/uspto-database

name: "uspto-database"
description: "Access USPTO patent data via PatentsView REST API and Google Patents Public Data (BigQuery). Search by inventor, assignee, CPC, or keywords; download metadata and claims; analyze portfolios; track tech trends. For IP landscape analysis, competitor monitoring, prior art search, and tech forecasting in life sciences and biotech."
license: "CC0-1.0"

uspto-database

Overview

The USPTO provides two primary programmatic access points for patent data: the **PatentsView API** (REST, free, no key required for basic use) for structured queries by inventor, assignee, CPC classification, and keywords; and **Google Patents Public Data** (BigQuery public dataset) for large-scale analytics across the full patent corpus. Both expose data under the CC0 Public Domain Dedication. This skill covers Python-based access patterns for both, plus basic patent portfolio analytics.

When to Use

• **Prior art search**: Finding existing patents relevant to a technology before filing or to assess freedom-to-operate.
• **Competitor IP landscape analysis**: Querying all patents from a specific assignee (company or institution) to map their technology portfolio.
• **CPC classification search**: Finding patents in a specific technology area using Cooperative Patent Classification codes (e.g., C12N for nucleotides/genetic engineering).
• **Inventor network analysis**: Identifying prolific inventors in a field and their institutional affiliations.
• **Technology trend tracking**: Counting patent filings by year and technology category to identify emerging areas.
• **Life sciences IP analysis**: Searching biotech-specific classifications (A61K for pharmaceuticals, C12N for genetics, G16B for bioinformatics).
• For full-text patent PDF downloads, use the USPTO Bulk Data Storage System (BDSS) or Google Patents direct links.
• **Rate limits**: PatentsView API allows 45 requests/minute without an API key; request a free key for 45 req/min with higher daily limits.

Prerequisites

• **Python packages**: `requests`, `pandas`, `matplotlib`
• **Optional**: `google-cloud-bigquery` for Google Patents Public Data queries
• **Data requirements**: No account needed for PatentsView basic queries; Google Cloud account required for BigQuery
• **Rate limits**: PatentsView — 45 requests/minute (unauthenticated), higher with free API key

pip install requests pandas matplotlib
pip install google-cloud-bigquery  # optional: for BigQuery access

Quick Start

import requests
import pandas as pd

# Search PatentsView API: patents assigned to "Genentech" in CPC class C12N
url = "https://api.patentsview.org/patents/query"
payload = {
    "q": {"_and": [
        {"_contains": {"assignee_organization": "Genentech"}},
        {"_contains": {"cpc_subgroup_id": "C12N"}},
    ]},
    "f": ["patent_number", "patent_title", "patent_date", "assignee_organization"],
    "o": {"per_page": 25},
}
resp = requests.post(url, json=payload)
data = resp.json()
df   = pd.DataFrame(data["patents"])
print(f"Found: {data['total_patent_count']} patents")
print(df[["patent_number", "patent_title", "patent_date"]].head())

Core API

Query Type 1: Search by Assignee (Company / Institution)

Find all patents granted to a specific organization.

import requests
import pandas as pd

def search_by_assignee(assignee_name: str, per_page: int = 100) -> pd.DataFrame:
    url     = "https://api.patentsview.org/patents/query"
    payload = {
        "q": {"_contains": {"assignee_organization": assignee_name}},
        "f": [
            "patent_number", "patent_title", "patent_date",
            "patent_abstract", "assignee_organization", "assignee_country",
        ],
        "o": {"per_page": per_page, "sort": [{"patent_date": "desc"}]},
    }
    resp = requests.post(url, json=payload)
    resp.raise_for_status()
    data = resp.json()
    df   = pd.DataFrame(data.get("patents", []))
    print(f"Assignee '{assignee_name}': {data.get('total_patent_count', 0)} total patents")
    return df

# Example: patents from Broad Institute
df_broad = search_by_assignee("Broad Institute")
print(df_broad[["patent_number", "patent_title", "patent_date"]].head(10))

# Paginate through all results for large portfolios
def search_assignee_all_pages(assignee_name: str, page_size: int = 100) -> pd.DataFrame:
    url  = "https://api.patentsview.org/patents/query"
    all_patents = []
    page = 1
    while True:
        payload = {
            "q": {"_contains": {"assignee_organization": assignee_name}},
            "f": ["patent_number", "patent_title", "patent_date", "cpc_subgroup_id"],
            "o": {"per_page": page_size, "page": page},
        }
        resp = requests.post(url, json=payload)
        data = resp.json()
        patents = data.get("patents", [])
        if not patents:
            break
        all_patents.extend(patents)
        total = data.get("total_patent_count", 0)
        if len(all_patents) >= total:
            break
        page += 1

    df = pd.DataFrame(all_patents)
    print(f"Retrieved {len(df)} patents for '{assignee_name}'")
    return df

Query Type 2: Search by CPC Classification

CPC (Cooperative Patent Classification) codes organize patents by technology. Life sciences codes include C12N (nucleotides/genetics), A61K (pharmaceuticals), and G16B (bioinformatics).

import requests
import pandas as pd

# Search by CPC subgroup: C12N15 (mutation/genetic engineering)
url = "https://api.patentsview.org/patents/query"
payload = {
    "q": {"_begins": {"cpc_subgroup_id": "C12N15"}},
    "f": [
        "patent_number", "patent_title", "patent_date",
        "assignee_organization", "cpc_subgroup_id",
    ],
    "o": {"per_page": 50, "sort": [{"patent_date": "desc"}]},
}
resp = requests.post(url, json=payload)
data = resp.json()
df   = pd.DataFrame(data["patents"])
print(f"C12N15 patents: {data['total_patent_count']}")
print(df[["pate