Skip to main content

This is the official Python library for the Myst Platform.

Project description

Myst Python Library

This is the official Python client library for the Myst Platform.

Requirements

  • Python 2.7+ or Python 3.4+

Installation

To install the package from PyPI:

$ pip install --upgrade myst

Authentication

The Myst API uses JSON Web Tokens (JWTs) to authenticate requests. The Myst Python library handles the sending of JWTs to the API automatically and currently supports two ways to authenticate to obtain a JWT: through your Google user account or a Myst service account.

Authenticating using your user account

If you don't yet have a Google account, you can create one on the Google Account Signup page.

Once you have access to a Google account, send an email to support@myst.ai with your email so we can authorize you to use the Myst Platform.

Use the following code snippet to authenticate using your user account:

import myst

myst.authenticate()

The first time you run this, you'll be presented with a web browser and asked to authorize the Myst Python library to make requests on behalf of your Google user account.

Authenticating using a service account

You can also authenticate using a Myst service account. To request a service account, email support@myst.ai.

To authenticate using a service account, set the MYST_APPLICATION_CREDENTIALS environment variable to the path to your service account key file and specify use_service_account=True:

$ export MYST_APPLICATION_CREDENTIALS=</path/to/key/file.json>
import myst

myst.authenticate(use_service_account=True)

You can also explicitly pass the path to your service account key when authenticating:

import myst

myst.authenticate(
    use_service_account=True,
    service_account_key_file_path='/path/to/key/file.json',
)

Working with time series

The Myst python library currently supports listing, getting, and fetching data for time series.

Listing time series

import myst

myst.authenticate()

all_time_series = myst.TimeSeries.list()

Getting a time series

import myst

myst.authenticate()

time_series = myst.TimeSeries.get('fc84...')

Fetching data from a time series

You can either fetch data by specifying absolute start and end times, or offsets relative to the as_of_time. If no as_of_time is given, it is assumed to mean "as of now":

import datetime
import pytz

import myst

myst.authenticate(...)

time_series = myst.TimeSeries.get('fc84...')

# Fetching data using absolute start and end times.
data = time_series.fetch_data(
    start_time=datetime.datetime(2019, 1, 1),
    end_time=datetime.datetime(2019, 1, 2),
)

# Fetching data specifying an as of time.
data = time_series.fetch_data(
    start_time=datetime.datetime(2019, 1, 1),
    end_time=datetime.datetime(2019, 1, 2),
    as_of_time=datetime.datetime(2019, 1, 1, 12),
)

# Fetching data using offsets relative to now.
data = time_series.fetch_data(
    start_offset=datetime.timedelta(hours=-12),
    end_offset=datetime.timedelta(hours=12),
)

# Fetching data specifying a combination of relative offsets and absolute timestamps.
data = time_series.fetch_data(
    start_offset=datetime.timedelta(hours=-12),
    end_time=datetime.datetime(2019, 1, 2),
)

Support

For questions or just to say hi, reach out to support@myst.ai.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for myst, version 0.1.1
Filename, size File type Python version Upload date Hashes
Filename, size myst-0.1.1-py2.py3-none-any.whl (35.4 kB) File type Wheel Python version py2.py3 Upload date Hashes View
Filename, size myst-0.1.1.tar.gz (26.5 kB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page