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Python SDK

The Python SDK is the primary and most actively maintained SDK for the LAMP Platform. It is recommended for data analysis, scripting, and automation.

Installation​

pip install LAMP-core

Connecting​

import LAMP
LAMP.connect('email@address.com', 'password', 'api.lamp.digital')

Replace with your credentials and server address. If using the default hosted server, use api.lamp.digital.

Querying Data​

List Researchers, Studies, and Participants​

# Get all researchers
researchers = LAMP.Researcher.all()

# Get studies for a researcher
studies = LAMP.Study.all_by_researcher(researcher_id)

# Get participants in a study
participants = LAMP.Participant.all_by_study(study_id)

Retrieve Sensor Data​

# Get GPS data for a participant
events = LAMP.SensorEvent.all_by_participant(
    participant_id,
    origin='lamp.gps'
)

Results are limited to 1000 entries per request. Use the _from and to parameters (Unix timestamps in milliseconds) for range queries:

events = LAMP.SensorEvent.all_by_participant(
    participant_id,
    origin='lamp.gps',
    _from=start_timestamp,
    to=end_timestamp
)

Retrieve Activity Data​

events = LAMP.ActivityEvent.all_by_participant(participant_id)

Each event contains:

  • timestamp — When the activity was completed (Unix ms).
  • duration — Time spent (milliseconds).
  • activity — Activity identifier.
  • temporal_slices — Array of individual responses.

Export to CSV​

import pandas as pd

# Collect GPS data for all participants in a study
all_data = []
for participant in LAMP.Participant.all_by_study(study_id)['data']:
    events = LAMP.SensorEvent.all_by_participant(
        participant['id'],
        origin='lamp.gps'
    )
    for event in events['data']:
        all_data.append({
            'participant': participant['id'],
            'timestamp': event['timestamp'],
            **event['data']
        })

df = pd.DataFrame(all_data)
df.to_csv('gps_data.csv', index=False)

Next Steps​

For automated feature computation from raw data, see Cortex.