docs(notes): add Python boom investment hotspots article

Author: lzwjava

_posts/en/2025-01-11-notes-en.md

@@ -7,7 +7,7 @@ generated: false
 translated: false
 ---
 
-These 2008 notes are primarily generated by AI chatbots. I used them to summarize key points and will walk through them to enhance my understanding.
+These 2009 notes are primarily generated by AI chatbots. I used them to summarize key points and will walk through them to enhance my understanding.
 
 * [OpenRouter AI Model Marketplace Guide](/notes/2025-08-20-ai-model-marketplace-guide-en)
 * [Top AI Models by Category 2025](/notes/2025-08-20-ai-models-2025-en)
@@ -18,6 +18,7 @@ These 2008 notes are primarily generated by AI chatbots. I used them to summariz
 * [Macs vs Windows Costs for Big Banks](/notes/2025-08-20-macs-win-costs-bigbanks-en)
 * [Node.js Upgrade Guide for Ubuntu](/notes/2025-08-20-nodejs-upgrade-ubuntu-en)
 * [Install Python 3.11 and pip3.11](/notes/2025-08-20-python-311-pip-install-en)
+* [Python Boom Investment Hotspots](/notes/2025-08-20-python-boom-hotspots-en)
 * [AI Model Cost and Performance Comparison](/notes/2025-08-18-ai-model-cost-perf-en)
 * [Balancing Cost and AI Model Performance](/notes/2025-08-18-cost-ai-performance-en)
 * [ETH Not ERC20 Use Mainnet Only](/notes/2025-08-18-eth-mainnet-only-en)

notes/2025-08-20-python-boom-hotspots-en.md

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+---
+title: Python Boom Investment Hotspots
+lang: en
+layout: post
+audio: false
+translated: false
+generated: true
+image: false
+---
+
+If Python usage grew **5× more popular** than today, that shift would ripple across multiple industries and create investment opportunities in several layers of the ecosystem. Here’s a structured breakdown:
+
+---
+
+### 1. **Developer Tools and Ecosystem**
+
+* **IDEs and Editors**: Companies like JetBrains (PyCharm) or Microsoft (VS Code) would see rising adoption. Investing in firms enhancing Python productivity (plugins, debuggers, refactoring tools) could pay off.
+* **Package Management & Hosting**: PyPI mirrors, dependency scanning, and vulnerability management companies (like Sonatype, JFrog) gain relevance as package use explodes.
+* **Testing & CI/CD**: Services specializing in Python-heavy pipelines (GitHub Actions, GitLab, CircleCI) get a tailwind.
+
+---
+
+### 2. **Cloud and Infrastructure**
+
+* **Python on Cloud Platforms**: AWS Lambda, Google Cloud Functions, and Azure Functions already support Python. A surge in use means more demand for serverless, managed runtimes, and ML-focused compute.
+* **Containerization & Orchestration**: Kubernetes operators, Docker registries optimized for Python apps, and firms offering lightweight Python runtimes.
+* **Edge Computing**: Python frameworks running on IoT and edge devices would grow—opportunity in companies bridging Python to constrained hardware.
+
+---
+
+### 3. **Machine Learning & AI**
+
+* Python dominates ML/AI. If its popularity 5×’s:
+
+  * **Framework maintainers** (TensorFlow, PyTorch, Hugging Face) gain strategic value.
+  * **GPU/TPU hardware demand rises** (NVIDIA, AMD, Intel, Google).
+  * **MLOps platforms** like Weights & Biases, Comet, and MLflow hosting services surge in importance.
+  * **Data labeling & synthetic data** firms benefit, as more devs enter ML.
+
+---
+
+### 4. **Education and Training**
+
+* **Bootcamps & MOOCs**: Companies like Coursera, Udemy, DataCamp, and Codecademy would experience huge demand for Python courses.
+* **Certifications**: Demand for recognized credentials (Google, AWS, Microsoft Python certs) expands.
+* **Books & Publishing**: Technical publishers (O’Reilly, Manning, Packt) see a revival in Python-focused content.
+
+---
+
+### 5. **Business Software and SaaS**
+
+* **Automation-first SaaS**: Python-based workflow automation (e.g., Airflow, Prefect, Dagster) adoption accelerates.
+* **APIs for Python Devs**: Companies offering dev-friendly APIs (Stripe, Twilio, OpenAI) capture more users.
+* **No-Code/Low-Code**: Python as a "glue language" might integrate deeper with these platforms, giving rise to hybrid “Python-assisted” automation SaaS.
+
+---
+
+### 6. **Open Source & Community**
+
+* **Sponsorship and Support Models**: Companies like Tidelift or GitHub Sponsors become critical as open-source maintainers gain financial support.
+* **Consulting & Custom Solutions**: Firms specializing in Python stack support (like Anaconda for data science) expand market share.
+
+---
+
+### 7. **Indirect Hardware & Services**
+
+* **Laptop Sales**: Developers prefer MacBooks and Linux laptops. A jump in Python devs may benefit Apple, Lenovo, Dell.
+* **GPU/Cloud Credits**: Rising demand for ML experiments fuels spending at AWS, GCP, Azure.
+* **Networking/Databases**: PostgreSQL, MongoDB, and Redis usage grows, as Python is tightly coupled to them in modern stacks.
+
+---
+
+✅ **Summary of Opportunities**:
+
+* Public equities: **NVIDIA, Microsoft (GitHub/VS Code, Azure), Amazon (AWS), Alphabet (TensorFlow, GCP)**.
+* Private startups: **MLOps, Python developer tools, workflow automation SaaS**.
+* Alternative assets: **Bootcamps, online education, open-source sustainability platforms**.
+
+---
+
+Would you like me to **rank these by risk/reward profile** (e.g., safer big tech plays vs. riskier but higher-upside startups), so it’s easier to see where you might actually place capital?

original/2025-01-11-notes-en.md

@@ -7,7 +7,7 @@ generated: false
 translated: false
 ---
 
-These 2008 notes are primarily generated by AI chatbots. I used them to summarize key points and will walk through them to enhance my understanding.
+These 2009 notes are primarily generated by AI chatbots. I used them to summarize key points and will walk through them to enhance my understanding.
 
 * [OpenRouter AI Model Marketplace Guide](/notes/2025-08-20-ai-model-marketplace-guide-en)
 * [Top AI Models by Category 2025](/notes/2025-08-20-ai-models-2025-en)
@@ -18,6 +18,7 @@ These 2008 notes are primarily generated by AI chatbots. I used them to summariz
 * [Macs vs Windows Costs for Big Banks](/notes/2025-08-20-macs-win-costs-bigbanks-en)
 * [Node.js Upgrade Guide for Ubuntu](/notes/2025-08-20-nodejs-upgrade-ubuntu-en)
 * [Install Python 3.11 and pip3.11](/notes/2025-08-20-python-311-pip-install-en)
+* [Python Boom Investment Hotspots](/notes/2025-08-20-python-boom-hotspots-en)
 * [AI Model Cost and Performance Comparison](/notes/2025-08-18-ai-model-cost-perf-en)
 * [Balancing Cost and AI Model Performance](/notes/2025-08-18-cost-ai-performance-en)
 * [ETH Not ERC20 Use Mainnet Only](/notes/2025-08-18-eth-mainnet-only-en)

scripts/merge/merge_posts.py

@@ -2,6 +2,7 @@
 import sys
 import glob
 import argparse
+import re
 
 sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
 
@@ -15,6 +16,16 @@ def get_post_date(content):
                 return line.split(':', 1)[1].strip().strip('"\'')
     return None
 
+def extract_date_from_filename(filename):
+    """Extract date from filename in format YYYY-MM-DD."""
+    # Match dates in filenames like 2025-07-30-beyond-expectations-en.md
+    match = re.search(r'(\d{4}-\d{2}-\d{2})', filename)
+    if match:
+        date_str = match.group(1)
+        # Convert from YYYY-MM-DD to YYYY.MM.DD format
+        return date_str.replace('-', '.')
+    return None
+
 def process_post_content(content):
     """Process a single post's content and extract metadata."""
     sub_parts = content.split("---", 2)