srilanka-epi 2.0.26

Live download and parsing of Sri Lanka Weekly Epidemiological Reports (WER) — dengue surveillance data by RDHS district

srilanka-epi

Production-grade Python library to live-download and parse Weekly Epidemiological Reports (WER) published by the Epidemiology Unit, Ministry of Health & Indigenous Medicine, Sri Lanka.

Built as part of DengueSense LK — Final Year Development Project, ICBT Campus / Cardiff Metropolitan University (2026).

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Features

Feature	Details
🔴 Live data	Auto-scrapes epid.gov.lk — no URL registration needed
📄 PDF parsing	pdfplumber word-coordinate parser
🔍 OCR fallback	pdf2image + Tesseract for corrupted-font PDFs
🗺️ Province mapping	All 9 provinces → 26 RDHS districts
🧹 Auto PDF cleanup	PDFs deleted after parsing by default — only the CSV stays
🐍 Typed	Full PEP 484 type hints + py.typed marker
✅ Tested	pytest suite with 40+ unit tests
📦 PyPI-ready	pip install srilanka-epi

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Installation

pip install srilanka-epi

With OCR fallback (for corrupted-font PDFs):

pip install "srilanka-epi[ocr]"

OCR also requires:

• Tesseract-OCR binary (Windows)
• Poppler (Windows) — for pdf2image

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Quick Start

🔴 Live Data — Get the Latest WER

import srilanka_epi

# One-shot: scrape epid.gov.lk, download PDF, parse dengue data
result = srilanka_epi.get_latest_wer()

print(result["metadata"])
# {'vol': 53, 'no': 18, 'week_no': 18, 'year': 2026, 'week_range': '29th April – 5th May 2026'}

print(result["dengue"])
#           rdhs  week_cases  cumulative_cases  week_no  year  vol  wer_no
# 0      Colombo         142              4521       18  2026   53      18
# 1      Gampaha          89              3102       18  2026   53      18
# ...

🔴 Live Data — Get a Specific Issue

result = srilanka_epi.get_wer(volume=53, number=17)
df = result["dengue"]
print(df.head())

🔴 Live Data — Full-Year Time Series

# Download all 2026 issues and build a time series
df = srilanka_epi.get_dengue_timeseries(volume=53)

# Province breakdown
df = srilanka_epi.add_province(df)
print(df.groupby("province")["week_cases"].sum().sort_values(ascending=False))

# Export
df.to_csv("dengue_2026.csv", index=False)

📋 List All Available Issues

issues = srilanka_epi.list_available_wers()
for (vol, no), url in issues.items():
    print(f"Vol {vol} No {no:02d}: {url}")

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Parsing a Local PDF

from srilanka_epi import parse_wer_pdf

# From file path
result = parse_wer_pdf("WER_Vol53_No18.pdf")

# From bytes
with open("WER.pdf", "rb") as f:
    result = parse_wer_pdf(f.read(), volume=53, number=18)

print(result["metadata"])  # {'vol': 53, 'no': 18, 'week_no': 18, 'year': 2026, ...}
print(result["dengue"])    # pd.DataFrame

Hybrid Parser (pdfplumber + OCR fallback)

Some WER PDFs have corrupted font encoding. Use extract_dengue_data() for automatic OCR fallback:

from srilanka_epi import extract_dengue_data

result = extract_dengue_data("WER_Vol53_No18.pdf")
print(result["method"])  # "pdfplumber" or "ocr"
print(result["dengue"])

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Full API Reference

Live Data Functions

Function	Description
get_latest_wer(...)	Scrape, download, and parse the most recent WER
get_wer(volume, number, ...)	Download and parse a specific WER issue
get_dengue_timeseries(volume, ...)	Full-year dengue time series
list_available_wers(refresh=False)	List all issues on epid.gov.lk

PDF Parsing

Function	Description
parse_wer_pdf(source, ...)	Fast pdfplumber parser
extract_dengue_data(source, ...)	Hybrid parser with OCR fallback

Dengue Helpers

Function	Description
add_province(df)	Add province column to dengue DataFrame
weekly_national_total(df)	Aggregate to national weekly totals
top_districts(df, week_no, year, n)	Top N districts by weekly cases

Download Utilities

Function	Description
download_wer_pdf(volume, number, ...)	Download one PDF (live URL)
download_range(volume, start_no, end_no, ...)	Batch download and parse range of issues
build_dengue_timeseries(results, district)	Combine parsed results
to_csv(df, path)	Export to CSV

Scraper Primitives

Function	Description
scrape_wer_index(url, ...)	Fetch + parse the WER index page
fetch_wer_index(url, ...)	Download raw HTML of WER index
parse_wer_links(html)	Extract PDF URLs from HTML
get_latest_wer_url(...)	Return ((vol, no), url) for the latest issue

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District & Province Constants

import srilanka_epi

# All 26 RDHS districts (+ SRILANKA national total)
print(srilanka_epi.DISTRICTS)

# Province → district mapping
print(srilanka_epi.PROVINCE_MAP)          # {district: province}
print(srilanka_epi.WESTERN_PROVINCE)     # ['Colombo', 'Gampaha', 'Kalutara']
print(srilanka_epi.NORTHERN_PROVINCE)    # ['Jaffna', 'Kilinochchi', 'Mannar', ...]

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Logging

The library uses Python's standard logging module. To see debug output:

import logging
logging.basicConfig(level=logging.INFO)

import srilanka_epi
result = srilanka_epi.get_latest_wer()

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Data Source

All data is sourced from the Epidemiology Unit, Ministry of Health & Indigenous Medicine, Sri Lanka.

• Website: https://www.epid.gov.lk
• WER Index: https://www.epid.gov.lk/weekly-epidemiological-report/weekly-epidemiological-report

Please acknowledge the Epidemiology Unit as the primary data source in any publications.

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Contributing

Contributions are welcome! Please see CONTRIBUTING.md for setup instructions, code style guide, and the PR process.

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Citation

@software{weerakoon2026srilankaepi,
  author    = {Weerakoon, R.B.H.G. Chathura Kavindu Bandara},
  title     = {srilanka-epi: Python library for live Sri Lanka Weekly Epidemiological Report data},
  year      = {2026},
  version   = {2.0.0},
  url       = {https://github.com/chathurakavinduweerakoon/srilanka-epi},
  note      = {ICBT Campus / Cardiff Metropolitan University}
}

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License

MIT License — see LICENSE for full text.