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Python: heavyai
The
heavyai client interface provides a Python DB API 2.0-compliant HEAVY.AI interface. In addition, it provides methods to get results in the Apache Arrow-based GDF format for efficient data interchange.Documentation
Examples
Create a Cursor and Execute a Query
Step 1: Create a connection
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>>> from heavyai import connect
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>>> con = connect(user="heavyai", password= "HyperInteractive", host="my.host.com", dbname="heavyai")
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Step 2: Create a cursor
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>>> c = con.cursor()
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>>> c
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Step 3: Query database table of flight departure and arrival delay times
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>>> c.execute("SELECT depdelay, arrdelay FROM flights LIMIT 100")
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Step 4: Display number of rows returned
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>>> c.rowcount
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100
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Step 5: Display the Description objects list
The list is a named tuple with attributes required by the specification. There is one entry per returned column, and we fill the
name, type_code, and null_ok attributes.1
>>> c.description
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[Description(name=u'depdelay', type_code=0, display_size=None, internal_size=None, precision=None, scale=None, null_ok=True), Description(name=u'arrdelay', type_code=0, display_size=None, internal_size=None, precision=None, scale=None, null_ok=True)]
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Step 6: Iterate over the cursor, returning a list of tuples of values
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>>> result = list(c)
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>>> result[:5]
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[(1, 14), (2, 4), (5, 22), (-1, 8), (-1, -2)]
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Select Data into a GpuDataFrame Provided by pygdf
Step 1: Create a connection to local HEAVY.AI instance
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>>> from heavyai import connect
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>>> con = connect(user="heavyai", password="HyperInteractive", host="localhost",
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... dbname="heavyai")
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Step 2: Query GpuDataFrame database table of flight departure and arrival delay times
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>>> query = "SELECT depdelay, arrdelay FROM flights_2008_10k limit 100"
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>>> df = con.select_ipc_gpu(query)
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Step 3: Display results
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>>> df.head()
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depdelay arrdelay
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0 -2 -13
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1 -1 -13
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2 -3 1
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3 4 -3
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4 12 7
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Last modified 1mo ago
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