CLICK SHOP API integratsiyasi haqida to'liq ma'lumot.

:► PyPi
✅ https://pypi.org/project/python-click/0.1/

🔥🔥🔥 Ushbu videodarsimizda: 🔥🔥🔥

1. python-click paketini o’rnatamiz.
2. Buyurtma yaratish uchun kerakli modellar va serializerslarni yozamiz.
3. Buyurtma yaratamiz.
4. Yaratilgan buyurtmani CLICK’ning dasturi yordamida local testdan o’tkazamiz.
5. Merchant CLICK’dagi billingimizni sozlaymiz.
6. Merchant CLICK orqali testlar o’tkazamiz.
7. O’tkazilgan to’lovni billingda tekshirib ko’ramiz.

🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥

► To'liq video youtube kanalimizda:
✅ https://www.youtube.com/watch?v=HHQ9QKSObyI

#click #integration #api #django #python #djangorestframework #dasturlash #webdasturlash #yakubovdeveloper

How to Handle a Million Requests in a Day Using Django 🤔


More: https://medium.com/@srinivasaravind5/how-to-handle-a-million-requests-in-a-day-using-django-25eefaee8aad

More: https://medium.com/@srinivasaravind5/turbocharge-your-django-application-mastering-database-partitioning-for-high-traffic-optimization-1c24031d34b8

ORMs offer great utility for developers but abstracting access to the database has its costs. Developers who are willing to poke around the database and change some defaults often find that great improvements can be made.

Advanced ORM: https://hakibenita.com/9-django-tips-for-working-with-databases

Customize Django admin dashboard

More: https://medium.com/@Evenword/how-to-turn-django-admin-into-a-lightweight-dashboard-77a45d275bbf

"Work-Life-Balance" yohud Men qilgan xatoliklar.😢

Dasturchi sifatida o'z "career" qurib borar ekanmiz "Work-Life-Balance" tamoili amal qilishimiz zarur. Aslida bu tamoili faqat dasturchilar uchun emas barcha soha egalari uchun. Lekin dasturlash sohasida yangiliklar tuxtamaydi, ishdan tashqari ham self study qilib turishingiz kerak. Hali o'qilmagan kitoblar, ko'rilmagan video darslar talaygina 📕

Ishimizga juda qatiq yondashib ketishimiz orqali, hayotimiz mazmuni yuqotib quyishimiz mumkin. Barchasini birdak olib ketishingiz uchun barcha holatlarni rejalashtiring va bularni eslatma sifatida yon daftarchangizga tushirib boring.

Short video: https://youtu.be/_vgpibecbPo (recommended)

I’m starting a new position as Full remote Python developer. 🎉 (alhamdulillah)

Bu 2chi ishxona sifatida va onlayn bulgani uchun ham job offer qabul qildim.

More: https://www.linkedin.com/posts/davronbek-boltayev_python-team-developer-activity-7046818952840196098-6JaK?utm_source=share&utm_medium=member_desktop

Method Resolution Order (MRO) in Python?👇

...Method Resolution Order (MRO) is a concept in Python that determines the order in which methods are searched for in a hierarchy of classes. When a method is called on an object, Python searches for the method in the class of the object, and then in its parent classes, following the MRO. This allows for multiple inheritance and method overriding, where a subclass can override a method defined in a parent class.

In the example, we create an instance of D and call its greet method, the method resolution order determines that the greet method of B is called first, followed by the greet method of C, and then the greet method

More: https://t.me/boboshersnotes/390

Threadan foydalanish har doim ham tug'ri yechim emasligini quyagi misolda ham kurishimiz mumkin:

threaded_loop.py

from concurrent.futures import ThreadPoolExecutor

def compute(i):
    return i**3 + 3**3

with ThreadPoolExecutor(max_workers=4) as executor:
    results = list(executor.map(compute, range(10_000_000)))

for result in results:
    print(result)

#####################

single_thread_loop.py

for i in list(range(10_000_000)):
      print(i**3+3**3)

terminalda run:

time python {file_name}.py

P/s loyhadaning maqsadiga asosida tanlov qilganiz maqul

cached_property

cached property — это декоратор, который преобразует метод класса в свойство. Значение вычисляется один раз, а затем кэшируется, как обычный атрибут. Кэшированное значение будет доступно до тех пор, пока объект или экземпляр класса не будут уничтожены. Делимся статьей, где автор рассказывает про cached property.

👉Читать статью

#статьи

Caching(Keshlash)
#System_design
https://medium.com/@gayratjonr/e0c56c2db0e4

Openbudget bot kodi ishlaydi 100%ishlaydi yangi kod asosiy fayl va webhook qilinadigan fayl -> hook.php

demo: @openbudjetuzbot

Manba: @PhpMasterlarUz & @Adhambec

Using Asyncio in Python

Автор: Caleb Hattingh
Год издания: 2020

#python #english

Скачать книгу

Статьи и задачи по Python - ТУТ

To'g'ri javob yo'q, if ichidagi kod ishlamaydi.

Bunga asosiy sabab barcha dasturlash tillarida hisob kitoblar binary holatda amalga oshiriladi. Masalan 6 soni 110 (ya'ni 0*2^0 + 1*2^1 + 1*2^2) ko'rinishida bo'ladi va shu ko'rinishdaligida ustida amallar bajariladi.

Yuqoridagi holatni endi ko'rib chiqamiz. Decimal sonlarni binary ko'rinishga o'tkazish unchalik ham murakkab emas. Buni google orqali tezda tushinib olishingiz mumkin.

0.2 = 0.00110011001100110011...

0.3 = 0.01001100110011001100...

Ikkala chiqqan binary sonlarni qo'shamiz.

0.00110011001100110011...
+ 0.01001100110011001100...
= 0.01111111111111111111...

0.5 ni ham binaryga o'tkazsak 0.1 qiymat olamiz.

0.1 > 0.01111111111111111111... .

Ko'rib turganimizdek 0.5 ning qiymati 0.2 + 0.3 nikidan juda kam miqdorda katta.

Orqaga qaytamiz. 0.1 ni decimalga o'zgartiramiz 0*2^0 + 1*2^-1 = 0.5.

0.011111111111111... ni qaytarsak 0*2^0 + 0*2^-1 + 1*2^-2 + 1*2^-3 + 1*2^-4 + 1*2^-5 + ... - "natija"si 0.5 ga teng cheksiz kamayuvchi geometrik progressiya. Kompyuterda esa cheksiz degan tushuncha yo'q, o'zgaruvchiga hotirada qancha joy ajratilgan bo'lsa shuncha aniqlikda hisoblaydi. Misol tariqasida verguldan keyingi 20ta raqam hotiraga sig'di deb hisoblasak 0.01111111111111111111 ni decimalga aylantiramiz, natija esa 0.499999046 chiqadi (aslida bundan ancha aniq ishlaydi).

0.5 ≠ 0.499999046

Bu holat floating point error deb ataladi.

Shu yergacha kelgan bo'lsangiz yana bitta savol 0.2 + 0.3 == 0.1 + 0.4 ning natijasi nima bo'ladi?

#math

@shukhratutaboev

Django 4.2 is Here ! 💥

More: https://www.linkedin.com/posts/davronbek-boltayev_django-42-activity-7050405075248177152-eBSW?utm_source=share&utm_medium=member_desktop

Dasturchilar uchun manitor hajmi qanchalik muhum? 🤔

Bazi holatlarda katta (34<) manitorlarda ko’z oynaklarsiz ko’p vaqt qolib ketish sog’liq uchun sezilarli darajada hafvli hisoblanadi. 🖥

Shaxsan menga 14 ekranli m2 16/512 MacBookPro uzi yetarli hisoblanadi. 😌

2, 3 ekranga esa qachongi haqiqatda ehtiyoj sezila boshlaganidagina foydalangan maqul va bu sizning foydali ish koefsintizga ijobiy ta’sir kursatadi shu vaqtda siz kuplab oynalar ochiq holatda va ko’p foydalaniladi. 📊

Meni uzimda har doim ochiq turadigan dasturlar VS code, chrome, telegram, PostMan bulardan kunlik ish davomida judda kup marotaba foydalanamiz 🗓

EPAM kabi companylarda interview jarayonida suralish ehtimoli mavjud bo’lgan mavzular (sinior akalar tavsiyasi 😉)

VCS - git merge vs git rebase
Docker, Conterinization - Image, Container, Volume
WEB - REST API, Django architecture
DataBase - Index , Inner Join
CI/CD
Python Types and Operations - Dictionaries, is vs ==, mutable vs immutable, copy vs deepcopy
Algorithms - Complexity
Functions in Python
Memory managemen - Ref counting
Multitasking - GIL, Thread vs process
OOP in Python - Encapsulation, Data hiding


1. Dictionaries in depth. Hash, hash function and its properties. Hashing vs. encrypting. Good reference material on how dictionaries work:https://stackoverflow.com/questions/327311/how-are-pythons-built-in-dictionaries-implemented
2. Decorators in depth. To see into what is decorator is and how it works. How to decorate function without using '@'. The same for parametrized decorators.(https://realpython.com/primer-on-python-decorators/)
3. Figure out how does inheritance in Python work. What is diamond problem. What is MRO. Difference between New Style Classes and Old Style Classes. C3 algorithm. Be able to calculate MRO of large inheritance tree on blackboard or paper(https://blog.pilosus.org/posts/2019/05/02/python-mro/).
4. reference counting (https://towardsdatascience.com/understanding-reference-counting-in-python-3894b71b5611)
5. Garbage collecting in python (https://pythoninternal.wordpress.com/2014/08/04/the-garbage-collector/)
6. Figure out what is scope and how LEGB rule works. (https://python-scripts.com/scope )
7. Algorithms complexity - https://introprogramming.info/english-intro-csharp-book/read-online/chapter-19-data-structures-and-algorithm-complexity/
8. Data hiding - https://www.upgrad.com/blog/data-hiding-in-python/#:~:text=Data%20hiding%20in%20Python%20is,and%20hides%20them%20from%20users.
9. Python GIL (http://www.dabeaz.com/GIL/)

I can suggest to take a look at this books:

* "Clean Code: A Handbook of Agile Software Craftsmanship" (Robert C. Martin )
* "Clean Architecture: A Craftsman's Guide to Software Structure and Design" (Robert C. Martin )
* "Clean Coder, The: A Code of Conduct for Professional Programmers " (Robert C. Martin )
Python:
* Programming Python ( Mark Lutz )
* "Learning Python" by Mark Lutz
* "Python Cookbook" by Brian Jones, David Beazley
* "Fluent Python" by Luciano Ramalho
More complex books:
* "Python Tricks: The Book A Buffet of Awesome Python Features" (Den Baden)
* "Clean Code in Python: Refactor your legacy code base" (by Mariano Anaya)
* "CPython Internals" (Anthony Shaw)

linkedin courses:
* https://www.linkedin.com/learning/effective-serialization-with-python/serialization-with-python
* https://www.linkedin.com/learning/python-parallel-and-concurrent-programming-part-1/learn-parallel-programming-basics
*https://www.linkedin.com/learning/python-parallel-and-concurrent-programming-part-2/learn-parallel-programming-basics?u=2113185
*https://www.linkedin.com/learning/python-code-challenges/put-your-python-skills-to-the-test?u=2113185»


@davron_dev

SQLda uzb contentda biroz izlanish qilayotgan edim. 📕

Shu yerda turib tursin arxiv bulib kerak buladi.

P/s uzizda bor DBga oid uzb content bulsa comentda qoldirishingiz mumkin 👇