# Python with Apache Spark using Jupyter notebook

### Python with Apache Spark using Jupyter notebook

Now let’s run the Python version of pi program. Start Anaconda Navigator, select Virtual Environment spark

![](https://2100080250-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-M1PNTHVApkPePuMdTu3%2F-M1fhs0MTNdgwk0Nvtuh%2F-M1fiKSo5cmLjTh1wX99%2Fscala-17.jpg?alt=media\&token=21b9cbcd-44d2-4ea1-b6af-087954075925)

Click Jupyter Notebook

In the Jupyter Notebook, need to import findspark and run findspark.init(), which will find where the SPARK\_HOME points to.

Following is the Python script that runs pi.py, you can simply run:

python pi.py

```
#!/usr/bin/env python
# coding: utf-8
from __future__ import print_function
import findspark
findspark.init()
import sys
from random import random
from operator import add
from pyspark.sql import SparkSession
spark =SparkSession.builder.appName("PythonPi").getOrCreate()
partitions = 1
n = 100000 * partitions
def f(_):
    x = random() * 2 - 1
    y = random() * 2 - 1
    return 1 if x ** 2 + y ** 2 <= 1 else 0
count = spark.sparkContext.parallelize(range(1, n + 1), partitions).map(f).reduce(add)
print("Pi is roughly %f" % (4.0 * count / n))
spark.stop()
```


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