from jasper import Jasper
from jasper.helpers import read_file, get_stations
from jasper.actions import export_csv
# General configuration
STATIONS_PER_CYCLE = 11
# Create Jasper instance
jsp = Jasper("export.bulk.monthly")
# Get weather station(s)
stations = get_stations(
jsp,
read_file("monthly_stations.sql"),
STATIONS_PER_CYCLE,
)
# Export data for each weather station
for station in stations:
result = jsp.query(
read_file("monthly.sql"), {"station": station[0], "timezone": station[1]}
)
if result.rowcount > 0:
# Fetch data
data = result.fetchall()
# Export data dump
export_csv(
import pandas as pd
from jasper import Jasper
from jasper.actions import persist
from jasper.helpers import get_stations, read_file
from jasper.schema import hourly_national
# General configuration
STATIONS_PER_CYCLE = 36
# Create Jasper instance
jsp = Jasper("import.noaa.hourly.national_metar")
# Get weather stations
stations = get_stations(
jsp, read_file("national_metar_stations.sql"), STATIONS_PER_CYCLE
)
# DataFrame which holds all data
df_full = None
# Import data for each weather station
if len(stations) > 0:
for station in stations:
try:
# Create request for JSON file
url = f"https://api.weather.gov/stations/{station['icao']}/observations/latest"
req = request.Request(
url, headers={"User-Agent": "meteostat.net [email protected]"}
)
The code is licensed under the MIT license.
"""
from jasper import Jasper
from jasper.helpers import read_file, get_stations
from jasper.actions import export_csv
# General configuration
STATIONS_PER_CYCLE = 10
# Create Jasper instance
jsp = Jasper("export.bulk.daily")
# Get weather station(s)
stations = get_stations(jsp, read_file("daily_stations.sql"),
STATIONS_PER_CYCLE)
# Export data for each weather station
for station in stations:
result = jsp.query(read_file("daily.sql"), {
"station": station[0],
"timezone": station[1]
})
if result.rowcount > 0:
# Fetch data
data = result.fetchall()
# Export data dump
export_csv(jsp, list(map(lambda d: d[:11], data)),
Export meta data for weather stations
The code is licensed under the MIT license.
"""
import json
from jasper import Jasper
from jasper.helpers import read_file
from jasper.actions import export_csv, export_json
# Create Jasper instance
jsp = Jasper("export.bulk.stations.meta")
# Export data for all weather stations
result = jsp.query(read_file("meta.sql"))
if result.rowcount > 0:
# Fetch data
data = result.fetchall()
# Data lists
full = []
lite = []
slim = []
for record in data:
# Create dict of names
try:
names = json.loads(record[2])
except BaseException:
"sleetandthunder": 25,
"sleetshowers": 19,
"sleetshowersandthunder": 25,
"snow": 15,
"snowandthunder": 25,
"snowshowers": 21,
"snowshowersandthunder": 25,
}
return condicodes.get(str(code).split("_")[0], None)
# Get weather stations
stations = get_stations(
jsp,
read_file("model_stations.sql"),
STATIONS_PER_CYCLE,
)
# DataFrame which holds all data
df_full = None
# Import data for each weather station
if len(stations) > 0:
for station in stations:
try:
# Create request for JSON file
url = (
"https://api.met.no/weatherapi/locationforecast/2.0/complete.json?"
+ f"altitude={station[3]}&lat={station[1]}&lon={station[2]}")
req = request.Request(
def write_station(data: dict) -> None:
"""
Add a new weather station or update existing
"""
try:
# Break if invalid data
if len(data["id"]) != 5 or len(data["country"]) != 2:
return None
# Extract alternate names
name_alt = {
key: data["name"][key]
for key in data["name"] if key != "en"
}
jsp.query(
read_file("stations_import.sql"),
{
"id":
data["id"],
"country":
data["country"],
"region":
data["region"],
"name":
data["name"]["en"],
"name_alt":
json.dumps(name_alt, ensure_ascii=False, sort_keys=True),
"national_id":
data["identifiers"]["national"] if
("national" in data["identifiers"]) else None,
"wmo":
data["identifiers"]["wmo"]
if "wmo" in data["identifiers"] else None,
"icao":
data["identifiers"]["icao"]
if "icao" in data["identifiers"] else None,
"iata":
data["identifiers"]["iata"]
if "iata" in data["identifiers"] else None,
"ghcn":
data["identifiers"]["ghcn"]
if "ghcn" in data["identifiers"] else None,
"wban":
data["identifiers"]["wban"]
if "wban" in data["identifiers"] else None,
"usaf":
data["identifiers"]["usaf"]
if "usaf" in data["identifiers"] else None,
"mosmix":
data["identifiers"]["mosmix"]
if "mosmix" in data["identifiers"] else None,
"lat":
data["location"]["latitude"],
"lon":
data["location"]["longitude"],
"elevation":
data["location"]["elevation"],
"tz":
data["timezone"],
},
)
except BaseException:
pass
[
"".join(sorted(list(set(flag)))) if flag is not None else None
for flag in d[13:]
]
),
data,
)
),
f"{path}/{station}.map.csv.gz",
)
# Get weather stations
stations = get_stations(
jsp,
read_file(f"hourly_stations_{MODE}.sql"),
STATIONS_PER_CYCLE,
)
# Start & end year
now = datetime.now()
start_year = now.year - 1 if MODE in ("recent", "live") else 1890
end_year = now.year + 1
# Export data for each weather station
for station in stations:
result = jsp.query(
read_file("hourly.sql"),
{
"station": station[0],
"start_datetime": f"{start_year}-01-01 00:00:00",