228 lines
7.9 KiB
Python
Executable File
228 lines
7.9 KiB
Python
Executable File
#! /usr/bin/python3
|
|
from smb.SMBConnection import SMBConnection
|
|
from flask import Flask, jsonify, request
|
|
from threading import Thread
|
|
from time import sleep
|
|
import time
|
|
import requests
|
|
import json
|
|
|
|
# global last_indoor_data
|
|
global indoor_server_ip
|
|
global indoor_server_password
|
|
global outdoor_api_url
|
|
global location
|
|
|
|
# Load the config file "config.json"
|
|
config = json.loads(open("config.json", "r").read())
|
|
indoor_server_ip = config["indoor_server_ip"]
|
|
indoor_server_password = config["indoor_server_password"]
|
|
outdoor_api_url = config["outdoor_api_url"]
|
|
location = config["location"]
|
|
|
|
# Assume that the indoor unit is offline
|
|
# The get_indoor_data() function will update this variable
|
|
last_indoor_data = {
|
|
"offline": True
|
|
}
|
|
|
|
# def get_indoor_data() -> list:
|
|
# global indoor_server_ip
|
|
# global indoor_server_password
|
|
# # SMB server details
|
|
# server_name = indoor_server_ip
|
|
# share_name = "airvisual"
|
|
# username = "airvisual"
|
|
# password = indoor_server_password
|
|
|
|
# # File details, The file is a text file with name:
|
|
# # <year><month>_AirVisual_values.txt
|
|
# # Get the prefix of the file name
|
|
# prefix = time.strftime("%Y%m", time.localtime())
|
|
# file_path = prefix + "_AirVisual_values.txt"
|
|
|
|
# # Connect to the SMB server
|
|
# conn = SMBConnection(username, password, "", "")
|
|
# conn.connect(server_name, 139)
|
|
|
|
# # Read the file contents
|
|
# file_obj = open(file_path, "wb")
|
|
# conn.retrieveFile(share_name, file_path, file_obj)
|
|
# conn.close()
|
|
|
|
# # Open the local cached file
|
|
# file_obj = open(file_path, "r")
|
|
|
|
# # The first line of the file contains the header
|
|
# # The header contains the column names separated by a semicolon (;)
|
|
# # The rest of the file contains the data separated by a semicolon (;)
|
|
# # Extract the column names and the data from the file
|
|
# file_obj.seek(0)
|
|
# header = file_obj.readline().strip().split(";")
|
|
# data = file_obj.readlines()
|
|
# # Split all the data into a list of lists
|
|
# data = [row.strip().split(";") for row in data]
|
|
# file_obj.close()
|
|
|
|
|
|
# # Remap the header names
|
|
# headers_map = {
|
|
# "PM2_5(ug/m3)": "pm25",
|
|
# "PM10(ug/m3)": "pm10",
|
|
# "PM1(ug/m3)": "pm1",
|
|
# "CO2(ppm)": "co2",
|
|
# "AQI(US)": "aqi",
|
|
# "Temperature(C)": "temperature",
|
|
# "Humidity(%RH)": "humidity",
|
|
# "Timestamp": "time"
|
|
# }
|
|
|
|
# # Remove rows with header names that are not in the header map
|
|
# # First, get the indices of the header names that are in the header map
|
|
# headers_indices = []
|
|
# for index, name in enumerate(header):
|
|
# if name in headers_map:
|
|
# headers_indices.append(index)
|
|
|
|
# # Construct the new header with the header names that are in the header map
|
|
# header = [header[index] for index in headers_indices]
|
|
|
|
# # Construct the new data with only the columns indicated by the header indices
|
|
# data = [[row[index] for index in headers_indices] for row in data]
|
|
|
|
# # Remap the header names
|
|
# headers = [headers_map[name] for name in header]
|
|
|
|
# # Convert unix timestamp to human readable time
|
|
# for row in data:
|
|
# row[headers.index("time")] = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(int(row[headers.index("time")])))
|
|
|
|
# # Create a list of dictionaries representing the data
|
|
# # Each dictionary represents a row of data
|
|
# data_list = []
|
|
# for row in data:
|
|
# data_dict = {}
|
|
# for header in headers:
|
|
# data_dict[header] = row[headers.index(header)]
|
|
# data_list.append(data_dict)
|
|
# return data_list
|
|
|
|
def get_outdoor_data_current() -> dict:
|
|
# Fetch the data from the AirVisual API
|
|
# Note that API call is rate limited to 5 calls per minute
|
|
# If this function is called within 1 minute of the previous call, return the cached data
|
|
|
|
# Check if the cache file exists
|
|
# If it does not exist, create a new cache file
|
|
try:
|
|
data = json.loads(open("outdoor_data_cache.txt", "r").read())
|
|
except:
|
|
default_data = {
|
|
"pm25": 0,
|
|
"pm10": 0,
|
|
"pm1": 0,
|
|
"aqi": 0,
|
|
"temperature": 0,
|
|
"humidity": 0,
|
|
"pressure": 0,
|
|
"time": 0,
|
|
"last_updated": 0 # Unix timestamp
|
|
}
|
|
open("outdoor_data_cache.txt", "w").write(json.dumps(default_data))
|
|
data = default_data
|
|
# Is the last_updated time more than 6 minute ago?
|
|
# If it is, fetch the data from the API
|
|
# If it is not, return the cached data
|
|
# Note that the cache file is a JSON object
|
|
data["last_updated"] = int(data["last_updated"])
|
|
# Remove the last_updated key
|
|
if data["last_updated"] + 60*6 < int(time.time()):
|
|
global outdoor_api_url
|
|
url = outdoor_api_url
|
|
response = requests.get(url)
|
|
try:
|
|
print("Fetching data from API!" )
|
|
data = response.json()
|
|
# Create a dictionary of the data
|
|
data = {
|
|
"pm25": data["current"]["pm25"]["conc"],
|
|
"pm10": data["current"]["pm10"]["conc"],
|
|
"pm1": data["current"]["pm1"]["conc"],
|
|
"aqi": data["current"]["aqius"],
|
|
"temperature": data["current"]["tp"],
|
|
"humidity": data["current"]["hm"],
|
|
"pressure": data["current"]["pr"],
|
|
"time": data["current"]["ts"]
|
|
}
|
|
# Time is in 2024-01-03T16:08:32.000Z
|
|
# Convert to GMT+7 in the format YYYY-MM-DD HH:MM:SS
|
|
# First parse the time string to a datetime object
|
|
# Then format the datetime object to YYYY-MM-DD HH:MM:SS
|
|
# The time string is in UTC time, we need to convert it to GMT+7
|
|
data["time"] = time.strptime(data["time"], "%Y-%m-%dT%H:%M:%S.000Z")
|
|
data["time"] = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(time.mktime(data["time"]) + 7 * 3600))
|
|
# Update the cache file
|
|
data["last_updated"] = int(time.time())
|
|
open("outdoor_data_cache.txt", "w").write(json.dumps(data))
|
|
# Remove the last_updated key
|
|
# TODO store the data in a database
|
|
return data
|
|
except:
|
|
# Oops, we got rate limited
|
|
# Return the cached data
|
|
print("Rate limited!")
|
|
# Remove the last_updated key
|
|
return data
|
|
else:
|
|
# Return the cached data
|
|
print("Using cached data!")
|
|
# Remove the last_updated key
|
|
return data
|
|
|
|
def merge_data(indoor_data_current: dict, outdoor_data: dict) -> dict:
|
|
# Indoor data dict's key are to be appended with "_indoor"
|
|
# Outdoor data dict's key are to be appended with "_outdoor"
|
|
# Merge the two dictionaries
|
|
merged_data = {}
|
|
for key, value in indoor_data_current.items():
|
|
merged_data[key + "_indoor"] = value
|
|
for key, value in outdoor_data.items():
|
|
merged_data[key + "_outdoor"] = value
|
|
return merged_data
|
|
|
|
|
|
app = Flask(__name__)
|
|
|
|
# Refresh the indoor data every 30 seconds
|
|
def refresh_data():
|
|
while True:
|
|
|
|
# print("Fetching indoor data!")
|
|
# indoor_data = get_indoor_data()
|
|
# global last_indoor_data
|
|
# # last_indoor_data the last dictionary in the list
|
|
# last_indoor_data = indoor_data[-1]
|
|
|
|
# Fetch the outdoor data
|
|
print("Fetching outdoor data!")
|
|
outdoor_data = get_outdoor_data_current()
|
|
|
|
sleep(30)
|
|
|
|
# Start the thread to refresh the data
|
|
Thread(target=refresh_data).start()
|
|
|
|
# Return All Data in the current month
|
|
@app.route("/get_data", methods=["GET"])
|
|
def get_data_route():
|
|
global location
|
|
# global last_indoor_data
|
|
# indoor_data = last_indoor_data
|
|
|
|
# Indoor data fetch is disabled
|
|
indoor_data = {}
|
|
|
|
outdoor_data = get_outdoor_data_current()
|
|
merged_data = merge_data(indoor_data, outdoor_data)
|
|
merged_data["location"] = location
|
|
return jsonify(merged_data) |