vnstock-ezchart
A production-ready, AI-agent-friendly charting toolkit for Vietnamese financial markets — built on Matplotlib, Seaborn & mplfinance with a Soft Premium styling engine, branded logo injection, and 20+ publication-quality chart types out of the box
What it is and what it does
vnstock_ezchart is a charting library purpose-built for Vietnamese financial markets, wrapping Matplotlib, Seaborn, and mplfinance to generate static, publication-ready charts. It addresses the friction of repeatedly writing chart code or prompting AI to generate visualizations from scratch by providing pre-styled templates, global theming, and logo injection. The library supports technical analysis indicators, portfolio allocation views, backtesting visualization, and stock summary cards—all with consistent branding and minimal setup.
The package is optimized for three workflows: embedding high-resolution charts in research reports and printed documents, automating portfolio reports for distribution via chat platforms (Telegram, Discord, Zalo), and providing static images to AI agents for visual analysis. It includes multiple built-in themes (vnstock, academic, minimal, flatui) and allows custom color palettes with semantic ordering (growth, primary, warning, decline). Runtime dependencies are standard data-science tools (numpy, pandas, matplotlib, seaborn, requests, openpyxl, cycler, mplfinance) plus vnstock for market data.
Use it for:
- Generate high-resolution technical analysis charts with multiple overlaid indicators (Ichimoku, Bollinger Bands, MACD) for embedding in research reports.
- Automate daily portfolio performance and risk dashboards, then send chart images to investors via Telegram or Discord.
- Create backtesting visualizations showing candlesticks, volume, entry/exit signals, and equity curves on a shared timeline.
- Build branded stock summary cards with current price, change, and key metrics using a consistent corporate theme.
- Feed static chart images to AI agents for visual analysis of market trends and trading signals.
- Generate academic-style financial charts for papers and theses with publication-quality aesthetics and no browser dependency.
Worth the install?
AI-flagged interpretation of the facts on this page — verify before relying
Generates publication-quality static financial charts for Vietnamese stock markets using Matplotlib and Seaborn, with built-in theming, logo branding, and support for technical analysis indicators.
Yes. The package is actively maintained, has no known vulnerabilities, uses permissive MIT licensing, and solves a real problem—eliminating repetitive chart styling for Vietnamese stock market analysis. Low install friction and broad Python version support (3.10–3.14) make adoption straightforward. Best suited for teams automating investment reports, researchers embedding charts in documents, or developers building AI-agent-driven trading systems. Start with the built-in themes; custom branding and multi-layer indicator support justify the dependency footprint.
Install
vnstock-ezchart on PyPI
pip
pip install vnstock-ezchartuv
uv add vnstock-ezchartpoetry
poetry add vnstock-ezchartInstalling vnstock-ezchart
Before you install
Low friction: pure Python wheel with common data-science dependencies (numpy, pandas, matplotlib, seaborn). Active maintenance with recent commits and current Python version support (3.10–3.14). No known vulnerabilities.
License in practice
MIT license permits unrestricted use, modification, and distribution in both open-source and commercial projects with minimal attribution requirements.
Quickstart
pip install vnstock-ezchart
from vnstock_ezchart import Chart
Chart.set_theme(theme_name='vnstock', font_name='Inter', lang='vi')
# Then call Chart methods to render financial plots
Requires Python 3.10 or later; matplotlib and seaborn must be installed (included in dependencies).
Verify before relying
- Whether the 20+ chart types mentioned in the summary are all documented and production-ready
- Performance characteristics when rendering large datasets or multiple overlaid indicators
- Extent of AI Agent integration beyond Google-style docstrings (e.g., structured metadata or API contracts)
- Availability and completeness of English documentation (description is primarily Vietnamese)
Package facts
| License | MIT (permissive) |
| Python support | supports the current Python release (>=3.10) |
| Install friction | low — pure-Python wheel |
| Runtime dependencies | 9 — numpy, pandas, matplotlib, seaborn, requests, vnstock, openpyxl, cycler, mplfinance |
| Maintenance | actively maintained — 89 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 103,257/month — #12,819 on PyPI (30-day window, as of 2026-08-14) |
| Known vulnerabilities | none known (OSV.dev, checked 2026-08-14) |
Evidence: vnstock_ezchart-1.0.2-py3-none-any.whl
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