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Overview

The orders_activity table stores snapshots of recent trade activity - a real-time feed of actual purchases and new listings as they happen on the Steam Market. Data Source: itemordersactivity API endpoint Update Frequency: Real-time (seconds) Use Case: Monitor trading velocity, detect price movements, track market sentiment

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Table Schema

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id
INTEGER
required
Auto-incrementing primary key for each record
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timestamp
DATETIME
default:"CURRENT_TIMESTAMP"
When this snapshot was taken (UTC)
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appid
INTEGER
required
Steam application ID (730 for CS2, 570 for Dota 2, etc.)
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market_hash_name
TEXT
required
Exact Steam market name
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item_nameid
INTEGER
required
Steam’s internal numeric item ID (required for this endpoint)
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currency
TEXT
required
ISO 4217 currency code (USD, EUR, GBP, etc.)
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country
TEXT
required
Two-letter country code used for the request
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language
TEXT
required
Language used for the request
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activity_raw
TEXT
JSON array of raw HTML activity strings from Steam’s APIExample:
[
  "<div>+3 at $5.25</div>",
  "<div>-1 at $5.30</div>"
]
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parsed_activities
TEXT
JSON array of parsed activity objects with structured dataEach object contains:
  • price (string) - The transaction price
  • action (string) - Type of activity (“buy”, “sell”, “listing”)
  • timestamp (string) - When the activity occurred (ISO format)
Example:
[
  {
    "price": "$5.25",
    "action": "buy",
    "timestamp": "2024-03-03T12:34:56Z"
  }
]
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activity_count
INTEGER
Number of activities in this snapshot
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steam_timestamp
INTEGER
required
Unix timestamp from Steam’s response indicating when the activity data was generated

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Indexes

-- Fast lookup for latest activity
CREATE INDEX idx_activity_item_time
  ON orders_activity(market_hash_name, timestamp DESC);

-- Time-based queries
CREATE INDEX idx_activity_timestamp
  ON orders_activity(timestamp DESC);

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Example Queries

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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;

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Track Activity Volume Over Time

SELECT 
    strftime('%Y-%m-%d %H:00', timestamp) AS hour,
    SUM(activity_count) AS total_activities,
    COUNT(*) AS snapshots_captured
FROM orders_activity
WHERE market_hash_name = 'AK-47 | Redline (Field-Tested)'
  AND timestamp > datetime('now', '-24 hours')
GROUP BY strftime('%Y-%m-%d %H:00', timestamp)
ORDER BY hour DESC;

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Extract Individual Activities from JSON

SELECT 
    timestamp,
    json_each.value ->> '$.price' AS trade_price,
    json_each.value ->> '$.action' AS trade_action,
    json_each.value ->> '$.timestamp' AS trade_time
FROM orders_activity,
     json_each(parsed_activities)
WHERE market_hash_name = 'AK-47 | Redline (Field-Tested)'
  AND id = (SELECT MAX(id) FROM orders_activity WHERE market_hash_name = 'AK-47 | Redline (Field-Tested)')
ORDER BY trade_time DESC;

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Count Activities by Type

SELECT 
    date(timestamp) AS day,
    json_each.value ->> '$.action' AS action_type,
    COUNT(*) AS occurrences
FROM orders_activity,
     json_each(parsed_activities)
WHERE market_hash_name = 'AK-47 | Redline (Field-Tested)'
  AND timestamp > datetime('now', '-7 days')
GROUP BY date(timestamp), action_type
ORDER BY day DESC, occurrences DESC;

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Find Most Active Trading Periods

SELECT 
    strftime('%H', timestamp) AS hour_of_day,
    AVG(activity_count) AS avg_activity,
    SUM(activity_count) AS total_activity
FROM orders_activity
WHERE market_hash_name = 'AK-47 | Redline (Field-Tested)'
  AND timestamp > datetime('now', '-30 days')
GROUP BY strftime('%H', timestamp)
ORDER BY avg_activity DESC;

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JSON Structure Examples

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parsed_activities Format

[
  {
    "price": "$5.25",
    "action": "buy",
    "timestamp": "2024-03-03T12:34:56Z"
  },
  {
    "price": "$5.30",
    "action": "sell",
    "timestamp": "2024-03-03T12:35:12Z"
  },
  {
    "price": "$5.28",
    "action": "listing",
    "timestamp": "2024-03-03T12:35:45Z"
  }
]

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activity_raw Format

Raw HTML strings from Steam’s API (for reference): 
[
  "<div class='market_activity_block'>+3 at $5.25</div>",
  "<div class='market_activity_block'>-1 at $5.30</div>"
]

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Data Flow

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Activity Types

The action field in parsed_activities can contain:
  • buy - Item purchased from a listing
  • sell - New listing created
  • listing - Listing price updated
Steam’s activity feed format may vary by region and language. The raw HTML is preserved in activity_raw for custom parsing if needed.

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Working with Activity Data

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Python Example: Parse Activities

import sqlite3
import json

conn = sqlite3.connect('data/market_data.db')
cursor = conn.cursor()

cursor.execute("""
    SELECT timestamp, parsed_activities
    FROM orders_activity
    WHERE market_hash_name = 'AK-47 | Redline (Field-Tested)'
    ORDER BY timestamp DESC
    LIMIT 1
""")

row = cursor.fetchone()
if row:
    timestamp, activities_json = row
    activities = json.loads(activities_json)
    
    for activity in activities:
        print(f"{activity['action']} at {activity['price']} - {activity['timestamp']}")

conn.close()

orders_histogram

Order book depth and bid-ask spreads

price_overview

Current market prices and volumes

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