phable 0.1.14

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About

Phable is a simple, modern Python toolkit for basic client connectivity to a Project Haystack server.

We aimed to make code within Phable's client.py and kinds.py modules self-documenting by using type hints and docstrings and carefully selecting what is publicly exposed. In the future we plan to improve docs and release a stable version 1.0.0 for Phable.

Installation

Phable requires Python version 3.11 or higher and generally has no required software dependencies. Download Phable from PyPI using:

$ pip install phable

Phable uses the zoneinfo module for IANA time zone support, which by default uses the system's time zone data if available. If no system time zone data is available, then Phable requires the tzdata package available on PyPI to be installed.

Phable has an optional pandas package dependency that is required for phable.kinds.Grid.to_pandas(). Download Phable with pandas from PyPI using:

$ pip install "phable[pandas]"

Note: Most of the below examples require the optional pandas package dependency.

Example: A Custom SSL Context & Haystack's About op

from datetime import date

from phable.client import Client
import ssl

# define these settings specific to your use case
uri = "https://host"
username = "<username>"
password = "<password>"
ssl_context = ssl.create_default_context()
ssl_context.check_hostname = False
ssl_context.verify_mode = ssl.CERT_NONE

with Client(uri, username, password, ssl_context) as ph:
    about = ph.about()

print("Here is information about the Haystack server:\n")
print(about)

Example: Haystack's Read & HisRead ops

from datetime import date

from phable.client import Client

# define these settings specific to your use case
uri = "http://localhost:8080/api/demo"
username = "<username>"
password = "<password>"

with Client(uri, username, password) as ph:
    # read history data on main electric meter power points
    pts = ph.read("point and power and equipRef->siteMeter")
    his_df = ph.his_read(pts, date.today()).to_pandas()

print("Here is the Pandas DataFrame showing point history data:\n")
print(his_df)
print()
print(f"Here are the DataFrame's attributes:\n{his_df.attrs}")

# Notes:
# 1. These attributes contain info from the point grid
# 2. Later we may add some funcs to help parse the DataFrame attributes
# 3. History Grids converted to Pandas DataFrames show point Ref display names
#    for their column names

Example: Haystack's Read & HisRead ops using IDs and DateRange

from datetime import date, timedelta

from phable.client import Client
from phable.kinds import DateRange, Ref

# define these settings specific to your use case
uri = "http://localhost:8080/api/demo"
username = "<username>"
password = "<password>"

# update the ids for your server
id1 = Ref("p:demo:r:2caffc8e-aa932383")
id2 = Ref("p:demo:r:2caffc8e-1768df4f")

end = date.today()
start = end - timedelta(days=2)
range = DateRange(start, end)

with Client(uri, username, password) as ph:
    pts_df = ph.read_by_ids([id1, id2]).to_pandas()
    his_df = ph.his_read_by_ids([id1, id2], range).to_pandas()

print("Here is the Pandas DataFrame showing point data:\n")
print(pts_df)
print()
print("Here is the Pandas DataFrame showing point history data:\n")
print(his_df)
print()
print(f"Here are attributes on the History DataFrame:\n{his_df.attrs}")

# Notes:
# 1. There are fewer attributes preserved when using Client.his_read_by_ids()
#    compared to Client.read_by_ids()
# 2. History Grids converted to Pandas DataFrames show point Ref display names
#    for their column names

Example: Async Usage without Context Manager

import asyncio

from phable.client import Client


async def main() -> None:
    # define these settings specific to your use case
    uri = "http://localhost:8080/api/demo"
    username = "<username>"
    password = "<password>"

    ph = Client(uri, username, password)

    ph.open()
    power_pt_read = asyncio.to_thread(ph.read, "power and point")
    energy_pt_read = asyncio.to_thread(ph.read, "energy and point")
    power_pt_read, energy_pt_read = await asyncio.gather(power_pt_read, energy_pt_read)
    ph.close()

    # convert Grids to Pandas DataFrames and print the results
    power_pt_read = power_pt_read.to_pandas()
    energy_pt_read = energy_pt_read.to_pandas()

    print(power_pt_read)
    print(energy_pt_read)


if __name__ == "__main__":
    asyncio.run(main())

Example: History Write to a Single Point

from datetime import datetime, timedelta
from zoneinfo import ZoneInfo

from phable.client import Client
from phable.kinds import Number, Ref

# define these settings specific to your use case
uri = "http://localhost:8080/api/demo"
username = "su"
password = "su"


ts_now = datetime.now(ZoneInfo("America/New_York"))
data_rows = [
    {
        "ts": ts_now - timedelta(seconds=30),
        "val": Number(1_000.0, "kW"),
    },
    {
        "ts": ts_now,
        "val": Number(2_000.0, "kW"),
    },
]

with Client(uri, username, password) as ph:
    ph.his_write_by_ids(Ref("2d6a2714-0d0a79fb"), data_rows)

Example: History Write to Multiple Points

from datetime import datetime, timedelta
from zoneinfo import ZoneInfo

from phable.client import Client
from phable.kinds import Number, Ref

# define these settings specific to your use case
uri = "http://localhost:8080/api/demo"
username = "su"
password = "su"


ts_now = datetime.now(ZoneInfo("America/New_York"))
data_rows = [
    {
        "ts": ts_now - timedelta(seconds=30),
        "v0": Number(3_000.0, "kW"),
    },
    {
        "ts": ts_now,
        "v1": Number(4_000.0, "kW"),
    },
]

# Ref at index 0 of ids corresponds to data values in col v0
# Ref at index 1 of ids corresponds to data values in col v1
ids = [Ref("2d6a2714-0d0a79fb"), Ref("2d6a2714-503317c5")]

with Client(uri, username, password) as ph:
    ph.his_write_by_ids(ids, data_rows)

Example: SkySpark's Eval Op

from phable.client import Client

# define these settings specific to your use case
uri = "http://localhost:8080/api/demo"
username = "su"
password = "su"


with Client(uri, username, password) as ph:
    his_df = ph.eval(
        """read(power and point and equipRef->siteMeter)
                        .hisRead(lastMonth)"""
    ).to_pandas()

print("Here is the Pandas DataFrame showing point history data:\n")
print(his_df)
print()
print(f"Here are the DataFrame's attributes:\n{his_df.attrs}")

Example: SkySpark's Commit Op

from phable.client import Client, CommitFlag
from phable.kinds import Grid, Marker

# define these settings specific to your use case
uri = "http://localhost:8080/api/demo"
username = "su"
password = "su"

# create the client object and open the connection
ph = Client(uri, username, password)
ph.open()

# create a new rec on SkySpark
rec = [{"dis": "TestRec", "testing": Marker(), "pytest": Marker()}]
response1: Grid = ph.commit(rec, CommitFlag.ADD)

# update the newly created rec
# Note:  the id column and current mod timestamp must be included
rec = [
    {"id": response1.rows[0]["id"], "mod": response1.rows[0]["mod"], "foo": "new tag"}
]
response2: Grid = ph.commit(rec, CommitFlag.UPDATE)

# delete the newly created and updated rec
# Note:  the rec should have only an id and mod column
rec = [{"id": response2.rows[0]["id"], "mod": response2.rows[0]["mod"]}]
response: Grid = ph.commit(rec, CommitFlag.REMOVE)

# close the session with the Haystack server (SkySpark)
ph.close()

Breaking Changes

The early focus of this project is to find the best practices for using modern Python with a Haystack server. This may lead to breaking changes in newer Phable versions. We plan to release a stable version 1.0.0 of Phable sometime in 2024 (TBD).