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# How to create the Fibonacci Sequence in Python

This blog post will go through how to create the famous Fibonacci sequence in Python.

Each number in the Fibonacci sequence is the sum of the previous two terms.

The sequence starts: 0, 1, 1, 2, 3, 5, 8, 13, … and carries on infinitely.

The Python code I used is:

The first two terms are entered into our list, then we specify the number of terms wanted in our sequence.

Next, we loop through from 2 to the number of terms we wanted appending the sum of the previous two terms.

Printing our list gives the first fifty terms of the Fibonacci sequence.

# Join 2 Python lists together using nested loops

In this blog post I will show you how to join two 2D Python lists together.

The code is in the screenshot below.

Lines 1 – 2 are two lists that are going to be joined, line 3 is an empty list where the output will be appended to.

Lines 4 – 5 are two loops (one nested inside the other) which cycle through the records in both lists, line 6 checks whether the first items (index 0) in the two records from each list that are currently i & j match. If yes: the Key, Capital and Country are appended to our new list.

Lines 9 – 10 show the output record by record showing the join has worked successfully.

This code can be expanded for 3 lists, the code would have a 3rd for loop and an extra check in the if statement to find the correct record in the 3rd list to join.

Joining lists together in Python is useful when there is data in different lists and it would be beneficial if it were combined.

# How to delay a Python loop

In this blog post, I will run through 3 different ways to execute a delayed Python loop. In these examples, we will aim to run the loop once every minute.
To show the delay, we will print out the current datetime using the datetime module.

1 – Sleep
The sleep function from Python’s time module pauses the Python execution by the number of seconds inputted. The example below pauses the script for 60 seconds.

The above script has a 60 second delay between the end of a loop and the start of the next. However, what if we wanted to execute the next loop 60 seconds after the start of the previous loop.
In other words, how do we start the loop at the same time every minute.

2 – Calculate Sleep
To do this we calculate how long the loop should sleep for.
We will print the datetime every time the minutes changes. At the start of the loop we lookup the number of seconds that have passed so far this minute.

The number of seconds that have passed this minute is calculated from date_time[-2:]. Subtracting this from 60 gives the length of time in seconds for which the loop should sleep for, to execute when the next minute starts.

Once the loop has slept for the required number of seconds, we lookup the datetime again and print it out.

The previous two options are good for executing a loop a few times, ten in our case. If we wanted to execute a python script continuously without expiring, we could use the above examples with an infinite appending loop.
However, if one loop errors the script will stop. Therefore, we want to execute the entire Python script once a minute using an external trigger. This is where we can use Task Scheduler.

Task Scheduler can execute a python script from source but it is often easier to use a batch file. The batch file includes the location of the python application (python.exe) and the location of the python script (.py). For more detail on using Task Scheduler and batch files to run Python scripts, please see the following datatofish post – https://datatofish.com/python-script-windows-scheduler

Our batch file is:

To demonstrate Task Scheduler, I’m going to run the following Python code every minute.
This code uses Pandas to produce a blank CSV file, but the name of CSV file is the datetime the script was run.

These following screenshots show the triggers and actions used.

This produced the following CSV files, we can see that the files takes 1 – 4 seconds to create.

In summary we have seen three different ways to delay a Python loop, two using loops inside Python and one using Task Scheduler. All can be used depending on what kind of delay is best.

The Frog Blog

Team Purple Frog specialise in designing and implementing Microsoft Data Analytics solutions, including Data Warehouses, Cubes, SQL Server, SSIS, ADF, SSAS, Power BI, MDX, DAX, Machine Learning and more.

This is a collection of thoughts, ramblings and ideas that we think would be useful to share.

Authors:

 Alex Whittles(MVP) Jeet Kainth Jon Fletcher Nick Edwards Joe Billingham Lewis Prince Reiss McSporran

Data Platform MVP