# Djinni.co Tech Jobs Scraper — Salary, English Level, Remote (`blackfalcondata/djinni-scraper`) Actor
Scrape djinni.co — Ukraine and Eastern Europe's largest IT job board — for structured tech listings with salary range, English level, remote flags, and experience filters. Incremental mode tracks new and changed jobs across runs via a stable stateKey.
- **URL**: https://apify.com/blackfalcondata/djinni-scraper.md
- **Developed by:** [Black Falcon Data](https://apify.com/blackfalcondata) (community)
- **Categories:** Jobs, Lead generation, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
from $2.00 / 1,000 results
This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
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
### What does Djinni.co Tech Jobs Scraper do?
Djinni.co Tech Jobs Scraper extracts structured job data from [djinni.co](https://djinni.co) — including salary data, apply URLs, company metadata, full descriptions, and remote-work indicators. It supports keyword search, location filters, and controllable result limits, so you can run the same query consistently over time. The actor also offers detail enrichment (full descriptions and company metadata) where the source provides them.
**New to Apify?** [Sign up free](https://console.apify.com/sign-up?fpr=1h3gvi) and use the included $5 monthly platform credit to test this actor.
### Key features
- **♻️ Incremental mode** — recurring runs emit only NEW / UPDATED / REAPPEARED records — UNCHANGED and EXPIRED are opt-in. First run builds the baseline; subsequent runs emit and charge only for the diff. Pair with notifications for daily "new jobs" alerts to your hiring team. Saves 80–95% on daily monitoring.
- **🔔 Notifications** — Telegram, Slack, Discord, WhatsApp Cloud API, generic webhook — out of the box. Pair with incremental + `notifyOnlyChanges` for daily "new Djinni jobs" pings to your hiring channel.
- **🔗 Paste-mode** — paste any djinni.co URL straight from your browser — single-job pages, search-results URLs, or category SEO URLs. Build the search you want in the UI, copy the URL, paste it here.
- **🎯 Batch searches** — batch `["python developer", "data engineer", "ML engineer"]` in one run — one dedup state across all searches, single dataset, one Actor-Start charge instead of N.
- **📧 Email + phone extraction** — every record carries `extractedEmails[]` and `extractedPhones[]` regex-pulled from the description — direct-outreach lists with no extra processing step.
- **🔗 URL + social-profile extraction** — every record carries `extractedUrls[]` and structured `socialProfiles { linkedin, twitter, github, … }` parsed from the description — useful when employers drop their careers page or recruiter LinkedIn in-line.
- **📦 Compact mode** — AI-agent and MCP-friendly compact payloads with core fields only — pipe straight into your ATS, salary-benchmarking tool, or LLM context without parsing extras.
- **✂️ Description truncation** — cap description length with `descriptionMaxLength` to control LLM prompt cost and dataset size — set 0 for full descriptions, or any char-limit to trim.
- **📤 Export anywhere** — Download the dataset as JSON, CSV, or Excel from the Apify Console, or stream live via the Apify API and integrations (Make, Zapier, Google Sheets, n8n, …).
- **💰 Structured salary** — salary parsed into structured `salaryMin` / `salaryMax` / `salaryCurrency` / period — no string parsing on your side. Includes `salaryHidden` flag when the source filtered against a bracket but the listing itself doesn't disclose.
### What data can you extract from djinni.co?
Each result includes Core listing fields (`jobId`, `jobKey`, `title`, `location`, `salaryText`, `salaryMin`, `salaryMax`, and `salaryCurrency`, and more), detail fields when enrichment is enabled (`description`, `descriptionText`, `descriptionHtml`, `descriptionMarkdown`, and `descriptionLength`), apply information (`directApply`), and company metadata (`company`, `companyLogo`, and `companyUrl`). In standard mode, all fields are always present — unavailable data points are returned as `null`, never omitted. In compact mode, only core fields are returned.
Enable detail enrichment in the input to get richer fields such as full descriptions and company metadata where the source provides them.
### Input
The main inputs are a search keyword, an optional location filter, and a result limit. Additional filters and options are available in the input schema.
Key parameters:
- **`query`** — Keyword(s) to search for (e.g. "python", "java", "devops"). Use a JSON array ["python","go"] for multi-query. Leave empty to browse all tech jobs.
- **`location`** — City, country, or region. Use a JSON array for multi-location. Applied as a post-fetch filter against the listing's location text.
- **`startUrls`** — Direct djinni.co search or job detail URLs (e.g. https://djinni.co/jobs/keyword-python/).
- **`experienceLevel`** — Filter to listings requesting exactly N years of experience. Use a JSON array like ["1","3"] for multi-select. Applied post-fetch.
- **`englishLevel`** — Filter by required English level (A1, A2, B1, B2, C1, C2). Use a JSON array for multi-select. Applied post-fetch.
- **`isRemote`** — Restrict to full-remote listings (drops office and hybrid roles). Leave unchecked to return all. (default: `false`)
- **`salaryFrom`** — Drop listings whose published salary range is below this amount. 0 = no minimum. (default: `0`)
- **`salaryTo`** — Drop listings whose published salary range exceeds this amount. 0 = no maximum. (default: `0`)
- **`maxResults`** — Maximum total job listings to return (0 = unlimited). Primary cost control — Apify charges per emitted record. (default: `25`)
- **`maxPages`** — Maximum SERP pages to scrape per source. Defensive bound — maxResults is the primary cap. (default: `5`)
- **`includeKeywords`** — Require at least one of these keywords in title/description. Example: {"keywords":["react","node"],"matchTitle":true,"matchDescription":true}.
- **`excludeKeywords`** — Exclude jobs containing any of these keywords. Same config shape as includeKeywords.
- ...and 29 more parameters
### Input examples
**Basic search** — Keyword-driven search with a result cap.
→ Full payload per result — all standard fields populated where the source provides them.
```json
{
"query": "python",
"maxResults": 50
}
````
**Incremental tracking** — Only emit jobs that changed since the previous run with this `stateKey`.
→ First run builds the baseline state. Subsequent runs emit only records that are new or whose tracked content changed. Set `emitUnchanged: true` to include unchanged records as well.
```json
{
"query": "python",
"maxResults": 200,
"incrementalMode": true,
"stateKey": "python-tracker"
}
```
**Compact filtered output** — Combine filters with compact mode for a lightweight AI-agent or MCP data source.
→ Core fields only — ideal for piping into LLMs or downstream tools without token overhead.
```json
{
"query": "python",
"experienceLevel": "1",
"maxResults": 50,
"compact": true
}
```
### Output
Each run produces a dataset of structured job records. Results can be downloaded as JSON, CSV, or Excel from the Dataset tab in Apify Console.
### Example job record
```json
{
"jobId": "3c64f699b91922d9dbec45db9d902fd64fe3feaf5dbabe273e0fcdada7ea33a5",
"jobKey": "820617",
"title": "Senior Python Engineer (AI / Automation)",
"company": "Oxigen",
"companyLogo": "https://p.djinni.co/50/e25dae07f58da9ba8e802b0935edd6/Social_Media_On_Dark_400.png",
"companyUrl": "https://0xigen.com/",
"location": "Poland",
"description": "About the project\n \nUS-founded media company operating email newsletters at scale – millions of subscribers across finance, health, and business verticals. Small engineering team, flat structure, dire...",
"descriptionText": "About the project\n \nUS-founded media company operating email newsletters at scale – millions of subscribers across finance, health, and business verticals. Small engineering team, flat structure, dire...",
"descriptionHtml": "\n About the project
US-founded media company operating email newsletters at scale – millions of subscribers across finance, health, and business vertical...",
"descriptionMarkdown": "**About the project**\n\nUS-founded media company operating email newsletters at scale – millions of subscribers across finance, health, and business verticals. Small engineering team, flat structure, d...",
"descriptionLength": 1840,
"salaryText": "$$$$",
"salaryMin": null,
"salaryMax": null,
"salaryCurrency": "USD",
"salaryPeriod": null,
"employmentType": "FULL_TIME",
"industry": "media",
"category": "Python",
"experienceMonths": 72,
"experienceYears": 6,
"englishLevel": "C1",
"isRemote": false,
"remoteText": "Office Work",
"jobLocationType": null,
"directApply": true,
"postedAt": "2026-05-16T20:31:21.893242",
"postedAtRaw": "20:31 16.05.2026",
"validThrough": "2026-06-15T20:31:21.893242",
"canonicalUrl": "https://djinni.co/jobs/820617-senior-python-engineer-ai-automation/",
"sourceUrl": "https://djinni.co/jobs/820617-senior-python-engineer-ai-automation/",
"sourceDomain": "djinni.co",
"sourceCountry": "UA",
"searchQuery": "python",
"searchUrl": "https://djinni.co/jobs/keyword-python/",
"isSponsored": false,
"fetchedAt": "2026-05-16T20:03:24.649Z",
"detailFetched": true,
"contentQuality": "full",
"contentHash": "991bc78a6f011a7c5554070df3cd73823bcc3a510721a33505699c4dac254127",
"extractedEmails": [],
"extractedPhones": [],
"extractedUrls": [
"https://0xigen.com",
"https://djinni.nolt.io/trending",
"https://p.djinni.co/1c/67b58d21cc46ea54da35f8b4a2a12b/social-banner__3_.png",
"https://p.djinni.co/50/e25dae07f58da9ba8e802b0935edd6/Social_Media_On_Dark_400.png",
"https://px.ads.linkedin.com/collect/?pid=3623514&fmt=gif",
"https://snap.licdn.com/li.lms-analytics/insight.min.js"
],
"socialProfiles": {
"linkedin": "https://px.ads.linkedin.com/collect/?pid=3623514&fmt=gif",
"twitter": null,
"instagram": null,
"facebook": null,
"youtube": null,
"tiktok": null,
"github": null,
"xing": null,
"bluesky": null,
"threads": null,
"mastodon": null
},
"isRepost": null,
"repostOfId": null,
"repostDetectedAt": null,
"changeType": null,
"trackedHash": null,
"firstSeenAt": null,
"lastSeenAt": null,
"previousSeenAt": null,
"expiredAt": null,
"stateKey": null
}
```
### Incremental fields
When `incremental: true`, each record also carries:
- `changeType` — one of `NEW`, `UPDATED`, `UNCHANGED`, `REAPPEARED`, `EXPIRED`. Default output covers `NEW` / `UPDATED` / `REAPPEARED`; set `emitUnchanged: true` or `emitExpired: true` to opt into the others.
- `firstSeenAt`, `lastSeenAt` — ISO-8601 timestamps tracking the listing across runs.
- `isRepost`, `repostOfId`, `repostDetectedAt` — populated when a new listing matches the tracked content of a previously expired one. Set `skipReposts: true` to drop detected reposts from the output.
### How to scrape djinni.co
1. Go to [Djinni.co Tech Jobs Scraper](https://apify.com/blackfalcondata/djinni-scraper?fpr=1h3gvi) in Apify Console.
2. Enter a search keyword and optional location filter.
3. Set `maxResults` to control how many results you need.
4. Enable `includeDetails` if you need full descriptions, company data.
5. Click **Start** and wait for the run to finish.
6. Export the dataset as JSON, CSV, or Excel.
### Use cases
- Extract job data from djinni.co for market research and competitive analysis.
- Track salary trends across regions and categories over time.
- Monitor new and changed listings on scheduled runs without processing the full dataset every time.
- Auto-apply or feed apply URLs into your ATS / hiring pipeline.
- Research company hiring patterns, employer profiles, and industry distribution.
- Feed structured data into AI agents, MCP tools, and automated pipelines using compact mode.
- Export clean, structured data to dashboards, spreadsheets, or data warehouses.
### How much does it cost to scrape djinni.co?
Djinni.co Tech Jobs Scraper uses [pay-per-event](https://docs.apify.com/platform/actors/paid-actors/pay-per-event) pricing. You pay a small fee when the run starts and then for each result that is actually produced.
- **Run start:** $0.005 per run
- **Per result:** $0.002 per job record
Example costs:
- 10 results: **$0.03**
- 100 results: **$0.21**
- 500 results: **$1**
#### Example: recurring monitoring savings
These examples compare full re-scrapes with incremental runs at different churn rates. Churn is the share of listings that are new or whose tracked content changed since the previous run. Actual churn depends on your query breadth, source activity, and polling frequency — the scenarios below are examples, not predictions.
Example setup: 100 results per run, daily polling (30 runs/month). Event-pricing examples scale linearly with result count.
| Churn rate | Full re-scrape run cost | Incremental run cost | Savings vs full re-scrape | Monthly cost after baseline |
|---|---:|---:|---:|---:|
| 5% — stable niche query | $0.21 | $0.01 | $0.19 (93%) | $0.45 |
| 15% — moderate broad query | $0.21 | $0.03 | $0.17 (83%) | $1.05 |
| 30% — high-volume aggregator | $0.21 | $0.07 | $0.14 (68%) | $1.95 |
Full re-scrape monthly cost at daily polling: $6.15. First month with incremental costs $0.64 / $1.22 / $2.09 for the 5% / 15% / 30% scenarios because the first run builds baseline state at full cost before incremental savings apply.
Platform usage (compute and proxies) is billed separately by Apify based on actual consumption. Incremental runs consume less on result processing, though fixed per-run overhead stays the same.
### FAQ
#### How many results can I get from djinni.co?
The number of results depends on the search query and available listings on djinni.co. Use the `maxResults` parameter to control how many results are returned per run.
#### Does Djinni.co Tech Jobs Scraper support recurring monitoring?
Yes. Enable incremental mode to only receive new or changed listings on subsequent runs. This is ideal for scheduled monitoring where you want to track changes over time without re-processing the full dataset.
#### Can I integrate Djinni.co Tech Jobs Scraper with other apps?
Yes. Djinni.co Tech Jobs Scraper works with Apify's [integrations](https://apify.com/integrations?fpr=1h3gvi) to connect with tools like Zapier, Make, Google Sheets, Slack, and more. You can also use webhooks to trigger actions when a run completes.
#### Can I use Djinni.co Tech Jobs Scraper with the Apify API?
Yes. You can start runs, manage inputs, and retrieve results programmatically through the [Apify API](https://docs.apify.com/api/v2). Client libraries are available for JavaScript, Python, and other languages.
#### Can I use Djinni.co Tech Jobs Scraper through an MCP Server?
Yes. Apify provides an [MCP Server](https://apify.com/apify/actors-mcp-server?fpr=1h3gvi) that lets AI assistants and agents call this actor directly. Use compact mode and `descriptionMaxLength` to keep payloads manageable for LLM context windows.
#### Is it legal to scrape djinni.co?
This actor extracts publicly available data from djinni.co. Web scraping of public information is generally considered legal, but you should always review the target site's terms of service and ensure your use case complies with applicable laws and regulations, including GDPR where relevant.
#### Your feedback
If you have questions, need a feature, or found a bug, please [open an issue](https://apify.com/blackfalcondata/djinni-scraper/issues?fpr=1h3gvi) on the actor's page in Apify Console. Your feedback helps us improve.
### You might also like
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- [APEC.fr Scraper - French Executive Jobs](https://apify.com/blackfalcondata/apec-scraper?fpr=1h3gvi) — Scrape apec.fr - French executive job listings with salary ranges, company, location, skills,.
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- [AutoScout24 Scraper — European Car Listings with Dealer Data](https://apify.com/blackfalcondata/autoscout24-scraper?fpr=1h3gvi) — Scrape autoscout24.com - Europe's largest used car marketplace with 770K+ listings. Structured.
- [Bayt.com Scraper — MENA Jobs with Salary & Skills Filter](https://apify.com/blackfalcondata/bayt-scraper?fpr=1h3gvi) — Scrape bayt.com — leading Middle East job board covering UAE, Saudi Arabia, Qatar, Egypt and 9 more.
### Getting started with Apify
New to Apify? [Create a free account with $5 credit](https://console.apify.com/sign-up?fpr=1h3gvi) — no credit card required.
1. Sign up — $5 platform credit included
2. Open this actor and configure your input
3. Click **Start** — export results as JSON, CSV, or Excel
Need more later? [See Apify pricing](https://apify.com/pricing?fpr=1h3gvi).
# Actor input Schema
## `query` (type: `string`):
Keyword(s) to search for (e.g. "python", "java", "devops"). Use a JSON array \["python","go"] for multi-query. Leave empty to browse all tech jobs.
## `location` (type: `string`):
City, country, or region. Use a JSON array for multi-location. Applied as a post-fetch filter against the listing's location text.
## `startUrls` (type: `array`):
Direct djinni.co search or job detail URLs (e.g. https://djinni.co/jobs/keyword-python/).
## `experienceLevel` (type: `string`):
Filter to listings requesting exactly N years of experience. Use a JSON array like \["1","3"] for multi-select. Applied post-fetch.
## `englishLevel` (type: `string`):
Filter by required English level (A1, A2, B1, B2, C1, C2). Use a JSON array for multi-select. Applied post-fetch.
## `isRemote` (type: `boolean`):
Restrict to full-remote listings (drops office and hybrid roles). Leave unchecked to return all.
## `salaryFrom` (type: `integer`):
Drop listings whose published salary range is below this amount. 0 = no minimum.
## `salaryTo` (type: `integer`):
Drop listings whose published salary range exceeds this amount. 0 = no maximum.
## `maxResults` (type: `integer`):
Maximum total job listings to return (0 = unlimited). Primary cost control — Apify charges per emitted record.
## `maxPages` (type: `integer`):
Maximum SERP pages to scrape per source. Defensive bound — maxResults is the primary cap.
## `includeKeywords` (type: `object`):
Require at least one of these keywords in title/description. Example: {"keywords":\["react","node"],"matchTitle":true,"matchDescription":true}.
## `excludeKeywords` (type: `object`):
Exclude jobs containing any of these keywords. Same config shape as includeKeywords.
## `fromDate` (type: `string`):
Only include jobs posted on or after this date. Accepts YYYY-MM-DD or ISO-8601.
## `toDate` (type: `string`):
Only include jobs posted on or before this date.
## `maxAgeMinutes` (type: `integer`):
Only include jobs posted within the last N minutes. 0 = no limit. Pairs well with scheduled runs (e.g. 60 for hourly cron).
## `customFilters` (type: `array`):
Array of rules applied to any output field. Each rule: {"field":"","op":"includes|notIncludes|equals|notEquals|gt|gte|lt|lte","value":...}.
## `includeDetails` (type: `boolean`):
Fetch each job's detail page for full description, salary range, employment type, industry, English level, and category.
## `descriptionFormat` (type: `string`):
Pick a single description representation. `all` keeps every variant; `text` / `html` / `markdown` drop the others.
## `descriptionMaxLength` (type: `integer`):
Truncate description to this many characters. 0 = no truncation.
## `compact` (type: `boolean`):
Output only core fields (for AI-agent / MCP workflows).
## `excludeEmptyFields` (type: `boolean`):
Drop null, empty-string, and empty-array fields from each record before push. Smaller payloads for AI agents and dashboards.
## `outputFields` (type: `array`):
Project the output to a specific list of fields. Empty = include all fields. Example: \["title","company","salaryMin","salaryMax","canonicalUrl"].
## `incrementalMode` (type: `boolean`):
Compare against previous run state. stateKey is optional — when omitted, it's auto-derived from your search inputs so different filter sets never share state.
## `stateKey` (type: `string`):
Optional. Stable identifier for the tracked search universe (e.g. "djinni-python-remote"). Leave empty to auto-generate.
## `emitUnchanged` (type: `boolean`):
When incremental, also emit records that haven't changed.
## `emitExpired` (type: `boolean`):
When incremental, also emit records no longer found.
## `skipReposts` (type: `boolean`):
When incremental, skip jobs whose content matches an expired job from a prior run (cross-run repost detection).
## `dedupStoreName` (type: `string`):
Optional. Reuse a named key-value store across runs to dedup by jobId (or another field).
## `dedupKey` (type: `string`):
Which output field to use as the dedup key. Default: jobId.
## `telegramToken` (type: `string`):
Telegram bot token (from @BotFather). Required for Telegram notifications.
## `telegramChatId` (type: `string`):
Telegram chat or channel ID (e.g. "-100123456789"). Required when telegramToken is set.
## `discordWebhookUrl` (type: `string`):
Discord incoming webhook URL. Server Settings → Integrations → Webhooks → New Webhook.
## `slackWebhookUrl` (type: `string`):
Slack incoming webhook URL. api.slack.com/messaging/webhooks.
## `whatsappAccessToken` (type: `string`):
WhatsApp Cloud API permanent access token (System User token from Meta Business). Recipient must have messaged the business number within the last 24h.
## `whatsappPhoneNumberId` (type: `string`):
Your WhatsApp Business phone-number ID. Required when whatsappAccessToken is set.
## `whatsappTo` (type: `string`):
Recipient phone in E.164 format without + (e.g. "380441234567").
## `webhookUrl` (type: `string`):
Receives a JSON POST with {metadata, items} after each run. Universal escape hatch for n8n / Make / Zapier / custom backends.
## `webhookHeaders` (type: `object`):
Optional JSON object of custom headers (e.g. {"Authorization":"Bearer ..."}).
## `notificationLimit` (type: `integer`):
Maximum number of jobs included in each notification message (1–20).
## `notifyOnlyChanges` (type: `boolean`):
When Incremental Mode is on, only send notifications for NEW and UPDATED jobs.
## `includeRunMetadata` (type: `boolean`):
Prepend a one-line summary (query + total count) to each notification batch.
## Actor input object example
```json
{
"query": "python",
"isRemote": false,
"salaryFrom": 0,
"salaryTo": 0,
"maxResults": 5,
"maxPages": 5,
"maxAgeMinutes": 0,
"includeDetails": true,
"descriptionFormat": "all",
"descriptionMaxLength": 0,
"compact": false,
"excludeEmptyFields": false,
"incrementalMode": false,
"emitUnchanged": false,
"emitExpired": false,
"skipReposts": false,
"dedupKey": "jobId",
"notificationLimit": 5,
"notifyOnlyChanges": false,
"includeRunMetadata": true
}
```
# Actor output Schema
## `results` (type: `string`):
No description
# 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 = {
"query": "python",
"maxResults": 5,
"includeDetails": true,
"descriptionFormat": "all",
"excludeEmptyFields": false
};
// Run the Actor and wait for it to finish
const run = await client.actor("blackfalcondata/djinni-scraper").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 = {
"query": "python",
"maxResults": 5,
"includeDetails": True,
"descriptionFormat": "all",
"excludeEmptyFields": False,
}
# Run the Actor and wait for it to finish
run = client.actor("blackfalcondata/djinni-scraper").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 '{
"query": "python",
"maxResults": 5,
"includeDetails": true,
"descriptionFormat": "all",
"excludeEmptyFields": false
}' |
apify call blackfalcondata/djinni-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=blackfalcondata/djinni-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Djinni.co Tech Jobs Scraper — Salary, English Level, Remote",
"description": "Scrape djinni.co — Ukraine and Eastern Europe's largest IT job board — for structured tech listings with salary range, English level, remote flags, and experience filters. Incremental mode tracks new and changed jobs across runs via a stable stateKey.",
"version": "0.1",
"x-build-id": "k9gdwzEdhSnYoOkp1"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/blackfalcondata~djinni-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-blackfalcondata-djinni-scraper",
"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/blackfalcondata~djinni-scraper/runs": {
"post": {
"operationId": "runs-sync-blackfalcondata-djinni-scraper",
"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/blackfalcondata~djinni-scraper/run-sync": {
"post": {
"operationId": "run-sync-blackfalcondata-djinni-scraper",
"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": {
"query": {
"title": "🔍 Search Term(s)",
"type": "string",
"description": "Keyword(s) to search for (e.g. \"python\", \"java\", \"devops\"). Use a JSON array [\"python\",\"go\"] for multi-query. Leave empty to browse all tech jobs."
},
"location": {
"title": "📍 Location",
"type": "string",
"description": "City, country, or region. Use a JSON array for multi-location. Applied as a post-fetch filter against the listing's location text."
},
"startUrls": {
"title": "🔗 Start URLs",
"type": "array",
"description": "Direct djinni.co search or job detail URLs (e.g. https://djinni.co/jobs/keyword-python/).",
"items": {
"type": "string"
}
},
"experienceLevel": {
"title": "🎓 Experience (years)",
"type": "string",
"description": "Filter to listings requesting exactly N years of experience. Use a JSON array like [\"1\",\"3\"] for multi-select. Applied post-fetch."
},
"englishLevel": {
"title": "🗣️ English Level",
"type": "string",
"description": "Filter by required English level (A1, A2, B1, B2, C1, C2). Use a JSON array for multi-select. Applied post-fetch."
},
"isRemote": {
"title": "🏠 Remote Only",
"type": "boolean",
"description": "Restrict to full-remote listings (drops office and hybrid roles). Leave unchecked to return all.",
"default": false
},
"salaryFrom": {
"title": "💵 Min Salary (USD/month)",
"minimum": 0,
"type": "integer",
"description": "Drop listings whose published salary range is below this amount. 0 = no minimum.",
"default": 0
},
"salaryTo": {
"title": "💵 Max Salary (USD/month)",
"minimum": 0,
"type": "integer",
"description": "Drop listings whose published salary range exceeds this amount. 0 = no maximum.",
"default": 0
},
"maxResults": {
"title": "💯 Max Results",
"minimum": 0,
"maximum": 1000,
"type": "integer",
"description": "Maximum total job listings to return (0 = unlimited). Primary cost control — Apify charges per emitted record.",
"default": 25
},
"maxPages": {
"title": "📄 Max Pages",
"minimum": 1,
"maximum": 50,
"type": "integer",
"description": "Maximum SERP pages to scrape per source. Defensive bound — maxResults is the primary cap.",
"default": 5
},
"includeKeywords": {
"title": "📝 Include Keywords",
"type": "object",
"description": "Require at least one of these keywords in title/description. Example: {\"keywords\":[\"react\",\"node\"],\"matchTitle\":true,\"matchDescription\":true}."
},
"excludeKeywords": {
"title": "🚫 Exclude Keywords",
"type": "object",
"description": "Exclude jobs containing any of these keywords. Same config shape as includeKeywords."
},
"fromDate": {
"title": "📅 From Date",
"type": "string",
"description": "Only include jobs posted on or after this date. Accepts YYYY-MM-DD or ISO-8601."
},
"toDate": {
"title": "📅 To Date",
"type": "string",
"description": "Only include jobs posted on or before this date."
},
"maxAgeMinutes": {
"title": "⏰ Max Age (minutes)",
"minimum": 0,
"type": "integer",
"description": "Only include jobs posted within the last N minutes. 0 = no limit. Pairs well with scheduled runs (e.g. 60 for hourly cron).",
"default": 0
},
"customFilters": {
"title": "🔧 Custom Filters (advanced)",
"type": "array",
"description": "Array of rules applied to any output field. Each rule: {\"field\":\"\",\"op\":\"includes|notIncludes|equals|notEquals|gt|gte|lt|lte\",\"value\":...}."
},
"includeDetails": {
"title": "📋 Include Full Details",
"type": "boolean",
"description": "Fetch each job's detail page for full description, salary range, employment type, industry, English level, and category.",
"default": true
},
"descriptionFormat": {
"title": "📝 Description format",
"enum": [
"all",
"text",
"html",
"markdown"
],
"type": "string",
"description": "Pick a single description representation. `all` keeps every variant; `text` / `html` / `markdown` drop the others.",
"default": "all"
},
"descriptionMaxLength": {
"title": "✂️ Description Max Length",
"minimum": 0,
"type": "integer",
"description": "Truncate description to this many characters. 0 = no truncation.",
"default": 0
},
"compact": {
"title": "📦 Compact Output",
"type": "boolean",
"description": "Output only core fields (for AI-agent / MCP workflows).",
"default": false
},
"excludeEmptyFields": {
"title": "🧹 Exclude empty fields",
"type": "boolean",
"description": "Drop null, empty-string, and empty-array fields from each record before push. Smaller payloads for AI agents and dashboards.",
"default": false
},
"outputFields": {
"title": "🎯 Output Fields",
"type": "array",
"description": "Project the output to a specific list of fields. Empty = include all fields. Example: [\"title\",\"company\",\"salaryMin\",\"salaryMax\",\"canonicalUrl\"].",
"items": {
"type": "string"
}
},
"incrementalMode": {
"title": "♻️ Incremental Mode",
"type": "boolean",
"description": "Compare against previous run state. stateKey is optional — when omitted, it's auto-derived from your search inputs so different filter sets never share state.",
"default": false
},
"stateKey": {
"title": "🔑 State Key",
"type": "string",
"description": "Optional. Stable identifier for the tracked search universe (e.g. \"djinni-python-remote\"). Leave empty to auto-generate."
},
"emitUnchanged": {
"title": "♻️ Emit Unchanged Records",
"type": "boolean",
"description": "When incremental, also emit records that haven't changed.",
"default": false
},
"emitExpired": {
"title": "⚰️ Emit Expired Records",
"type": "boolean",
"description": "When incremental, also emit records no longer found.",
"default": false
},
"skipReposts": {
"title": "🚫 Skip Reposts",
"type": "boolean",
"description": "When incremental, skip jobs whose content matches an expired job from a prior run (cross-run repost detection).",
"default": false
},
"dedupStoreName": {
"title": "🗂️ Dedup KV Store Name",
"type": "string",
"description": "Optional. Reuse a named key-value store across runs to dedup by jobId (or another field)."
},
"dedupKey": {
"title": "🔑 Dedup Key Field",
"type": "string",
"description": "Which output field to use as the dedup key. Default: jobId.",
"default": "jobId"
},
"telegramToken": {
"title": "🔑 Telegram Bot Token",
"type": "string",
"description": "Telegram bot token (from @BotFather). Required for Telegram notifications."
},
"telegramChatId": {
"title": "💬 Telegram Chat ID",
"type": "string",
"description": "Telegram chat or channel ID (e.g. \"-100123456789\"). Required when telegramToken is set."
},
"discordWebhookUrl": {
"title": "🎮 Discord Webhook URL",
"type": "string",
"description": "Discord incoming webhook URL. Server Settings → Integrations → Webhooks → New Webhook."
},
"slackWebhookUrl": {
"title": "💼 Slack Webhook URL",
"type": "string",
"description": "Slack incoming webhook URL. api.slack.com/messaging/webhooks."
},
"whatsappAccessToken": {
"title": "📱 WhatsApp Access Token",
"type": "string",
"description": "WhatsApp Cloud API permanent access token (System User token from Meta Business). Recipient must have messaged the business number within the last 24h."
},
"whatsappPhoneNumberId": {
"title": "📞 WhatsApp Phone Number ID",
"type": "string",
"description": "Your WhatsApp Business phone-number ID. Required when whatsappAccessToken is set."
},
"whatsappTo": {
"title": "📲 WhatsApp Recipient",
"type": "string",
"description": "Recipient phone in E.164 format without + (e.g. \"380441234567\")."
},
"webhookUrl": {
"title": "🪝 Generic Webhook URL",
"type": "string",
"description": "Receives a JSON POST with {metadata, items} after each run. Universal escape hatch for n8n / Make / Zapier / custom backends."
},
"webhookHeaders": {
"title": "📋 Webhook Headers",
"type": "object",
"description": "Optional JSON object of custom headers (e.g. {\"Authorization\":\"Bearer ...\"})."
},
"notificationLimit": {
"title": "📊 Max Jobs Per Notification",
"minimum": 1,
"maximum": 20,
"type": "integer",
"description": "Maximum number of jobs included in each notification message (1–20).",
"default": 5
},
"notifyOnlyChanges": {
"title": "🔄 Notify Only New/Updated",
"type": "boolean",
"description": "When Incremental Mode is on, only send notifications for NEW and UPDATED jobs.",
"default": false
},
"includeRunMetadata": {
"title": "📣 Include Run Summary in Notifications",
"type": "boolean",
"description": "Prepend a one-line summary (query + total count) to each notification batch.",
"default": 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
}
}
}
}
}
}
}
}
}
}
```