139 lines
4.4 KiB
Python
Executable file
139 lines
4.4 KiB
Python
Executable file
#!/usr/bin/env python3
|
|
|
|
from pyquery import PyQuery # install using `pip install pyquery`
|
|
import json
|
|
|
|
|
|
################################### CONFIGURATION ###################################
|
|
|
|
# set your location_id
|
|
# to get your location_id, go to https://weather.com & search for your location.
|
|
# once you choose your location, you can see the location_id in the URL(64 chars long hex string)
|
|
# like this: https://weather.com/en-IN/weather/today/l/c3e96d6cc4965fc54f88296b54449571c4107c73b9638c16aafc83575b4ddf2e
|
|
# once you get the location_id, you can replace the below location_id with your own location_id
|
|
location_id = "e42bb25a58c2e689ec85e632d82e69d7e46c82defb9ad7a5551b6c3a70fbc282" # TODO
|
|
|
|
# celcius or fahrenheit
|
|
unit = "metric" # metric or imperial
|
|
|
|
# forcase type
|
|
forecast_type = "Daily" # Hourly or Daily
|
|
|
|
########################################## MAIN ##################################
|
|
|
|
# weather icons
|
|
weather_icons = {
|
|
"sunnyDay": "",
|
|
"clearNight": "",
|
|
"cloudyFoggyDay": "",
|
|
"cloudyFoggyNight": "",
|
|
"rainyDay": "",
|
|
"rainyNight": "",
|
|
"snowyIcyDay": "",
|
|
"snowyIcyNight": "",
|
|
"severe": "",
|
|
"default": "",
|
|
}
|
|
|
|
# get html page
|
|
_l = "en-IN" if unit == "metric" else "en-US"
|
|
url = f"https://weather.com/{_l}/weather/today/l/{location_id}"
|
|
|
|
# get html data
|
|
html_data = PyQuery(url=url)
|
|
|
|
# current temperature
|
|
temp = html_data("span[data-testid='TemperatureValue']").eq(0).text()
|
|
|
|
# current status phrase
|
|
status = html_data("div[data-testid='wxPhrase']").text()
|
|
status = f"{status[:16]}.." if len(status) > 17 else status
|
|
|
|
# status code
|
|
status_code_class = html_data("#regionHeader").attr("class")
|
|
status_code = str(status_code_class).split(" ")[2].split("-")[2]
|
|
|
|
# status icon
|
|
icon = (
|
|
weather_icons[status_code]
|
|
if status_code in weather_icons
|
|
else weather_icons["default"]
|
|
)
|
|
|
|
# temperature feels like
|
|
temp_feel = html_data(
|
|
"div[data-testid='FeelsLikeSection'] > span > span[data-testid='TemperatureValue']"
|
|
).text()
|
|
temp_feel_text = f"Feels like {temp_feel}{'c' if unit == 'metric' else 'f'}"
|
|
|
|
# min-max temperature
|
|
temp_min = (
|
|
html_data("div[data-testid='wxData'] > span[data-testid='TemperatureValue']")
|
|
.eq(1)
|
|
.text()
|
|
)
|
|
temp_max = (
|
|
html_data("div[data-testid='wxData'] > span[data-testid='TemperatureValue']")
|
|
.eq(0)
|
|
.text()
|
|
)
|
|
temp_min_max = f" {temp_min}\t\t {temp_max}"
|
|
|
|
# wind speed
|
|
wind_speed = str(html_data("span[data-testid='Wind']").text())
|
|
wind_text = f" {wind_speed}"
|
|
|
|
# humidity
|
|
humidity = html_data("span[data-testid='PercentageValue']").text()
|
|
humidity_text = f" {humidity}"
|
|
|
|
# visibility
|
|
visbility = html_data("span[data-testid='VisibilityValue']").text()
|
|
visbility_text = f" {visbility}"
|
|
|
|
# air quality index
|
|
air_quality_index = html_data("text[data-testid='DonutChartValue']").text()
|
|
|
|
# rain prediction
|
|
r_prediction_text = html_data(f"section[aria-label='{forecast_type} Forecast']")(
|
|
"div[data-testid='SegmentPrecipPercentage'] > span"
|
|
).text()
|
|
r_prediction = str(r_prediction_text).replace("Chance of Rain", "")
|
|
r_prediction = f" ({forecast_type}) {r_prediction}" if len(r_prediction) > 0 else r_prediction
|
|
|
|
# temperature prediction
|
|
t_prediction_text = html_data(f"section[aria-label='{forecast_type} Forecast']")(
|
|
"div[data-testid='SegmentHighTemp'] > span"
|
|
).text()
|
|
t_prediction = str(t_prediction_text).replace(" /", "/")
|
|
t_prediction = f" ({forecast_type}) {t_prediction}" if len(t_prediction) > 0 else t_prediction
|
|
|
|
#pretty print all data
|
|
# print(f"temp: {temp}\nstatus: {status}\nstatus_code: {status_code}\nicon: {icon}\
|
|
# \ntemp_feel_text: {temp_feel_text}\ntemp_min_max: {temp_min_max}\nwind_text: {wind_text}\
|
|
# \nhumidity_text: {humidity_text}\nvisbility_text: {visbility_text}\nair_quality_index: {air_quality_index}\
|
|
# \nprediction: \n{r_prediction}\n{t_prediction}")
|
|
|
|
# tooltip text
|
|
tooltip_text = str.format(
|
|
"\t\t{}\t\t\n{}\n{}\n{}\n\n{}\n{}\n{}\n\n{}\n{}",
|
|
f'<span size="xx-large">{temp}C 🇩🇴</span>',
|
|
f"<big>{icon}</big>",
|
|
f"<big>{status}</big>",
|
|
f"<small>{temp_feel_text}</small>",
|
|
f"<big>{temp_min_max}</big>",
|
|
f"{wind_text}\t{humidity_text}",
|
|
f"{visbility_text}\tAQI {air_quality_index}",
|
|
f"<i>{r_prediction}</i>",
|
|
f"<i>{t_prediction}</i>"
|
|
)
|
|
|
|
# print waybar module data
|
|
out_data = {
|
|
"text": f"{icon} {temp}",
|
|
"alt": status,
|
|
"tooltip": tooltip_text,
|
|
"class": status_code,
|
|
}
|
|
print(json.dumps(out_data))
|
|
|