How to implement __repr__ and __str__ in Python

This is code Of Caption Generation (Inference) By Python. def generate_caption(photo, tokenizer, max_length): in_text = 'startseq' for _ in range(max_length): sequence = tokenizer.texts_to_sequences([in_text])[0] sequence = pad_sequences([sequence], maxlen=max_length) yhat = model.predict([photo, sequence], verbose=0) yhat = np.argmax(yhat) word = tokenizer.index_word.get(yhat) if word is None: break in_text += ' ' + word if word == 'endseq': break return in_text

Python String Slicing 🐍 The most important rule for variable[start:stop]1: start: IS included2. stop: is NOT included3. 3 key patterns: variable[start:stop] ➔ Grabs a middle section. "HELLO PYTHON"[0:5] gives HELLO 4 variable[start:] ➔ Grabs from start to the end. "HELLO PYTHON"[6:] gives PYTHON 5 variable[:stop] ➔ Grabs from the beginning to stop. "HELLO PYTHON"[:5] gives HELLO 6 Bonus Tip: Use [start:stop:step] to "jump" #Python #Programming #PythonTips #Coding

🚀 Big news for the Power Platform ecosystem! Microsoft just enabled Python execution directly within Power Platform — a massive leap for automation, analytics, and AI integration. 💡 Why it matters: For business users: This means you can now access advanced data transformation, AI, and visualization capabilities without leaving Power Apps or Power Automate. Think predictive analytics, natural language models, and data science workflows — all in one low-code environment. For developers: It bridges low-code and pro-code like never before. You can now reuse Python scripts, leverage existing libraries (Pandas, NumPy, OpenAI, etc.), and supercharge Power Platform solutions with real computation power. For organizations: Expect faster innovation, less dependency on external pipelines, and more value extracted from your data — directly within Microsoft’s governance and security layer. This is the convergence of low-code + pro-code + AI, and it’s going to reshape how we build and automate business solutions. 🔥 #PowerPlatform #Python #AI #Automation #DataScience #LowCode

7 Must-Know Dictionary Methods in Python: 1️⃣ get() — Safely access a key without KeyError. 2️⃣ update() — Merge or add key-value pair. 3️⃣ items() — Iterate over key-value pair. 4️⃣ setdefault() — Add a key only if it doesn’t exist. 5️⃣ pop() — Remove and return an item by key. 6️⃣ fromkeys() — Create a new dict from a list of keys. 7️⃣ popitem() — Remove the last inserted key-value pair. #Python #PythonProgramming #Coding #Developers #LearnPython

Ever felt your Python code runs slow or gets messy? Chances are — you’re using the wrong data structure. This 10-second cheat sheet shows when to use Lists, Tuples, Sets, and Dictionaries 👇 Master this, and you’ll instantly write faster, cleaner, smarter code. #Python #DataScience #LearningEveryday #CodingTips #DataAnalytics #WomenInTech

Ever felt your Python code runs slow or gets messy? Chances are — you’re using the wrong data structure. This 10-second cheat sheet shows when to use Lists, Tuples, Sets, and Dictionaries 👇 Master this, and you’ll instantly write faster, cleaner, smarter code. #Python #DataScience #LearningEveryday #CodingTips #DataAnalytics #WomenInTech

💡 Python Tip — Even seasoned developers might overlook this! When dividing two integers in Python: print(6 / 4) # Output: 1.5 Python automatically converts the integers into floating-point numbers to give a precise decimal result. But what if you want an integer instead? You can type cast the result manually: print(int(6 / 4)) # Output: 1 This simply truncates the decimal — no rounding! 🔥 A cleaner and more Pythonic way: Use integer division with the // operator — it divides and converts in one step: print(6 // 4) # Output: 1 print(9 // 4) # Output: 2 print(-9 // 4) # Output: -3 # (Rounds down toward negative infinity!) Subtle details like these make your code both cleaner and more predictable. #Python #CodingTips #SoftwareDevelopment #LearningPython #Programming

🐍 Day 2/30 — Comments in Python Today, I learned about comments in Python a simple but very important concept. Comments help us explain code, and Python completely ignores them during execution. ✔️ Single-line Comment # This is a comment print("Comments are ignored by Python") ✔️ Multi-line Comment """ This is a multi-line comment """ print("Learning comments!") 🧠 Tip: Use comments to explain logic, make code readable, and help others understand your program. #Python #Programming #LearnPython #PythonBasics #Scaler #CodingJourney #PythonForBeginners #30DaysOfCode #30DaysOfPythonjourney!