Add 'bom_wind'

bom-wind/README.md

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+# bom_wind.py
+
+Download latest time series data from BOM website and update local copy.
+
+BOM does not allow direct http requests to data files, so a requests session
+is opened on the product page before accessing the resource.

bom-wind/bom_wind.py

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+"""Download latest time series data from BOM website and update local copy.
+
+BOM does not allow direct http requests to data files, so a requests session
+is opened on the product page before accessing the resource.
+
+D. Howe
+2019-09-04
+"""
+import os
+import json
+import requests
+import pandas as pd
+from lxml import html
+
+# Set base URL
+bom_url = 'http://www.bom.gov.au/'
+
+# Set product URL for North Head
+product_url = 'products/IDN60901/IDN60901.95768.shtml'
+
+# Set output directory
+output_dir = 'bom'
+
+# Set output column names
+cols = [
+    'wind_dir',
+    'wind_spd_kmh',
+    'gust_kmh',
+]
+
+
+def update_master(output_dir, csv_name, df):
+    """Update master csv time series.
+
+    Args:
+        output_dir (str): path to time series directory
+        csv_name (str):   name of time series file
+        df (dataframe):   dataframe with datetime index
+
+    Returns:
+        None
+    """
+    try:
+        # Load local master table if it exists
+        master = pd.read_csv(os.path.join(output_dir, csv_name),
+                             index_col=0,
+                             parse_dates=True)
+
+        # Only include timestamps that do not already exist
+        df = df[~df.index.isin(master.index)]
+
+        # Update master
+        master = master.append(df)
+
+    except FileNotFoundError:
+        # Create new master table if none exists
+        master = df
+
+    # Export master table
+    master.to_csv(os.path.join(output_dir, csv_name))
+
+
+# Open new session with BOM website
+with requests.session() as session:
+    # Load product page
+    page = session.get(bom_url + product_url)
+    tree = html.fromstring(page.content)
+
+    # Find and download JSON data
+    json_url = tree.xpath('//*[@id="content"]/p[4]/a')[0].get('href')
+    json_data = json.loads(session.get(bom_url + json_url).content)
+
+# Extract file base name
+csv_name = json_url.split('/')[-1].replace('.json', '.csv')
+
+# Create dataframe
+df = pd.DataFrame(json_data['observations']['data'])
+
+# Set local time as index
+df.index = pd.to_datetime(df['local_date_time_full'])
+
+# Extract columns of interest
+df = df[cols]
+
+# Update master table
+update_master(output_dir, csv_name, df)