Skip to main content

High-performance SVG chart rendering engine for financial data visualization

Project description

zengeld-canvas

High-performance SVG chart rendering engine for financial data visualization

Crates.io PyPI npm

Python bindings for the high-performance zengeld-canvas chart rendering engine. Built in Rust with zero runtime dependencies.

Installation

pip install zengeld-canvas

Examples


Dark Theme

MACD Indicator

Multi-Chart Layout

Channels

Gann Tools

Chart Patterns

Features

  • 80+ Drawing Primitives - Fibonacci, Gann, Pitchforks, Patterns, Elliott Waves, and more
  • 12 Series Types - Candlestick, Line, Area, Histogram, and more
  • Platform Agnostic - RenderContext trait for any rendering backend
  • Zero Dependencies - Only serde for serialization
  • High Performance - Optimized for real-time chart rendering

Quick Start

from zengeld_canvas import Bar, Viewport, PriceScale, Theme

# Create bars
bar = Bar(time=1703721600, open=100.0, high=105.0, low=98.0, close=103.0)
print(f"Bullish: {bar.is_bullish()}")

# Create viewport
viewport = Viewport(width=800.0, height=600.0)
viewport.first_bar = 0.0
viewport.last_bar = 100.0

# Create price scale
price_scale = PriceScale()
price_scale.set_range(95.0, 110.0)

# Use dark theme
theme = Theme.dark()
print(f"Background: {theme.background}")

License

MIT OR Apache-2.0

Support the Project

If you find this library useful, consider supporting development:

Currency Network Address
USDT TRC20 TNxMKsvVLYViQ5X5sgCYmkzH4qjhhh5U7X
USDC Arbitrum 0xEF3B94Fe845E21371b4C4C5F2032E1f23A13Aa6e
ETH Ethereum 0xEF3B94Fe845E21371b4C4C5F2032E1f23A13Aa6e
BTC Bitcoin bc1qjgzthxja8umt5tvrp5tfcf9zeepmhn0f6mnt40
SOL Solana DZJjmH8Cs5wEafz5Ua86wBBkurSA4xdWXa3LWnBUR94c

zengeld

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

zengeld_canvas-0.1.5.tar.gz (370.9 kB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

zengeld_canvas-0.1.5-cp312-cp312-win_amd64.whl (128.4 kB view details)

Uploaded CPython 3.12Windows x86-64

zengeld_canvas-0.1.5-cp312-cp312-macosx_11_0_arm64.whl (224.3 kB view details)

Uploaded CPython 3.12macOS 11.0+ ARM64

zengeld_canvas-0.1.5-cp312-cp312-macosx_10_12_x86_64.whl (230.6 kB view details)

Uploaded CPython 3.12macOS 10.12+ x86-64

zengeld_canvas-0.1.5-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (248.6 kB view details)

Uploaded CPython 3.8manylinux: glibc 2.17+ x86-64

File details

Details for the file zengeld_canvas-0.1.5.tar.gz.

File metadata

  • Download URL: zengeld_canvas-0.1.5.tar.gz
  • Upload date:
  • Size: 370.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for zengeld_canvas-0.1.5.tar.gz
Algorithm Hash digest
SHA256 72d0a4e4a057234372586a4515182d5283d1f06d8017efdfd1a04fce43d60dee
MD5 55c1ad84b921ee6d9a3c94b5982ce9bb
BLAKE2b-256 127bb121d4df9717f04a9d7646f0aaa53ad7ccc190fb9639e875466ab107ec7a

See more details on using hashes here.

File details

Details for the file zengeld_canvas-0.1.5-cp312-cp312-win_amd64.whl.

File metadata

File hashes

Hashes for zengeld_canvas-0.1.5-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 db38f41eeb58ac09266683ba797650784155a61c3cb6d45c56ef6ec3213dc9a3
MD5 cc5cedaccba71727dd8233da2595c46f
BLAKE2b-256 e7fca8bfb0325e1c22dd9291925718d7e64a9485ae87cefb35af0e6e65971d97

See more details on using hashes here.

File details

Details for the file zengeld_canvas-0.1.5-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for zengeld_canvas-0.1.5-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 1c7725c9baed9f4543f8bbf4b6f3fc5e59d2c81ace63f3265013d5437bba032f
MD5 a85d7141804f869ba6c232368c7bf238
BLAKE2b-256 ae5e3bfb4f3f3e1facfbe72d2970e508fada23cb3af8a6091002c6bfdd473416

See more details on using hashes here.

File details

Details for the file zengeld_canvas-0.1.5-cp312-cp312-macosx_10_12_x86_64.whl.

File metadata

File hashes

Hashes for zengeld_canvas-0.1.5-cp312-cp312-macosx_10_12_x86_64.whl
Algorithm Hash digest
SHA256 66219991ccfd29b4bd0df4b41783069fd226942a05150ea79f407f44dccd91dd
MD5 ff2563493b47cdd80e2b83ae650112a3
BLAKE2b-256 d487d0e65e5029d31b08e84721267daa008cef1714425036bb7cb944e3a79223

See more details on using hashes here.

File details

Details for the file zengeld_canvas-0.1.5-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for zengeld_canvas-0.1.5-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 3c4fd14305480aff7e7ed09fab3cb31c86c3aba95b96611d3b939d34bc185166
MD5 3df078a6ed9ceee47adbda0ea92ef08d
BLAKE2b-256 bde53b4f6022f471f35533e328345a3a90ec7d352186732ca8259d819e4548c8

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page