finvfamily

finvfamily / finshare

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专业的金融数据获取工具库 - A Professional Financial Data Fetching Toolkit for Python

www.meepoquant.com china-stock data-fetching dataframe eastmoney finance
15
2
89% credibility
Found Mar 03, 2026 at 16 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

A Python library that simplifies fetching historical price charts and live stock snapshots from multiple Chinese financial websites into uniform tables.

How It Works

1
🔍 Discover finshare

You hear about a handy tool that grabs stock prices and history from reliable places without hassle.

2
📥 Add the tool

You easily add this stock data helper to your computer so it's ready to use anytime.

3
🚀 Wake up the data grabber

You start the tool and simply name the stock you're curious about, like a favorite company.

4
📈 Pull past prices

You pick a time range, like last month, and get a neat list of daily ups and downs.

5
⚡ See live updates

You check the current price, volume, and trading buzz right as markets move.

6
📊 Gather for many stocks

You list several companies and collect all their info in one go for easy comparison.

🎉 Ready to explore

With clean, organized stock data in hand, you dive into trends and spot smart opportunities.

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Star Growth

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AI-Generated Review

What is finshare?

finshare is a Python toolkit for pulling Chinese stock market data—K-lines, real-time snapshots, adjusted prices—from free sources like Eastmoney, Tencent, Sina, TDX, and BaoStock. It delivers clean pandas DataFrames via a dead-simple API: grab a manager, pass a 6-digit code like '000001' with start/end dates, and get data without market suffixes or auth hassles. Unlike fineshare ai or fineshare voice changer tools, this handles professional financial services data for advisors and planners needing reliable feeds.

Why is it gaining traction?

Automatic failover across sources keeps fetches running even if one flakes, outputting uniform DataFrames so you swap providers seamlessly. Batch kline and snapshot pulls speed up bulk jobs, with front/back adjustment options out of the box—no scraping boilerplate. Devs dig the pip-install ease and production-tested stability from its quant platform roots.

Who should use this?

Quant devs backtesting A-share strategies, algo traders needing real-time snapshots for live signals, or analysts bulk-loading historical data for research reports. Ideal for Python scripters tired of pytdx/baostock quirks or building professional financial advisor dashboards.

Verdict

Grab it for quick Chinese market prototyping—solid API and docs make eval a breeze—but with 15 stars, beta status, and 0.9% credibility score, pair it with your own tests before production. Pairs well with pandas for instant analysis.

(178 words)

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