pymapd

The pymapd client interface provides a python DB API 2.0-compliant OmniSci interface. In addition, it provides methods to get results in the Apache Arrow-based GDF format for efficient data interchange.
Documentation
See the GitHub pymapd repository for full documentation:
​Installation​
​Getting started​
​API reference​
Examples
Create a Cursor and Execute a Query
Step 1: Create a connection
>>> from pymapd import connect
>>> con = connect(user="mapd", password= "HyperInteractive", host="my.host.com", dbname="mapd")
>>> con
Connection(omnisci://omnisci:***@my.host.com:6274/omnisci?protocol=binary)
Step 2: Create a cursor
>>> c = con.cursor()
>>> c
<pymapd.cursor.Cursor object at 0x7f0117fe2490>
Step 3: Query database table of flight departure and arrival delay times
>>> c.execute("SELECT depdelay, arrdelay FROM flights LIMIT 100")
<pymapd.cursor.Cursor object at 0x7f0117fe2490>
Step 4: Display number of rows returned
>>> c.rowcount
100
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.
>>> c.description
[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)]
Step 6: Iterate over the cursor, returning a list of tuples of values
>>> result = list(c)
>>> result[:5]
[(1, 14), (2, 4), (5, 22), (-1, 8), (-1, -2)]
Select Data into a GpuDataFrame Provided by pygdf
Step 1: Create a connection to local OmniSci instance
>>> from pymapd import connect
>>> con = connect(user="mapd", password="HyperInteractive", host="localhost",
...               dbname="mapd")
Step 2: Query GpuDataFrame database table of flight departure and arrival delay times
>>> query = "SELECT depdelay, arrdelay FROM flights_2008_10k limit 100"
>>> df = con.select_ipc_gpu(query)
Step 3: Display results
>>> df.head()
  depdelay arrdelay
0       -2      -13
1       -1      -13
2       -3        1
3        4       -3
4       12        7

Last modified 2yr ago