jarvisms

### WARNING: READ CAREFULLY BEFORE ATTEMPTING ###
#
# Officially, this is not recommended. YMMV
# https://www.raspberrypi.com/news/bookworm-the-new-version-of-raspberry-pi-os/
#
# This mostly works if you are on 64bit. You are on your own if you are on 32bit or mixed 64/32bit
#
# Credit to anfractuosity and fgimenezm for figuring out additional details for kernels
#

jarvisms

import sqlite3
from datetime import datetime

# Connect directly with the database file and make a "connection" object
conn = sqlite3.connect(r"/home/pywws/weather-data/pywws.db")

start = datetime(2020,1,1).timestamp()  # Timestamp in seconds 1577836800.0
end = datetime(2020,2,1).timestamp()    # Timestamp in seconds 1580515200.0

# SQL query with named variables :start and :end which are supplied by a dictionary and substituted in place.

jarvisms

#!/usr/bin/env python3
import datetime
import os
import os.path
import shutil

def striptime(dt):
  try:
    return datetime.datetime.strptime(dt,"%Y-%m-%dT%H-%M-%S") # Convert it
  except ValueError:  # If it doesn't look like a date, return None (boolean False)

jarvisms

# Note this uses advanced (and unsupported) features, hence pythondcsPRO
import pythondcspro as pythondcs  # From https://github.com/jarvisms/pythondcs
import csv  # Standard Library
dcs = pythondcs.DCSSession(DCSURL,USERNAME,PASSWORD)    # Credentials as needed

backup={}   # Keep original copies as backup
with open("input.csv", newline="") as inputcsv:   # Adjust file as needed
    # File format is literally just "<id>,<name>" on each row
    csvreader = csv.reader(inputcsv)
    for id,name in csvreader:

jarvisms

import pythondcs  # From https://github.com/jarvisms/pythondcs
import csv  # Standard Library
dcs = pythondcs.DCSSession(DCSURL,USERNAME,PASSWORD)    # Credentials as needed

targets = [123,456,789]   # List of meters you want details for

with open(r"MetersDetails.csv", "w", newline="") as outputcsv:   # Adjust file as needed
  csvwriter = csv.writer(outputcsv)
  for id in targets:
    meter = dcs.get_meters(id)

jarvisms

import pythondcs  # From https://github.com/jarvisms/pythondcs
import csv  # Standard Library
from datetime import date
dcs = pythondcs.DCSSession(DCSURL,USERNAME,PASSWORD)    # Credentials as needed

targetmeters = [123,456,789]    # List as many IDs as you need. In this case all assumed to be registers.

with open("output.csv", "w", newline="") as outputcsv:   # Adjust file as needed
  csvwriter = csv.writer(outputcsv)
  ### Output in "Periodic Channel Export" format as needed to import into TEAM Sigma aM&T software, coloumns are: