Install & Compatibility
Where this runs
tested against v1.7.0 · pip install
no network on importno background threads
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
py 3.10
✕ build_error
✓ 57.9s
py 3.11
✕ build_error
✓ 54.7s
py 3.12
✕ build_error
✓ 55.4s
py 3.13
✕ build_error
✓ 56.2s
py 3.9
✕ build_error
✕ build_error
2637MB installed
● package 2637MB
Code
Verified usage
Verified import paths — ran on the pinned version, not inferred.
Meridian
✓ from meridian import Meridian
Correct import from the top-level meridian package.
MeridianData
✓ from meridian.data import MeridianData
Data container class.
setup_data
✓ from meridian.data import setup_data
Helper to load data into MeridianData.
run_inference
✓ from meridian.analysis import run_inference
Run inference on a fitted model.
plot_media_effectiveness_curves
✓ from meridian.analysis import plot_media_effectiveness_curves
Generate diagnostic plots.
Model
✓
✗ import meridian.Model
Model is not a direct module; Meridian is the main class in the meridian package.
Basic workflow: load data, prepare MeridianData, initialize Meridian model, fit, and get ROI summary.
import pandas as pd
from meridian import Meridian
from meridian.data import setup_data
# Load your data (example: CSV)
data = pd.read_csv('mmm_data.csv')
# Create MeridianData object
md = setup_data(data, media_channels=['tv', 'digital'],
non_media_variables=['price', 'macro_index'],
response='sales', target_roi=2.0)
# Initialize model
model = Meridian()
# Fit model (sampling may take time)
model.fit(md)
# Run inference and get ROI summary
summary = model.get_summary(md)
print(summary)
Upgrade
Version history
1.7.0latest on PyPI · released Jun 18, 2026
Audit
Dependencies
numpyrequiredNumerical computations
pandasrequiredData handling
google-api-python-clientoptionalGoogle API client (for some features)
google-cloud-bigqueryoptionalBigQuery data source