Tutorials & guides

Three options: call an HTTP API directly, install a data SDK, or scrape pages. Start with the first — no signup, the least code, and the price you get is live; below are runnable samples, trade-offs, and when not to use each.

MCP lets your AI Agent fetch real data instead of answering from memory. Set it up once — paste `https://api.ashareapi.com/mcp`; free tools need no key at all.

Configure MCP once and the AI Agent fetches quotes, financials and money flow itself in chat; backtesting and adjudication stay with you — here is the full flow with copy-paste code.

Four options: call an HTTP API directly, Tushare, AkShare, or scrape pages. Start with the first — it returns institution, hot-money and active-seat boards in one call (other routes usually give only flat detail rows). Below: runnable code and when not to use each.

The official SDK is live: `pip install ashareapi`. Five endpoints need no key, results come back as pandas DataFrames (plain `list[dict]` without pandas), symbol formats are forgiving, and 5 exception types tell you exactly what to do.

The official Node SDK is live: `npm install ashareapi`. Five endpoints need no key, it has zero runtime dependencies (native `fetch`), ships full TypeScript types, returns arrays of objects, accepts forgiving symbol formats, and 5 exception types tell you exactly what to do.

Mood is not a feeling — it is numbers: breadth, limit-up counts, turnover, style rotation. Three free endpoints are enough to read "how hot is the market today". Code and caveats below.

Sectors reveal direction earlier than single stocks: rankings find strength, valuation percentiles judge price, supply chains show the logic. Three endpoints make one sector check-up — code below.

Avoiding landmines beats picking winners: profits without cash, surging holder counts, large lock-up expiries — all visible in public data through four endpoints. This tutorial identifies risks only; it makes no recommendations.

AkShare wins on breadth; we win on not having to maintain it yourself. If you already use AkShare and are tired of "upstream redesign → broken function", migration is three changes: code format, call style, field names. Below is the mapping and runnable code — and the parts that do not migrate.

Two things convertible-bond holders fear most: missing a redemption announcement (the premium vanishes overnight) and buying at a high premium. Both are visible up front in one `/v1/bond` call — below is the screening and warning code.

Money flow is not a price predictor — it is a thermometer for participation and the direction of chips. One `/v1/fund` request returns main-capital inflow (today / 5 / 10 / 20-day) + market rank + top-trader detail. The hard part is reading it; code and four common misreadings below.

Factor screening turns financial and market metrics into conditions and filters the whole market. This guide covers three things: how to write the expression, how to read the result, and why you must run a data health check afterwards (otherwise it is easy to mistake an outlier for an opportunity).

The previous guide covered how to screen; this one covers how to write conditions: expression structure, operators, unit traps, and a lookup-ready 85-factor dictionary. Written to be copied and run.

Do not want to write screening conditions yourself? The API ships 22 ready-made strategies (called `preset` in the interface): low PE, high dividend, high ROE, growth, main-capital inflow and more — tweak and run. This guide walks them by category: what each screens, who it suits, and what the output looks like — with live results from five of them.

The previous three guides covered syntax, factors and ready-made strategies. This is the full walkthrough: write a four-condition value screen, run it, then investigate the top result in depth to show how a "looks like free money" value is verified as unusable step by step.

A block trade is a large off-orderbook transfer agreed between two parties. It never shows on the intraday chart, yet it often reveals intent before price moves. This guide covers: how to read the fields, what the discount rate means, and how to scan in bulk with Python (with live 2026-09-29 data).

Holder count is the most direct public signal of "whose hands are the chips in": a falling count = concentration in fewer hands (often positive), a surging count = dispersion (retail crowding in). This guide covers the three tables, the fields, and a real case.

With raw K-lines, indicators are easy to compute yourself - no expensive tools needed. This guide uses the free endpooint for forward-adjusted daily bars and writes MA / MACD / RSI / KDJ / BOLL in pure Python + pandas, no TA-Lib.

Market breadth (advancing vs declining) is the most direct way to tell whether "today was a broad rally or a split" — it reflects the true sentiment of the whole market better than a single index. This guide uses a free endpoint, covering how to read temperature, track several days, and spot a turning point.

Getting "what is this stock worth right now" takes one GET: `/v1/quote` is free, needs no Key and no signup, and returns the last 30 trading days of OHLC plus volume/value/turnover. `data[0]` is the most recent day.