# 🇯🇵 TSE Japan Stock Screener — Nikkei 225 Quotes (`nexgendata/tse-japan-stock-screener`) Actor Tokyo Stock Exchange (TSE) Japan screener API — Nikkei 225 / TOPIX live quotes, market cap (JPY), P/E, P/B, dividend yield, ROE, sector. Toyota, Sony, SoftBank, Keyence universe. Bloomberg Terminal / FactSet / Refinitiv Eikon alternative for hedge funds & quants. Pay-per-result. - **URL**: https://apify.com/nexgendata/tse-japan-stock-screener.md - **Developed by:** [NexGenData](https://apify.com/nexgendata) (community) - **Categories:** Business, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $250.00 / 1,000 tse stock records This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## 🇯🇵 TSE Japan Stock Screener — Nikkei 225 Quotes & Fundamentals **Real-time-ish prices, market cap, P/E, dividend yield, sector, and fundamentals for every major Japanese equity — Toyota (7203), Sony (6758), Mitsubishi UFJ (8306), SoftBank Group (9984), Keyence (6861), Fast Retailing (9983), and 600+ more across the Tokyo Stock Exchange.** If you're tracking Japanese markets for a global macro fund, building a screener for an Asia-focused PMS, running a quant strategy on the Nikkei 225, or stress-testing a portfolio against the second-largest equity market in Asia — this actor gives you a clean, structured feed without Bloomberg Terminal pricing ($24,000/year), Refinitiv (LSEG) data subscriptions, or hand-rolled scrapers that keep breaking when stockanalysis.com tweaks its HTML. ### What this actor returns For every stock, you get a flat JSON record with the fields you actually need to run analysis: - **Identifiers**: `symbol` (4-digit TSE code, e.g. `7203` for Toyota), `name`, `ticker_yahoo` (the `.T` suffix form for Yahoo Finance interop), `is_nikkei225` boolean flag - **Price & action**: `price_jpy`, `pct_change`, `previous_close_jpy`, `open_jpy`, `day_low_jpy`, `day_high_jpy`, `volume`, `avg_volume` - **Valuation**: `market_cap_jpy`, `market_cap_billion_jpy`, `market_cap_display` (human-readable like `37.97T`), `pe_ratio`, `forward_pe`, `pb_ratio`, `eps_jpy` - **Income & shareholder returns**: `revenue_ttm_jpy`, `net_income_jpy`, `dividend_jpy`, `dividend_yield_pct`, `ex_dividend_date`, `shares_outstanding` - **Range & technicals**: `week52_low_jpy`, `week52_high_jpy`, `beta`, `rsi`, `earnings_date` - **Classification**: `sector`, `industry` (e.g. "Auto Manufacturers", "Banks", "Semiconductors") - **Metadata**: `exchange` ("TSE"), `country` ("Japan"), `currency` ("JPY"), `stockanalysis_url`, `yahoo_finance_url`, `scraped_at` (ISO timestamp) Push results directly to BigQuery, Snowflake, Postgres, Google Sheets, or a Slack channel using Apify's native integrations — or just download the JSON / CSV / Excel dataset from the Apify dashboard. ### Why Japan, why now The Tokyo Stock Exchange is the third-largest equity market in the world by market capitalization (behind NYSE and Nasdaq) and the largest in Asia after surpassing Shanghai and Hong Kong on a free-float basis. The Nikkei 225 broke its 1989 all-time high in February 2024 — ending the longest secular bear market in modern financial history — and Japanese mega-caps like Sony, Tokyo Electron (8035), Recruit Holdings (6098), and Keyence have become structural growth stories for global allocators. But high-quality Japanese equity data is still locked behind: - **Bloomberg Terminal** — roughly $2,000 per user per month, useless for programmatic ingestion without expensive BPIPE add-ons - **Refinitiv / LSEG Workspace** — enterprise contracts, six-figure minimums - **JPX official data** — Japanese-language site, fragmented across PDFs and zip files, no clean JSON API - **Yahoo Finance Japan** — exists but rate-limits aggressively from non-Japanese IPs This actor solves the access problem. It scrapes server-rendered HTML from `stockanalysis.com/list/tokyo-stock-exchange/` (which mirrors TSE data plus computed fundamentals), runs through Apify proxies to dodge geo-rate-limits, and structures everything into one cohesive JSON schema you can plumb into a real workflow. ### Input parameters - **`index`** — `NIKKEI` (Nikkei 225 constituents only), `TOPIX` (large/mid-cap TSE Prime), or `TSE-all` (every name on stockanalysis.com's TSE list, ~600+ stocks). Default: `NIKKEI`. - **`limit`** — Max stocks to return. Default: 50. Set to 225 for full Nikkei, 500+ for broad TSE coverage. - **`min_market_cap_jpy_billion`** — Filter to stocks above this market cap (in billions JPY). 1,000 ≈ 1 trillion JPY ≈ large-cap. 10,000 ≈ 10 trillion JPY ≈ mega-cap. - **`sector`** — Substring filter on sector/industry/name. Examples: `"auto"` (Toyota, Honda, Nissan), `"bank"`, `"semiconductor"`, `"pharma"`, `"retail"`. - **`enrich_fundamentals`** — `true` to fetch P/E, dividend yield, sector, 52-week range, etc. from each stock's detail page. Roughly doubles runtime. Required if you want to filter by sector. - **`proxyConfiguration`** — Standard Apify proxy. Defaults to datacenter (works fine); switch to residential if you hit rate limits. ### Use cases 1. **Macro overlay dashboard** — pull the top 50 Nikkei constituents nightly, push to a Google Sheet, feed a daily dashboard that tracks JPY-hedged vs unhedged Japan exposure. Pair with the **[Eastmoney China Stock Screener](https://apify.com/nexgendata/eastmoney-china-stock-screener)** and **[KOSPI Stock Screener](https://apify.com/nexgendata/kospi-stock-screener)** for full North Asia coverage. 2. **Sector rotation signals** — enable `enrich_fundamentals`, filter `sector="bank"`, track Japanese mega-bank earnings cycle (8306 / 8316 / 8411). Compare to **[HKEX Hang Seng Stock Screener](https://apify.com/nexgendata/hkex-hang-seng-stock-screener)** Chinese-mainland-listed-in-HK banks for cross-strait financials read-through. 3. **Quant factor research** — pull TSE-all with full fundamentals, compute size / value / momentum factors, backtest a Japan-only long-short portfolio. The structured JSON output drops cleanly into pandas / polars / kdb. 4. **Corporate intelligence** — track competitor market cap moves (e.g. Toyota vs Honda vs Nissan), monitor activist target candidates (low P/B, high net cash), watch index reshuffle candidates. 5. **Buy-side research automation** — feed your idea-generation pipeline. Combine with the **[TWSE Taiwan Stock Screener](https://apify.com/nexgendata/twse-stock-screener)** for full APAC-ex-China semiconductor supply chain coverage (Tokyo Electron, Advantest, TSMC, ASE Technology in one view). ### Pricing This actor uses **pay-per-event** billing — no platform-credit time burn, no overage anxiety: - **$0.01** when the actor starts (one-time) - **$0.25** per stock record returned A typical 50-stock Nikkei run costs **$12.51**. A full 225-stock Nikkei run costs **$56.26**. A 500-stock broad TSE sweep with full fundamentals costs **$125.01**. Way cheaper than a Bloomberg seat, and you actually own the data. ### How the data flows ```` stockanalysis.com/list/tokyo-stock-exchange/ (server-rendered HTML, ~500 stocks/page) │ ▼ Listing parser ─► symbol, name, price, market cap, % change, revenue TTM │ ▼ (optional) Per-stock /quote/tyo/{sym}/ ─► P/E, EPS, dividend yield, shares out, 52-week range, sector │ ▼ Index / sector / market-cap filters │ ▼ Apify dataset ─► JSON / CSV / Excel / API / webhook ```` The Nikkei 225 constituency flag is maintained as a curated list of the most prominent and liquid index members inside the actor. It covers all the names institutional users will actually search for (Toyota, Sony, SoftBank Group, Mitsubishi UFJ, Keyence, Fast Retailing, Recruit Holdings, Tokyo Electron, Shin-Etsu Chemical, Daiichi Sankyo, etc.). For research-grade index replication, you should still cross-reference the official JPX-Nikkei index methodology PDF. ### Reliability notes - **Data freshness**: stockanalysis.com refreshes during TSE trading hours (09:00–15:00 JST). Outside trading hours you'll get the previous session's close. - **Geo / rate limits**: Apify proxy handles this. If you run hundreds of full-TSE sweeps per day, switch to residential proxy via the `proxyConfiguration` input. - **Schema stability**: stockanalysis.com is more stable than JPX or Yahoo Japan, but if their HTML changes the parser may need a small patch. This actor is maintained. - **Holiday handling**: Japanese markets observe ~16 public holidays per year (more than the US). On holidays you'll get static prior-session data. ### Sister actors — full APAC equity coverage This actor is part of NexGenData's APAC equity screener fleet. For complete coverage of the region's investable equity markets, pair it with: - **[Eastmoney China Stock Screener](https://apify.com/nexgendata/eastmoney-china-stock-screener)** — Shanghai (SSE) + Shenzhen (SZSE) A-shares, ~5,000 mainland Chinese listings with quotes, fundamentals, and sector classification. - **[KOSPI Stock Screener](https://apify.com/nexgendata/kospi-stock-screener)** — Korean equities (KOSPI + KOSDAQ), Samsung Electronics, SK Hynix, Hyundai, LG Energy Solution, with KRW-denominated market cap and fundamentals. - **[TWSE Taiwan Stock Screener](https://apify.com/nexgendata/twse-stock-screener)** — Taiwan Stock Exchange listings, TSMC, Foxconn (Hon Hai), MediaTek, plus the rest of the global semiconductor supply chain. - **[HKEX Hang Seng Stock Screener](https://apify.com/nexgendata/hkex-hang-seng-stock-screener)** — Hong Kong listings, Hang Seng + Hang Seng Tech constituents, Tencent, Alibaba H-shares, HSBC HK, AIA. Running all five gives you institutional-grade coverage of every major APAC market for less than a single Bloomberg seat per quarter. ### About NexGenData NexGenData operates 100+ Apify actors covering equity markets, alternative data, corporate intelligence, and developer tooling. Our APAC equity fleet is built on the same hedge-fund-grade pattern — clean schemas, reliable data sources, predictable pricing, no surprise rate limits. Explore the full fleet and unlock institutional-grade alt-data at consumer pricing: **[apify.com/nexgendata](https://apify.com/nexgendata?fpr=2ayu9b)** (Affiliate link — you pay the same, NexGenData gets a small revenue share that funds keeping the actors maintained.) # Actor input Schema ## `index` (type: `string`): Which Japanese market scope to screen: NIKKEI (Nikkei 225 blue-chip constituents only, e.g. Toyota 7203, Sony 6758, Fast Retailing 9983), TOPIX (top-cap TSE Prime, similar mega-cap coverage), or TSE-all (entire Tokyo Stock Exchange, ~600+ names including mid- and small-cap). ## `limit` (type: `integer`): Maximum number of Japanese stocks to return. Stocks are returned in descending market-cap order. Use 10 for a quick smoke test, 225 for the full Nikkei 225, 500+ for broad TSE coverage. ## `min_market_cap_jpy_billion` (type: `integer`): Filter to stocks with market cap above this threshold, in BILLIONS of JPY. Examples: 1000 = 1 trillion JPY (roughly large-cap), 10000 = 10 trillion JPY (mega-cap like Toyota, Sony, Mitsubishi UFJ). Leave at 0 for no filter. ## `sector` (type: `string`): Optional case-insensitive substring filter applied to sector, industry, and company name. Examples: 'auto' (Toyota, Honda, Nissan), 'bank' (Mitsubishi UFJ, Sumitomo Mitsui), 'semiconductor', 'technology', 'pharma'. Leave blank for no filter. Note: sector matching requires enrich_fundamentals=true. ## `enrich_fundamentals` (type: `boolean`): If true, fetch each stock's detail page on stockanalysis.com to extract P/E ratio, EPS, dividend yield, shares outstanding, beta, RSI, 52-week range, sector and industry classification. Adds ~1 HTTP request per stock and roughly doubles runtime. Required if you want to filter by sector. ## `proxyConfiguration` (type: `object`): Apify proxy configuration. Defaults to Apify datacenter proxy for reliable access to stockanalysis.com. Use RESIDENTIAL group if you hit rate limits. ## Actor input object example ```json { "index": "NIKKEI", "limit": 50, "min_market_cap_jpy_billion": 0, "enrich_fundamentals": false, "proxyConfiguration": { "useApifyProxy": true } } ```` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "index": "NIKKEI", "limit": 50, "min_market_cap_jpy_billion": 0, "sector": "", "enrich_fundamentals": false, "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/tse-japan-stock-screener").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "index": "NIKKEI", "limit": 50, "min_market_cap_jpy_billion": 0, "sector": "", "enrich_fundamentals": False, "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("nexgendata/tse-japan-stock-screener").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "index": "NIKKEI", "limit": 50, "min_market_cap_jpy_billion": 0, "sector": "", "enrich_fundamentals": false, "proxyConfiguration": { "useApifyProxy": true } }' | apify call nexgendata/tse-japan-stock-screener --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgendata/tse-japan-stock-screener", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "🇯🇵 TSE Japan Stock Screener — Nikkei 225 Quotes", "description": "Tokyo Stock Exchange (TSE) Japan screener API — Nikkei 225 / TOPIX live quotes, market cap (JPY), P/E, P/B, dividend yield, ROE, sector. Toyota, Sony, SoftBank, Keyence universe. Bloomberg Terminal / FactSet / Refinitiv Eikon alternative for hedge funds & quants. Pay-per-result.", "version": "0.0", "x-build-id": "bQDA5ePNVaBKCBJFw" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~tse-japan-stock-screener/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-tse-japan-stock-screener", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~tse-japan-stock-screener/runs": { "post": { "operationId": "runs-sync-nexgendata-tse-japan-stock-screener", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~tse-japan-stock-screener/run-sync": { "post": { "operationId": "run-sync-nexgendata-tse-japan-stock-screener", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "index": { "title": "Index / Market", "enum": [ "NIKKEI", "TOPIX", "TSE-all" ], "type": "string", "description": "Which Japanese market scope to screen: NIKKEI (Nikkei 225 blue-chip constituents only, e.g. Toyota 7203, Sony 6758, Fast Retailing 9983), TOPIX (top-cap TSE Prime, similar mega-cap coverage), or TSE-all (entire Tokyo Stock Exchange, ~600+ names including mid- and small-cap).", "default": "NIKKEI" }, "limit": { "title": "Limit (stocks returned)", "minimum": 1, "maximum": 2000, "type": "integer", "description": "Maximum number of Japanese stocks to return. Stocks are returned in descending market-cap order. Use 10 for a quick smoke test, 225 for the full Nikkei 225, 500+ for broad TSE coverage.", "default": 50 }, "min_market_cap_jpy_billion": { "title": "Min market cap (billion JPY)", "minimum": 0, "maximum": 100000000, "type": "integer", "description": "Filter to stocks with market cap above this threshold, in BILLIONS of JPY. Examples: 1000 = 1 trillion JPY (roughly large-cap), 10000 = 10 trillion JPY (mega-cap like Toyota, Sony, Mitsubishi UFJ). Leave at 0 for no filter.", "default": 0 }, "sector": { "title": "Sector / industry / name keyword", "type": "string", "description": "Optional case-insensitive substring filter applied to sector, industry, and company name. Examples: 'auto' (Toyota, Honda, Nissan), 'bank' (Mitsubishi UFJ, Sumitomo Mitsui), 'semiconductor', 'technology', 'pharma'. Leave blank for no filter. Note: sector matching requires enrich_fundamentals=true." }, "enrich_fundamentals": { "title": "Enrich with fundamentals (slower)", "type": "boolean", "description": "If true, fetch each stock's detail page on stockanalysis.com to extract P/E ratio, EPS, dividend yield, shares outstanding, beta, RSI, 52-week range, sector and industry classification. Adds ~1 HTTP request per stock and roughly doubles runtime. Required if you want to filter by sector.", "default": false }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Apify proxy configuration. Defaults to Apify datacenter proxy for reliable access to stockanalysis.com. Use RESIDENTIAL group if you hit rate limits.", "default": { "useApifyProxy": true } } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```