PyChartMogul

NOTE: This library is not mantained. ChartMogul now has an official Python API.

Basic Python wrapper for ChartMogul API

Installation

You can use pip to install PyChartMogul.

pip install git+https://github.com/davidgasquez/pychartmogul

If you prefer, you can clone it and run the setup.py file. Use the following commands to get a copy from Github and install all dependencies:

git clone https://github.com/davidgasquez/pychartmogul
cd pychartmogul
python setup.py install

Usage

Although you don't need to know anything about the ChartMogul API to use this module, you'll need an account token and a secret key to use it.

To use the wrapper:

from pychartmogul.client import ChartMogulClient

account_token = '********************************'
secret_key = '********************************'

client = ChartMogulClient(account_token, secret_key)

client.metrics.get_metric('mrr', '2016-06-01', '2016-06-10')
client.enrichment.list_customers()

Features

Support for datetime instead of str dates.
Response parsing to Pandas DataFrame.

Current Metrics

mrr: Retrieves the Monthly Recurring Revenue (MRR), for the specified time period.
arr: Retrieves the Annualized Run Rate (ARR), for the specified time period.
arpa: Retrieves the Average Revenue Per Account (ARPA), for the specified time period.
asp: Retrieves the Average Sale Price (ASP), for the specified time period.
customer-count: Retrieves the number of active customers, for the specified time period.
customer-churn-rate: Retrieves the Customer Churn Rate, for the specified time period.
mrr-churn-rate: Retrieves the Net MRR Churn Rate, for the specified time period.
ltv: Retrieves the Customer Lifetime Value (LTV), for the specified time period.

Is also possible to get a summary for a time-period:

client.metrics.get_summary('2016-06-01', '2016-06-10')

Roadmap

Custom number of Timeout retries.
Retrieve long periods splitting the initial request.

davidgasquez / pychartmogul