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What is the is 80/20 principle topics in Learning Python.

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Does the 80/20 rule apply to programming? The 80/20 rule is often interpreted as a tradeoff between the level of effort and quality of the solution. 20% of the effort gets you to 80% of the solution; the other 80% of effort goes to polish up the remaining 20% for a more perfect solution. It definitely...
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Does the 80/20 rule apply to programming? The 80/20 rule is often interpreted as a tradeoff between the level of effort and quality of the solution. 20% of the effort gets you to 80% of the solution; the other 80% of effort goes to polish up the remaining 20% for a more perfect solution. It definitely applies to software. There are many problems which can be quickly and easily solved with an imperfect solution. The key question is often whether or not the imperfect solution is sufficient, or if you have to put in significantly more effort for a better solution. One concrete example might be adding functionality to an existing data model in a data store (blob store, SQL database, etc). The perfect solution may be to redefine the data model with the appropriate schema to solve your problem. However, this is often very difficult and time consuming, so most software organizations instead go to great length to overload their existing data models without modification until its absolutely necessary to put in that time and effort.

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Does the 80/20 rule apply to programming? The 80/20 rule is often interpreted as a tradeoff between the level of effort and quality of the solution. 20% of the effort gets you to 80% of the solution; the other 80% of effort goes to polish up the remaining 20% for a more perfect solution. It definitely...
read more
Does the 80/20 rule apply to programming? The 80/20 rule is often interpreted as a tradeoff between the level of effort and quality of the solution. 20% of the effort gets you to 80% of the solution; the other 80% of effort goes to polish up the remaining 20% for a more perfect solution. It definitely applies to software. There are many problems which can be quickly and easily solved with an imperfect solution. The key question is often whether or not the imperfect solution is sufficient, or if you have to put in significantly more effort for a better solution. One concrete example might be adding functionality to an existing data model in a data store (blob store, SQL database, etc). The perfect solution may be to redefine the data model with the appropriate schema to solve your problem. However, this is often very difficult and time consuming, so most software organizations instead go to great length to overload their existing data models without modification until its absolutely necessary to put in that time and effort. read less
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U get 80% result by performing 20% hard work
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While learning a new programming language, there's always a sense that there will be a few commands, tricks and work-arounds that we'll keep reusing; commonly known as the 80/20 rule — 20% of activities are responsible for 80% of the work.
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When learning a new programming language, there's always a sense that there will be a few commands, tricks and work-arounds that we'll keep reusing; commonly known as the 80/20 rule —20% of activities are responsible for 80% of the work.
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80/20 principle is the Pareto principle where 80% of the problem is caused by 20%of the causes.
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Thank you for reaching out. Well, the 80/20 principle is you're going to learn 20% of python and 80% of the work, this rule is commonly based on the power of distribution which applies in business and learning, and python counts in learning.
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I have 3 years teaching experience

When learning a new programming language, there's always a sense that there will be a few commands, tricks and work-arounds that we'll keep reusing; commonly known as the 80/20 rule — 20% of activities are responsible for 80% of the work
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