Querying > Python (Subgrounds)

Query The Graph with Python and Subgrounds

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Subgrounds is an intuitive Python library for querying subgraphs, built by Playgrounds. It allows you to directly connect subgraph data to a Python data environment, letting you use libraries like pandas to perform data analysis!

Subgrounds offers a simple Pythonic API for building GraphQL queries, automates tedious workflows such as pagination, and empowers advanced users through controlled schema transformations.

Getting Started

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Subgrounds requires Python 3.10 or higher and is available on pypi.

pip install --upgrade subgrounds
# or
python -m pip install --upgrade subgrounds

Once installed, you can test out subgrounds with the following query. The following example grabs a subgraph for the Aave v2 protocol and queries the top 5 markets ordered by TVL (Total Value Locked), selects their name and their TVL (in USD) and returns the data as a pandas DataFrame.

from subgrounds import Subgrounds
sg = Subgrounds()
# Load the subgraph
aave_v2 = sg.load_subgraph(
# Construct the query
latest_markets = aave_v2.Query.markets(
# Return query to a dataframe


Link to this section

Subgrounds is built and maintained by the Playgrounds team and can be accessed on the Playgrounds docs.

Since subgrounds has a large feature set to explore, here are some helpful starting places:

  • Getting Started with Querying
    • A good first step for how to build queries with subgrounds.
  • Building Synthetic Fields
    • A gentle introduction to defining synthetic fields that transform data defined from the schema.
  • Concurrent Queries
    • Learn how to level up your queries by parallelizing them.
  • Exporting Data to CSVs
    • A quick article on how to seemlessly save your data as CSVs for further analysis.
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Building Subgraphs on Base
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