#phyton

[one-time-i-dreamt]

I was a wizard in the middle of a war on Earth, and I brought my best friend back from the dead (he’s not dead in real life). Also, the wizard spells were structured like Python code.

#dream #text #December 3rd 2023 #wizard #war tw #death tw #phyton #code #coding #queueueueueueueueueueueueueue

[cybtch]

#art #music #science #computer science #scientist #java #phyton #meme #mathmatics #chemistry #physics #computer #artist #me

[openprogrammer]

Border styles in CSS! Save this for later reference- Let me know your thoughts down in the comments and check out my profile for more coding related content. #html #js #javascript #phyton #beginner #100daysofcode #dotnet #code #coding #scss #manojdeshwal #connectedprogrammer #youtubeassistance #youtubemotivation  #css #programming #frontenddeveloper (at India) https://www.instagram.com/p/CjI8PXavFg6/?igshid=NGJjMDIxMWI=

#html #js #javascript #phyton #beginner #100daysofcode #dotnet #code #coding #scss #manojdeshwal #connectedprogrammer #youtubeassistance #youtubemotivation #css #programming #frontenddeveloper

[jhavtechstudios]

Pros of Django in Backend Mobile App Development

Django is a high-level open-source framework that has grown in usage and emerge as the most popular python web framework. A Stack Overflow Survey conducted this year showed that Django is preferred by 53% of professional developers. It was used to build the backend for Instagram. You can use the Django Rest Frame on the backend of mobile apps with either React Native, Cordova Flutter or Ionic on the frontend. Here are the main benefits of using this Python-based framework: • Scalability: Apps can efficiently handle traffic demand thanks to Django’s caching option and code reusability feature • Security: Django helps developers in avoiding security issues like SQL injections and CSRF attacks • With Django’s added battery, developers can use packages to include functions instead of starting from scratch with their code, thus saving time and allowing them to focus on other facets of their apps • Django has a superb set of Libraries • Asynchronous programming thanks to the Model-View-Template architecture • Django has great documentation and tutorials

#django #phyton #programming #coding #programmer #developer #mobile app #mobile applications #app developer #jhavtech studios

[blacklinesw9]

(via Chaos theory: Lorenz equation Clock by Blacklinesw9)

#findyourthing #redbubble #Lorenz equation #chaos theory #non linear #physics #butterfly effect #blacklinesw9 #science #phyton #geekart

[aibyrdidini]

Latexify is library available to Julia and Python

Latexify is a versatile tool that bridges the gap between programming and typesetting, making it easier for developers and researchers to incorporate mathematical expressions and code into their documents. It is available in various programming languages, including Julia and Python, each offering unique features and capabilities.

Python Implementation: latexify_py

For Python users, `latexify_py` is a powerful package that allows for the conversion of Python code into LaTeX expressions. This is particularly useful for academic and corporate settings where mathematical expressions and code snippets need to be included in documents. Here are five Python code snippets demonstrating the use of `latexify_py`:

1. Basic Usage

```python

from latexify_py import latexify

latexify(1/2)

```

This converts the fraction 1/2 into its LaTeX representation.

2. Function Conversion

```python

@latexify_py.latexify

def f(x):

return x**2 + 2*x + 1

```

This decorator converts the function `f(x)` into a LaTeX formula.

3. Complex Numbers

```python

latexify(1 + 2j)

```

Converts the complex number 1 + 2j into its LaTeX representation.

4. Numpy Arrays

```python

import numpy as np

latexify(np.array([1, 2, 3]))

```

Converts a numpy array into a LaTeX array.

5. Sympy Expressions

```python

from sympy import symbols, sin

x = symbols('x')

latexify(sin(x))

```

Converts a sympy expression into a LaTeX formula.

Use Cases

- Academics: Researchers and academics can use Latexify to include mathematical expressions, equations, and code snippets in their papers, reports, and presentations. This is particularly useful in fields like mathematics, physics, and computer science where precise mathematical notation is crucial.

- Corporates: In corporate settings, Latexify can be used to document algorithms, mathematical models, and code snippets in technical reports, presentations, and documentation. This ensures that the mathematical and code elements are accurately represented and easily understandable.

Examples

- Academic Documents: In a research paper on quantum mechanics, Latexify can be used to include complex equations and mathematical models in the LaTeX document. This ensures that the equations are rendered correctly and are easily readable by the audience.

- Corporate Reports: A corporate report on a new algorithm can use Latexify to include the algorithm's pseudocode and mathematical expressions in the report. This makes the report more professional and ensures that the technical details are accurately represented.

Accessing Latexify

For Python users, `latexify_py` can be installed via pip:

```bash

pip install latexify_py

```

For Julia users, `Latexify.jl` can be added to the Julia environment using the Julia package manager:

```julia

using Pkg

Pkg.add("Latexify")

```

Latexify is a valuable tool for anyone working with mathematical expressions or code in their documents, making it easier to ensure that these elements are accurately represented and easily understandable.

RDIDINI PROMPT ENGINEER

#ai solutions #ai trends #ai-driven #libraries #Phyton #Julia

[cyber-techs]

Automating in Python: A Developer's Handbook for 2024

In today's rapidly evolving technological landscape, automation has become an indispensable tool for developers seeking to streamline their workflows, increase productivity, and reduce repetitive tasks. Python, with its simplicity, versatility, and extensive ecosystem of libraries, continues to be the language of choice for automation tasks across various domains. Whether you're a seasoned developer or just starting your journey in programming, mastering automation in Python can significantly enhance your efficiency and effectiveness. This developer's handbook for 2024 will explore the latest trends, tools, and best practices in Python automation.

Why Python for Automation?

Python's popularity in automation stems from several key advantages:

Ease of Learning and Use: Python's clean syntax and readability make it accessible to developers of all skill levels. Its simplicity allows developers to focus more on solving problems rather than wrestling with complex syntax.

Rich Ecosystem of Libraries: Python boasts an extensive collection of libraries and frameworks tailored for automation tasks. From web scraping to data manipulation, machine learning, and beyond, Python offers libraries like BeautifulSoup, Pandas, Selenium, and TensorFlow, enabling developers to tackle a wide range of automation challenges.

Cross-platform Compatibility: Python runs on major operating systems like Windows, macOS, and Linux, making it a versatile choice for automation across different environments.

Active Community Support: Python has a vibrant community of developers who actively contribute to its ecosystem, creating tutorials, documentation, and open-source projects that facilitate learning and problem-solving.

Latest Trends in Python Automation

As we delve into 2024, several trends are shaping the landscape of Python automation:

AI-Powered Automation: With the integration of machine learning and artificial intelligence into automation workflows, developers can build intelligent systems capable of making autonomous decisions and adapting to changing conditions. Python's libraries such as TensorFlow, PyTorch, and scikit-learn empower developers to incorporate AI capabilities into their automation projects.

Robotic Process Automation (RPA): RPA involves automating repetitive, rule-based tasks traditionally performed by humans. Python, combined with RPA frameworks like UiPath and Automation Anywhere, enables developers to create software robots that mimic human interactions with digital systems, leading to significant efficiency gains in industries such as finance, healthcare, and manufacturing.

Infrastructure as Code (IaC): As organizations embrace cloud computing and containerization technologies, the need for automating infrastructure deployment and management becomes paramount. Python, along with tools like Terraform, Ansible, and Kubernetes, facilitates the automation of provisioning, configuration, and orchestration tasks, enabling developers to build and manage scalable, resilient infrastructure with ease.

DevOps Automation: DevOps practices emphasize collaboration, automation, and continuous integration/continuous deployment (CI/CD) pipelines to accelerate software delivery and improve reliability. Python plays a pivotal role in DevOps automation, enabling developers to automate code deployment, testing, monitoring, and infrastructure provisioning, fostering a culture of agility and innovation within organizations.

Best Practices for Python Automation

To harness the full potential of Python for automation, developers should adhere to best practices:

Modularization: Break automation scripts into modular components, promoting code reuse, readability, and maintainability.

Error Handling: Implement robust error handling mechanisms to gracefully handle exceptions and failures, ensuring the reliability of automation workflows.

Version Control: Leverage version control systems like Git to track changes in automation scripts, collaborate with team members, and roll back changes if necessary.

Documentation: Document code comprehensively, including comments, docstrings, and README files, to aid understanding and facilitate knowledge sharing among team members.

Testing: Develop automated tests to validate the functionality and performance of automation scripts, ensuring they meet the desired requirements and specifications.

Security: Adhere to security best practices, such as securely storing credentials, sanitizing inputs, and implementing encryption, to safeguard sensitive data and protect automation workflows from vulnerabilities.

Conclusion

As automation continues to redefine the way developers work, Python remains an indispensable tool for automating tasks across diverse domains. By staying abreast of the latest trends, leveraging Python's rich ecosystem of libraries, and adhering to best practices, developers can unlock new levels of efficiency, productivity, and innovation in their automation endeavors. Whether you're automating routine administrative tasks, orchestrating cloud infrastructure, or building intelligent systems powered by AI, Python empowers developers to automate with confidence in 2024 and beyond.

#Phyton #Developer Guides

[aenderlara]

New #blender3d tutorial is now on YouTube go and take a look ❤️

#blender3d #tutorial #expression #driver #phyton

[devstreeau]

Future Directions for Android App Development in 2024

Devstree Australia pioneers Android app development in 2024, embracing cutting-edge technologies for seamless user experiences. Our skilled team harnesses the latest trends, from AI integration to immersive AR/VR solutions, ensuring innovative and responsive applications. As a leading Android App Development Company in Australia, we prioritize user-centric design, scalability, and security, delivering solutions that redefine the mobile landscape. Stay ahead with Devstree for future-proof Android apps that elevate your business in the dynamic digital era.

#australia #devstreeau #mobileappdevelopment #iphone #mobile app developer company #web app development #ios #mobile app company #iot app development #iot applications #javascript #phyton #nodejs #angular #developer #design

[gilbartar]

#website #programming #writing #bloggingtips #phyton #google colab #seo expert #seo #keywords

[one-time-i-dreamt]

Elsa from Frozen was turned into a giant white python with anime eyes and an aggressive number of eyelashes. She tried to change back but got turned into a fire breathing sea dragon that specifically hoarded the treasured collections of children, which as queen she demanded.

#dream #elsa #frozen #body horror #phyton #snake #snakes #snakes tw #snake tw #body horror tw #anime eyes #eyes mention #eyelashes #fire #fire tw #sea dragon #treasure

[natureinhouse]

Terrarium dla węża, pytona królewskiego, projekt i wykonanie

https://www.natureinhouse.com/terrarium-dla-weza-pytona-krolewskiego/

#terrarium #phyton

[feroz-ov]

Article: Python is coming to Microsoft Excel

Python is coming to Microsoft Excel.

This is a boom. Is like... ONE RING TO RULE THEM ALL.

#Phyton #science #stadistics #statistics #software

[openprogrammer]

Weekends are perfect for self-learn and skills development. . . . Follow @openprogrammer Follow @openprogrammer Follow @openprogrammer . . . #workfromhome #phyton #wfh #covid #entrepreneur #stayathome #business #stayhome #motivation #success #money #staysafe #work #onlinebusiness #love #socialdistancing #makemoneyonline #digitalmarketing #homeoffice #networkmarketing #smallbusiness #marketing #coronavirus #reactjs #workfromhomelife #businessowner #affiliatemarketing #instagram #makemoney #lockdown (at India) https://www.instagram.com/p/Ci6_XUVPc74/?igshid=NGJjMDIxMWI=

#workfromhome #phyton #wfh #covid #entrepreneur #stayathome #business #stayhome #motivation #success #money #staysafe #work #onlinebusiness #love #socialdistancing #makemoneyonline #digitalmarketing #homeoffice #networkmarketing #smallbusiness #marketing #coronavirus #reactjs #workfromhomelife #businessowner #affiliatemarketing #instagram #makemoney #lockdown

[jhavtechstudios]

Two Types of Programming Languages

A programming language is basically a set of syntactical rules that instruct a computer to perform certain tasks. There are two main types: Low-level Programming Languages These are your 0s and 1s. These languages can be run directly by a processor without a compiler or interpreter. They are therefore extremely fast but can be difficult for humans to understand. High-level programming languages These languages are readable and more user-friendly, but require a compiler or interpreter to translate to machine language. Examples include Python, PHP, Java, JavaScript, and Swift.

#programming languages #programming #phyton #coding #php #developerlife #swift #app developer #javascript #jhavtech studios

[digilearnteach]

#CSS #phyton #C Language #HTML #C++ Language #Learn CSS #Coding Classes #Java Script #Learn HTML #java language #Programming Language #HTML Language #CSS Language #coding for beginners #online coding courses