prism-pull 0.1.4

Python package to pull PRISM weather data via web automation.

prism-pull

prism-pull is a python package made to pull data from PRISM Group via web automation. Via the the PRISM website:

The PRISM Group gathers weather observations from a wide range of monitoring networks, applies
 sophisticated quality control measures, and develops spatial datasets to reveal short- and 
 long-term weather patterns. The resulting datasets incorporate a variety of modeling techniques 
 and are available at multiple spatial/temporal resolutions, covering the period from 1895 to 
 the present. 

The types of weather data consist of:

• precipitaion totals
• minimum temperatures
• mean temperatures
• maximum temperatures
• minimum vapor pressure deficit
• maximum vapor pressure deficit
• mean dewpoint temperature
• cloud transmittance
• horizontal surface solar radiation data
• sloped surface solar radiation data
• clear sky solar radiation data

These data are available across a variety of timescales for each cell of a 4km by 4km or 800m by 800m grid covering the entire continential United States. This makes it an especially great source for locations where weather stations may not be operating.

Installation

Prerequisites:

• pip
• Google Chrome
• Python3.13
  • Working on finding lowest compatible python version at the moment. Install with: pip install prism-pull

Usage

Remember to follow the PRISM Group terms of use for whatever your project may be. Usage is simple, and will be familiar to anyone who has used the PRISM GUI in the past. The package consists of one class, and it's associated getter methods:

• PrismSession
  • get_30_year_monthly_normals
  • get_30_year_daily_normals
  • get_annual_values
  • get_single_month_values
  • get_monthly_values
  • get_daily_values

Each method has two to three required arguments which are common to all of them. They are:

• is_bulk_request
  • Set to True if you are providing a .csv for bulk location request. False otherise.
  • If set to True, you must provide a string csv_path.
  • If set to False, you must provide int/float latitude and longitude.
• csv_path
  • A string path pointing to the .csv you want to use for a bulk request.
  • Your .csv input should have three columns:
    • Column 1:
      • latitude: int/float
    • Column 2:
      • longitude: int/float
    • Column 3:
      • name: string fewer than 13 characters in length
• latitude
  • An integer or floating point latitude coordinate.
• longitude
  • An integer of floating point longitude coordinate.

PrismSession

Generate a new PrismSession:

import prism-pull as pp

session = pp.PrismSession()

Your PrismSession object can be initialized with two optional arguments:

• download_dir:
  • The directory where prism-pull will download the results of your PRISM queries.
  • default: your current working directory
• driver_wait:
  • The time (in seconds) prism-pull web driver will wait before moving onto the next step. Consider increasing if you have poor download speeds.
  • default: 5 seconds Here's an example of setting up a session with these arguments:

import prism-pull as pp

session = pp.PrismSession(download_dir='absolute/path/to/download/to', driver_wait=10)

get_30_year_monthly_normals

Returns the average monthly conditions over the previous three decades for the specified area or areas. Here's an example usage showing a non-bulk request, and all the available weather inputs (precipitation, min_temp, etc.) set to their defaults:

import prism-pull as pp

session = pp.PrismSession()

session.get_30_year_monthly_normals(
    is_bulk_request: False,
    latitude=40.9473,
    longitude=-112.2170,
    precipitation=True,
    min_temp=False,
    mean_temp=True,
    max_temp=False,
    min_vpd=False,
    max_vpd=False,
    mean_dewpoint_temp=False,
    cloud_transmittance=False,
    solar_rad_horiz_sfc=False,
    solar_rad_sloped_sfc=False,
    solar_rad_clear_sky=False
)

Here's an example using a .csv for a bulk request, and setting a few non-default weather inputs:

import prism-pull as pp

session = pp.PrismSession()

session.get_30_year_monthly_normals(
    is_bulk_request: True,
    csv_path="tests/resources/small_coordinates.csv",
    max_temp=True,
    solar_rad_horiz_sfc=True,
    solar_rad_sloped_sfc=True
)

get_30_year_daily_normals

Returns the average daily conditions over the previous three decades for the specified area or areas. Here's an example usage showing a non-bulk request, and all the available weather inputs (precipitation, min_temp, etc.) set to their defaults:

import prism-pull as pp

session = pp.PrismSession()

session.get_30_year_daily_normals(
    is_bulk_request: False,
    latitude=40.9473,
    longitude=-112.2170,
    precipitation=True,
    min_temp=False,
    mean_temp=True,
    max_temp=False,
    min_vpd=False,
    max_vpd=False,
    mean_dewpoint_temp=False,
)

Here's an example using a .csv for a bulk request, and setting a few non-default weather inputs:

import prism-pull as pp

session = pp.PrismSession()

session.get_30_year_daily_normals(
    is_bulk_request: True,
    csv_path="tests/resources/small_coordinates.csv",
    max_temp=True,
    mean_temp=False
)

get_annual_values

Returns data for selected measurements in the specified range of years. Here's an example usage showing a non-bulk request, and all the available weather inputs (precipitation, min_temp, etc.) set to their defaults:

import prism-pull as pp

session = pp.PrismSession()

session.get_annual_values(
    is_bulk_request: False,
    start_year=2015,
    end_year=2023,
    latitude=40.9473,
    longitude=-112.2170,
    precipitation=True,
    min_temp=False,
    mean_temp=True,
    max_temp=False,
    min_vpd=False,
    max_vpd=False,
    mean_dewpoint_temp=False,
)

Here's an example using a .csv for a bulk request, and setting a few non-default weather inputs:

import prism-pull as pp

session = pp.PrismSession()

session.get_annual_values(
    is_bulk_request: False,
    start_year=1960,
    end_year=1966,
    csv_path="tests/resources/small_coordinates.csv",
    precipitation=False,
    max_temp=True,
    min_vpd=True,
    max_vpd=True,
)

get_single_month_values

Returns data for selected measurements for a given month each year in the specified range of years. Here's an example usage showing a non-bulk request, and all the available weather inputs (precipitation, min_temp, etc.) set to their defaults:

import prism-pull as pp

session = pp.PrismSession()

session.get_single_month_values(
    is_bulk_request: False,
    month=4,
    start_year=1980,
    end_year=1990,
    latitude=40.9473,
    longitude=-112.2170,
    precipitation=True,
    min_temp=False,
    mean_temp=True,
    max_temp=False,
    min_vpd=False,
    max_vpd=False,
    mean_dewpoint_temp=False,
)

Here's an example using a .csv for a bulk request, and setting a few non-default weather inputs:

import prism-pull as pp

session = pp.PrismSession()

session.get_single_month_values(
        is_bulk_request: True,
        month=11,
        start_year=2021,
        end_year=2024,
        csv_path="tests/resources/small_coordinates.csv",
        min_vpd=True,
        max_vpd=True,
)

get_monthly_values

Returns monthly data for selected measurements for each month between the starting month and year, to ending month and year. Here's an example usage showing a non-bulk request, and all the available weather inputs (precipitation, min_temp, etc.) set to their defaults:

import prism-pull as pp

session = pp.PrismSession()

session.get_monthly_values(
    is_bulk_request: False,
    start_month=2,
    start_year=2011,
    end_month=9,
    end_year=2024,
    latitude=40.9473,
    longitude=-112.2170,
    precipitation=True,
    min_temp=False,
    mean_temp=True,
    max_temp=False,
    min_vpd=False,
    max_vpd=False,
    mean_dewpoint_temp=False,

)

Here's an example using a .csv for a bulk request, and setting a few non-default weather inputs:

import prism-pull as pp

session = pp.PrismSession()

session.get_monthly_values(
    is_bulk_request: True,
    start_month=2,
    start_year=2011,
    end_month=9,
    end_year=2024,
    csv_path="tests/resources/small_coordinates.csv",
    precipitation=False,
    mean_dewpoint_temp=True,
)

get_daily_values

Returns daily data for selected measurements for each dat between the starting date, month, and year, to ending date, month, and year. Here's an example usage showing a non-bulk request, and all the available weather inputs (precipitation, min_temp, etc.) set to their defaults:

import prism-pull as pp

session = pp.PrismSession()

session.get_daily_values(
    is_bulk_request: False,
    start_date=16,
    start_month=11,
    start_year=1995,
    end_date=16,
    end_month=11,
    end_year=2009,
    latitude=40.9473,
    longitude=-112.2170,
    precipitation=True,
    min_temp=False,
    mean_temp=True,
    max_temp=False,
    min_vpd=False,
    max_vpd=False,
    mean_dewpoint_temp=False,
)

Here's an example using a .csv for a bulk request, and setting a few non-default weather inputs:

import prism-pull as pp

session = pp.PrismSession()

session.get_daily_values(
    is_bulk_request: True,
    start_date=16,
    start_month=11,
    start_year=1995,
    end_date=16,
    end_month=11,
    end_year=2009,
    csv_path="tests/resources/small_coordinates.csv",
    min_temp=True,
    min_vpd=True,
)

Testing

This repo uses pytest for testing. In order to run locally, execute the following from the terminal:

pytest tests

Contributing

If you work on this repo as a collaborator, shoot me an email at [e-mail].