Leer en Español | Read in English

Welcome to pydap

pydap is a Python implementation of the Data Access Protocol (DAP), also known as OPeNDAP. Pydap’s client now offers robust DAP4 support, enabling data users to access thousands of scientific datasets available via OPeNDAP servers in a secure, transparent, and efficient way through the internet, or you can set up pydap as a server to make your data available through the internet via a URL.

Pydap now supports DAP4 data access in a much performant way!

Figure 1. Benchmarks comparing data streaming using Xarray (with pydap as backend engine) and pydap-only new streaming API. Non-supported implies data cannot be aggregated directly with Xarray

Figure 2. Benchmarks comparing data streaming using Xarray (with pydap as backend) and pydap-only new streaming API. Non-supported implies data cannot be aggregated directly with Xarray

To read more about benchmarks displayed above, and the specifics on how pydap’s performance has been improved over the past year, check out this free zenodo resource

The following tutorials show pydap-only streaming workflows from NASA Earthdata:

• Access Calipso L2 data

• Access TEMPO Near-Real-Time data

• Access Ecostress data

• Access DAYMET data

Dive into the documentation to learn best practices for accessing remote data on OPeNDAP servers.

Why OPeNDAP?

Equitable open data access remains essential for advancing effective Open Science frameworks, enabling data-driven discoveries, and empowering inclusive science education and citizen science practices. At the institution level, OPeNDAP servers represent a free, open-source solution to enable data access as an alternative to the comercial cloud, as a cost-effective solution when data is stored on the cloud and data file formats that are not cloud-native, or when the collections are too large to re-format.

For researchers, educators, and citizen scientists, OPeNDAP allows to share scientific data freely under well-known standard protocols over the web, making data publishable, citable, and findable. Importantly, data users can access and subset data in a data-proximate way, downloading only the subregion of interest.

Beginner OPeNDAP users may rapidly find themselves spending the time to better understand OPeNDAP to enable efficient data access. Some of the OPeNDAP elements that require developing a varying degree of skill by the user to better exploit OPeNDAP are:

1. Constraint Expressions.

2. Escaping URL characters for safe internet use.

3. Differences between DAP2 / DAP4 protocol.

Quickstart

• How to install
• Get Started
• What’s New

Examples

• Basic Authentication
• Discovering OPeNDAP URLs from NASA’s Earthdata
• Access Cloud and Aerosol Lidar CALIPSO Data from NASA Earthdata
• Access Precipitation data from DAYMET
• Stream and deserialize data
• Access Land Surface Temperature Data From ECOSTRESS
• Access Near-Real-Time (NRT) Air Quality Data from TEMPO
• ECCOv4 access via NASA’s OPeNDAP in the Cloud.
• PACE Chlorophyll A data over a region in the NorthAtlantic Ocean
• SWOT
• CMIP6
• MERRA-2 Data via NASA’s OPeNDAP in the Cloud.

Frequently Asked Questions

• FAQs

Documentation

• PyDAP as a client
• Responses
• Running a server
• Handlers

Guide for Developer

• The Pydap data model
• Handlers
• Responses

Contributing

• Guide for new contributors
  • Guide to version control
  • Contributing to the code
  • Report Issues on GitHub
  • Contributing to the documentation