Pmc Ftp Bulk Download

File List Index

Download the master index to plan your downloads:

# Download the OA file list (CSV, ~200MB)
wget https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_file_list.csv

# CSV columns:
# File, Article Citation, AccessionID, LastUpdated, PMID, License

Download Strategies

Strategy 1: Download Specific Articles

import requests
import tarfile
import io
import csv

def download_article_package(pmcid: str, base_url: str = "https://ftp.ncbi.nlm.nih.gov/pub/pmc"):
    """Download and extract a specific PMC article package."""
    # First, look up the file path from the file list
    # (In practice, you'd load this once and index by PMCID)
    file_list_url = f"{base_url}/oa_file_list.csv"
    # ... lookup pmcid in file list to get path ...

    # Download the tar.gz package
    resp = requests.get(f"{base_url}/{file_path}", stream=True)
    resp.raise_for_status()

    # Extract
    with tarfile.open(fileobj=io.BytesIO(resp.content), mode="r:gz") as tar:
        tar.extractall(path=f"./articles/{pmcid}")
    print(f"Extracted {pmcid}")

Strategy 2: Bulk Download by License

#!/bin/bash
# Download all commercial-use articles (CC BY / CC0)
# WARNING: This is ~100GB+ compressed

mkdir -p pmc_corpus/commercial
cd pmc_corpus/commercial

# Download the baseline (all current articles)
wget -r -np -nH --cut-dirs=3 \
  https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_comm/xml/

# Incremental updates (run periodically)
wget -r -np -nH --cut-dirs=3 -N \
  https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_comm/xml/

Strategy 3: Filtered Download via File List

import csv
import requests
from pathlib import Path

def download_filtered_corpus(file_list_path: str, output_dir: str,
                              license_filter: str = "CC BY",
                              max_articles: int = 1000):
    """Download articles matching a license filter."""
    output = Path(output_dir)
    output.mkdir(parents=True, exist_ok=True)
    base = "https://ftp.ncbi.nlm.nih.gov/pub/pmc"
    downloaded = 0

    with open(file_list_path) as f:
        reader = csv.DictReader(f)
        for row in reader:
            if license_filter and license_filter not in row.get("License", ""):
                continue
            if downloaded >= max_articles:
                break

            file_path = row["File"]
            url = f"{base}/{file_path}"
            local_path = output / Path(file_path).name

            if local_path.exists():
                continue

            resp = requests.get(url, stream=True, timeout=60)
            if resp.status_code == 200:
                local_path.write_bytes(resp.content)
                downloaded += 1
                if downloaded % 100 == 0:
                    print(f"Downloaded {downloaded} articles...")

    print(f"Total downloaded: {downloaded}")

PMC ID Cross-Referencing

Convert between different article identifiers:

# PMID → PMCID → DOI conversion
curl "https://www.ncbi.nlm.nih.gov/pmc/utils/idconv/v1.0/?ids=29346600&format=json"

# Batch conversion (up to 200 IDs)
curl "https://www.ncbi.nlm.nih.gov/pmc/utils/idconv/v1.0/?ids=29346600,30266829,31048553&format=json"

Package Contents

Each article package (.tar.gz) typically contains:

PMC1234567/
├── PMC1234567.xml       # Full text in JATS XML
├── PMC1234567.pdf       # PDF (if available)
├── figure1.jpg          # Figures
├── figure2.jpg
├── table1.html          # Tables (sometimes)
└── supplement1.pdf      # Supplementary materials

Best Practices

• Start with the file list: Download oa_file_list.csv first and filter locally
• Respect rate limits: Space requests 0.3s apart for individual downloads
• Use incremental updates: After initial download, use -N flag to only get new/updated files
• Check licenses: OA Commercial (CC BY) allows any use; Non-Commercial restricts commercial applications
• Storage planning: Full OA Subset is ~500GB+ uncompressed

References

• PMC FTP Documentation
• PMC Open Access Subset
• PMC ID Converter API