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DA Cost Analyzer

$13

Analyze data availability costs across Celestia, EigenDA, Avail, and Ethereum blobs.

📁 13 files
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📁 File Structure 13 files

da-cost-analyzer/ ├── README.md ├── config/ │ └── default.yaml ├── pyproject.toml ├── security-notes.md ├── src/ │ ├── __init__.py │ ├── analyzers/ │ │ ├── __init__.py │ │ ├── blob_analyzer.py │ │ ├── calldata_analyzer.py │ │ └── comparison.py │ ├── cli.py │ ├── models/ │ │ └── __init__.py │ └── utils/ │ └── __init__.py └── tests/ └── test_analyzer.py

📖 Documentation Preview README excerpt

DA Cost Analyzer

EIP-4844 blob cost analysis and data availability optimization for rollup operators.

Price: $12.99 | License: MIT | Category: Tooling | Python: >=3.10

Overview

da-cost-analyzer is a Python toolkit for analyzing and comparing data availability costs on Ethereum. It tracks blob gas prices, compares calldata vs blob posting costs, simulates compression ratios, and benchmarks costs across multiple rollups.

Built for rollup operators and researchers who need to make data-driven decisions about their DA strategy post-EIP-4844 (Dencun upgrade).

Features

  • Blob gas price tracking — Monitor blob base fee trends over time with historical charts
  • Calldata vs blob cost comparison — Side-by-side cost analysis for any given data payload
  • Compression ratio simulation — Test how different compression algorithms affect effective cost per byte
  • Multi-rollup cost comparison — Benchmark DA costs across Optimism, Base, Arbitrum, and custom rollups
  • Cost projection — Forecast DA spend based on transaction volume growth scenarios
  • Rich terminal output — Color-coded tables and charts directly in your terminal

Tech Stack

ComponentTechnology
CorePython 3.10+
Chain Dataweb3.py
Analysispandas, numpy
Visualizationmatplotlib, rich
ConfigurationYAML, python-dotenv

Quick Start

Prerequisites

  • Python 3.10+
  • An Ethereum L1 RPC endpoint (archive node recommended for historical analysis)

Install


pip install -e .

# With dev dependencies
pip install -e ".[dev]"

Usage


# Analyze blob gas costs over the last 1000 blocks
da-cost analyze --rpc $L1_RPC --blocks 1000

# Compare calldata vs blob for a specific payload size
da-cost compare --bytes 128000 --rpc $L1_RPC

# Run compression simulation
da-cost compress --input sample_batch.bin --algorithms zlib,zstd,brotli

*... continues with setup instructions, usage examples, and more.*

📄 Code Sample .py preview

src/cli.py """ DA Cost Analyzer — CLI Entry Point ════════════════════════════════════ Command-line interface for blob and calldata cost analysis. """ import argparse import sys from .analyzers import BlobCostAnalyzer, CalldataAnalyzer, CostComparison from .models import AnalyzerConfig from .utils import format_eth, format_pct, export_json def main() -> int: parser = argparse.ArgumentParser( prog="da-cost-analyzer", description="EIP-4844 blob cost analysis and optimization", ) parser.add_argument("--rpc-url", required=True, help="Ethereum L1 RPC URL") parser.add_argument("--batcher", action="append", default=[], help="Batcher address(es)") subparsers = parser.add_subparsers(dest="command") # Blob analysis blob_parser = subparsers.add_parser("blob", help="Analyze blob gas costs") blob_parser.add_argument("--blocks", type=int, default=100, help="Number of blocks to analyze") blob_parser.add_argument("--output", help="Output JSON file path") # Comparison compare_parser = subparsers.add_parser("compare", help="Compare calldata vs blob costs") compare_parser.add_argument("--size-kb", type=int, default=128, help="Data size in KB") compare_parser.add_argument("--gas-price", type=float, default=30.0, help="Gas price in gwei") # Report report_parser = subparsers.add_parser("report", help="Generate full cost report") report_parser.add_argument("--output", default="da-report.json", help="Output file path") args = parser.parse_args() if not args.command: parser.print_help() return 1 blob_analyzer = BlobCostAnalyzer(rpc_url=args.rpc_url) if args.command == "blob": print(f"Analyzing blob gas costs for last {args.blocks} blocks...") latest = blob_analyzer.w3.eth.block_number snapshots = blob_analyzer.fetch_range(latest - args.blocks, latest) # ... 30 more lines ...
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