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14 Top Data Pipeline Key Terms Explained

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 Here are some key terms commonly used in data pipelines 1. Data Sources Definition: Points where data originates (e.g., databases, APIs, files, IoT devices). Examples: Relational databases (PostgreSQL, MySQL), APIs, cloud storage (S3), streaming data (Kafka), and on-premise systems. 2. Data Ingestion Definition: The process of importing or collecting raw data from various sources into a system for processing or storage. Methods: Batch ingestion, real-time/streaming ingestion. 3. Data Transformation Definition: Modifying, cleaning, or enriching data to make it usable for analysis or storage. Examples: Data cleaning (removing duplicates, fixing missing values). Data enrichment (joining with other data sources). ETL (Extract, Transform, Load). ELT (Extract, Load, Transform). 4. Data Storage Definition: Locations where data is stored after ingestion and transformation. Types: Data Lakes: Store raw, unstructured, or semi-structured data (e.g., S3, Azure Data Lake). Data Warehous...

How to Use Python Try and Except Logic Correctly

In Python, you can avoid exceptions using Try and Except logic. The Error-free programs save a lot of time. Also, you can keep away defects in production.
 

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How to Use Python Try and Except Logic Correctly


In Python, you can handle un-known errors by using TRY and EXCEPT logic. If the programmer does not take care of this, the default is for Python to print an error message and stops execution. 



So the responsibility of a programmer is upfront he/she has to find errors and handle them correctly. It is possible if you use the TRY and EXCEPT.


Python Syntax for Try and Except.


try:
      c = a/b
except:
      c = 1000000

Try ends with ':' it says that Try block start here. In this block, you can write actual logic. The Except: is another block. That means in this block programmer can specify some value. And that value populates when any error happens.

Try and Except Examples.

Example: 1.

Below is the example to give the expected error in except.

try:
      c = a/b
except ZeroDivisionError:
      c = 1000000


The above example is you can give a name to an error in Except.  When this error happens, it assigns 1000000.


Example: 2.

Below is an example to give anticipated errors.

try:
      c = a/b
except (ValueError, ZeroDivisionError):
      c = 1000000


Also, there can be many except statements associated with a single Try.

Example: 3.

Below is an example to use multiple excepts.

try:
      c = a/b
except ValueError:
    c = 0
except ZeroDivisionError:
      c = 1000000

And, as was mentioned, a variable can hold the value of the error to be caught:

Example: 4.

The below example is to assign a value to the variable when an error happens. 

k = ZeroDivisionError
try:
      c = a/b
except k:
      c = 1000000


If we left out the exception name, it assigns value C for other errors.

try:
      c = a/b
except:
      c = 0


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