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@ -1,7 +1,13 @@
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"""Download latest time series data from BOM website and update local copy.
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BOM does not allow direct http requests to data files, so a requests session
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is opened on the product page before accessing the resource.
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BOM does not allow direct http requests to data files unless it believes the
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request comes from a browser. For example:
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>>> pd.read_csv(url) # This does not work
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HTTPError: HTTP Error 403: Forbidden
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>>> requests.get(url) # This works!
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<Response [200]>
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D. Howe
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2019-09-04
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@ -10,13 +16,10 @@ import os
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import json
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import requests
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import pandas as pd
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from lxml import html
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# Set base URL
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bom_url = 'http://www.bom.gov.au/'
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# Set product URL for North Head
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product_url = 'products/IDN60901/IDN60901.95768.shtml'
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# Set json product URL for North Head
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# http://www.bom.gov.au/products/IDN60901/IDN60901.95768.shtml
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json_url = 'http://www.bom.gov.au/fwo/IDN60901/IDN60901.95768.json'
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# Set output directory
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output_dir = 'bom'
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@ -60,18 +63,8 @@ def update_master(output_dir, csv_name, df):
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master.to_csv(os.path.join(output_dir, csv_name))
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# Open new session with BOM website
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with requests.session() as session:
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# Load product page
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page = session.get(bom_url + product_url)
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tree = html.fromstring(page.content)
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# Find and download JSON data
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json_url = tree.xpath('//*[@id="content"]/p[4]/a')[0].get('href')
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json_data = json.loads(session.get(bom_url + json_url).content)
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# Extract file base name
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csv_name = json_url.split('/')[-1].replace('.json', '.csv')
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# Download JSON data
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json_data = json.loads(requests.get(json_url).content)
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# Create dataframe
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df = pd.DataFrame(json_data['observations']['data'])
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@ -84,4 +77,5 @@ df = df.sort_index()
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df = df[cols]
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# Update master table
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csv_name = json_url.split('/')[-1].replace('.json', '.csv')
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update_master(output_dir, csv_name, df)
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