Hands-on Python: Finding Nth most repeated words using sorted() and Lambda functions

Quick Intro

This is a follow-along and learn by doing article and definitely not a production-like solution.

However, it's supposed to train your thought process to get to a production-like solution while at the same time getting some hands-on exposure to Python.

In this article, I'm going to show the following:

  • What my function is supposed to do (yes, this is the first step, not the how)
  • Breaking down the words using Regex (Python's re module)
  • Creating a dictionary with words and its corresponding counter (i.e. how many times it repeats in a line)
  • Returning top Nth words of above dictionary sorted by highest count

We should get to a solution with just a few lines at the end but the key learning thing here is the use of Lambda function as key of sorted() function.

How the Function is Supposed to Work

The function receives a string and how many words we'd like to display and returns a sorted list of words with most repeated word first: 

In above example, Rodrigo is returned because it appears 3 times in the string.

The last argument 1 is just in case we want to return more than one result.

For example, if we want the most repeated word (Rodrigo) but also the 2nd most repeated word (DevCentral), we can set it to 2:

But how do we do it in Python in an efficient way?

Also, how do we code this in a more 'Pythonic' way?

So, here's what I'll do next:

  • Quickly go through how to filter words/number (i.e. removing punctuation, space, etc)
  • Create a dictionary with each word as the key and the number of times they repeat
  • Return top Nth most repeated words

Filtering only words or numbers using Regex

We first define and compile a regular expression pattern that matches only alphanumeric characters (no space or punctuation):

\w is similar to [A-Za-z0-9_ ], i.e. it matches all letters and numbers.

The plus sign means that each subsequent character that is also alphanumeric would also match if they repeat ONE or more times (do not confuse with * that means ZERO or more times).

We can confirm that it works by testing it with findall() function:

This is what we need.

The pattern above can be adjusted according to our needs but as this is mostly a learning example we'll stop here so it doesn't get too complex.

Let's now focus on counting the repeated words..

Creating a counter for words/numbers

We can create a dictionary to keep track of number of words:

But why reinvent the wheel, right?

We can use collections.Counter instead:

Now that we have broken down the words into a list using Regex and added each word and corresponding counter to a dictionary, we're ready for the final solution.

How to return top Nth words 

How do we find the top Nth words from highest to lowest counter?

The Not-so-pythonic Way

Sorting the words

The first thing we can do is to first reverse the dictionary and create a tuple like this:

Then sort the tuple by the number of occurrences (from highest to lowest):

reverse=True means we're sorting from highest to lowest as the default is the opposite.

Returning only first Nth words using Slicing and List comprehension

Let's imagine we want to list the first 2 words with highest count and set variable n to represent this counter.

We've got this:

But we want just the first 2 words with highest number of repetitions, so we can use slicing like this:

However, we're only interested in the words, not the counter.

In this case, we can do a for loop to return only the second word of above list:

Is there an easier or more efficient way?

The Pythonic Way

Is there a way to return Nth most repeated word without having to reverse the dictionary?

We could perhaps throw our counter dictionary straight into sorted function!

Before we jump to the solution we need to learn 2 things:

  • How to use key argument from sorted() function
  • How to use lambda function as the key to sorted() function

Using key argument from sorted function

sorted() function allows us to sort things matching pretty much any pattern using key argument.

The key argument expects us to tell it what to match so sorted() function can sort based on that.

Let's use a simple list of names:

By default, sort would allow us to sort it alphabetically from A-to-Z or in reverse from Z-to-A:

Let's say we want to come up with a crazy sorting rule and we want to sort it alphabetically but based on last character of each word.

Can we do that? Not by default though!

We can create a function that returns the last character [-1] of a string like this:

And then pass it on as the key to sorted() function:

Nice, isn't it?

But that's still a lot of work to create a separate function.

Is there an easier and more pythonic way to do this?

Using lambda function

Yes, there is.

If we just need to use a function as an argument to sorted() function, we can do it like this:

The above lambda function is the equivalent to the function we created before with the added benefit that it can be added directly to key argument.

It is much more readable and reduces the number of lines in our code.

Let's now go back to our problem as we also need a cray rule to return a sorted list based on our dictionary values, i.e. the word counter.

Returning top Nth repeated words in one line

Let's check our dictionary again:

To create a matching function, we need a function that returns the kind of item we want sorted() to match so it can sort based on it.

In this case, we want sorted() to sort based on our dictionary values (the counters!).

Therefore, our function has to receive a dictionary key as an input and return its value:

When we apply it to sorted we should also remember to set reverse to True because we want highest to lowest count, remember?

However, we can use a lambda function instead like this:

We can now use n to do the slicing and find Nth word:

And this is our code in one line:

Putting it all together

This is how our pythonic code could look like:

And here's the final output:

Published Mar 18, 2015
Version 1.0
  • In V11 partitions are present, but not quite as visible as in prior versions.

     

     

    Partitions and top level folders mirror each other.

     

    When a partition is created a top level folder is created

     

    tmsh create auth partition abc

     

    Will create a partition and will also create the folder /abc.

     

    tmsh list sys folder /abc

     

     

    When a top level folder is created a corresponding partition will also be created.

     

    tmsh create sys folder /efg

     

    Will create the folder and also create a partition

     

    tmsh list auth partition /efg

     

     

    The cd command is used to move to a different partition.

     

     

    tmsh cd /efg (you are now in the /efg folder and the efg partition)

     

     

    tmsh create sys folder /efg/xzy

     

    tmsh cd /efg/xyz (you are in the /efg/xyz folder and still in the efg partition)

     

     

  • Hi Mark,

     

     

    Thanks for your Reply, i tried to create new folders/partition and I can navigate among them and create objects as I want.

     

     

    But when I upgrade a box from v10 to v11, partitions (created on v10, before the upgrade) are correctly available on v11 but folders are not created, so I can't navigate and update or create new objects on a partition created in v10 on a box updated in v11.

     

     

    I continue to investigate but if you have a tip, i'm interrested.

     

     

    Best Regards.
  • It may be worth noting here that when you are using a TMSH script to create or modify in v11 you can reference them thusly:

     

     

    tmsh::command module partition/object { parameters }

     

     

    for example:

     

    tmsh::create ltm virtual /Common/VS_abc {destination ... }
  • Can I execute a comand/action on all partitions at the same time? Is there an "ALL" option? I need to remove an irules across 600 partitions and can't find a good way to do it. I'm thinking in remove the actions of the irule to simulate a near zero activity but I would like a more elegant way to do it. (meaning remove the irule from each VS). Thanks

     

  • You could use a TMSH script to retrieve a list of partitions, set irulename set tmsh::get_config partitions foreach $partitions { cd $partition tmsh::delete $irulename }

     

  • You could use a TMSH script to retrieve a list of partitions, set irulename set tmsh::get_config partitions foreach $partitions { cd $partition tmsh::delete $irulename }

     

    • Ariel_Santa_Cr1's avatar
      Ariel_Santa_Cr1
      Historic F5 Account
      Thanks Brent, I've been working over the following Jason's script to make it "partitions aware" using the commands you recommended. https://devcentral.f5.com/s/articles/rapid-irule-removal-via-tmsh-script Unfortunately there's somthing still missing in the code, but Jason is helping me to troubleshoot the issue. Hope to have it ready later today.
    • Phil_Wedel_7401's avatar
      Phil_Wedel_7401
      Icon for Nimbostratus rankNimbostratus
      Hate to revive an old thread... but did you get the script working across partitions? Trying to deploy an iRule for the new Bash shell exploit.
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Since the very early days of 2G and 3G deployments, mobile operators from all around the world have been deploying and using content optimization platforms. The reasons for deploying these technologies were pretty straightforward. Bandwidth at the 2G and 3G radio layers was pretty low compared to bit rates that were available on wireline networks, so reducing the bit rates of the ever increasing amount of video streams helped save bandwidth at the radio layer and hence costs. At the same time reducing the video bit rates by using video transrating and transcoding techniques also helped improve the subscriber experience as it is better to keep a lower quality video stream steadily flowing rather than a high quality video stream stalling all the time.

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A couple of recent industry evolutions are now forcing mobile operators to rethink how to optimize their subscribers’ traffic. Since the Snowden revelations the internet has seen a massive surge in encrypted traffic (https). Speaking to several mobile operators in Europe we are hearing that in many countries between 40% and 50% of all internet traffic is encrypted these days, and the trend is still going up. Also videos are delivered more and more over encrypted https instead of over unencrypted http. In addition LTE technology is capable of delivering very high bandwidths to mobile users at much lower costs (per bit transported) than 2G and 3G technologies. So the primary motivation for deploying video optimization platforms which originally was saving costs, is now shifting more and more towards either differentiating the subscriber’s quality of experience or to make use of this technology for specific traffic only instead of for all data traffic. Examples of selectively using video optimization are to optimize videos on the 3G network but not on LTE, or to only optimize subscribers that are on specific tariff plans.

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Given that less and less traffic can be ‘content optimized’ due to the increasing percentage of encrypted traffic on the network, mobile operators have started to focus heavily on TCP optimization. Over 90% of all traffic on the mobile network is TCP based, and therefore a TCP optimizer can optimize almost all traffic on the network regardless of whether that traffic is encrypted or not. Indeed, TCP optimization works at the TCP layer, which in the OSI model is the layer sitting on top of IP, but below the encryption and application layers. TCP optimization is used to enhance the subscriber’s quality of experience in two ways. First, it helps to increase the peak and average bandwidth that a subscriber can enjoy over the mobile network and hence it increases the quality of experience. You could argue that because of this, it also helps to make more efficient use of the available radio spectrum and as such provides a cost benefit. Second, and this is very often overlooked, this technology also helps to reduce web page load times. One of the most frustrating experiences for mobile subscribers is that very often it takes so long to load your favorite web pages or open your facebook home page even on a high bandwidth connection. It is important to note that web page load times are not so much impacted by the available bandwidth but much more by the latency on the mobile network, and latency on mobile networks is much higher than on wireline networks. So TCP optimization not only delivers faster downloads but it also helps to keep the latency in the mobile network at much lower levels than without TCP optimization, ultimately leading to faster web browsing experiences for the mobile subscribers.

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Mobile operators that have started trialing or deploying LTE Advanced have also noticed that TCP optimization will be important to achieve the maximum possible throughput rates that these new technologies promise. So TCP optimization should not be looked at solely to improve the performance in some 3G areas with poor coverage, but as a key building block on the Gi LAN that will help mobile operators achieve the maximum possible throughput and hence maximized subscriber satisfaction on any radio technologies that get deployed today and in the future.

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Technically speaking, what a TCP optimization platform actually does is decoupling any TCP connection between a mobile client and a content server in two separate TCP connections by acting as a full TCP proxy in between as shown in the picture below. The TCP proxy ensures that the TCP flow and congestion management techniques are fully adapted and tuned to the specific characteristics of the networks the proxy is connected to. The bandwidth, delay and packet loss characteristics from the cellular network are very different from the IP backbone network and the internet and therefore the TCP optimization proxy is capable of getting the maximum efficiency out of the networks it is connected to. Satellite networks also exhibit much higher latencies then wireline networks so also in that market sector you will find TCP technology being heavily used to optimize overall performance over satellite links.

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Even though TCP optimization as a technology is not new (it has been deployed for many years), the heavily increased focus of mobile operators towards this technology in the last 9 to 12 months is. And given that TCP optimisation is agnostic for the encryption and application layers, plus the fact that we see great benefits not only for 3G and LTE, but also for LTE advanced, it is a technology worth exploring for any mobile operator. 

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Interested in hearing more?  Stop by our booth at MWC  Hall 5, G11

","body@stringLength":"5659","rawBody":"

Since the very early days of 2G and 3G deployments, mobile operators from all around the world have been deploying and using content optimization platforms. The reasons for deploying these technologies were pretty straightforward. Bandwidth at the 2G and 3G radio layers was pretty low compared to bit rates that were available on wireline networks, so reducing the bit rates of the ever increasing amount of video streams helped save bandwidth at the radio layer and hence costs. At the same time reducing the video bit rates by using video transrating and transcoding techniques also helped improve the subscriber experience as it is better to keep a lower quality video stream steadily flowing rather than a high quality video stream stalling all the time.

\n\n

A couple of recent industry evolutions are now forcing mobile operators to rethink how to optimize their subscribers’ traffic. Since the Snowden revelations the internet has seen a massive surge in encrypted traffic (https). Speaking to several mobile operators in Europe we are hearing that in many countries between 40% and 50% of all internet traffic is encrypted these days, and the trend is still going up. Also videos are delivered more and more over encrypted https instead of over unencrypted http. In addition LTE technology is capable of delivering very high bandwidths to mobile users at much lower costs (per bit transported) than 2G and 3G technologies. So the primary motivation for deploying video optimization platforms which originally was saving costs, is now shifting more and more towards either differentiating the subscriber’s quality of experience or to make use of this technology for specific traffic only instead of for all data traffic. Examples of selectively using video optimization are to optimize videos on the 3G network but not on LTE, or to only optimize subscribers that are on specific tariff plans.

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Given that less and less traffic can be ‘content optimized’ due to the increasing percentage of encrypted traffic on the network, mobile operators have started to focus heavily on TCP optimization. Over 90% of all traffic on the mobile network is TCP based, and therefore a TCP optimizer can optimize almost all traffic on the network regardless of whether that traffic is encrypted or not. Indeed, TCP optimization works at the TCP layer, which in the OSI model is the layer sitting on top of IP, but below the encryption and application layers. TCP optimization is used to enhance the subscriber’s quality of experience in two ways. First, it helps to increase the peak and average bandwidth that a subscriber can enjoy over the mobile network and hence it increases the quality of experience. You could argue that because of this, it also helps to make more efficient use of the available radio spectrum and as such provides a cost benefit. Second, and this is very often overlooked, this technology also helps to reduce web page load times. One of the most frustrating experiences for mobile subscribers is that very often it takes so long to load your favorite web pages or open your facebook home page even on a high bandwidth connection. It is important to note that web page load times are not so much impacted by the available bandwidth but much more by the latency on the mobile network, and latency on mobile networks is much higher than on wireline networks. So TCP optimization not only delivers faster downloads but it also helps to keep the latency in the mobile network at much lower levels than without TCP optimization, ultimately leading to faster web browsing experiences for the mobile subscribers.

\n\n

Mobile operators that have started trialing or deploying LTE Advanced have also noticed that TCP optimization will be important to achieve the maximum possible throughput rates that these new technologies promise. So TCP optimization should not be looked at solely to improve the performance in some 3G areas with poor coverage, but as a key building block on the Gi LAN that will help mobile operators achieve the maximum possible throughput and hence maximized subscriber satisfaction on any radio technologies that get deployed today and in the future.

\n\n

Technically speaking, what a TCP optimization platform actually does is decoupling any TCP connection between a mobile client and a content server in two separate TCP connections by acting as a full TCP proxy in between as shown in the picture below. The TCP proxy ensures that the TCP flow and congestion management techniques are fully adapted and tuned to the specific characteristics of the networks the proxy is connected to. The bandwidth, delay and packet loss characteristics from the cellular network are very different from the IP backbone network and the internet and therefore the TCP optimization proxy is capable of getting the maximum efficiency out of the networks it is connected to. Satellite networks also exhibit much higher latencies then wireline networks so also in that market sector you will find TCP technology being heavily used to optimize overall performance over satellite links.

\n\n\n

Even though TCP optimization as a technology is not new (it has been deployed for many years), the heavily increased focus of mobile operators towards this technology in the last 9 to 12 months is. And given that TCP optimisation is agnostic for the encryption and application layers, plus the fact that we see great benefits not only for 3G and LTE, but also for LTE advanced, it is a technology worth exploring for any mobile operator. 

\n\n

Interested in hearing more?  Stop by our booth at MWC  Hall 5, G11

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