Steam API Endpoints - Hridaya Steam Market Tracker

Overview

Hridaya supports four distinct Steam Community Market API endpoints. Each serves a different purpose and returns different data structures.

Quick Reference

Endpoint	Auth Required	Update Frequency	Use Case
`priceoverview`	No	Seconds	Current prices and 24h volume
`itemordershistogram`	No	Seconds	Full order book depth
`itemordersactivity`	No	Seconds	Real-time trade feed
`pricehistory`	Yes	Hourly	Historical trend analysis

You can use multiple endpoints for the same item to get comprehensive market data. Simply add multiple entries with different apiid values.

priceoverview

Provides current market snapshot: lowest listing price, median sale price, and 24-hour trading volume.

When to Use

Monitor current market prices
Track price movements over time
Compare items by volume/liquidity
Build price alert systems
Simple portfolio valuation

Configuration

TRACKING_ITEMS:
  - market_hash_name: "AK-47 | Redline (Field-Tested)"
    appid: 730
    currency: 1
    country: 'US'
    language: 'english'
    polling-interval-in-seconds: 30
    apiid: 'priceoverview'

item_nameid

integer

Not required for this endpoint

Response Data

Returned fields (from dataClasses.py:PriceOverviewData):

success

boolean

Whether the API call succeeded

lowest_price

string

Current lowest listing price (formatted with currency symbol)Example: "$12.34", "€10.50"

median_price

string

Recent median sale price (formatted with currency symbol)Example: "$12.00"

volume

string

Number of sales in the last 24 hours (formatted with commas)Example: "1,234", "56"

Database Schema

Stored in table price_overview:

Column	Type	Description
`id`	INTEGER	Auto-incrementing row ID
`timestamp`	DATETIME	When this snapshot was taken (UTC)
`appid`	INTEGER	Steam app ID
`market_hash_name`	TEXT	Item name
`item_nameid`	INTEGER	Steam’s internal item ID (if available)
`currency`	TEXT	Currency code
`country`	TEXT	Country code
`language`	TEXT	Language
`lowest_price`	REAL	Cheapest current listing (numeric)
`median_price`	REAL	Median sale price (numeric)
`volume`	INTEGER	Sales in last 24h

Example Query

Get the latest price for an item:

SELECT timestamp, lowest_price, median_price, volume
FROM price_overview
WHERE market_hash_name = 'AK-47 | Redline (Field-Tested)'
ORDER BY timestamp DESC
LIMIT 1;

API Endpoint Details

URL: https://steamcommunity.com/market/priceoverview/ Method: GET Query Parameters (from steamAPIclient.py:fetch_price_overview):

appid - Application ID
market_hash_name - Item name (URL-encoded)
currency - Currency code
country - Country code
language - Language

itemordershistogram

Provides complete order book with all buy orders (bids) and sell orders (asks) at each price level. Think “market depth chart”.

When to Use

Analyze market liquidity
Calculate bid-ask spread
Find support/resistance levels
Detect market manipulation (spoofed orders)
Build order book visualizations
Algorithmic trading strategies

Configuration

TRACKING_ITEMS:
  - market_hash_name: "Dreams & Nightmares Case"
    appid: 730
    currency: 1
    country: 'US'
    language: 'english'
    polling-interval-in-seconds: 15
    apiid: 'itemordershistogram'
    item_nameid: 175985258  # REQUIRED

item_nameid

integer

required

Required for this endpoint. See Config Reference for how to find it.

Response Data

Returned fields (from dataClasses.py:OrdersHistogramData):

success

boolean | integer

Whether the API call succeeded (Steam returns 1 for true)

highest_buy_order

string

Best bid price (highest price buyers are willing to pay)

lowest_sell_order

string

Best ask price (lowest price sellers are willing to accept)

buy_order_count

integer

Total number of buy orders across all price levels

sell_order_count

integer

Total number of sell orders across all price levels

buy_order_table

array

Array of buy order entries. Each entry has:

price (string) - Price level
quantity (string) - Number of orders at this price

Example: [{"price": "12.50", "quantity": "15"}, {"price": "12.45", "quantity": "8"}]

sell_order_table

array

Array of sell order entries (same structure as buy_order_table)

buy_order_graph

array

Graph visualization data for buy orders (cumulative depth)

sell_order_graph

array

Graph visualization data for sell orders (cumulative depth)

Database Schema

Stored in table orders_histogram:

Column	Type	Description
`id`	INTEGER	Auto-incrementing row ID
`timestamp`	DATETIME	When this snapshot was taken (UTC)
`appid`	INTEGER	Steam app ID
`market_hash_name`	TEXT	Item name
`item_nameid`	INTEGER	Steam’s internal item ID
`currency`	TEXT	Currency code
`country`	TEXT	Country code
`language`	TEXT	Language
`buy_order_table`	TEXT	JSON array of buy orders
`sell_order_table`	TEXT	JSON array of sell orders
`buy_order_graph`	TEXT	JSON graph data
`sell_order_graph`	TEXT	JSON graph data
`buy_order_count`	INTEGER	Total buy orders
`sell_order_count`	INTEGER	Total sell orders
`highest_buy_order`	REAL	Best bid
`lowest_sell_order`	REAL	Best ask

Example Query

Calculate current bid-ask spread:

SELECT 
  timestamp,
  highest_buy_order,
  lowest_sell_order,
  (lowest_sell_order - highest_buy_order) AS spread,
  ((lowest_sell_order - highest_buy_order) / highest_buy_order * 100) AS spread_pct
FROM orders_histogram
WHERE market_hash_name = 'AK-47 | Redline (Field-Tested)'
ORDER BY timestamp DESC
LIMIT 1;

Extract top buy orders using JSON:

SELECT 
  json_extract(buy_order_table, '$[0].price') AS top_bid_price,
  json_extract(buy_order_table, '$[0].quantity') AS top_bid_quantity
FROM orders_histogram
WHERE market_hash_name = 'AK-47 | Redline (Field-Tested)'
ORDER BY timestamp DESC
LIMIT 1;

API Endpoint Details

URL: https://steamcommunity.com/market/itemordershistogram Method: GET Query Parameters (from steamAPIclient.py:fetch_orders_histogram):

norender - Set to 1 (returns JSON instead of HTML)
appid - Application ID
item_nameid - Numeric item ID
currency - Currency code
country - Country code
language - Language

itemordersactivity

Provides real-time feed of recent market activity: purchases and new listings as they happen.

When to Use

Monitor trading velocity
Detect price trends from actual trades
Track market sentiment (buying vs selling pressure)
Build activity notifications
Analyze trading patterns

Configuration

TRACKING_ITEMS:
  - market_hash_name: "Revolution Case"
    appid: 730
    currency: 1
    country: 'US'
    language: 'english'
    polling-interval-in-seconds: 8
    apiid: 'itemordersactivity'
    item_nameid: 175995756  # REQUIRED

item_nameid

integer

required

Required for this endpoint. See Config Reference for how to find it.

This is the most rate-limit-sensitive endpoint. Steam returns HTML strings that require parsing. Recommended minimum polling interval: 8 seconds.

Response Data

Returned fields (from dataClasses.py:OrdersActivityData):

success

boolean | integer

Whether the API call succeeded (Steam returns 1 for true)

timestamp

integer

Unix timestamp when Steam generated this response

activity

array

Array of HTML strings describing recent activityExample: ["+$0.85\n" + " at 16:23:45"]

parsed_activities

array

Array of structured activity entries (parsed from HTML). Each entry has:

price (string) - Trade price
currency (string) - ISO currency code (“USD”, “EUR”, etc.)
action (string) - Activity type (“Purchased”, “Listed”)
timestamp (datetime) - When the activity occurred
raw_html (string) - Original HTML string

Note: This field is populated by parseActivityHTML_utility.py after fetching.

Database Schema

Stored in table orders_activity:

Column	Type	Description
`id`	INTEGER	Auto-incrementing row ID
`timestamp`	DATETIME	When this snapshot was taken (UTC)
`appid`	INTEGER	Steam app ID
`market_hash_name`	TEXT	Item name
`item_nameid`	INTEGER	Steam’s internal item ID
`currency`	TEXT	Currency code
`country`	TEXT	Country code
`language`	TEXT	Language
`activity_raw`	TEXT	JSON array of raw HTML strings
`parsed_activities`	TEXT	JSON array of parsed activities
`activity_count`	INTEGER	Number of activities in snapshot
`steam_timestamp`	INTEGER	Unix timestamp from Steam

Example Query

Get recent trades:

SELECT timestamp, parsed_activities, activity_count
FROM orders_activity
WHERE market_hash_name = 'AK-47 | Redline (Field-Tested)'
ORDER BY timestamp DESC
LIMIT 10;

API Endpoint Details

URL: https://steamcommunity.com/market/itemordersactivity Method: GET Query Parameters (from steamAPIclient.py:fetch_orders_activity):

country - Country code
language - Language
currency - Currency code
item_nameid - Numeric item ID
two_factor - Two factor flag (default 0)

Response Format: JSON with text/html Content-Type (requires manual parsing)

pricehistory

Provides complete historical price data: hourly aggregated prices and volumes going back years. Like stock OHLC data.

When to Use

Long-term trend analysis
Volatility calculations
Seasonal pattern detection
Backtesting trading strategies
Portfolio historical valuation
Market research and reporting

Configuration

TRACKING_ITEMS:
  - market_hash_name: "AWP | Neo-Noir (Factory New)"
    appid: 730
    currency: 1
    country: 'US'
    language: 'english'
    polling-interval-in-seconds: 3600  # Hourly recommended
    apiid: 'pricehistory'

item_nameid

integer

Not required for this endpoint

This endpoint requires authentication. You must provide Steam session cookies in your .env file. See Authentication for setup instructions.

Historical data doesn’t change frequently. Use longer polling intervals (3600s / 1 hour) to conserve rate limits. The system fetches all available history on first request.

Response Data

Returned fields (from dataClasses.py:PriceHistoryData):

success

boolean

Whether the API call succeeded

price_prefix

string

Currency prefix symbol (e.g., "$")

price_suffix

string

Currency suffix symbol (e.g., "€")

prices

array

Array of price history data points. Each entry is a 3-element array:

[0] (string) - Date/time string (e.g., "Jul 02 2014 01: +0")
[1] (float) - Median price during this hour
[2] (string) - Trading volume during this hour

Example: [["Mar 03 2026 14: +0", 12.34, "156"], ["Mar 03 2026 15: +0", 12.50, "142"]]

Database Schema

Stored in table price_history:

Column	Type	Description
`id`	INTEGER	Auto-incrementing row ID
`time`	DATETIME	The hour this data point represents (UTC)
`appid`	INTEGER	Steam app ID
`market_hash_name`	TEXT	Item name
`item_nameid`	INTEGER	Steam’s internal item ID (if available)
`currency`	TEXT	Currency code
`country`	TEXT	Country code
`language`	TEXT	Language
`price`	REAL	Median price during this hour
`volume`	INTEGER	Number of sales during this hour
`fetched_at`	DATETIME	When we fetched this data

Example Queries

Daily average price over last 30 days:

SELECT 
  date(time) AS day,
  AVG(price) AS avg_price,
  SUM(volume) AS total_volume
FROM price_history
WHERE market_hash_name = 'AK-47 | Redline (Field-Tested)'
  AND time > datetime('now', '-30 days')
GROUP BY date(time)
ORDER BY day DESC;

Find price spikes (20% above average):

WITH avg_price AS (
  SELECT AVG(price) AS mean 
  FROM price_history
  WHERE market_hash_name = 'AK-47 | Redline (Field-Tested)'
)
SELECT time, price, volume
FROM price_history, avg_price
WHERE market_hash_name = 'AK-47 | Redline (Field-Tested)'
  AND price > mean * 1.2
ORDER BY time DESC;

API Endpoint Details

URL: https://steamcommunity.com/market/pricehistory Method: GET Authentication: Required - Steam session cookies Query Parameters (from steamAPIclient.py:fetch_price_history):

appid - Application ID
market_hash_name - Item name (URL-encoded)
currency - Currency code
country - Country code
language - Language

Required Cookies:

sessionid - Your Steam session ID
steamLoginSecure - Your Steam login token
browserid (optional) - Browser identifier
steamCountry (optional) - Steam country code

Required Headers:

User-Agent - Browser user agent string
Referer - Steam market listing page URL

Choosing the Right Endpoint

Decision Matrix

Need current prices? → priceoverview Need order book depth? → itemordershistogram Need real-time trades? → itemordersactivity Need historical trends? → pricehistory

Combining Endpoints

For comprehensive market coverage, track the same item with multiple endpoints:

TRACKING_ITEMS:
  # Same item, different endpoints
  - market_hash_name: "AK-47 | Redline (Field-Tested)"
    apiid: 'priceoverview'
    polling-interval-in-seconds: 60
    
  - market_hash_name: "AK-47 | Redline (Field-Tested)"
    apiid: 'itemordershistogram'
    item_nameid: 176582392
    polling-interval-in-seconds: 30
    
  - market_hash_name: "AK-47 | Redline (Field-Tested)"
    apiid: 'itemordersactivity'
    item_nameid: 176582392
    polling-interval-in-seconds: 15
    
  - market_hash_name: "AK-47 | Redline (Field-Tested)"
    apiid: 'pricehistory'
    polling-interval-in-seconds: 3600

Each endpoint consumes separate rate limit tokens. Make sure your total request load stays within limits.

Rate Limiting Considerations

Endpoint impact on rate limits (requests per 60s with example intervals):

Endpoint	Example Interval	Requests/60s
`priceoverview`	30s	2
`itemordershistogram`	15s	4
`itemordersactivity`	8s	7.5
`pricehistory`	3600s	0.017

Total: 13.5 requests per 60s (within limit of 15)

Next Steps

Authentication

Setup cookies for pricehistory endpoint

Config Reference

Complete parameter reference

Get Started

Configuration

Architecture

Guides

​Overview

​Quick Reference

​priceoverview

​When to Use

​Configuration

​Response Data

​Database Schema

​Example Query

​API Endpoint Details

​itemordershistogram

​When to Use

​Configuration

​Response Data

​Database Schema

​Example Query

​API Endpoint Details

​itemordersactivity

​When to Use

​Configuration

​Response Data

​Database Schema

​Example Query

​API Endpoint Details

​pricehistory

​When to Use

​Configuration

​Response Data

​Database Schema

​Example Queries

​API Endpoint Details

​Choosing the Right Endpoint

​Decision Matrix

​Combining Endpoints

​Rate Limiting Considerations

​Next Steps

Authentication

Config Reference

Build docs developers (and LLMs) love

Overview

Quick Reference

priceoverview

When to Use

Configuration

Response Data

Database Schema

Example Query

API Endpoint Details

itemordershistogram

When to Use

Configuration

Response Data

Database Schema

Example Query

API Endpoint Details

itemordersactivity

When to Use

Configuration

Response Data

Database Schema

Example Query

API Endpoint Details

pricehistory

When to Use

Configuration

Response Data

Database Schema

Example Queries

API Endpoint Details

Choosing the Right Endpoint

Decision Matrix

Combining Endpoints

Rate Limiting Considerations

Next Steps