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Getting Started

Get started with CodeRx in minutes. Subscribe today and get instant access to our comprehensive drug database, weekly-updated data marts, and powerful integration tools.

Want to try before you subscribe?

CodeRx Open is a free, annually updated version of the database covering active, prescribable drugs, their NDCs, and drug classes. Request free access →

Subscribe to CodeRx

Subscribe to CodeRx and get instant access to our comprehensive drug database. Explore weekly-updated data marts and integrate with your existing workflows.

Subscription Plans

We offer two plans:

  • CodeRx Open: A free yearly snapshot of drugs, packages, and classes — currently prescribable products only, with a limited column set.

  • Enterprise: The full CodeRx Drug Database. Every table, every column, weekly updates, and AWS S3 delivery — including pricing, packaging, J-codes, Part D plans, indications, and more.

Ready to Get Started?

Subscribe to CodeRx Enterprise today. Get instant access to our comprehensive drug database with weekly updates, complete RxNorm mappings, and rich drug knowledge graphs. Annual billing available.

View Pricing & Book a Demo →

After Your Subscription

Once you've confirmed your subscription, you'll receive:

  • AWS S3 Access Credentials - Access key ID and secret access key
  • S3 Bucket Information - Bucket name and region details
  • Connection Instructions - Step-by-step setup guide
  • Welcome Email - Additional resources and documentation links

Note: Access credentials are typically provided within 24 hours of subscription confirmation.

Accessing Your Data

After receiving your credentials, you can access your data from AWS S3 using Python:

Authentication

You'll receive:

  • Access Key ID: Your AWS access key
  • Secret Access Key: Your AWS secret key
  • S3 Bucket Info: The address of your AWS s3 bucket

Keep these credentials secure and never commit them to version control.

Querying Data with Python

Here's how to access and query CodeRx data using Python with s3fs:

Note: You'll need to install s3fs, pandas, and pyarrow to work with parquet files. Install them with:

pip install s3fs pandas pyarrow
import s3fs
import pandas as pd

# Create filesystem interface
fs = s3fs.S3FileSystem(
key='YOUR_ACCESS_KEY_ID',
secret='YOUR_SECRET_ACCESS_KEY'
)

# Read parquet file directly
df = pd.read_parquet(
'YOUR_S3_BUCKET/drugs/drugs.parquet',
filesystem=fs
)

# Filter and analyze
print(df.head())
print(f"Total drugs: {len(df)}")

Data Mart Structure

Your Enterprise S3 bucket contains the full set of data marts, including:

  • drugs/ - Drug products with names, RXCUIs, dose forms
  • packages/ - NDC packages with pack sizes and marketing detail
  • ingredients/ - Active and inactive ingredients
  • classes/ - Drug classification systems
  • excipients/ - Inactive ingredients with safety data
  • synonyms/ - Drug name synonyms and aliases

Enterprise also includes pricing, packaging details, label images, REMS, indications, Part D plans, e-prescribing, and storage and handling. See the subscription plans and Pricing for the full comparison.

Version Control

Each data mart folder contains:

  • Latest snapshot: {data_mart}/{data_mart}.csv or {data_mart}/{data_mart}.parquet (e.g., drugs/drugs.parquet)
  • Dated snapshots: {data_mart}/{data_mart}_YYYY-MM-DD.csv or {data_mart}/{data_mart}_YYYY-MM-DD.parquet (e.g., drugs/drugs_2026-01-16.parquet)

Files are updated weekly, with new dated snapshots added while the latest file is always updated to point to the most recent data.

Next Steps

Support

Need help? Contact us at support@coderx.io or visit our Slack community.