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Bezier curve simulation (including reductions the dimension from 3 to 2)

Project description

1 HistoricalWeatherTW 台灣歷史天氣爬蟲

This script is to crawl the information of 觀測資料查詢 website

Data from 觀測資料查詢系統

2 Usage

  1. Prepare station.csv.

  2. run the function of collect_weather_tw you will see the result!

    def collect_weather_tw(station_csv_path: Path, output_path,
                           end_date:, begin_date:,

You can refer to for more help

  1. Prepare config.yaml and use this path as input parameter

  2. run


from Carson.Tool.HistoricalWeatherTW import collect_weather_tw, QueryFormat
from pathlib import Path
import datetime
import os

if __name__ == '__main__':
    STATION_CSV = '../config/CSV/station_test.csv'
    OUTPUT_PATH = Path(f'../temp/year_result.csv')
    BEGIN_DATE =, 10, 1)
    END_DATE =, 10, 2)
    QUERY_FORMAT = QueryFormat.DAY
    CONVERT2NUM = True
    collect_weather_tw(Path(STATION_CSV), OUTPUT_PATH,
                       BEGIN_DATE, END_DATE,

3 Data


3.1 資料欄位如下

ObsTime 觀測時間(LST)

StnPres 測站氣壓(hPa)

SeaPres 海平面氣壓(hPa)

Temperature 氣溫(℃)

Tddewpoint 露點溫度(℃)

RH 相對溼度(%)

WS 風速(m/s)

WD 風向(360degree)

WSGust 最大陣風(m/s)

WDGust 最大陣風風向(360degree)

Precp 降水量(mm)

PrecpHour 降水時數(hr)

SunShine 日照時數(hr)

GloblRad 全天空日射量(MJ/㎡)

Visb 能見度(km)

4 Release note

4.1 v4.0

Encapsulated as API

4.2 v3.0


  • All outputs into a single file. (making it easier to use for SQL)

  • The output header field will automatically grab the content on the web page (not use hard coding)

  • You can choose the type of query (year, month, day) according to your needs.


  • Make the code easier to read.

4.3 V2.0


4.4 V1.0


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