Shine baby, shine

Dear Kamil,

Remember this.

Success is a process not outcomes of goals. Focus on the process.
- But deliver staff.
don’t compare to others.
- But do your staff systematic
get some balance.
- Start moving more. Come back to walking for per hour a day.
if you stumble, miss a day of blogging, get up!

Love, KK

ideas

TODO: article: Why using ORMS are awesome
- (thanks chatgpt for couple some points, to get draftg),
- But with examples with code
  - Agenda:
    1. Abstraction of Database Complexity: ORMs provide a high-level abstraction over database operations, allowing data scientists to focus on analysis without dealing with intricate SQL queries.
    2. Rapid Development: ORMs expedite development by eliminating the need for manual SQL code, enabling data teams to iterate quickly on projects.
    3. Code Maintainability: ORMs enhance code readability and maintainability, as they use object-oriented programming principles, making it easier for data scientists to collaborate and understand each other’s code.
    4. Cross-Database Compatibility: ORMs abstract away database-specific syntax, facilitating smoother transitions between different database systems and reducing compatibility issues for data science projects.
    5. Query Optimization: Some ORMs automatically optimize queries, aiding data scientists in writing efficient code without delving into the intricacies of query optimization.
    6. Object-Relational Mapping: ORMs map database tables to objects, providing a natural and intuitive way for data scientists to interact with and manipulate data within their programming language of choice.
    7. Reduced Boilerplate Code: ORMs reduce the amount of boilerplate code needed for database interactions, streamlining the development process for data science teams.
    8. Integration with Frameworks: Many ORMs seamlessly integrate with popular frameworks, simplifying the process of incorporating data science functionality into web applications or other software projects.
    9. Version Control: ORMs facilitate version control for database schema changes, enabling data teams to track and manage database modifications more efficiently.
    10. Community Support: Widely adopted ORMs often have large and active communities, providing data scientists with access to a wealth of resources, tutorials, and solutions to common challenges.
TODO: article: why I hate string in code
TODO: [SPIKE][Python] automation typing when writing code
- - maybe add typing, mypy? alternative
  - in vscode, Inlay Type Hints https://devblogs.microsoft.com/python/python-in-visual-studio-code-july-2022-release/#inlay-type-hints
  - in pycharm, Inlay Hints https://www.jetbrains.com/help/pycharm/inlay-hints.html#enable_inlay_hints
TODO: [Python] how work get_attributes, dict

TODO Use AI, chatgpt to help me on my write skillset in english

TODO: better work on blog

maybe create or find extension to show changes correct for example this sign ‘

’ change change line in to table in jekyll engine

maybe run blog locally

TODO: create medium post
TODO: create dev.to post
TODO: simple PWA app for shortcuts with filters

challlenges

day has only 24 hours
I went to bed too late
It was hard to start working
I work on Sunday
- without any order
- out of a sense of duty
- of my own free and uncoerced will
- I’m disappointed in myself
- bad Kamil, bad
I was good ligher today. “Are you shining for yourself or me? Yes”

77026A99-626F-4F80-A5E9-52D64C99F4EB

achievements

another day of blogging, 3!
write draft for article “Why Embracing Systematic Conference Attendance Is a Game-Changer”
[WORK] prepare for monday meeting about refactor code, plan it, create some summary, notes
- prepare process, list of task when you refactor some code,
  - first e2e test, if it’s not enough do more, if you want to edit structure,
  - do integration for each endpoint
    - by endpoint I mean some staff that we know what we give and what we get
  - now start refactor, try write code for
- maybe start to use ORM like SQLAlchemy?
- maybe too much OOP code, best is gold rule, to use some OOP and functionl
- when use OOP, you need to use power of it, polymorphism, and design patterns
  - to find polymorphism find if-ology
    - not forget that could be overengineering,
  - why we need main class? maybe we could do everything more functional?
  - easier to tests function if it’s not on huge main class with a lot of attributes
  - easiet to tests function if haver clear in and out
- not SOLID code
- be more DRY, Don’t Repeat Yourself,
  - functions have arguments!, delete similar functions, maybe if, maybe polymorphism
- add more in readme, how to start use it, how to start develop it
- add linter & code formatter like ruff
  - solve many MY struggles to look at this code XD NAZI coder XD
- get out of for’s in pandas part of code
- [SPIKE] columns like pandas class, enums, if name change, we will change in one place?
- start to use Pokemon Exception Handling, “Pokemon - gotta catch ‘em all!!!”
- are comments necessary?
  - maybe sometimes, maybe variable names are not perfect, not fitting
  - maybe add typing, mypy? alternative
    - in vscode, Inlay Type Hints https://devblogs.microsoft.com/python/python-in-visual-studio-code-july-2022-release/#inlay-type-hints
    - in pycharm, Inlay Hints https://www.jetbrains.com/help/pycharm/inlay-hints.html#enable_inlay_hints
- don’t use “from super_fantstic_lib import *”
- prove_is_not_None_is_unessesary

def prove_is_not_None_is_unessesary(argument):

  print(argument, type(argument))
  
  if argument:
  
    print("Not None")
  
  else:
  
    print("None")

  if argument is not None:
  
    print("Not None")
  
  else:
  
    print("None")

my_social_life = None

prove_is_not_None_is_unessesary(my_social_life)

lucky_number = 7 

prove_is_not_None_is_unessesary(lucky_number)

learning

[NO IT] how to shine
[NO IT] how change chandelier

STEP TWO

Me gusta jugar a la “Siesta Roulette”