'first_feature': 2.,
'second_feature': 12.,
}
# First, we delete any existing `models/` folder on HDFS.
client.delete('models', recursive=True)
# We can now upload the data, first as CSV.
with client.write('models/1.csv', encoding='utf-8') as writer:
for item in model.items():
writer.write(u'%s,%s\n' % item)
# We can also serialize it to JSON and directly upload it.
with client.write('models/1.json', encoding='utf-8') as writer:
dump(model, writer)
# We can check that the files exist and get their properties.
assert client.list('models') == ['1.csv', '1.json']
status = client.status('models/1.csv')
content = client.content('models/1.json')
# Later, we can download the files back. The `delimiter` option makes it
# convenient to read CSV files.
with client.read('models/1.csv', delimiter='\n', encoding='utf-8') as reader:
items = (line.split(',') for line in reader if line)
assert dict((name, float(value)) for name, value in items) == model
# Loading JSON directly from HDFS is even simpler.
with client.read('models/1.json', encoding='utf-8') as reader:
assert load(reader) == model
