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import time | |
import numpy | |
import redis | |
# a 2D array to serialize | |
A = 10 * numpy.random.randn(10000).reshape(1000, 10) | |
# flatten the 2D NumPy array and save it as a binary string |
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(jd@XXX) /home/jd/shovel> time ./shovel.py jd_test | |
got 901 messages | |
real 0m1.617s | |
user 0m0.558s | |
sys 0m0.044s |
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(jd@XXX) /home/jd/shovel> time ./shovel.py jd_test | |
got 901 messages | |
real 0m1.617s | |
user 0m0.558s | |
sys 0m0.044s |
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def pandas_to_elasticsearch(df): | |
""" | |
Generator that converts `pandas.DataFrame` rows into ElasticSearch actions | |
""" | |
# ElasticSearch will raise an exception on `NaN` values | |
df = df.dropna() | |
for i, row in df.iterrows(): | |
action = { | |
'_op_type': 'index', | |
'_index': 'my_index', |
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import pandas | |
import fastavro | |
def avro_df(filepath, encoding): | |
# Open file stream | |
with open(filepath, encoding) as fp: | |
# Configure Avro reader | |
reader = fastavro.reader(fp) | |
# Load records in memory | |
records = [r for r in reader] |
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