Plos Open Access API

https://api.plos.org/search

# Basic keyword search
curl "https://api.plos.org/search?q=CRISPR+gene+editing&rows=20&wt=json"

# Search in specific fields
curl "https://api.plos.org/search?q=title:\"machine learning\"+AND+abstract:biomarker&wt=json"

# Filter by journal
curl "https://api.plos.org/search?q=microbiome&fq=journal:\"PLOS ONE\"&wt=json"

# Filter by date range
curl "https://api.plos.org/search?q=COVID-19+vaccine&\
fq=publication_date:[2024-01-01T00:00:00Z TO 2026-12-31T23:59:59Z]&wt=json"

# Filter by article type
curl "https://api.plos.org/search?q=climate+change&fq=article_type:\"Research Article\"&wt=json"

# Return specific fields only
curl "https://api.plos.org/search?q=deep+learning&fl=id,title,author,publication_date,score&wt=json"

import requests

BASE_URL = "https://api.plos.org/search"


def search_plos(query: str, rows: int = 20,
                journal: str = None,
                from_date: str = None,
                fields: str = None) -> list:
    """Search PLOS open access articles."""
    params = {
        "q": query,
        "wt": "json",
        "rows": rows,
        "fl": fields or "id,title,author,abstract,publication_date,journal,score",
    }

    fq_parts = []
    if journal:
        fq_parts.append(f'journal:"{journal}"')
    if from_date:
        fq_parts.append(
            f"publication_date:[{from_date}T00:00:00Z TO NOW]"
        )
    if fq_parts:
        params["fq"] = " AND ".join(fq_parts)

    resp = requests.get(BASE_URL, params=params)
    resp.raise_for_status()
    data = resp.json()

    results = []
    for doc in data.get("response", {}).get("docs", []):
        results.append({
            "doi": doc.get("id"),
            "title": doc.get("title"),
            "authors": doc.get("author", []),
            "date": doc.get("publication_date", "")[:10],
            "journal": doc.get("journal"),
            "abstract": (doc.get("abstract", [""])[0])[:300]
                        if isinstance(doc.get("abstract"), list)
                        else (doc.get("abstract", ""))[:300],
        })
    return results


def get_full_text(doi: str) -> str:
    """Retrieve full text body of a PLOS article."""
    params = {
        "q": f'id:"{doi}"',
        "fl": "body",
        "wt": "json",
    }
    resp = requests.get(BASE_URL, params=params)
    resp.raise_for_status()
    docs = resp.json().get("response", {}).get("docs", [])
    return docs[0].get("body", "") if docs else ""


# Example: search PLOS Computational Biology
papers = search_plos(
    "protein structure prediction",
    journal="PLOS Computational Biology",
    from_date="2024-01-01",
)
for p in papers:
    print(f"[{p['date']}] {p['title']}")
    print(f"  DOI: {p['doi']}")

# Example: full-text search across all PLOS
papers = search_plos("body:reinforcement+learning AND title:robot")
for p in papers:
    print(f"{p['title']} — {p['journal']}")

# Phrase proximity search (words within 5 of each other)
q=abstract:"machine learning"~5

# Boosted field search
q=title:"CRISPR"^2 OR abstract:"CRISPR"

# Wildcard search
q=title:neuro*

# Range query on dates
fq=publication_date:[2024-01-01T00:00:00Z TO 2024-12-31T23:59:59Z]