Getting Started

Installation and configuration of the SynMax/Hyperion API Client:

Installation

pip install --upgrade synmax-api-python-client

Requirements

Before you install the client, make sure you have Python 3.7+ and pip installed.

Additionally, the following dependency packages will automatically be installed alongside synmax-api-python-client: aioretry, aiohttp, nest_asyncio, pandas, pydantic, tqdm, urllib3, wheel.

To install these dependencies yourself, run:

pip install aiohttp aioretry nest_asyncio pandas pydantic tqdm urllib3 wheel

Jupyter Notebooks

If you are using Jupyter Notebooks, please install the nest_asyncio package in order for async to work correctly:

!pip install nest_asyncio

To use the package, simply import it in your Python project and apply the patch.

import nest_asyncio
nest_asyncio.apply()

Note

In Python versions <3.7 you need to call apply() before importing nest_asyncio and in Python 3.7+ you call it after importing nest_asyncio.

---

Quickstart

Configuration of the Hyperion/Synmax client is a simple step-by-step process.

⮞ Import modules

from synmax.hyperion import HyperionApiClient, ApiPayload

⮞ Pass an access token

There are two ways to pass the access token:

A. Set an environment variable

os.environ['access_token'] = 'your token'

OR

B. Pass the access token to the HyperionApiClient instance

access_token = 'your access token goes here'
client = HyperionApiClient(access_token=access_token)

For more information on access tokens, please see the section on Authentication.

⮞ Enable logging

Logging may be enabled if required…

logging.basicConfig(level=logging.DEBUG)

To read more about logging, please see the Python documentation.

⮞ Fetch data

# to fetch region data:
region_df = client.fetch_regions()
print(region_df)

To see all available API methods…

print(dir(client))
# output: ['completions', 'dailyfrackedfeet', 'dailyproduction', 'ducsbyoperator', 'fraccrews', 'longtermforecast', 'operatorclassification', 'productionbywell', 'regions', 'rigs', 'shorttermforecast', 'shorttermforecasthistory', 'wells']

Note

The Hyperion/Synmax client returns objects in a pandas DataFrame. To understand more about interacting with DataFrames, please see the pandas documentation.

---

A complete example

This example fetches data on wells.

import logging
from synmax.hyperion import HyperionApiClient, ApiPayload

logging.basicConfig(level=logging.DEBUG)

access_token = 'your token'
client = HyperionApiClient(access_token=access_token)
payload = ApiPayload(start_date='2022-05-1', end_date='2022-07-1', state_code=['CO','TX'])

result_df = client.wells(payload)
print(result_df)