('Candidal UTI\n(Candiduria)',
     'Fluconazole 200–400mg IV\nthen oral (Zocon IV)',
     'Amphotericin B 0.3–0.6mg/kg\nIV OD (Fungizone) if resistant',
     'Treat only if symptomatic\nor immunocompromised;\nremove catheter if possible',
     '14 days'),
]

SEPSIS_DATA = [
    ('Sepsis (Unknown\nSource – Empirical)',
     'Piperacillin-Tazobactam 4.5g\nIV 6-hrly (Tazact)\n± Gentamicin 5mg/kg IV OD\n(Garamycin)',
     'Meropenem 1g IV 8-hrly\n(Meromer) + Vancomycin\n15mg/kg IV 8-hrly',
     'De-escalate in 48–72h based\non cultures; follow Sepsis-3\nprotocol; measure lactate',
     'Minimum 5–7 days;\nde-escalate early'),
    ('Septic Shock\n(ICU)',
     'Meropenem 2g IV 8-hrly\n(Meromer) + Vancomycin\n25–30mg/kg loading then\n15mg/kg 8-hrly (Vancorid)',
     'Cefoperazone-Sulbactam 3g\nIV 12-hrly (Magnex-Forte)\n+ Colistin (if pan-resistant)',
     'Source control paramount;\nprocalcitonin-guided\nde-escalation recommended',
     '7–10 days\n(guided by PCT)'),
    ('Bacteremia / Primary\nBloodstream Infection',
     'Based on blood culture\n(empirical: Vancomycin IV\n+ Piperacillin-Tazobactam IV)',
     'Teicoplanin 400mg IV\nOD (Targocid) if MRSA',
     'Two sets blood cultures before\nstarting; echocardiogram if\nS. aureus bacteremia',
     'S. aureus: 14 days;\nother organisms: 7–14 days'),
    ('Neutropenic Fever\n(Febrile Neutropenia)',
     'Piperacillin-Tazobactam 4.5g\nIV 6-hrly (Tazact)',
     'Cefepime 2g IV 8-hrly\n(Cefepim) or Meropenem 1g\nIV 8-hrly if unstable',
     'Add Vancomycin if skin\ninfection/catheter infection;\nadd Antifungal after 72–96h fever',
     'Until ANC >500;\nmin 7 days'),
]

CNS_DATA = [
    ('Bacterial Meningitis\n(Community-acquired adult)',
     'Ceftriaxone 2g IV 12-hrly\n(Monocef 2g)',
     'Chloramphenicol 1g IV 6-hrly\n(Enteromycetin)\n[if Cephalosporin allergy]',
     'Add Dexamethasone 0.15mg/kg\nIV 6-hrly x4 days (1st dose\nbefore/with antibiotic)\nEmpiric Ampicillin if Listeria risk (elderly/immuno)',
     '10–14 days\n(S. pneumoniae)\n21 days (Listeria)'),
    ('Bacterial Meningitis\n(Post-neurosurgery / Trauma)',
     'Meropenem 2g IV 8-hrly\n(Meromer) + Vancomycin\n15mg/kg IV 8-hrly (Vancorid)',
     'Cefepime 2g IV 8-hrly +\nVancomycin 15mg/kg IV 8-hrly',
     'Gram-negatives and\nS. aureus most common;\nAcinetobacter frequent in ICU\nNeurosurgery settings',
     '14–21 days\n(based on organism)'),
    ('Brain Abscess',
     'Ceftriaxone 2g IV 12-hrly +\nMetronidazole 500mg IV 8-hrly\n(Metrogyl IV)',
     'Meropenem 2g IV 8-hrly\n+ Vancomycin (if MRSA risk)',
     'Neurosurgical drainage often\nrequired; prolong IV 4–6 weeks;\nfollow MRI response',
     '4–6 weeks IV'),
    ('Tuberculous Meningitis\n(TBM)',
     'HRZE regimen (Isoniazid +\nRifampicin + Pyrazinamide +\nEthambutol) – 2 months\nthen HR x10 months',
     'Dexamethasone IV adjunctive\n0.3–0.4mg/kg tapered over 8 wks',
     'Add Pyridoxine with INH;\nSteroids reduce mortality;\nDrug interactions with antiretrovirals',
     '12 months total\nfor TBM'),
]

ABDOMINAL_DATA = [
    ('Intra-abdominal Sepsis /\nSecondary Peritonitis',
     'Piperacillin-Tazobactam 4.5g\nIV 6-hrly (Tazact)',
     'Ceftriaxone 2g IV OD +\nMetronidazole 500mg IV 8-hrly\n(Metrogyl IV)',
     'Source control (surgery/drainage)\nmandatory; anaerobic coverage\nessential for colonic perforation',
     '4–7 days\n(after source control)'),
    ('Acute Cholecystitis /\nCholangitis',
     'Piperacillin-Tazobactam 4.5g\nIV 6-hrly (Tazact)',
     'Ceftriaxone 2g IV OD +\nMetronidazole 500mg IV 8-hrly',
     'Tokyo Guidelines severity:\nGrade III – early biliary\ndrainage + IV antibiotics',
     '4–7 days\n(mild–moderate)'),
    ('Liver Abscess\n(Pyogenic)',
     'Ceftriaxone 2g IV OD +\nMetronidazole 500mg IV 8-hrly\n(Metrogyl IV)',
     'Piperacillin-Tazobactam 4.5g\nIV 6-hrly',
     'Drainage (percutaneous)\nfor >5cm abscess; E. coli most\ncommon organism in India',
     'IV 2–3 weeks then\noral 4–6 weeks'),
    ('Amoebic Liver Abscess\n(Severe)',
     'Metronidazole 500mg IV\n8-hrly (Metrogyl IV)',
     'Tinidazole IV if available\n(Tinidazole 800mg IV BD)',
     'Most respond to medical\ntherapy; drainage only if\n>10cm or left lobe/impending rupture',
     'IV 7–10 days then\noral completion'),
    ('Spontaneous Bacterial\nPeritonitis (SBP)',
     'Cefotaxime 2g IV 8-hrly\n(Claforan) or Ceftriaxone\n2g IV OD (Monocef)',
     'Piperacillin-Tazobactam 4.5g\nIV 6-hrly if nosocomial SBP',
     'Give IV Albumin 1.5g/kg\nDay 1 + 1g/kg Day 3;\nreduces renal failure/mortality;\nPrimary prophylaxis: Norfloxacin\n400mg OD (in Child-Pugh C)',
     '5 days IV'),
    ('Typhoid with\nComplications',
     'Ceftriaxone 2g IV OD\n(Monocef, Oframax)',
     'Azithromycin 500mg IV OD\n(Azithral IV)',
     'IV for all complicated\ntyphoid; intestinal perforation\nrequires surgery + broad-spectrum\ncover (add Metronidazole)',
     '10–14 days IV'),
]

BONE_DATA = [
    ('Acute Osteomyelitis\n(Haematogenous)',
     'Cloxacillin 2g IV 6-hrly\n(Cloxacillin inj) – MSSA\nor Cefazolin 2g IV 8-hrly',
     'Vancomycin 15–20mg/kg\nIV 8-hrly (Vancorid) – if\nMRSA suspected',
     'S. aureus most common;\nMRI for diagnosis; bone biopsy\nbefore starting if possible;\nseek orthopedic input',
     'IV 4–6 weeks\nthen oral step-down'),
    ('Diabetic Foot\nOsteomyelitis (MSSA)',
     'Cloxacillin 2g IV 6-hrly +\nMetronidazole 500mg IV 8-hrly',
     'Amoxiclav 1.2g IV 8-hrly\n(Augmentin IV)',
     'Vascular assessment;\nbone biopsy for organism ID;\noral step-down with Cloxacillin/\nClindamycin after initial IV response',
     'IV 4–6 weeks total'),
    ('Diabetic Foot\nOsteomyelitis (MRSA)',
     'Vancomycin 15–20mg/kg\nIV 8-hrly (Vancorid)',
     'Linezolid 600mg IV BD\n(Linox IV, Zyvox IV)',
     'Linezolid: monitor CBC weekly;\nexcellent bone bioavailability;\nconsider oral Linezolid for\nstep-down',
     'IV 4–6 weeks;\noral Linezolid step-down'),
    ('Septic Arthritis',
     'Cloxacillin 2g IV 6-hrly\n(MSSA) or Ceftriaxone\n2g IV OD (Gram-neg)',
     'Vancomycin 15mg/kg IV\n8-hrly if MRSA suspected',
     'Drainage (arthrocentesis/\narthroscopy) is primary therapy;\ncontinue until synovial WBC <50k',
     'IV 2–4 weeks;\noral step-down after\nclinical improvement'),
]

SKIN_DATA = [
    ('Severe Cellulitis /\nErysipelas',
     'Cloxacillin 2g IV 6-hrly\n(MSSA)',
     'Cefazolin 2g IV 8-hrly\nor Amoxiclav 1.2g IV 8-hrly\n(Augmentin IV)',
     'Mark lesion borders;\nIV until fever resolves\nand lesion not progressing;\nstep down to oral Cefalexin',
     'IV 3–5 days then\noral 7–10 days total'),
    ('MRSA Skin/Soft\nTissue Infection (Severe)',
     'Vancomycin 15–20mg/kg\nIV 8-hrly (Vancorid)',
     'Teicoplanin 12mg/kg IV BD\nx3 doses then 6mg/kg OD\n(Targocid)',
     'I&D for abscesses;\nmonitor vancomycin trough\n15–20 mcg/mL; AUC-guided\ndosing preferred',
     '7–14 days'),
    ('Necrotizing Fasciitis',
     'Meropenem 1g IV 8-hrly +\nClindamycin 900mg IV 8-hrly +\nVancomycin 15mg/kg IV 8-hrly',
     'Piperacillin-Tazobactam 4.5g\nIV 6-hrly + Clindamycin\n900mg IV 8-hrly',
     'SURGICAL EMERGENCY:\ndebridement within hours;\nClindamycin inhibits toxin\nproduction (Group A Strep)',
     'IV until wound\nhealed post-surgery'),
    ('Gas Gangrene\n(Clostridial Myonecrosis)',
     'Benzylpenicillin 4MU IV\n4-hrly + Clindamycin\n900mg IV 8-hrly',
     'Meropenem 1g IV 8-hrly +\nClindamycin 900mg IV 8-hrly',
     'SURGICAL EMERGENCY;\namputation may be needed;\nHyperbaric O2 adjunctive;\nClindamycin blocks toxin',
     'IV until wound healed'),
    ('Burns Wound\nInfection',
     'Piperacillin-Tazobactam 4.5g\nIV 6-hrly (Tazact)',
     'Meropenem 1g IV 8-hrly +\nVancomycin 15mg/kg IV 8-hrly',
     'P. aeruginosa most common;\ntopical Silver Sulfadiazine;\nculture-guided adjustment;\nearly enteral nutrition',
     '7–14 days\n(culture-guided)'),
]

CARDIAC_DATA = [
    ('Infective Endocarditis\n(Native Valve – Streptococcal)',
     'Benzylpenicillin 12–18MU\nIV/day in 6 divided doses\n(Crystapen)',
     'Ceftriaxone 2g IV OD\n(Monocef 2g)',
     'Confirm with ECHO;\nDuke criteria for diagnosis;\nadd Gentamicin 1mg/kg IV 8-hrly\nfor synergy in first 2 weeks',
     '4 weeks IV\n(uncomplicated)'),
    ('Infective Endocarditis\n(Staphylococcal / MRSA)',
     'Vancomycin 15–20mg/kg\nIV 8-hrly (Vancorid)',
     'Daptomycin 6–8mg/kg IV OD\n[if available]',
     'Rifampicin 300mg oral BD\nadded for prosthetic valve;\nsurgery if large vegetation\nor heart failure',
     'Native valve: 6 wks\nProsthetic: ≥6 wks'),
    ('Infective Endocarditis\n(HACEK organisms)',
     'Ceftriaxone 2g IV OD\n(Monocef)',
     'Ampicillin-Sulbactam 3g\nIV 6-hrly (Unasyn)',
     'Ampicillin if beta-lactamase\nnegative; FQ alternative\nif cephalosporin-intolerant',
     '4 weeks IV'),
]

MDR_DATA = [
    ('ESBL-Producing\nEnterobacteriaceae',
     'Meropenem 1g IV 8-hrly\n(Meromer, Meronem)',
     'Ertapenem 1g IV OD\n(Invanz) for non-ICU',
     'Do NOT use\nCephalosporins/Piperacillin-\nTazobactam for definitive ESBL\ntreatment; preserve Carbapenems',
     'Based on source\n(UTI: 10–14d;\nSepsis: 14d)'),
    ('Carbapenem-Resistant\nEnterobacteriaceae (CRE/KPC)',
     'Colistin 9MU loading then\n4.5MU IV 12-hrly (Colistin-CMS)\n+ Meropenem 2g IV 8-hrly\n(extended infusion)',
     'Ceftazidime-Avibactam\n2.5g IV 8-hrly (Avycaz)\n[if KPC-producer confirmed]',
     'Nephrotoxicity with Colistin;\nmonitor renal function daily;\ninfection control isolation\nmandatory',
     '14 days minimum'),
    ('Acinetobacter baumannii\n(Pan-Drug Resistant)',
     'Colistin 9MU loading then\n4.5MU IV 12-hrly\n+ Sulbactam 3g IV 6-hrly',
     'Tigecycline 100mg IV loading\nthen 50mg IV 12-hrly\n(Tygacil)',
     'Contact precautions;\ncombination therapy;\nTigecycline NOT for bloodstream;\nAmpicillin-Sulbactam active\nagainst some strains',
     '14–21 days'),
    ('MRSA Bacteremia /\nDeep Infections',
     'Vancomycin 25–30mg/kg\nloading then 15mg/kg IV\n8-hrly (Vancorid)\n[target AUC/MIC >400]',
     'Teicoplanin 12mg/kg IV BD\nx3 then 12mg/kg OD\n(Targocid)',
     'Echocardiogram for all\nS. aureus bacteremia;\nremove all foreign bodies;\nLinezolid for osteoarticular',
     'Bacteremia: 14d\nEndocarditis: 6 wks\nOsteomyelitis: 6 wks'),
    ('Pseudomonas aeruginosa\n(Severe)',
     'Piperacillin-Tazobactam 4.5g\nIV 6-hrly (Tazact)\nor Cefepime 2g IV 8-hrly',
     'Meropenem 1g IV 8-hrly\n(Meromer) + Ciprofloxacin\n400mg IV 12-hrly if sensitive',
     'Combination therapy for\nbacteremia/pneumonia;\nDuration: 7 days minimum\nfor non-severe\n14 days for bacteremia',
     '7–14 days'),
]

SPECIAL_DATA = [
    ('Leptospirosis\n(Severe / Weil\'s Disease)',
     'Benzylpenicillin 1.5MU IV\n6-hrly x7 days (Crystapen)',
     'Ceftriaxone 1g IV OD\n(Monocef)',
     'Most common in India:\nMaharashtra, Kerala post-flood;\nICU for ARDS/renal failure\n(Weil\'s disease)',
     '7 days IV'),
    ('Scrub Typhus\n(Severe / Complicated)',
     'Doxycycline 100mg IV BD\n(IV Doxycycline)',
     'Azithromycin 500mg IV OD\n(Azithral IV) – pregnancy',
     'IV if severe/cannot\ntake orally; switch to oral\ndoxycycline once stable;\nCommon in NE India, Himalayas',
     '7 days'),
    ('Malaria (Severe\nP. falciparum)',
     'Artesunate 2.4mg/kg IV\nat 0, 12, 24h then OD\n(IV Artesunate)',
     'Quinine 20mg/kg IV\nloading then 10mg/kg 8-hrly\n+ Doxycycline IV',
     'Artesunate preferred over\nQuinine (SEAQUAMAT trial);\nICU monitoring: hypoglycemia,\ncerebral malaria, ARDS',
     'IV until oral possible\nthen oral ACT to\ncomplete course'),
    ('Tetanus\n(Adjunctive antibiotics)',
     'Metronidazole 500mg IV\n8-hrly (Metrogyl IV)',
     'Benzylpenicillin 1MU IV\n6-hrly',
     'Antibiotics secondary to\nHuman TIG + wound debridement;\nMetronidazole preferred over\nPenicillin (less convulsant)',
     '7–10 days'),
    ('Cholera\n(Severe / Hospitalized)',
     'Azithromycin 1g IV then\noral (Azithral)',
     'Doxycycline 100mg IV BD\n(IV Doxy)',
     'Aggressive IV rehydration\n(Ringer\'s Lactate) is primary\ntherapy; antibiotics reduce\nduration/shedding',
     'Single dose (adults);\n3 days (children)'),
    ('Rabies Post-Exposure\n(Infected wound antibiotics)',
     'Amoxiclav 1.2g IV 8-hrly\n(Augmentin IV)',
     'Ceftriaxone 1g IV OD\n(Monocef)',
     'Antibiotics for wound infection\nonly – NOT for rabies itself;\nRabies immunoglobulin (RIG) +\nvaccine is the prevention',
     '5–7 days\n(wound prophylaxis)'),
]

OB_GYN_DATA = [
    ('Chorioamnionitis\n(Intrapartum)',
     'Ampicillin 2g IV 6-hrly +\nGentamicin 5mg/kg IV OD',
     'Piperacillin-Tazobactam\n4.5g IV 6-hrly (if polymicrobial)',
     'Continue until\n24–48h afebrile post-delivery;\nClindamycin added if\nC-section done',
     'IV until 24–48h\nafebrile'),
    ('Post-Partum\nEndometritis',
     'Clindamycin 900mg IV 8-hrly\n+ Gentamicin 5mg/kg IV OD\n(Garamycin)',
     'Piperacillin-Tazobactam\n4.5g IV 6-hrly',
     'Most effective regimen per\nCochrane reviews;\ncontinue until 24–48h afebrile',
     'IV until 24–48h\nafebrile, then oral'),
    ('Septic Abortion',
     'Piperacillin-Tazobactam\n4.5g IV 6-hrly (Tazact)',
     'Clindamycin 900mg IV 8-hrly\n+ Gentamicin 5mg/kg IV OD',
     'Surgical evacuation of uterus\nurgent; Clostridium and\nanaerobes coverage critical',
     '7–10 days IV'),
    ('Pre-operative\nProphylaxis (C-section)',
     'Cefazolin 2g IV single dose\n30–60 min before incision',
     'Clindamycin 600mg IV\n(if Pen allergy)',
     'Single dose adequate;\ndo NOT extend postoperatively;\nreduce SSI risk by >50%',
     'Single dose'),
]

WARNING_NOTES = [
    ('⚠ ESBL Epidemic in India',
     'ESBL-producing E. coli and Klebsiella are extremely prevalent. Do NOT use Cephalosporins or Piperacillin-Tazobactam for definitive treatment of confirmed ESBL infections. Carbapenems are the drug of choice.'),
    ('⚠ Vancomycin Dosing',
     'Use AUC/MIC-guided dosing (target AUC 400–600 mg·h/L). Trough-only monitoring is outdated. Load 25–30 mg/kg for seriously ill patients. Monitor renal function daily.'),
    ('⚠ Aminoglycoside Toxicity',
     'Gentamicin and Amikacin are nephrotoxic and ototoxic. Once-daily dosing is preferred. Monitor peak/trough levels; adjust for renal impairment. Avoid in elderly and existing CKD.'),
    ('⚠ Colistin Nephrotoxicity',
     'Colistin causes acute kidney injury in ~50% of patients. Use only as last resort for pan-resistant organisms. Monitor creatinine daily. Hydration and avoidance of other nephrotoxins is critical.'),
    ('⚠ De-escalation Mandatory',
     'Broad-spectrum empirical therapy must be de-escalated within 48–72h based on culture reports. Prolonged broad-spectrum use drives resistance. Follow PCT/CRP to guide antibiotic discontinuation.'),
    ('⚠ Blood Cultures First',
     'Draw TWO sets of blood cultures from DIFFERENT sites before starting antibiotics in all sepsis cases. Never delay antibiotics >1 hour in septic shock, but cultures must be drawn first.'),
    ('⚠ Carbapenem Stewardship',
     'Reserve Meropenem/Imipenem for ESBL, CRE, or severe infections only. Ertapenem can be used for outpatient/non-Pseudomonal coverage. Inappropriate Carbapenem use creates XDR/PDR organisms.'),
]

COMMON_PARENTERALS = [
    ('Benzylpenicillin\n(Penicillin G)', 'Crystapen\n(Pfizer)', 'Meningitis (Strep/Listeria),\nEndocarditis, Gas gangrene, Tetanus', '1–4 MU IV q4–6h'),
    ('Ampicillin', 'Roscillin inj\n(Ranbaxy)', 'Meningitis (Listeria), Chorioamnionitis,\nUTI (step-up)', '0.5–2g IV q6h'),
    ('Cloxacillin', 'Clox inj (Cipla)', 'MSSA osteomyelitis, cellulitis,\nsevere SSTI', '1–2g IV q4–6h'),
    ('Amoxiclav IV', 'Augmentin IV\n(GSK)', 'CAP, intra-abdominal, SSTI,\nbite wounds', '1.2g IV q8h'),
    ('Piperacillin-Tazobactam', 'Tazact (Sun)\nPipcin-TZ (Cipla)', 'Sepsis, HAP, urosepsis, ICU infections\nwith Pseudomonal risk', '4.5g IV q6h'),
    ('Ceftriaxone', 'Monocef (Biochem)\nOframax (Ranbaxy)', 'CAP, meningitis, typhoid, SBP,\nabdominal, bone, gonorrhea', '1–2g IV q12–24h'),
    ('Cefazolin', 'Reflin (Cipla)\nCefazone', 'Surgical prophylaxis, MSSA\nskin/bone (alternative to Cloxacillin)', '1–2g IV q8h'),
    ('Cefotaxime', 'Claforan (Sanofi)\nCefotax (Biochem)', 'SBP, neonatal meningitis,\ngonorrhea, RTI', '1–2g IV q6–8h'),
    ('Ceftazidime', 'Fortum (GSK)\nTazide (Cipla)', 'Pseudomonal infections,\nfebrile neutropenia', '1–2g IV q8h'),
    ('Cefepime', 'Cefipim (Sun)\nMaxipime', 'HAP, febrile neutropenia, UTI\n(Pseudomonal coverage)', '1–2g IV q8–12h'),
    ('Cefoperazone-Sulbactam', 'Magnex-Forte (Pfizer)\nSulbacef (Cipla)', 'ICU infections, HAP, intra-abdominal,\nAcinetobacter (sulbactam activity)', '1.5–3g IV q8–12h'),
    ('Meropenem', 'Meromer (Zydus)\nMeronem (AZ)', 'ESBL, CRE, sepsis, meningitis,\nfebrile neutropenia, HAP', '0.5–2g IV q8h'),
    ('Imipenem-Cilastatin', 'Tienam (MSD)\nImipem (Cipla)', 'Polymicrobial, intra-abdominal,\nICU (avoid CNS infections)', '500mg–1g IV q6–8h'),
    ('Ertapenem', 'Invanz (MSD)', 'ESBL infections, non-pseudomonal\noutpatient IV therapy, diabetic foot', '1g IV/IM q24h'),
    ('Vancomycin', 'Vancorid (Abbott)\nVancotex', 'MRSA, Gram-pos endocarditis,\nC. diff (oral), MRSA meningitis', '15–20mg/kg IV q8–12h\n[AUC-guided]'),
    ('Teicoplanin', 'Targocid (Sanofi)\nTeicomine', 'MRSA, MSSA, VRE (some), endocarditis\nas Vancomycin alternative', '12mg/kg IV BD x3\nthen OD'),
    ('Linezolid IV', 'Linox IV (Cipla)\nZyvox IV (Pfizer)', 'MRSA pneumonia, MRSA SSTI,\nVRE, MDR-TB', '600mg IV q12h'),
    ('Gentamicin', 'Garamycin (Schering)\nGenatcin', 'Sepsis synergy, UTI (Gram-neg),\nchorioamnionitis combination', '5mg/kg IV OD\n[once-daily]'),
    ('Amikacin', 'Amikin (BMS)\nBiklin (Cipla)', 'Gentamicin-resistant Gram-negatives,\nNTM infections', '15–20mg/kg IV OD'),
    ('Metronidazole IV', 'Metrogyl IV (J.B.Chem)\nFlagyl IV (Abbott)', 'Anaerobic infections, peritonitis,\namoebiasis, tetanus adjuvant', '500mg IV q8h'),
    ('Colistin (Polymyxin E)', 'Colistin-CMS\n(Cipla/Sun)', 'XDR Acinetobacter, PDR KPC,\nlast-resort only', '9MU load then\n4.5MU IV q12h'),
    ('Azithromycin IV', 'Azithral IV\n(Alembic)', 'Severe atypical CAP, typhoid IV,\nCampylobacter (hospitalized)', '500mg IV OD'),
]


# ── Helpers ────────────────────────────────────────────────────────────────────
def sec_header(title, bg, styles):
    t = Table([[Paragraph(title, styles['sec_title'])]], colWidths=[W - 3*cm])
    t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), bg),
        ('LEFTPADDING', (0,0), (-1,-1), 10),
        ('TOPPADDING', (0,0), (-1,-1), 6),
        ('BOTTOMPADDING', (0,0), (-1,-1), 6),
    ]))
    return t


def make_table(rows, styles, col_widths=None):
    S = styles
    if col_widths is None:
        col_widths = [4.0*cm, 5.0*cm, 4.6*cm, 5.4*cm, 2.4*cm]
    header = [
        Paragraph('<b>Infection / Indication</b>', S['cell_bold']),
        Paragraph('<b>First-Line IV/IM + Dose + Brand</b>', S['cell_bold']),
        Paragraph('<b>Alternative IV/IM</b>', S['cell_bold']),
        Paragraph('<b>Notes / Cautions</b>', S['cell_bold']),
        Paragraph('<b>Duration</b>', S['cell_bold']),
    ]
    tbl_rows = [header]
    for inf, first, alt, notes, dur in rows:
        tbl_rows.append([
            Paragraph(inf, S['cell_bold']),
            Paragraph(first.replace('\n', '<br/>'), S['drug_first']),
            Paragraph(alt.replace('\n', '<br/>'), S['drug_alt']),
            Paragraph(notes.replace('\n', '<br/>'), S['cell_body']),
            Paragraph(dur.replace('\n', '<br/>'), S['cell_body']),
        ])
    t = Table(tbl_rows, colWidths=col_widths, repeatRows=1)
    t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,0), DARK_NAVY),
        ('TEXTCOLOR', (0,0), (-1,0), colors.white),
        ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
        ('FONTSIZE', (0,0), (-1,0), 8),
        ('TOPPADDING', (0,0), (-1,0), 6),
        ('BOTTOMPADDING', (0,0), (-1,0), 6),
        ('GRID', (0,0), (-1,-1), 0.4, BORDER_GREY),
        ('VALIGN', (0,0), (-1,-1), 'TOP'),
        ('TOPPADDING', (0,1), (-1,-1), 5),
        ('BOTTOMPADDING', (0,1), (-1,-1), 5),
        ('LEFTPADDING', (0,0), (-1,-1), 5),
        ('RIGHTPADDING', (0,0), (-1,-1), 5),
        ('ROWBACKGROUNDS', (0,1), (-1,-1), [ROW_NORM, ROW_ALT]),
        ('LINEBELOW', (0,0), (-1,0), 1.5, ACCENT_RED),
    ]))
    return t


def make_drug_table(styles):
    S = styles
    header_data = [[Paragraph('<b>💊  QUICK REFERENCE: COMMON PARENTERAL ANTIBIOTICS IN INDIA</b>', S['sec_title'])]]
    header_t = Table(header_data, colWidths=[W - 3*cm])
    header_t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), DARK_NAVY),
        ('LEFTPADDING', (0,0), (-1,-1), 10),
        ('TOPPADDING', (0,0), (-1,-1), 6),
        ('BOTTOMPADDING', (0,0), (-1,-1), 6),
    ]))
    col_h = [
        Paragraph('<b>Drug (Generic)</b>', S['cell_bold']),
        Paragraph('<b>India Brand(s)</b>', S['cell_bold']),
        Paragraph('<b>Key Uses</b>', S['cell_bold']),
        Paragraph('<b>Typical IV Dose</b>', S['cell_bold']),
    ]
    rows = [col_h]
    for i, (drug, brand, use, dose) in enumerate(COMMON_PARENTERALS):
        rows.append([
            Paragraph(drug.replace('\n', '<br/>'),
                ParagraphStyle('dr', fontName='Helvetica-Bold', fontSize=7.5, textColor=DARK_NAVY, leading=11)),
            Paragraph(brand.replace('\n', '<br/>'),
                ParagraphStyle('br', fontName='Helvetica', fontSize=7.5, textColor=ACCENT_TEAL, leading=11)),
            Paragraph(use,
                ParagraphStyle('us', fontName='Helvetica', fontSize=7.5, textColor=TEXT_DARK, leading=11)),
            Paragraph(dose.replace('\n', '<br/>'),
                ParagraphStyle('ds', fontName='Helvetica-Bold', fontSize=7.5, textColor=ACCENT_AMBER, leading=11)),
        ])
    t = Table(rows, colWidths=[4.5*cm, 4.0*cm, 8.5*cm, 4.4*cm], repeatRows=1)
    t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,0), NAVY2),
        ('TEXTCOLOR', (0,0), (-1,0), colors.white),
        ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
        ('FONTSIZE', (0,0), (-1,0), 8),
        ('TOPPADDING', (0,0), (-1,0), 6),
        ('BOTTOMPADDING', (0,0), (-1,0), 6),
        ('GRID', (0,0), (-1,-1), 0.4, BORDER_GREY),
        ('VALIGN', (0,0), (-1,-1), 'TOP'),
        ('TOPPADDING', (0,1), (-1,-1), 4),
        ('BOTTOMPADDING', (0,1), (-1,-1), 4),
        ('LEFTPADDING', (0,0), (-1,-1), 5),
        ('RIGHTPADDING', (0,0), (-1,-1), 5),
        ('ROWBACKGROUNDS', (0,1), (-1,-1), [ROW_NORM, ROW_ALT]),
        ('LINEBELOW', (0,0), (-1,0), 1.5, MED_BLUE),
    ]))
    return header_t, t


def make_warn_table(styles):
    S = styles
    header_data = [[Paragraph('<b>⚠  CRITICAL WARNINGS FOR PARENTERAL ANTIBIOTIC USE IN INDIA</b>', S['sec_title'])]]
    header_t = Table(header_data, colWidths=[W - 3*cm])
    header_t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), ACCENT_RED),
        ('LEFTPADDING', (0,0), (-1,-1), 10),
        ('TOPPADDING', (0,0), (-1,-1), 6),
        ('BOTTOMPADDING', (0,0), (-1,-1), 6),
    ]))
    rows = []
    for t, n in WARNING_NOTES:
        rows.append([
            Paragraph(t, S['warn_title']),
            Paragraph(n, S['warn_body']),
        ])
    body_t = Table(rows, colWidths=[5.5*cm, 15.9*cm])
    body_t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), RED_LIGHT),
        ('GRID', (0,0), (-1,-1), 0.4, HexColor('#fca5a5')),
        ('VALIGN', (0,0), (-1,-1), 'TOP'),
        ('TOPPADDING', (0,0), (-1,-1), 5),
        ('BOTTOMPADDING', (0,0), (-1,-1), 5),
        ('LEFTPADDING', (0,0), (-1,-1), 8),
        ('RIGHTPADDING', (0,0), (-1,-1), 8),
    ]))
    return header_t, body_t


# ── COVER ──────────────────────────────────────────────────────────────────────
def make_cover(styles):
    elems = []
    elems.append(Spacer(1, 2.5*cm))

    title_rows = [
        [Paragraph('PARENTERAL', ParagraphStyle('c1', fontName='Helvetica-Bold', fontSize=36,
            textColor=colors.white, leading=40, alignment=TA_CENTER))],
        [Paragraph('ANTIBIOTIC', ParagraphStyle('c2', fontName='Helvetica-Bold', fontSize=36,
            textColor=HexColor('#fca5a5'), leading=40, alignment=TA_CENTER))],
        [Paragraph('QUICK REFERENCE GUIDE', ParagraphStyle('c3', fontName='Helvetica-Bold', fontSize=19,
            textColor=HexColor('#93c5fd'), leading=24, alignment=TA_CENTER))],
    ]
    cover_t = Table(title_rows, colWidths=[W - 3*cm])
    cover_t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), HEADER_BG),
        ('TOPPADDING', (0,0), (-1,-1), 10),
        ('BOTTOMPADDING', (0,0), (-1,-1), 10),
        ('LEFTPADDING', (0,0), (-1,-1), 20),
        ('RIGHTPADDING', (0,0), (-1,-1), 20),
    ]))
    elems.append(cover_t)
    elems.append(Spacer(1, 0.4*cm))

    sub_data = [[Paragraph(
        'India Hospital / ICU Practice  |  IV &amp; IM Selection by Infection Type  |  Edition 2025–26',
        ParagraphStyle('csub', fontName='Helvetica', fontSize=11,
            textColor=DARK_NAVY, leading=16, alignment=TA_CENTER))]]
    sub_t = Table(sub_data, colWidths=[W - 3*cm])
    sub_t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), LIGHT_BLUE),
        ('TOPPADDING', (0,0), (-1,-1), 10),
        ('BOTTOMPADDING', (0,0), (-1,-1), 10),
    ]))
    elems.append(sub_t)
    elems.append(Spacer(1, 0.8*cm))

    sections = [
        ('🫁', 'Respiratory Tract Infections',    'Severe CAP, HAP, VAP, aspiration pneumonia, empyema, lung abscess'),
        ('🔬', 'Urinary Tract Infections',         'Pyelonephritis, urosepsis, CA-UTI, candidal UTI'),
        ('🔥', 'Sepsis & Bacteremia',              'Empirical sepsis, septic shock, bloodstream infection, febrile neutropenia'),
        ('🧠', 'CNS Infections',                   'Bacterial meningitis, brain abscess, TBM'),
        ('🍽', 'Abdominal / GI Infections',        'Peritonitis, cholangitis, liver abscess, SBP, typhoid complications'),
        ('🦴', 'Bone & Joint Infections',          'Osteomyelitis (MSSA/MRSA), septic arthritis, diabetic foot'),
        ('🩹', 'Skin & Soft Tissue',               'Severe cellulitis, necrotizing fasciitis, MRSA SSTI, gas gangrene, burns'),
        ('❤', 'Cardiac Infections',               'Infective endocarditis (streptococcal, staphylococcal, HACEK)'),
        ('🦠', 'MDR / Resistant Organisms',        'ESBL, CRE/KPC, XDR Acinetobacter, MRSA bacteremia, Pseudomonas'),
        ('🌡', 'Tropical & Special Situations',    'Leptospirosis, scrub typhus, severe malaria, tetanus, cholera'),
        ('🤰', 'Obstetric Infections',             'Chorioamnionitis, endometritis, septic abortion, surgical prophylaxis'),
        ('💊', 'Drug Reference Table',             '22 common parenteral antibiotics: brands, doses, key uses'),
    ]
    toc_rows = []
    for icon, sec, detail in sections:
        toc_rows.append([
            Paragraph(icon, ParagraphStyle('icon', fontName='Helvetica-Bold', fontSize=13,
                leading=18, alignment=TA_CENTER)),
            Paragraph(f'<b>{sec}</b><br/><font size="8" color="#64748b">{detail}</font>',
                ParagraphStyle('ti', fontName='Helvetica', fontSize=9.5, leading=14, textColor=DARK_NAVY)),
        ])
    toc_t = Table(toc_rows, colWidths=[1.1*cm, W - 3*cm - 1.1*cm])
    toc_t.setStyle(TableStyle([
        ('VALIGN', (0,0), (-1,-1), 'MIDDLE'),
        ('TOPPADDING', (0,0), (-1,-1), 5),
        ('BOTTOMPADDING', (0,0), (-1,-1), 5),
        ('LEFTPADDING', (0,0), (-1,-1), 8),
        ('ROWBACKGROUNDS', (0,0), (-1,-1), [LIGHT_BLUE, ROW_NORM]),
        ('BOX', (0,0), (-1,-1), 0.5, BORDER_GREY),
        ('LINEBELOW', (0,0), (-1,-1), 0.3, BORDER_GREY),
    ]))
    elems.append(toc_t)
    elems.append(Spacer(1, 0.8*cm))

    disc = Paragraph(
        '<b>⚠ Disclaimer:</b> This guide is for clinical reference only. Antibiotic selection must be based on local '
        'resistance data, cultures, patient allergies, renal/hepatic function, and clinical severity. '
        'Empirical regimens must be reviewed and de-escalated within 48–72h. Always refer to NCDC, IDSA, and '
        'institutional antibiotic stewardship protocols for definitive guidance.',
        ParagraphStyle('disc', fontName='Helvetica-Oblique', fontSize=7.5, textColor=TEXT_MED, leading=11))
    disc_t = Table([[disc]], colWidths=[W - 3*cm])
    disc_t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), AMBER_LIGHT),
        ('BOX', (0,0), (-1,-1), 0.8, ACCENT_AMBER),
        ('TOPPADDING', (0,0), (-1,-1), 8),
        ('BOTTOMPADDING', (0,0), (-1,-1), 8),
        ('LEFTPADDING', (0,0), (-1,-1), 10),
        ('RIGHTPADDING', (0,0), (-1,-1), 10),
    ]))
    elems.append(disc_t)
    elems.append(PageBreak())
    return elems


# ── BUILD ──────────────────────────────────────────────────────────────────────
def build_pdf():
    outpath = '/tmp/workspace/antibiotic-guide/Parenteral_Antibiotic_Quick_Reference_India.pdf'

    doc = BaseDocTemplate(
        outpath, pagesize=A4,
        leftMargin=1.5*cm, rightMargin=1.5*cm,
        topMargin=2.3*cm, bottomMargin=1.5*cm,
        title='Parenteral Antibiotic Quick Reference Guide – India',
        author='Hospital Practice Reference',
        subject='Parenteral antibiotic selection by infection type',
    )

    cover_frame = Frame(0, 0, W, H, leftPadding=1.5*cm, rightPadding=1.5*cm,
                        topPadding=1.5*cm, bottomPadding=1.5*cm)

    def cover_bg(c, d):
        c.setFillColor(HEADER_BG)
        c.rect(0, 0, W, H, fill=1, stroke=0)
        c.setFillColor(ACCENT_RED)
        c.rect(0, 0, W, 8, fill=1, stroke=0)
        c.rect(0, H - 8, W, 8, fill=1, stroke=0)

    cover_tpl = PageTemplate(id='Cover', frames=[cover_frame])
    cover_tpl.beforeDrawPage = cover_bg

    content_frame = Frame(1.5*cm, 1.5*cm, W - 3*cm, H - 3.9*cm,
                          leftPadding=0, rightPadding=0, topPadding=0, bottomPadding=0)
    content_tpl = PageTemplate(id='Content', frames=[content_frame], onPage=make_header)

    doc.addPageTemplates([cover_tpl, content_tpl])

    S = build_styles()
    elems = []
    elems.extend(make_cover(S))
    elems.append(NextPageTemplate('Content'))

    def add_section(title, bg, data, gap=True):
        sh = sec_header(title, bg, S)
        tb = make_table(data, S)
        elems.append(sh)
        elems.append(tb)
        if gap:
            elems.append(Spacer(1, 0.35*cm))

    add_section('🫁  RESPIRATORY TRACT INFECTIONS (IV/IM)',  MED_BLUE,      RESP_DATA)
    add_section('🔬  URINARY TRACT INFECTIONS (Parenteral)', ACCENT_TEAL,   UTI_DATA)
    add_section('🔥  SEPSIS, BACTEREMIA & FEBRILE NEUTROPENIA', ACCENT_RED, SEPSIS_DATA)
    add_section('🧠  CNS INFECTIONS (IV)',                    ACCENT_PURPLE, CNS_DATA)
    add_section('🍽  ABDOMINAL & GI INFECTIONS (IV)',         ACCENT_AMBER,  ABDOMINAL_DATA)
    add_section('🦴  BONE & JOINT INFECTIONS (IV)',           HexColor('#92400e'), BONE_DATA)
    add_section('🩹  SKIN & SOFT TISSUE INFECTIONS (IV)',     ACCENT_ORANGE, SKIN_DATA)
    add_section('❤  INFECTIVE ENDOCARDITIS (IV)',            ACCENT_ROSE,   CARDIAC_DATA)
    add_section('🦠  MDR / RESISTANT ORGANISM REGIMENS',     HexColor('#374151'), MDR_DATA)
    add_section('🌡  TROPICAL & SPECIAL SITUATIONS (IV)',     ACCENT_CYAN,   SPECIAL_DATA)
    add_section('🤰  OBSTETRIC INFECTIONS (IV)',              HexColor('#7c3aed'), OB_GYN_DATA)

    # Drug reference table
    dh, dt = make_drug_table(S)
    elems.append(dh)
    elems.append(dt)
    elems.append(Spacer(1, 0.35*cm))

    # Warnings
    wh, wt = make_warn_table(S)
    elems.append(wh)
    elems.append(wt)
    elems.append(Spacer(1, 0.35*cm))

    # Footer references
    ref = Paragraph(
        '<b>References:</b> NCDC National Treatment Guidelines (India) | IDSA Sepsis / Endocarditis / Osteomyelitis Guidelines | '
        'WHO AWaRe 2023 | Harrison\'s Principles of Internal Medicine 22E | Surviving Sepsis Campaign 2021 | '
        'Goldman-Cecil Medicine | SEAQUAMAT Trial (Artesunate vs Quinine)',
        ParagraphStyle('ref', fontName='Helvetica-Oblique', fontSize=7, textColor=TEXT_LIGHT, leading=10))
    ref_t = Table([[ref]], colWidths=[W - 3*cm])
    ref_t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), HexColor('#f8fafc')),
        ('BOX', (0,0), (-1,-1), 0.4, BORDER_GREY),
        ('TOPPADDING', (0,0), (-1,-1), 6),
        ('BOTTOMPADDING', (0,0), (-1,-1), 6),
        ('LEFTPADDING', (0,0), (-1,-1), 8),
        ('RIGHTPADDING', (0,0), (-1,-1), 8),
    ]))
    elems.append(ref_t)

    doc.build(elems, canvasmaker=NumberedCanvas)
    return outpath


if __name__ == '__main__':
    path = build_pdf()
    print(f'SUCCESS: {path}')

"""
Drug-to-Bacteria Cross-Reference Table PDF
Reverse lookup: given a drug, which organisms does it cover?
India Hospital & GP Practice | 2025-26
"""
from reportlab.lib.pagesizes import A4
from reportlab.lib import colors
from reportlab.lib.styles import ParagraphStyle
from reportlab.lib.units import cm
from reportlab.platypus import (
    BaseDocTemplate, PageTemplate, Frame, Paragraph, Spacer, Table,
    TableStyle, KeepTogether, PageBreak, NextPageTemplate
)
from reportlab.lib.enums import TA_CENTER, TA_LEFT
from reportlab.lib.colors import HexColor
from reportlab.pdfgen import canvas

# ── Palette ────────────────────────────────────────────────────────────────────
C = {
    'navy':        HexColor('#0f172a'),
    'navy2':       HexColor('#1e3a5f'),
    'blue':        HexColor('#1d4ed8'),
    'blue_lt':     HexColor('#dbeafe'),
    'teal':        HexColor('#0f766e'),
    'teal_lt':     HexColor('#ccfbf1'),
    'red':         HexColor('#b91c1c'),
    'red_lt':      HexColor('#fee2e2'),
    'amber':       HexColor('#b45309'),
    'amber_lt':    HexColor('#fef3c7'),
    'green':       HexColor('#15803d'),
    'green_lt':    HexColor('#dcfce7'),
    'purple':      HexColor('#6d28d9'),
    'purple_lt':   HexColor('#ede9fe'),
    'orange':      HexColor('#c2410c'),
    'orange_lt':   HexColor('#ffedd5'),
    'rose':        HexColor('#be123c'),
    'rose_lt':     HexColor('#ffe4e6'),
    'cyan':        HexColor('#0e7490'),
    'cyan_lt':     HexColor('#cffafe'),
    'lime':        HexColor('#4d7c0f'),
    'lime_lt':     HexColor('#ecfccb'),
    'slate':       HexColor('#334155'),
    'slate_lt':    HexColor('#f1f5f9'),
    'border':      HexColor('#cbd5e1'),
    'text':        HexColor('#1e293b'),
    'text_med':    HexColor('#475569'),
    'text_lt':     HexColor('#94a3b8'),
    'white':       colors.white,
    'row_alt':     HexColor('#f8fafc'),
    'row_norm':    HexColor('#ffffff'),
    # Coverage cell colours
    'doc':         HexColor('#15803d'),   # dark green  – Drug of Choice
    'doc_bg':      HexColor('#bbf7d0'),   # light green
    'eff':         HexColor('#1d4ed8'),   # blue        – Effective
    'eff_bg':      HexColor('#bfdbfe'),   # light blue
    'var':         HexColor('#b45309'),   # amber       – Variable/Conditional
    'var_bg':      HexColor('#fef3c7'),   # light amber
    'res':         HexColor('#b91c1c'),   # red         – Resistant/Inactive
    'res_bg':      HexColor('#fee2e2'),   # light red
}
W, H = A4

# ── Numbered canvas ────────────────────────────────────────────────────────────
class NC(canvas.Canvas):
    def __init__(self, *a, **kw):
        canvas.Canvas.__init__(self, *a, **kw)
        self._saved = []
    def showPage(self):
        self._saved.append(dict(self.__dict__))
        self._startPage()
    def save(self):
        n = len(self._saved)
        for s in self._saved:
            self.__dict__.update(s)
            self._footer(n)
            canvas.Canvas.showPage(self)
        canvas.Canvas.save(self)
    def _footer(self, total):
        self.setFillColor(C['navy'])
        self.rect(0, 0, W, 22, fill=1, stroke=0)
        self.setFillColor(C['white'])
        self.setFont('Helvetica', 7.5)
        self.drawString(20, 7, 'Drug-to-Bacteria Cross-Reference Table  |  India Clinical Practice  |  2025–26')
        self.drawRightString(W - 20, 7, f'Page {self._pageNumber} of {total}')
        self.setStrokeColor(C['blue'])
        self.setLineWidth(2)
        self.line(0, 22, W, 22)


def make_header(c, doc):
    c.saveState()
    c.setFillColor(C['navy'])
    c.rect(0, H - 54, W, 54, fill=1, stroke=0)
    c.setFillColor(C['blue'])
    c.rect(0, H - 57, W, 3, fill=1, stroke=0)
    c.setFillColor(C['white'])
    c.setFont('Helvetica-Bold', 14)
    c.drawString(18, H - 31, 'DRUG-TO-BACTERIA CROSS-REFERENCE TABLE')
    c.setFont('Helvetica', 8.5)
    c.setFillColor(HexColor('#94a3b8'))
    c.drawString(18, H - 47, 'Reverse Lookup: Given a Drug, Which Organisms Does it Cover?  |  India Practice 2025–26')
    c.restoreState()

# ── Styles ─────────────────────────────────────────────────────────────────────
def S(name, **kw):
    base = dict(fontName='Helvetica', fontSize=8, textColor=C['text'], leading=11)
    base.update(kw)
    return ParagraphStyle(name, **base)

ST = {
    'sec':      S('sec', fontName='Helvetica-Bold', fontSize=10, textColor=C['white'], leading=13),
    'hdr':      S('hdr', fontName='Helvetica-Bold', fontSize=7.5, textColor=C['white'], leading=10),
    'drug':     S('drug', fontName='Helvetica-Bold', fontSize=8.5, textColor=C['navy'], leading=12),
    'brand':    S('brand', fontName='Helvetica-Oblique', fontSize=7.5, textColor=C['teal'], leading=10),
    'class_':   S('class_', fontName='Helvetica-Bold', fontSize=7.5, textColor=C['white'], leading=10),
    'doc':      S('doc', fontName='Helvetica-Bold', fontSize=7.5, textColor=C['doc'], leading=10),
    'eff':      S('eff', fontName='Helvetica', fontSize=7.5, textColor=C['eff'], leading=10),
    'var':      S('var', fontName='Helvetica-Oblique', fontSize=7, textColor=C['var'], leading=10),
    'res':      S('res', fontName='Helvetica', fontSize=7, textColor=C['text_lt'], leading=10),
    'note':     S('note', fontName='Helvetica-Oblique', fontSize=7, textColor=C['text_med'], leading=10),
    'body':     S('body', fontName='Helvetica', fontSize=7.5, textColor=C['text'], leading=10),
    'warn_t':   S('warn_t', fontName='Helvetica-Bold', fontSize=7.5, textColor=C['red'], leading=10),
    'warn_b':   S('warn_b', fontName='Helvetica', fontSize=7.5, textColor=C['text'], leading=10),
    'leg':      S('leg', fontName='Helvetica-Bold', fontSize=8, textColor=C['navy'], leading=11),
    'leg_desc': S('leg_desc', fontName='Helvetica', fontSize=7.5, textColor=C['text_med'], leading=10),
}

# ── Coverage cell builder ──────────────────────────────────────────────────────
def doc_cell(text):   # Drug of choice
    return Paragraph(f'<b>★ {text}</b>', ST['doc'])
def eff_cell(text):   # Effective
    return Paragraph(text, ST['eff'])
def var_cell(text):   # Variable/conditional
    return Paragraph(f'~ {text}', ST['var'])
def no_cell():        # Not active
    return Paragraph('<font color="#94a3b8">✗  Not active</font>', ST['res'])
def na_cell():
    return Paragraph('<font color="#94a3b8">–</font>', ST['res'])

# ── DATA ───────────────────────────────────────────────────────────────────────
# Each entry:
# (Drug name, Brand (India), Drug class, coverage_dict, clinical_note)
# coverage_dict keys = organism groups (defined below)
# values: 'doc' | 'eff' | 'var' | 'no'

# Organism column headers (abbreviated to fit)
ORG_COLS = [
    'Strep\n(GAS/GBS/\nViridans)',
    'Pneumo-\ncoccus',
    'MSSA\n(S. aureus)',
    'MRSA',
    'Entero-\ncoccus',
    'E. coli /\nKlebsiella\n(Sensitive)',
    'ESBL\nOrganisms',
    'Pseudo-\nmonas',
    'Acineto-\nbacter',
    'H. influ-\nenzae',
    'Anaer-\nobes',
    'Atypicals\n(Myco/Chlam\n/Rickett)',
]

# Row format: (Drug, Brand, Class, [cov per col 0..11], note)
# Coverage codes: D=doc, E=eff, V=var, N=no
DRUG_DATA = [
    # ── PENICILLINS ──────────────────────────────────────────────────────────
    ('Benzylpenicillin\n(Penicillin G)',
     'Crystapen (Pfizer)',
     'Natural Penicillin',
     ['D','D','N','N','E','N','N','N','N','N','N','N'],
     'IV only. Drug of choice: GAS, GBS, viridans strep IE, meningococcus, pneumococcus (sensitive). Inactive against Staph.'),

    ('Amoxicillin',
     'Mox, Novamox\n(Cipla/Ranbaxy)',
     'Aminopenicillin',
     ['D','E','N','N','E','E','N','N','N','E','N','N'],
     'Oral. Drug of choice for pharyngitis, otitis media, mild CAP. ESBL/beta-lactamase-producing strains inactive.'),

    ('Amoxicillin +\nClavulanic Acid',
     'Augmentin (GSK)\nClavam (Alkem)',
     'Aminopenicillin\n+ BLI',
     ['D','E','E','N','E','E','V','N','N','E','E','N'],
     'Oral/IV. Most prescribed antibiotic combination in India (102+ brands). Covers beta-lactamase producers. ESBL coverage marginal; do not rely for definitive ESBL treatment.'),

    ('Cloxacillin /\nFlucloxacillin',
     'Clox (Cipla)\nBioclox (Alkem)',
     'Penicillinase-\nResistant Pen.',
     ['V','N','D','N','N','N','N','N','N','N','N','N'],
     'Oral/IV. Drug of choice for MSSA skin, bone, endocarditis. Completely inactive against MRSA and Gram-negatives. Must be taken on empty stomach.'),

    ('Ampicillin /\nAmpicillin-\nSulbactam',
     'Roscillin inj\nUnasyn',
     'Aminopenicillin\n(± BLI)',
     ['D','E','N','N','D','E','N','N','V','E','E','N'],
     'Ampicillin alone: covers Listeria (critical for neonatal/elderly meningitis). Sulbactam component has intrinsic activity against Acinetobacter.'),

    ('Piperacillin-\nTazobactam',
     'Tazact (Sun)\nPipcin-TZ (Cipla)',
     'Anti-pseudomonal\nPenicillin + BLI',
     ['E','E','E','N','E','E','V','D','V','E','E','N'],
     'IV only. Broadest penicillin. ESBL coverage unreliable (inoculum effect – do NOT use for definitive ESBL). Best single agent for Pseudomonal sepsis empirically. NOT for MRSA.'),

    # ── CEPHALOSPORINS ───────────────────────────────────────────────────────
    ('Cephalexin /\nCefadroxil\n(1st Gen)',
     'Sporidex (Sun)\nDroxyl (Cipla)',
     '1st Gen\nCephalosporin',
     ['E','E','E','N','N','V','N','N','N','V','N','N'],
     'Oral. Excellent for MSSA SSTI and Strep pharyngitis. No Gram-negative activity of clinical significance. Step-down from IV for MSSA osteomyelitis.'),

    ('Cefuroxime\nAxetil\n(2nd Gen)',
     'Zinnat (GSK)\nCeftin (Alkem)',
     '2nd Gen\nCephalosporin',
     ['E','E','E','N','N','E','N','N','N','E','N','N'],
     'Oral. Broader than 1st gen. Good for otitis media, sinusitis, mild CAP with H. influenzae risk. Lyme disease (early). No Pseudomonal activity.'),

    ('Ceftriaxone\n(3rd Gen)',
     'Monocef (Biochem)\nOframax (Ranbaxy)',
     '3rd Gen\nCephalosporin',
     ['E','D','E','N','N','E','N','N','N','E','N','N'],
     'IV/IM. Workhorse of hospital practice. Drug of choice: pneumococcal meningitis, CAP, typhoid (IV). Once-daily dosing. Does NOT cover Pseudomonas, MRSA, anaerobes, Enterococcus.'),

    ('Cefixime\n(3rd Gen Oral)',
     'Taxim-O (Alkem)\nZifi (FDC)',
     '3rd Gen Oral\nCephalosporin',
     ['E','E','N','N','N','E','N','N','N','E','N','N'],
     'Oral only. Drug of choice for typhoid in India (14d) and gonorrhea (400mg single dose). No MSSA, no Pseudomonas. Most widely prescribed oral 3rd-gen ceph in India.'),

    ('Ceftazidime\n(3rd Gen Anti-\npseudomonal)',
     'Fortum (GSK)\nTazide (Cipla)',
     '3rd Gen Anti-\npseudomonal Ceph',
     ['E','E','N','N','N','E','N','D','N','E','N','N'],
     'IV. Anti-pseudomonal cephalosporin. Less Gram-positive coverage than Ceftriaxone. Used in febrile neutropenia, VAP with Pseudomonas risk.'),

    ('Cefepime\n(4th Gen)',
     'Cefipim (Sun)\nMaxipime',
     '4th Gen\nCephalosporin',
     ['E','E','E','N','N','E','N','E','N','E','N','N'],
     'IV. Broader spectrum than ceftazidime. Good Pseudomonas and Gram-positive coverage. Used in HAP, febrile neutropenia, complicated UTI.'),

    ('Cefoperazone-\nSulbactam',
     'Magnex-Forte (Pfizer)\nSulbacef (Cipla)',
     '3rd Gen Ceph\n+ BLI',
     ['E','E','E','N','N','E','V','E','E','E','E','N'],
     'IV. Sulbactam component has intrinsic activity against Acinetobacter baumannii. Used widely in Indian ICUs for HAP/VAP. Variable ESBL coverage.'),

    ('Ceftazidime-\nAvibactam',
     'Avycaz (Pfizer)',
     'Advanced Ceph\n+ Novel BLI',
     ['N','N','N','N','N','E','E','E','V','E','N','N'],
     'IV. Reserved for KPC-producing CRE and MDR Pseudomonas. Not active against MBL (NDM, VIM). Game-changer for KPC infections in India.'),

    # ── CARBAPENEMS ──────────────────────────────────────────────────────────
    ('Meropenem',
     'Meromer (Zydus)\nMeronem (AZ)',
     'Carbapenem',
     ['E','E','E','N','E','D','D','E','E','E','D','N'],
     'IV. Broadest spectrum beta-lactam. Drug of choice for ESBL infections. Preferred carbapenem for CNS infections (no seizure risk unlike Imipenem). NOT active against MRSA.'),

    ('Imipenem-\nCilastatin',
     'Tienam (MSD)\nImipem (Cipla)',
     'Carbapenem',
     ['E','E','E','N','E','D','D','E','E','E','D','N'],
     'IV. Similar to Meropenem. Avoid for CNS infections (seizure risk). Cilastatin prevents renal metabolism. Less Pseudomonal activity than Meropenem.'),

    ('Ertapenem',
     'Invanz (MSD)',
     'Carbapenem\n(No Pseudo)',
     ['E','E','E','N','N','D','D','N','N','E','D','N'],
     'IV/IM once daily. Excellent for ESBL outpatient/step-down therapy. Critically: NO activity against Pseudomonas or Acinetobacter. Preserves carbapenems active against MDR organisms.'),

    # ── GLYCOPEPTIDES ────────────────────────────────────────────────────────
    ('Vancomycin',
     'Vancorid (Abbott)\nVancotex',
     'Glycopeptide',
     ['E','E','E','D','E','N','N','N','N','N','N','N'],
     'IV (or oral for C. diff). Drug of choice: MRSA all infections. AUC/MIC-guided dosing. NEVER use for MSSA if Cloxacillin is available (inferior outcomes). Nephrotoxic.'),

    ('Teicoplanin',
     'Targocid (Sanofi)\nTeicomine',
     'Glycopeptide',
     ['E','E','E','D','E','N','N','N','N','N','N','N'],
     'IV. Alternative to Vancomycin. Easier monitoring. Used for MRSA, endocarditis, prosthetic joint infections. Add Rifampicin for biofilm infections.'),

    # ── OXAZOLIDINONES ───────────────────────────────────────────────────────
    ('Linezolid',
     'Linox (Cipla)\nZyvox (Pfizer)',
     'Oxazolidinone',
     ['E','E','E','D','E','N','N','N','N','N','N','N'],
     'IV/Oral (100% bioavailability). Drug of choice for MRSA pneumonia and osteoarticular infections. Also active in MDR-TB regimens. Bacteriostatic. Monitor CBC weekly (thrombocytopenia). Serotonin syndrome risk.'),

    # ── LIPOPEPTIDES ─────────────────────────────────────────────────────────
    ('Daptomycin',
     'Cubicin (MSD)',
     'Lipopeptide\n(Cyclic)',
     ['E','E','E','D','E','N','N','N','N','N','N','N'],
     'IV only. Rapidly bactericidal. Drug of choice: MRSA bacteremia, right-sided endocarditis. NEVER use for pneumonia (inactivated by pulmonary surfactant). Monitor CPK weekly.'),

    # ── FLUOROQUINOLONES ─────────────────────────────────────────────────────
    ('Ciprofloxacin',
     'Cifran (Ranbaxy)\nCiplox (Cipla)',
     '2nd Gen\nFluoroquinolone',
     ['N','N','N','N','N','E','N','E','N','E','N','V'],
     'Oral/IV. Best oral anti-pseudomonal. Drug of choice: chronic bacterial prostatitis (4 weeks), anthrax prophylaxis. HIGH resistance in India for UTI (>60%). Poor Strep/Pneumo coverage.'),

    ('Levofloxacin',
     'Glevo (Glenmark)\nLox (Cipla)',
     '3rd Gen\nFluoroquinolone\n(Respiratory)',
     ['E','D','N','N','N','E','N','V','N','E','N','D'],
     'Oral/IV. "Respiratory quinolone" – excellent Pneumococcus and atypical coverage. Drug of choice: severe CAP when beta-lactam fails, Legionella. Used in MDR-TB second-line.'),

    ('Moxifloxacin',
     'Avelox (Bayer)\nMoxiford (Alkem)',
     '4th Gen\nFluoroquinolone',
     ['E','D','N','N','N','N','N','N','N','N','E','D'],
     'Oral/IV. Best anaerobic coverage among FQs. Excellent for CAP, sinusitis, AECB. NO urinary concentration – never use for UTI. No Pseudomonal or MRSA activity.'),

    ('Ofloxacin',
     'Zanocin (Ranbaxy)\nOflox (Cipla)',
     '2nd Gen\nFluoroquinolone',
     ['N','N','N','N','N','E','N','V','N','E','N','E'],
     'Oral/IV. Active against Chlamydia, Mycobacterium leprae (MDT). Used in MDR-TB regimens. Similar to Ciprofloxacin for Gram-negatives.'),

    # ── MACROLIDES ───────────────────────────────────────────────────────────
    ('Azithromycin',
     'Azithral (Alembic)\nAzee (Cipla)',
     'Macrolide\n(Azalide)',
     ['E','E','N','N','N','N','N','N','N','E','N','D'],
     'Oral/IV. Drug of choice: atypical pneumonia (Mycoplasma, Chlamydophila), Chlamydia trachomatis (1g single dose), Campylobacter, typhoid (alternative), MAC prophylaxis. Prolonged tissue half-life.'),

    ('Clarithromycin',
     'Claribid (Cipla)\nKlaricid (Abbott)',
     'Macrolide',
     ['E','E','N','N','N','N','N','N','N','E','N','D'],
     'Oral. Drug of choice (component): H. pylori eradication triple therapy. Also atypical CAP. Better GI tolerability than Erythromycin. MAC prophylaxis/treatment in HIV.'),

    ('Erythromycin',
     'Erythrocin (Abbott)\nAlthrocin (Alembic)',
     'Macrolide\n(Original)',
     ['E','E','N','N','N','N','N','N','N','E','N','E'],
     'Oral. Oldest macrolide. Used for Strep infections in penicillin-allergic, Chlamydia (inferior to Azithromycin), diphtheria carriers. Prokinetic at low doses (gastroparesis).'),

    # ── TETRACYCLINES ────────────────────────────────────────────────────────
    ('Doxycycline',
     'Doxicip (Cipla)\nDoxt (Alkem)',
     'Tetracycline\n(2nd Gen)',
     ['V','V','N','N','N','N','N','N','N','V','V','D'],
     'Oral/IV. Drug of choice: scrub typhus, rickettsial diseases, brucellosis (+ Rifampicin), leptospirosis (mild), Chlamydia, malaria prophylaxis, acne (long-term). Avoid in pregnancy and children <8y.'),

    ('Minocycline',
     'Minoz (Sun)\nMinolox (Cipla)',
     'Tetracycline\n(2nd Gen)',
     ['V','V','E','V','N','N','N','N','V','V','N','D'],
     'Oral. Drug of choice: acne vulgaris (long-term). Also community MRSA skin infections (CA-MRSA). Nocardiosis. Penetrates CSF better than Doxycycline. Vestibular side effects.'),

    # ── NITROIMIDAZOLES ──────────────────────────────────────────────────────
    ('Metronidazole',
     'Flagyl (Abbott)\nMetrogyl (J.B.Chem)',
     'Nitroimidazole',
     ['N','N','N','N','N','N','N','N','N','N','D','N'],
     'Oral/IV. Drug of choice: amoebiasis, giardiasis, BV, anaerobic infections (B. fragilis, C. difficile), tetanus (preferred over Penicillin). Zero aerobic coverage. Avoid alcohol.'),

    ('Tinidazole',
     'Fasigyn (Pfizer)\nTiniba (Cipla)',
     'Nitroimidazole\n(2nd Gen)',
     ['N','N','N','N','N','N','N','N','N','N','D','N'],
     'Oral. Better tolerated than Metronidazole (less nausea). Drug of choice: giardiasis (2g single dose). Amoebiasis, trichomoniasis, BV. Shorter course than Metro.'),

    # ── SULFONAMIDES ─────────────────────────────────────────────────────────
    ('Cotrimoxazole\n(TMP-SMX)',
     'Septran (GSK)\nBactrim (Roche)',
     'Sulfonamide +\nTMP',
     ['E','E','N','V','V','V','N','N','N','E','N','N'],
     'Oral/IV. Drug of choice: PCP prophylaxis/treatment (HIV), Nocardia, Toxoplasma prophylaxis. CA-MRSA skin infections (Septran 960mg BD). UTI where E. coli sensitive. Avoid in 1st trimester.'),

    # ── LINCOSAMIDES ─────────────────────────────────────────────────────────
    ('Clindamycin',
     'Dalacin C (Pfizer)\nClinmycin (Cipla)',
     'Lincosamide',
     ['E','E','E','V','N','N','N','N','N','N','D','N'],
     'Oral/IV. Excellent anaerobic and Gram-positive coverage. Drug of choice: dental/oral anaerobic infections, bone osteomyelitis (excellent bone penetration), CA-MRSA (combination), NF (blocks GAS toxin). C. diff risk with use.'),

    # ── AMINOGLYCOSIDES ──────────────────────────────────────────────────────
    ('Gentamicin /\nAmikacin',
     'Garamycin (Schering)\nAmikin (BMS)',
     'Aminoglycoside',
     ['N','N','E','N','V','E','V','E','E','E','N','N'],
     'IV/IM only. Used for synergy (+ Penicillin for IE), Gram-neg sepsis. Amikacin for Gentamicin-resistant organisms. Nephrotoxic + ototoxic – once-daily dosing preferred. Monitor levels. Avoid in CKD.'),

    # ── POLYMYXINS ───────────────────────────────────────────────────────────
    ('Colistin\n(Polymyxin E)',
     'Colistin-CMS\n(Cipla/Sun)',
     'Polymyxin\n(Last Resort)',
     ['N','N','N','N','N','E','E','D','D','N','N','N'],
     'IV/inhaled. Last-resort only. Drug of choice: XDR Acinetobacter, PDR Pseudomonas, CRE. Nephrotoxic (~50% AKI). Always use in combination. Monitor creatinine daily. 9MU loading dose mandatory.'),

    # ── RIFAMYCINS ───────────────────────────────────────────────────────────
    ('Rifampicin',
     'Rifampicin (Lupin)\nRimactane',
     'Rifamycin',
     ['E','N','E','E','N','N','N','N','N','N','N','V'],
     'Oral. NEVER use as monotherapy (rapid resistance). Combinations: TB (HRZE), leprosy (MDT), Brucellosis (+ Doxy), MRSA prosthetic infections (+ Vancomycin/Teicoplanin), meningococcal prophylaxis. Strong CYP450 inducer.'),

    ('Rifaximin',
     'Rcifax (Cipla)\nRifagut (Sun)',
     'Rifamycin\n(Non-absorbed)',
     ['N','N','N','N','N','V','N','N','N','N','E','N'],
     'Oral only (non-absorbed – acts in gut lumen). Traveler\'s diarrhea (non-invasive E. coli), hepatic encephalopathy prevention (550mg BD), SIBO (200mg TDS). Not for systemic infections.'),

    # ── NITROFURANS ──────────────────────────────────────────────────────────
    ('Nitrofurantoin',
     'Niftran (Alkem)\nFuradantin',
     'Nitrofuran',
     ['N','N','N','N','E','E','V','N','N','N','N','N'],
     'Oral only. Concentrated exclusively in urine – use ONLY for lower UTI/cystitis. Drug of choice: uncomplicated UTI in women and pregnancy (2nd trimester). NOT for pyelonephritis (inadequate tissue levels). Do not use if CrCl <30.'),

    # ── TIGECYCLINE ──────────────────────────────────────────────────────────
    ('Tigecycline',
     'Tygacil (Pfizer)',
     'Glycylcycline',
     ['E','E','E','E','E','E','E','N','E','E','E','E'],
     'IV only. Broadest non-carbapenem spectrum. Drug of choice: XDR Acinetobacter combination therapy. NOT active against Pseudomonas. Do NOT use for bacteremia or UTI (inadequate serum/urine levels). High mortality in bloodstream infections.'),
]

# ── Table builders ─────────────────────────────────────────────────────────────
ORG_WIDTHS = [2.15*cm] * 12
CELL_RENDERERS = {
    'D': doc_cell,
    'E': eff_cell,
    'V': var_cell,
    'N': no_cell,
}

def cov_cell(code, text=''):
    if code == 'D':
        p = Paragraph('<b>★ DOC</b>', ParagraphStyle('dc',
            fontName='Helvetica-Bold', fontSize=7, textColor=C['doc'], leading=9))
        bg = C['doc_bg']
    elif code == 'E':
        p = Paragraph('✔ Eff.', ParagraphStyle('ec',
            fontName='Helvetica', fontSize=7, textColor=C['eff'], leading=9))
        bg = C['eff_bg']
    elif code == 'V':
        p = Paragraph('~ Var.', ParagraphStyle('vc',
            fontName='Helvetica-Oblique', fontSize=7, textColor=C['var'], leading=9))
        bg = C['var_bg']
    else:
        p = Paragraph('✗ No', ParagraphStyle('nc',
            fontName='Helvetica', fontSize=6.5, textColor=C['text_lt'], leading=9))
        bg = C['row_norm']
    return p, bg


def build_drug_table(drug_entries, styles):
    """Build the main cross-reference table for a set of drug entries."""
    # Column widths: drug col + 12 org cols
    drug_col_w = 3.0*cm
    brand_col_w = 2.6*cm
    # Org cols spread across remaining width
    avail_w = W - 3.0*cm - drug_col_w - brand_col_w
    oc_w = avail_w / 12

    col_widths = [drug_col_w, brand_col_w] + [oc_w] * 12

    # Header row
    header_row = [
        Paragraph('<b>Drug</b>', ST['hdr']),
        Paragraph('<b>Brand / Class</b>', ST['hdr']),
    ]
    for org in ORG_COLS:
        header_row.append(Paragraph(f'<b>{org}</b>', ParagraphStyle('oh',
            fontName='Helvetica-Bold', fontSize=6, textColor=C['white'], leading=8, alignment=TA_CENTER)))

    rows = [header_row]
    style_cmds = [
        # Header
        ('BACKGROUND', (0,0), (-1,0), C['navy']),
        ('TEXTCOLOR', (0,0), (-1,0), C['white']),
        ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
        ('TOPPADDING', (0,0), (-1,0), 5),
        ('BOTTOMPADDING', (0,0), (-1,0), 5),
        ('LEFTPADDING', (0,0), (-1,-1), 4),
        ('RIGHTPADDING', (0,0), (-1,-1), 4),
        ('VALIGN', (0,0), (-1,-1), 'MIDDLE'),
        ('TOPPADDING', (0,1), (-1,-1), 4),
        ('BOTTOMPADDING', (0,1), (-1,-1), 4),
        ('GRID', (0,0), (-1,-1), 0.3, C['border']),
        ('LINEBELOW', (0,0), (-1,0), 1.2, C['blue']),
        ('ALIGN', (2,0), (-1,-1), 'CENTER'),
    ]

    for row_i, (drug, brand, cls, cov, note) in enumerate(drug_entries):
        r = row_i + 1  # 0 = header
        bg_base = C['row_alt'] if row_i % 2 == 0 else C['row_norm']
        style_cmds.append(('BACKGROUND', (0,r), (1,r), bg_base))

        row = [
            Paragraph(drug.replace('\n', '<br/>'), ST['drug']),
            Paragraph(f'{brand.replace(chr(10), "<br/>")}<br/><font size="6.5" color="#6d28d9"><i>{cls.replace(chr(10), " ")}</i></font>', ST['brand']),
        ]
        for col_i, code in enumerate(cov):
            p, cell_bg = cov_cell(code)
            row.append(p)
            c_col = 2 + col_i
            style_cmds.append(('BACKGROUND', (c_col,r), (c_col,r), cell_bg))

        rows.append(row)

    t = Table(rows, colWidths=col_widths, repeatRows=1)
    t.setStyle(TableStyle(style_cmds))
    return t


def build_notes_table(drug_entries):
    """Build clinical notes table."""
    header = [
        Paragraph('<b>Drug</b>', ST['hdr']),
        Paragraph('<b>Clinical Notes &amp; Key Facts</b>', ST['hdr']),
    ]
    rows = [header]
    for drug, brand, cls, cov, note in drug_entries:
        rows.append([
            Paragraph(drug.replace('\n', '<br/>') + f'<br/><font size="6.5" color="#0f766e"><i>{cls.replace(chr(10), " ")}</i></font>',
                ST['drug']),
            Paragraph(note, ST['note']),
        ])
    t = Table(rows, colWidths=[4.5*cm, W - 3*cm - 4.5*cm], repeatRows=1)
    t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,0), C['navy2']),
        ('TEXTCOLOR', (0,0), (-1,0), C['white']),
        ('TOPPADDING', (0,0), (-1,0), 5),
        ('BOTTOMPADDING', (0,0), (-1,0), 5),
        ('GRID', (0,0), (-1,-1), 0.3, C['border']),
        ('VALIGN', (0,0), (-1,-1), 'TOP'),
        ('TOPPADDING', (0,1), (-1,-1), 4),
        ('BOTTOMPADDING', (0,1), (-1,-1), 4),
        ('LEFTPADDING', (0,0), (-1,-1), 5),
        ('RIGHTPADDING', (0,0), (-1,-1), 5),
        ('ROWBACKGROUNDS', (0,1), (-1,-1), [C['row_norm'], C['row_alt']]),
        ('LINEBELOW', (0,0), (-1,0), 1.2, C['blue']),
    ]))
    return t


def sec_hdr(title, bg):
    t = Table([[Paragraph(title, ST['sec'])]], colWidths=[W - 3*cm])
    t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), bg),
        ('LEFTPADDING', (0,0), (-1,-1), 10),
        ('TOPPADDING', (0,0), (-1,-1), 6),
        ('BOTTOMPADDING', (0,0), (-1,-1), 6),
    ]))
    return t


# ── Legend ─────────────────────────────────────────────────────────────────────
def build_legend():
    items = [
        (C['doc_bg'], C['doc'], '★  DOC', 'Drug of Choice – best proven agent for this organism'),
        (C['eff_bg'], C['eff'], '✔  Eff.', 'Effective – clinically active, used routinely'),
        (C['var_bg'], C['var'], '~  Var.', 'Variable – conditional activity (resistance patterns, site-specific, or organism sub-type dependent)'),
        (C['red_lt'], C['red'], '✗  No', 'Not active – intrinsically resistant or clinically inactive'),
    ]
    rows = []
    for bg, fg, label, desc in items:
        p_label = Paragraph(f'<b>{label}</b>', ParagraphStyle('ll',
            fontName='Helvetica-Bold', fontSize=8, textColor=fg, leading=11))
        p_desc = Paragraph(desc, ST['leg_desc'])
        swatch = Table([['']], colWidths=[0.8*cm], rowHeights=[0.55*cm])
        swatch.setStyle(TableStyle([('BACKGROUND', (0,0), (0,0), bg),
                                    ('BOX', (0,0), (0,0), 0.5, C['border'])]))
        rows.append([swatch, p_label, p_desc])

    t = Table(rows, colWidths=[1.0*cm, 3.0*cm, W - 3*cm - 4.0*cm])
    t.setStyle(TableStyle([
        ('VALIGN', (0,0), (-1,-1), 'MIDDLE'),
        ('TOPPADDING', (0,0), (-1,-1), 3),
        ('BOTTOMPADDING', (0,0), (-1,-1), 3),
        ('LEFTPADDING', (0,0), (-1,-1), 5),
    ]))
    wrap = Table([[t]], colWidths=[W - 3*cm])
    wrap.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), C['slate_lt']),
        ('BOX', (0,0), (-1,-1), 0.5, C['border']),
        ('TOPPADDING', (0,0), (-1,-1), 4),
        ('BOTTOMPADDING', (0,0), (-1,-1), 4),
    ]))
    return wrap


# ── Cover page ─────────────────────────────────────────────────────────────────
def make_cover():
    elems = []
    elems.append(Spacer(1, 2.5*cm))

    rows = [
        [Paragraph('DRUG-TO-BACTERIA', ParagraphStyle('t1', fontName='Helvetica-Bold',
            fontSize=30, textColor=C['white'], leading=34, alignment=TA_CENTER))],
        [Paragraph('CROSS-REFERENCE TABLE', ParagraphStyle('t2', fontName='Helvetica-Bold',
            fontSize=24, textColor=HexColor('#93c5fd'), leading=28, alignment=TA_CENTER))],
        [Paragraph('Reverse Lookup: For Each Drug, Which Organisms Are Covered?',
            ParagraphStyle('t3', fontName='Helvetica', fontSize=12,
            textColor=HexColor('#94a3b8'), leading=16, alignment=TA_CENTER))],
    ]
    ct = Table(rows, colWidths=[W - 3*cm])
    ct.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), C['navy']),
        ('TOPPADDING', (0,0), (-1,-1), 10),
        ('BOTTOMPADDING', (0,0), (-1,-1), 10),
        ('LEFTPADDING', (0,0), (-1,-1), 20),
        ('RIGHTPADDING', (0,0), (-1,-1), 20),
    ]))
    elems.append(ct)
    elems.append(Spacer(1, 0.4*cm))

    sub = Table([[Paragraph(
        'India Hospital &amp; General Practice  |  Edition 2025–26  |  40 Antibiotics × 12 Organism Groups',
        ParagraphStyle('s', fontName='Helvetica', fontSize=10.5, textColor=C['navy'],
                       leading=14, alignment=TA_CENTER))]], colWidths=[W - 3*cm])
    sub.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), C['blue_lt']),
        ('TOPPADDING', (0,0), (-1,-1), 10),
        ('BOTTOMPADDING', (0,0), (-1,-1), 10),
    ]))
    elems.append(sub)
    elems.append(Spacer(1, 0.8*cm))

    # Classes covered
    classes = [
        ('💊', 'Penicillins', 'Benzylpenicillin, Amoxicillin, Co-amoxiclav, Cloxacillin, Ampicillin-Sulbactam, Pip-Tazo'),
        ('💊', 'Cephalosporins', 'Cephalexin (1G), Cefuroxime (2G), Ceftriaxone, Cefixime, Ceftazidime, Cefepime (4G), Cef-Avibactam'),
        ('💊', 'Carbapenems', 'Meropenem, Imipenem-Cilastatin, Ertapenem'),
        ('💊', 'Glycopeptides & Lipopeptides', 'Vancomycin, Teicoplanin, Daptomycin'),
        ('💊', 'Oxazolidinones', 'Linezolid'),
        ('💊', 'Fluoroquinolones', 'Ciprofloxacin, Levofloxacin, Moxifloxacin, Ofloxacin'),
        ('💊', 'Macrolides', 'Azithromycin, Clarithromycin, Erythromycin'),
        ('💊', 'Tetracyclines', 'Doxycycline, Minocycline'),
        ('💊', 'Nitroimidazoles', 'Metronidazole, Tinidazole'),
        ('💊', 'Others', 'Cotrimoxazole, Clindamycin, Aminoglycosides, Colistin, Rifampicin, Rifaximin, Nitrofurantoin, Tigecycline'),
    ]
    cls_rows = []
    for icon, cls, detail in classes:
        cls_rows.append([
            Paragraph(icon, ParagraphStyle('ic', fontName='Helvetica-Bold', fontSize=11,
                leading=14, alignment=TA_CENTER)),
            Paragraph(f'<b>{cls}</b><br/><font size="7.5" color="#64748b">{detail}</font>',
                ParagraphStyle('cr', fontName='Helvetica', fontSize=9, leading=13, textColor=C['navy'])),
        ])
    cls_t = Table(cls_rows, colWidths=[0.9*cm, W - 3*cm - 0.9*cm])
    cls_t.setStyle(TableStyle([
        ('VALIGN', (0,0), (-1,-1), 'MIDDLE'),
        ('TOPPADDING', (0,0), (-1,-1), 5),
        ('BOTTOMPADDING', (0,0), (-1,-1), 5),
        ('LEFTPADDING', (0,0), (-1,-1), 8),
        ('ROWBACKGROUNDS', (0,0), (-1,-1), [C['blue_lt'], C['row_norm']]),
        ('BOX', (0,0), (-1,-1), 0.5, C['border']),
        ('LINEBELOW', (0,0), (-1,-1), 0.3, C['border']),
    ]))
    elems.append(cls_t)
    elems.append(Spacer(1, 0.6*cm))

    # Organism columns legend
    org_info = [
        ('Strep (GAS/GBS/Viridans)', 'Group A/B Strep, viridans strep, oral Streptococci'),
        ('Pneumococcus', 'S. pneumoniae – CAP, meningitis, sinusitis, otitis media'),
        ('MSSA (S. aureus)', 'Methicillin-sensitive S. aureus – skin, bone, bacteremia'),
        ('MRSA', 'Methicillin-resistant S. aureus – hospital and community'),
        ('Enterococcus', 'E. faecalis / E. faecium – UTI, endocarditis'),
        ('E. coli / Klebsiella (Sensitive)', 'Common Enterobacteriaceae – UTI, sepsis, pneumonia'),
        ('ESBL Organisms', 'Extended-spectrum beta-lactamase producers – resistant Enterobacteriaceae'),
        ('Pseudomonas', 'P. aeruginosa – VAP, burn infections, UTI, cystic fibrosis'),
        ('Acinetobacter', 'A. baumannii – ICU-acquired, ventilator-associated infections'),
        ('H. influenzae', 'Haemophilus – otitis media, sinusitis, AECB, epiglottitis'),
        ('Anaerobes', 'B. fragilis, Clostridia, oral anaerobes – abdominal, dental'),
        ('Atypicals', 'Mycoplasma, Chlamydophila, Rickettsia, Legionella'),
    ]
    o_rows = []
    for org, desc in org_info:
        o_rows.append([
            Paragraph(f'<b>{org}</b>', ParagraphStyle('on', fontName='Helvetica-Bold',
                fontSize=7.5, textColor=C['navy'], leading=10)),
            Paragraph(desc, ParagraphStyle('od', fontName='Helvetica',
                fontSize=7.5, textColor=C['text_med'], leading=10)),
        ])
    org_t = Table(o_rows, colWidths=[5.5*cm, W - 3*cm - 5.5*cm])
    org_t.setStyle(TableStyle([
        ('ROWBACKGROUNDS', (0,0), (-1,-1), [C['teal_lt'], C['row_norm']]),
        ('GRID', (0,0), (-1,-1), 0.3, C['border']),
        ('VALIGN', (0,0), (-1,-1), 'TOP'),
        ('TOPPADDING', (0,0), (-1,-1), 4),
        ('BOTTOMPADDING', (0,0), (-1,-1), 4),
        ('LEFTPADDING', (0,0), (-1,-1), 7),
        ('RIGHTPADDING', (0,0), (-1,-1), 7),
    ]))
    org_hdr = Table([[Paragraph('<b>ORGANISM COLUMN GUIDE</b>',
        ParagraphStyle('oh2', fontName='Helvetica-Bold', fontSize=9,
        textColor=C['white'], leading=12))]], colWidths=[W - 3*cm])
    org_hdr.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), C['teal']),
        ('LEFTPADDING', (0,0), (-1,-1), 10),
        ('TOPPADDING', (0,0), (-1,-1), 5),
        ('BOTTOMPADDING', (0,0), (-1,-1), 5),
    ]))
    elems.append(org_hdr)
    elems.append(org_t)
    elems.append(Spacer(1, 0.6*cm))

    disc = Paragraph(
        '<b>⚠ Important:</b> This table represents general spectrum of activity under typical susceptibility patterns. '
        'Coverage may vary based on local resistance rates, organism sub-type, and infection site. '
        'ALWAYS confirm with culture/sensitivity results and local antibiogram data. '
        'De-escalate empiric broad-spectrum therapy within 48–72 hours.',
        ParagraphStyle('d', fontName='Helvetica-Oblique', fontSize=7.5, textColor=C['text_med'], leading=11))
    disc_t = Table([[disc]], colWidths=[W - 3*cm])
    disc_t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), C['amber_lt']),
        ('BOX', (0,0), (-1,-1), 0.8, C['amber']),
        ('TOPPADDING', (0,0), (-1,-1), 8),
        ('BOTTOMPADDING', (0,0), (-1,-1), 8),
        ('LEFTPADDING', (0,0), (-1,-1), 10),
        ('RIGHTPADDING', (0,0), (-1,-1), 10),
    ]))
    elems.append(disc_t)
    elems.append(PageBreak())
    return elems


# ── Drug class sections ─────────────────────────────────────────────────────────
CLASS_SECTIONS = [
    ('💊  PENICILLINS', C['blue'],
     [d for d in DRUG_DATA if 'Penicillin' in d[2] or 'penicillin' in d[2].lower() or 'Aminopenicillin' in d[2] or 'BLI' in d[2]]),
    ('💊  CEPHALOSPORINS', C['teal'],
     [d for d in DRUG_DATA if 'Cephalosporin' in d[2] or 'Ceph' in d[2]]),
    ('💊  CARBAPENEMS', C['amber'],
     [d for d in DRUG_DATA if 'Carbapenem' in d[2]]),
    ('💊  GLYCOPEPTIDES, LIPOPEPTIDES & OXAZOLIDINONES', C['purple'],
     [d for d in DRUG_DATA if any(x in d[2] for x in ['Glycopeptide','Lipopeptide','Oxazolidinone'])]),
    ('💊  FLUOROQUINOLONES', C['orange'],
     [d for d in DRUG_DATA if 'Fluoroquinolone' in d[2]]),
    ('💊  MACROLIDES & TETRACYCLINES', C['rose'],
     [d for d in DRUG_DATA if any(x in d[2] for x in ['Macrolide','Tetracycline'])]),
    ('💊  NITROIMIDAZOLES, SULFONAMIDES & LINCOSAMIDES', C['cyan'],
     [d for d in DRUG_DATA if any(x in d[2] for x in ['Nitroimidazole','Sulfonamide','Lincosamide'])]),
    ('💊  AMINOGLYCOSIDES, POLYMYXINS, RIFAMYCINS & OTHERS', C['slate'],
     [d for d in DRUG_DATA if any(x in d[2] for x in ['Aminoglycoside','Polymyxin','Rifamycin','Nitrofuran','Glycylcycline'])]),
]


# ── Build PDF ──────────────────────────────────────────────────────────────────
def build():
    out = '/tmp/workspace/antibiotic-guide/Drug_Bacteria_CrossReference_India.pdf'
    doc = BaseDocTemplate(
        out, pagesize=A4,
        leftMargin=1.5*cm, rightMargin=1.5*cm,
        topMargin=2.3*cm, bottomMargin=1.5*cm,
        title='Drug-to-Bacteria Cross-Reference Table – India',
        author='Clinical Reference',
        subject='Antibiotic spectrum reverse lookup',
    )

    # Cover template (no header)
    cf = Frame(0, 0, W, H, leftPadding=1.5*cm, rightPadding=1.5*cm,
               topPadding=1.5*cm, bottomPadding=1.5*cm)
    def cover_bg(c, d):
        c.setFillColor(C['navy']); c.rect(0, 0, W, H, fill=1, stroke=0)
        c.setFillColor(C['blue']); c.rect(0, 0, W, 8, fill=1, stroke=0)
        c.rect(0, H - 8, W, 8, fill=1, stroke=0)
    cover_tpl = PageTemplate(id='Cover', frames=[cf])
    cover_tpl.beforeDrawPage = cover_bg

    # Content template
    content_f = Frame(1.5*cm, 1.5*cm, W - 3*cm, H - 3.9*cm,
                      leftPadding=0, rightPadding=0, topPadding=0, bottomPadding=0)
    content_tpl = PageTemplate(id='Content', frames=[content_f], onPage=make_header)
    doc.addPageTemplates([cover_tpl, content_tpl])

    elems = []
    elems.extend(make_cover())
    elems.append(NextPageTemplate('Content'))

    # Legend first
    leg_hdr = Table([[Paragraph('<b>COVERAGE LEGEND</b>', ST['sec'])]], colWidths=[W - 3*cm])
    leg_hdr.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), C['navy']),
        ('LEFTPADDING', (0,0), (-1,-1), 10),
        ('TOPPADDING', (0,0), (-1,-1), 5),
        ('BOTTOMPADDING', (0,0), (-1,-1), 5),
    ]))
    elems.append(leg_hdr)
    elems.append(build_legend())
    elems.append(Spacer(1, 0.4*cm))

    # One table per class section
    for sec_title, sec_color, drug_list in CLASS_SECTIONS:
        if not drug_list:
            continue
        elems.append(sec_hdr(sec_title, sec_color))
        elems.append(build_drug_table(drug_list, ST))
        elems.append(Spacer(1, 0.35*cm))

    # Clinical notes section
    elems.append(sec_hdr('📋  CLINICAL NOTES & KEY FACTS (All Drugs)', C['slate']))
    elems.append(build_notes_table(DRUG_DATA))
    elems.append(Spacer(1, 0.4*cm))

    # Critical rules table
    rules = [
        ('MSSA → Cloxacillin, NOT Vancomycin', 'Vancomycin is clinically inferior to Cloxacillin for MSSA. Use only if true penicillin allergy documented.'),
        ('ESBL → Carbapenem, NOT Cephalosporin', 'Cephalosporins fail against ESBL despite low MIC on sensitivity report (inoculum effect). Meropenem is drug of choice.'),
        ('MRSA pneumonia → Linezolid preferred over Daptomycin', 'Daptomycin is inactivated by pulmonary surfactant. Vancomycin or Linezolid for MRSA lung infections.'),
        ('GAS Strep → Penicillin always works', 'Group A Streptococcus has never developed clinical resistance to Penicillin.'),
        ('Listeria → Add Ampicillin', 'Cephalosporins (including Ceftriaxone) do NOT cover Listeria. Critical for elderly/neonatal meningitis.'),
        ('Gonorrhea → Ceftriaxone IM, not Ciprofloxacin', 'Fluoroquinolone resistance >50% globally. Always use Ceftriaxone IM + Azithromycin 1g oral.'),
        ('Tetanus → Metronidazole > Penicillin', 'Penicillin G is a GABA antagonist and may worsen tetanic spasms. Metronidazole is preferred.'),
        ('Typhoid in India → Cefixime or Azithromycin', 'FQ resistance high in India. Do NOT use Ciprofloxacin empirically for enteric fever.'),
        ('Acinetobacter → Colistin + Sulbactam', 'XDR Acinetobacter: only Colistin, Tigecycline (not bacteremia), and Sulbactam (Magnex-Forte) have activity.'),
        ('C. diff → Oral Vancomycin (not IV)', 'IV Vancomycin does NOT reach colon lumen. Use oral Vancomycin 125–500mg QID for C. difficile colitis.'),
        ('Atypicals → No cell wall → Beta-lactams inactive', 'Mycoplasma, Chlamydia, Rickettsia, Legionella lack cell walls. All penicillins and cephalosporins are completely inactive.'),
        ('De-escalate at 48–72h', 'Always review and narrow empirical broad-spectrum antibiotics once culture sensitivity results are available.'),
    ]
    rules_hdr = Table([[Paragraph('<b>🚨  CRITICAL RULES – NEVER FORGET</b>', ST['sec'])]], colWidths=[W - 3*cm])
    rules_hdr.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), C['red']),
        ('LEFTPADDING', (0,0), (-1,-1), 10),
        ('TOPPADDING', (0,0), (-1,-1), 6),
        ('BOTTOMPADDING', (0,0), (-1,-1), 6),
    ]))
    rules_rows = [[
        Paragraph('<b>Rule</b>', ST['hdr']),
        Paragraph('<b>Explanation</b>', ST['hdr']),
    ]]
    for rule, expl in rules:
        rules_rows.append([
            Paragraph(f'<b>{rule}</b>', ParagraphStyle('rt', fontName='Helvetica-Bold',
                fontSize=7.5, textColor=C['red'], leading=10)),
            Paragraph(expl, ST['note']),
        ])
    rules_t = Table(rules_rows, colWidths=[6.5*cm, W - 3*cm - 6.5*cm], repeatRows=1)
    rules_t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,0), C['navy']),
        ('TEXTCOLOR', (0,0), (-1,0), C['white']),
        ('GRID', (0,0), (-1,-1), 0.3, C['border']),
        ('VALIGN', (0,0), (-1,-1), 'TOP'),
        ('TOPPADDING', (0,0), (-1,-1), 5),
        ('BOTTOMPADDING', (0,0), (-1,-1), 5),
        ('LEFTPADDING', (0,0), (-1,-1), 6),
        ('RIGHTPADDING', (0,0), (-1,-1), 6),
        ('ROWBACKGROUNDS', (0,1), (-1,-1), [C['red_lt'], C['row_norm']]),
        ('LINEBELOW', (0,0), (-1,0), 1.2, C['red']),
    ]))
    elems.append(rules_hdr)
    elems.append(rules_t)
    elems.append(Spacer(1, 0.35*cm))

    # Ref footer
    ref = Paragraph(
        '<b>References:</b> KD Tripathi Essentials of Medical Pharmacology 9E | Harrison\'s Principles of Internal Medicine 22E (2025) | '
        'NCDC National Treatment Guidelines India | IDSA Antimicrobial Guidelines | WHO AWaRe Classification 2023 | '
        'Mandell Douglas Bennett\'s Principles of Infectious Diseases',
        ParagraphStyle('ref', fontName='Helvetica-Oblique', fontSize=7, textColor=C['text_lt'], leading=10))
    ref_t = Table([[ref]], colWidths=[W - 3*cm])
    ref_t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), C['slate_lt']),
        ('BOX', (0,0), (-1,-1), 0.4, C['border']),
        ('TOPPADDING', (0,0), (-1,-1), 6),
        ('BOTTOMPADDING', (0,0), (-1,-1), 6),
        ('LEFTPADDING', (0,0), (-1,-1), 8),
        ('RIGHTPADDING', (0,0), (-1,-1), 8),
    ]))
    elems.append(ref_t)

    doc.build(elems, canvasmaker=NC)
    return out


if __name__ == '__main__':
    p = build()
    print(f'SUCCESS: {p}')