ohm-ai 1.0.7

Python library to export data from and interact with the Ohm AI Platform

Ohm AI Library Documentation

Welcome to the Ohm library documentation!

This Python library provides tools for interacting with the Ohm API, allowing you to access and analyze your battery data.

Key Features

• Data Retrieval: Easily fetch battery observation metrics, dataset cycle data, and metadata.
• Filtering: Refine your data retrieval using flexible filter options.
• Data Handling: Work with data in a structured format using pandas DataFrames.

Installation

pip install ohm-ai

Usage

1. Initialization:

from ohm_ai import OhmClient, OhmFilter, OhmFilterOperator, OhmFilterGroup, OhmFilterGroupType

# For synchronous operations
ohm_client = OhmClient(api_key="YOUR_API_TOKEN")

2. Data Retrieval:

• Get Battery Observation Metrics:

# Get all battery observation metrics
observation_data = ohm_client.get_observation_data()

• Get Battery Dataset Cycle Data:

# Get all battery dataset cycle data
cycle_data = ohm_client.get_dataset_cycle_data()

• Get Battery Metadata:

# Get all battery metadata
metadata = ohm_client.get_metadata()

3. Filtering:

# Create filters using OhmFilterOperator enumerable or their string values direcly
filter_1 = OhmFilter(column="voltage", operator=OhmFilterOperator.EQ, value=3.5)
filter_2 = OhmFilter(column="voltage", operator="equals", value=3.5)

# Create a filter group using the OhmFilterGroupType or their string values directly
filter_group_1 = OhmFilterGroup([filter_1, filter_2], type=OhmFilterGroupType.AND)
filter_group_2 = OhmFilterGroup([filter_1, filter_2], type="and")

# OhmFilterGroup objects can be nested to create complex logic
filter_group_3 = OhmFilterGroup([filter_group_1, filter_group_2], type="or")

# Retrieve a chunk of filtered observation data -> Returns a pandas dataframe object
# Use either a list of filters or a OhmFilterGroup object
filtered_observation_data = ohm_client.get_observation_data(filters=[filter_1, filter_2])
filtered_observation_data = ohm_client.get_observation_data(filters=filter_group_3)

# Retrieve a chunk of filtered dataset cycle data -> Returns a pandas dataframe object
filtered_cycle_data = ohm_client.get_dataset_cycle_data(filters=[filter_1, filter_2])
filtered_cycle_data = ohm_client.get_dataset_cycle_data(filters=filter_group_3)

# Retrieve a chunk of filtered metadata -> Returns a pandas dataframe object
filtered_metadata = ohm_client.get_metadata(filters=[filter_1, filter_2])
filtered_metadata = ohm_client.get_metadata(filters=filter_group_3)