Camelot - PDF Table Extraction

Camelot: PDF Table Extraction for Humans

Python library for extracting tables from PDF files with high accuracy:

Key Features:

  • Multiple Parsing Methods: Stream and Lattice parsers for different table types
  • High Accuracy: Better results than traditional PDF parsing tools
  • Pandas Integration: Direct conversion to pandas DataFrames
  • Visual Debugging: Plot detected table areas for validation
  • Customizable: Fine-tune detection parameters

Usage Examples:

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import camelot

# Extract tables from PDF
tables = camelot.read_pdf('document.pdf')
print(f"Found {tables.n} tables")

# Convert to pandas DataFrame
df = tables[0].df

# Export to various formats
tables.export('output.csv', f='csv')
tables.export('output.xlsx', f='excel')

When to Use:

  • Financial reports with tabular data
  • Research papers with data tables
  • Government documents with statistics
  • Any structured data trapped in PDFs

PostgreSQL Row Level Security for Multi-Tenancy

Multi-tenant data isolation with PostgreSQL Row Level Security

Advanced PostgreSQL feature for implementing secure multi-tenant applications:

What is Row Level Security (RLS):

  • Fine-Grained Access: Control access at the row level within tables
  • Policy-Based: Define security policies for different user types
  • Transparent: Application code doesn’t need complex filtering logic
  • Performance: Database-level enforcement with optimized execution

Implementation Pattern:

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-- Enable RLS on table
ALTER TABLE customer_data ENABLE ROW LEVEL SECURITY;

-- Create policy for tenant isolation
CREATE POLICY tenant_isolation ON customer_data
    FOR ALL TO tenant_user
    USING (tenant_id = current_setting('app.current_tenant')::integer);

-- Set tenant context in application
SET app.current_tenant = '123';

Benefits:

  • Data Isolation: Strong tenant boundaries
  • Security: Prevents data leaks between tenants
  • Simplicity: Reduces application complexity
  • Compliance: Meets regulatory requirements

Use Cases:

  • SaaS applications with multiple customers
  • Healthcare systems with patient data isolation
  • Financial applications with account separation
  • Any system requiring strict data boundaries

Zerodha Varsity - Free Trading Education

Varsity by Zerodha – Markets, Trading, and Investing Simplified

Comprehensive free educational platform for learning about financial markets:

What It Covers:

Trading Fundamentals:

  • Technical Analysis: Chart patterns, indicators, candlesticks
  • Fundamental Analysis: Financial statement analysis, valuation
  • Options Trading: Strategies, Greeks, risk management
  • Futures Trading: Contract specifications, margin requirements

Investment Concepts:

  • Portfolio Management: Asset allocation, diversification
  • Risk Management: Position sizing, stop losses
  • Market Psychology: Behavioral finance concepts
  • Regulatory Framework: SEBI guidelines and compliance

Learning Approach:

  • Module-Based: Structured progression from basics to advanced
  • Practical Examples: Real market scenarios and case studies
  • Interactive Content: Charts, calculators, and tools
  • Free Access: No cost for high-quality financial education

Value Proposition:

  • Democratizes financial education
  • Reduces dependence on expensive courses
  • Provides practical, actionable knowledge
  • Builds informed investor community

Write Yourself a Git

Write yourself a Git!

Educational project to understand Git internals by implementing it from scratch:

Learning Objectives:

  • Version Control Concepts: How distributed version control works
  • Git Internals: Objects, references, and storage mechanisms
  • Data Structures: Trees, graphs, and hash-based storage
  • File System Operations: Blob storage and retrieval

Key Components to Implement:

Core Git Objects:

  • Blobs: File content storage
  • Trees: Directory structure representation
  • Commits: Snapshots with metadata
  • Tags: Named references to commits

Repository Operations:

  • Initialize: Create new repository structure
  • Add: Stage files for commit
  • Commit: Create snapshot with message
  • Checkout: Switch between branches/commits

Implementation Benefits:

  • Deep Understanding: Learn Git’s internal architecture
  • Debugging Skills: Better troubleshoot Git issues
  • System Design: Understand distributed system principles
  • Programming Practice: File I/O, data structures, algorithms

Technologies Used:

  • Python for implementation simplicity
  • File system operations for storage
  • Hashing algorithms for content addressing
  • Command-line interface design

Each resource provides deep technical knowledge in its domain - from practical data extraction to advanced database security, financial literacy, and version control system design.