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Event Stage Participation Evidence

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Merge supplied participant intervals inside explicit opening, breakout and closing stages. Retain reconnect/parallel-room evidence, coverage limits, missing identities and source ambiguity. JSON or mapped CSV; no certificates or attendance decisions.

Pricing

$0.25 / completed report

Rating

0.0

(0)

Developer

Gilad Ronen

Actor stats

Bookmarked

Total users

Monthly active users

17 days ago

Last modified

Categories

Business

Automation

You can access the Event Stage Participation Evidence programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in API & Integrations in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4# Replace '<YOUR_API_TOKEN>' with your token.
5client = ApifyClient("<YOUR_API_TOKEN>")
6
7# Prepare the Actor input
8run_input = {
9    "eventId": "workshop-001",
10    "rosterRows": [
11        {
12            "rowId": "roster-1",
13            "participantId": "001",
14        },
15        {
16            "rowId": "roster-2",
17            "participantId": "002",
18        },
19        {
20            "rowId": "roster-3",
21            "participantId": "003",
22        },
23    ],
24    "rosterCsv": "",
25    "rosterColumns": {
26        "rowId": "rowId",
27        "participantId": "participantId",
28    },
29    "stageRows": [
30        {
31            "stageId": "opening",
32            "startTime": "2026-10-01T09:00:00Z",
33            "endTime": "2026-10-01T10:00:00Z",
34            "sessionIds": ["teams-opening"],
35        },
36        {
37            "stageId": "breakout",
38            "startTime": "2026-10-01T10:00:00Z",
39            "endTime": "2026-10-01T12:00:00Z",
40            "sessionIds": [
41                "zoom-A",
42                "zoom-B",
43            ],
44        },
45        {
46            "stageId": "closing",
47            "startTime": "2026-10-01T12:00:00Z",
48            "endTime": "2026-10-01T13:00:00Z",
49            "sessionIds": ["teams-closing"],
50        },
51    ],
52    "stagesCsv": "",
53    "stageColumns": {
54        "stageId": "stageId",
55        "startTime": "startTime",
56        "endTime": "endTime",
57        "sessionIds": "sessionIds",
58    },
59    "coverageRows": [
60        {
61            "sessionId": "teams-opening",
62            "coverage": "complete",
63        },
64        {
65            "sessionId": "zoom-A",
66            "coverage": "complete",
67        },
68        {
69            "sessionId": "zoom-B",
70            "coverage": "partial",
71        },
72        {
73            "sessionId": "teams-closing",
74            "coverage": "not-provided",
75        },
76    ],
77    "coverageCsv": "",
78    "coverageColumns": {
79        "sessionId": "sessionId",
80        "coverage": "coverage",
81    },
82    "intervalRows": [
83        {
84            "rowId": "o1",
85            "sessionId": "teams-opening",
86            "participantId": "001",
87            "joinTime": "2026-10-01T08:55:00Z",
88            "leaveTime": "2026-10-01T09:30:00Z",
89        },
90        {
91            "rowId": "o2",
92            "sessionId": "teams-opening",
93            "participantId": "001",
94            "joinTime": "2026-10-01T09:20:00Z",
95            "leaveTime": "2026-10-01T09:50:00Z",
96        },
97        {
98            "rowId": "b1",
99            "sessionId": "zoom-A",
100            "participantId": "001",
101            "joinTime": "2026-10-01T10:00:00Z",
102            "leaveTime": "2026-10-01T11:00:00Z",
103        },
104        {
105            "rowId": "b2",
106            "sessionId": "zoom-B",
107            "participantId": "001",
108            "joinTime": "2026-10-01T10:30:00Z",
109            "leaveTime": "2026-10-01T11:30:00Z",
110        },
111        {
112            "rowId": "c1",
113            "sessionId": "teams-closing",
114            "participantId": "001",
115            "joinTime": "2026-10-01T12:55:00Z",
116            "leaveTime": "2026-10-01T13:05:00Z",
117        },
118        {
119            "rowId": "b3",
120            "sessionId": "zoom-A",
121            "participantId": "002",
122            "joinTime": "2026-10-01T10:00:00Z",
123            "leaveTime": "2026-10-01T10:30:00Z",
124        },
125        {
126            "rowId": "b4",
127            "sessionId": "zoom-B",
128            "participantId": "002",
129            "joinTime": "2026-10-01T10:10:00Z",
130            "leaveTime": "2026-10-01T10:40:00Z",
131        },
132        {
133            "rowId": "orphan",
134            "sessionId": "zoom-A",
135            "participantId": "unknown",
136            "joinTime": "2026-10-01T10:00:00Z",
137            "leaveTime": "2026-10-01T10:30:00Z",
138        },
139        {
140            "rowId": "missing",
141            "sessionId": "zoom-A",
142            "participantId": "",
143            "joinTime": "2026-10-01T10:00:00Z",
144            "leaveTime": "2026-10-01T10:30:00Z",
145        },
146        {
147            "rowId": "unknown-session",
148            "sessionId": "other-room",
149            "participantId": "001",
150            "joinTime": "2026-10-01T10:00:00Z",
151            "leaveTime": "2026-10-01T10:30:00Z",
152        },
153        {
154            "rowId": "outside",
155            "sessionId": "teams-opening",
156            "participantId": "001",
157            "joinTime": "2026-10-01T14:00:00Z",
158            "leaveTime": "2026-10-01T14:30:00Z",
159        },
160    ],
161    "intervalsCsv": "",
162    "intervalColumns": {
163        "rowId": "rowId",
164        "sessionId": "sessionId",
165        "participantId": "participantId",
166        "joinTime": "joinTime",
167        "leaveTime": "leaveTime",
168    },
169}
170
171# Run the Actor and wait for it to finish
172run = client.actor("h_murdock/event-stage-participation-evidence").call(run_input=run_input)
173
174# Fetch and print Actor results from the run's dataset (if there are any)
175print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
176for item in client.dataset(run.default_dataset_id).iterate_items():
177    print(item)
178
179# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

Event Stage Participation Evidence API in Python

The Apify API client for Python is the official library that allows you to use Event Stage Participation Evidence API in Python, providing convenience functions and automatic retries on errors.

Install the apify-client

$pip install apify-client

Other API clients include:

Event Stage Participation Evidence API in JavaScript

Event Stage Participation Evidence API through CLI

Event Stage Participation Evidence OpenAPI definition

Event Stage Participation Evidence API

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