The 6 Best Time Tracking Apps for Data Scientists and Analysts on a Mac in 2026

Dayflow fits most data scientists on a Mac. It captures notebooks, papers and dashboards from the screen and is free under the MIT license. ActivityWatch wins if you want free, local, scriptable data across Mac and Linux. Timing wins for billable reports on a Mac. WakaTime wins for pure coding metrics, and Toggl wins for team timesheets and client billing.

This ranking is for data scientists, ML engineers and analysts who work on a Mac and want an honest record of where their hours go. The work rarely stays in one editor. A normal day might include a Jupyter notebook in a browser tab, SQL in a database client, a paper open in Preview, a BI dashboard, a Slack thread about a metric that moved, and a training run you check on between other tasks. You want a tracker that captures that mix without making you start timers. Later it should answer two questions: “what did I actually do on Tuesday?” and “how many hours went into this analysis?”

Dayflow is our product, so read the ranking with that in mind. It ranks first for one reason. It is the only tool here that records what is on screen, at one frame every 10 seconds, and has AI write the day into a timeline. That suits work spread across notebooks, papers and tabs. It is also free and MIT licensed. Dayflow does not win on two criteria. The first is billing and team reporting, where Toggl (formerly Toggl Track) and Timing are stronger. See our Toggl for Mac and Timing alternative pages. The second is per-language coding metrics, where WakaTime is built for the job. The other two tools here are ActivityWatch, covered in ActivityWatch vs Dayflow, and Rize, covered in our Rize alternative comparison.

Quick comparison

Tool	Best for	How it tracks	Price
Dayflow	Research-heavy days across notebooks, papers and tabs	Screen frame every 10 seconds, AI-written timeline	$0 (MIT), optional Pro $20 a month
Timing	Billable analysis work on a Mac	Automatic app, website and document tracking	From $9/month billed annually, or $11 billed monthly
ActivityWatch	Free, local, scriptable data	Active app, window title, AFK, plus browser and editor plugins	Free
WakaTime	Coding time by project and language	Editor and terminal plugins	Free, paid from $9/month billed monthly

Quick picks by use case

Best overall for research work: Dayflow. It costs $0 and has an optional Pro plan at $20 a month. It picks up the work that happens outside an editor, which is a large share of an analyst’s day.

Best free and fully local: ActivityWatch. It is free, with no feature gates, and all data stays on your device. It also runs on Linux, which matters if you split time with a workstation.

Best for billing analysis work: Timing. Professional is $9 per month billed annually or $11 billed monthly. It has billing status, report rounding and invoicing integration on a Mac.

Best for teams: Toggl. It is free for up to 3 users. Starter is $9 per user per month billed annually, and Premium is $16 per user per month billed annually with timesheet approvals and profitability reports.

Best for pure coding metrics: WakaTime. The Free plan keeps one week of history. Premium is $14 a month billed monthly and adds full history.

Best cloud AI insights: Rize. Basic is $9.99 a month billed annually or $12.99 billed monthly, with 500 AI credits a month.

How we compared them

For a general ranking of Mac time trackers, see our main guide. This page weights the criteria for people whose work is notebooks, queries, papers and long jobs.

• Captures research and notebook work (25%). High scores go to tools that see notebooks in browser tabs, PDFs and dashboards without setup. Low scores go to tools that only see one editor.
• Privacy of what is on screen (20%). High scores go to tools that keep data on the Mac by default, since analysts often have customer or regulated data on screen. Cloud-only storage scores low.
• Data access and export (15%). High scores go to open source code, a local API or plain-text export you can analyze yourself. Locked dashboards score low.
• Handles long-running jobs and idle time (15%). High scores go to tools that make it clear when you were waiting, working or away. Tools that silently drop or inflate that time score low.
• Price (15%). A usable free tier scores high. Subscription-only scores low.
• Project reporting and billing (10%). Billable rates, client reports and team views score high. A personal record only scores low.

We compared the tools using each vendor’s own pricing and product pages as of 2026-10-04, and Dayflow using its 2.2.0 release facts. No benchmark was run, and the scores behind the ranking are judgments.

The 6 best time tracking apps for data scientists on a Mac, ranked

1. Dayflow

Dayflow is a free, open-source Mac app that records your screen at one frame every 10 seconds and has AI write the day into a readable timeline.

It works from what is on screen rather than from which app has focus. A notebook in a browser tab, a paper in a PDF viewer, a dashboard and a terminal tailing a training log all end up in the record without plugins or timers. You get a timeline you can read back when someone asks what two weeks of model work consisted of. You can also export any date range as Markdown from Settings → Export.

Recordings and the timeline are stored on your Mac. You choose where analysis runs, as explained in local and cloud processing:

• Local AI runs through Ollama or LM Studio and keeps screenshot analysis on-device.
• Your own cloud provider or Dayflow Pro processes selected screenshots off-device.

Dayflow is $0 under the MIT license, and Pro is $20 a month.

The limit: it has no invoices, payroll approvals, team reports or website blocking, and it needs macOS 14 or later. AI summaries can also miss or misinterpret work, so check them before sharing.

Pick it if your work is spread across notebooks, papers and tabs and you want a readable record without timers.

2. Timing

Timing is a Mac-only automatic tracker positioned for people who need billable-hour records.

It records time across apps, websites and documents, down to specific URLs and Mail threads. It also lists manual entries, iOS activity import and call tracking. For analysts, the URL and document detail is the useful part, because time in a particular notebook URL or spreadsheet can be assigned to a project. On all plans, the vendor lists AI activity summaries, AI-powered suggestions for time entries and AI integration via MCP.

Tracked times are stored locally and stay on your Mac unless you opt into sync. Reporting is the strongest of the Mac-native options. It includes billing status, customizable reports with rounding, two-way ClickUp, Linear and Clio sync, GrandTotal invoicing, and scripting, a Web API and Zapier, depending on plan.

Pricing:

• Professional: $9 per month billed annually, or $11 billed monthly
• Expert: $11 annually, or $14 monthly
• Connect: $16 per user per month annually, or $20 monthly

There is a 30-day trial with no credit card.

The limit: there is no free tier, it is Mac only, and Professional covers one Mac with limited web app access.

Pick it if you bill clients for analysis and want automatic capture that rolls into invoice-ready reports.

3. ActivityWatch

ActivityWatch is a free, open-source automatic tracker under MPL-2.0 that runs on Windows, Mac, Linux and Android.

It records three things: the active application, the window title, and whether you are away from keyboard. Browser extensions add the active tab title and URL, and editor plugins add coding activity.

This design suits data people well:

• Everything is stored on your own device and never sent to a server, so screens full of customer data stay local.
• The local API and custom watchers let you pull your activity into a notebook and analyze it like any other dataset.
• If you split time between a Mac laptop and a Linux workstation, it is the only tool here that runs on both.
• The away-from-keyboard signal shows plainly when you walked away from a running job.

Price: free, with no feature gates, usage limits or ads.

The limit: it records titles and URLs, not what is on screen. An afternoon in one long-lived notebook tab can therefore read as a single block. There are no AI summaries listed, and device sync is still work in progress.

Pick it if you want raw, local, scriptable data and are happy to do the analysis yourself.

4. WakaTime

WakaTime is a developer time tracker built on open source plugins for more than 100 editors, IDEs and terminals.

The plugins automatically record coding time and AI usage per project, language and editor, and send it to a hosted dashboard. If you write most of your code in an IDE, it gives the cleanest answer to “how much time went into the feature pipeline versus the evaluation scripts?” It also tracks AI coding usage: adoption, model usage and spend, and AI-generated versus human-written lines across tools such as Claude Code, Cursor, Copilot and Codex. Check the plugin list for your notebook setup before you commit.

Pricing:

• Free: $0, with one week of dashboard history
• Basic: $9/mo billed monthly, or $8.25/mo billed $99 yearly
• Premium: $14/mo billed monthly, or $12.83/mo billed $153.96 yearly
• Team: $21 per dev per month billed monthly

There is a 14-day Team trial with no credit card.

The limit: it only sees supported editors and terminals. Papers, meetings and dashboard work never appear. Full history needs Premium, and data lives in WakaTime’s cloud.

Pick it if code is the part of your work you want measured. Our developer roundup covers this side in more depth.

5. Rize

Rize is a cloud-hosted automatic tracker for Mac and Windows built around AI categorization.

It tracks apps and websites automatically, categorizes and tags them with AI, and can connect Google Calendar to capture meeting time. You get AI chat over your activity and AI productivity and focus insights. Pro and above add client and scheduled reports in PDF and CSV, an API, webhooks, Zapier and MCP server access. AI features are metered in monthly credits.

Pricing:

• Basic: $9.99/mo billed annually, or $12.99 billed monthly, with 500 AI credits
• Pro: $23.99/mo billed annually, with 1,000 credits
• Max: $39.99/mo billed annually, with 3,000 credits
• Team: $29.99 per seat per month billed annually, or $39.99 monthly

The trial is 7 days with full access and no credit card.

The limit for this audience is data location. The vendor hosts data on Amazon Web Services with encryption at rest and in transit, which some data teams will need to clear with security. There is also no permanently free tier, and Linux is not yet available.

Pick it if you want polished AI focus insights, are fine with cloud hosting, and want CSV exports or an API without building anything. Timing vs Rize compares the two paid automatic options directly.

6. Toggl (formerly Toggl Track)

Toggl is a timer-based tracker that now combines time tracking with planning.

You start and stop timers, fill in timesheets, or pull entries from calendar integrations. The vendor also lists automated background tracking and a timeline in the desktop app, and states that Toggl does not take screenshots or record keystrokes. It runs on web, Mac, Windows, iOS, Android and browser extensions.

Timers suit one data-science habit well. When you kick off a long training or ETL job for a client, a timer on that project records the session deliberately, instead of leaving an automatic tracker to guess. Toggl AI answers natural-language questions about workspace data, and there is an MCP server and an AI Task Creator.

Pricing:

• Free: up to 3 users
• Starter: $9 per user per month billed annually, or $12 monthly
• Premium: $16 per user per month billed annually, or $24 monthly, adding timesheet approvals, profitability reports and Jira and Asana integrations
• Enterprise: contact the vendor

Paid plans have a 30-day trial.

The limit: it is mainly timer and manual entry, so a forgotten timer means missing hours. Billable rates need a paid plan, and data lives in the cloud.

Pick it if you bill or report hours as a team and need rates, approvals and capacity planning.

Full comparison table

Tool	Price	Automatic capture	AI summaries	Where data lives	Open source	Platforms
Dayflow	$0, optional Pro $20 a month	Yes, a screen frame every 10 seconds	Yes, via Local AI, your own provider or Pro	On your Mac; selected screenshots go off-device with your own provider or Pro	Yes, MIT	macOS 14 or later
Timing	From $9/month billed annually	Yes, apps, websites and documents	Yes, AI activity summaries	Local, optional sync	No	Mac
ActivityWatch	Free	Yes, active app, window title and AFK	None listed	Local, on your device	Yes, MPL-2.0	Windows, Mac, Linux, Android
WakaTime	Free; paid from $9/month billed monthly	Yes, inside editors and terminals only	No; tracks AI coding usage instead	Cloud	Plugins only	100+ editors, IDEs and terminals; web dashboard
Rize	From $9.99/month billed annually	Yes, apps and websites	AI categorization, chat and insights	Cloud (Amazon Web Services)	No	Mac, Windows
Toggl	Free for up to 3 users; from $9/user/month billed annually	Mainly timers; background tracking listed	Toggl AI for workspace questions	Cloud	No	Web, Mac, Windows, iOS, Android, browser extensions

Can a time tracker see the time you spend in Jupyter notebooks?

It depends on how the tracker captures time. There are three approaches, and they give very different answers for notebook work.

Window and tab titles. ActivityWatch, Timing and Rize work from the active app plus the tab or document. A notebook served in a browser usually shows its filename in the tab title, and trackers that record URLs can tell one notebook from another. The weakness is resolution. Three hours in the same tab show up as three hours in one place, whether you were cleaning data, debugging a join or reading a stack trace.

Editor plugins. WakaTime only counts what happens inside a supported editor, IDE or terminal. That is precise for code and blind to everything else. Whether browser-based notebook time shows up depends on your setup being covered by a plugin, so check before relying on it.

Screen content. Dayflow looks at what is actually on screen, then summarizes it. A notebook, a paper and a dashboard can each get described for what they are, even when they share one browser window. The tradeoff is that AI summaries can misread a screen, so treat the timeline as a draft you correct, not an audit log.

Research time is where these differences matter most. Reading a paper, scanning a dashboard and thinking through an experiment design rarely produce code. If you want that time counted, a code-only tracker will undercount your week. A quick way to see the gap is to run a time audit on your Mac and compare it with what your editor tracker reports. If you want the raw record in a format you can query, the export work history workflow shows how to pull Dayflow data out as Markdown.

Does waiting on a training run count as work time?

Every analyst has to answer this, and the tools answer it differently, so decide your rule first.

If wait time counts and you want it logged on purpose, a timer is the most honest tool. Start a Toggl timer on the client project when the job starts and stop it when you have read the results. Nothing gets inferred.

If you want to see the gaps, ActivityWatch’s away-from-keyboard signal shows when you stepped away. You can then decide later whether a two-hour training window was work, a lunch break or both.

If you stay at the desk and do something else while the job runs, automatic trackers record the something else. Usually that is the truth you want for a time audit, but it is not the number you want for a client who is paying for the experiment. Timing and Toggl both let you add or edit entries to bring the two in line.

Dayflow’s timeline reflects what was on screen, so a stretch of watching loss curves or a log tail shows up as that. A screen left untouched while you were away may be summarized imperfectly, so check those stretches.

To estimate how much of a typical week goes to waiting, meetings and actual analysis before you pick a tool, try the where does my week go calculator.

Where Dayflow is the wrong pick

Dayflow is a personal record of your day. It is not a billing system, a team dashboard or a policy tool. Choose something else in these cases.

• You bill clients by the hour. Dayflow has no billable rates, invoices or client reports. Timing is the better Mac choice, with billing status, report rounding and GrandTotal invoicing. Toggl is better if a team bills together.
• You need team timesheets or approvals. Dayflow has no team reports or payroll approvals. Toggl Premium adds timesheet approvals and profitability reports. WakaTime’s Team plan covers coding dashboards for engineering teams.
• You want per-language coding metrics or AI coding spend. WakaTime is purpose-built for this, and Dayflow does not break time down by language.
• You also work on Linux or Windows. Dayflow is Mac only. ActivityWatch runs on Windows, Mac, Linux and Android, and Rize covers Windows.
• Your Mac is older than macOS 14. Dayflow needs macOS 14 or later. Rize lists macOS Mojave 10.14.6 or later, and ActivityWatch is another option.
• Your data policy forbids screen capture, even locally. Some regulated environments will not allow full screen recordings on a laptop, however they are processed. ActivityWatch records only app and window titles and keeps them on your device. Toggl states it does not take screenshots.
• You want website blocking. Dayflow does not block sites, and none of the other five tools list blocking either.

How much do they cost?

Tool	Plan	Price
Dayflow	Free	$0, MIT licensed
Dayflow	Pro	$20 a month
Timing	Professional	$9 per month billed annually, or $11 billed monthly
Timing	Expert	$11 per month billed annually, or $14 billed monthly
Timing	Connect	$16 per user per month billed annually, or $20 billed monthly
ActivityWatch	ActivityWatch	Free
WakaTime	Free	$0
WakaTime	Basic	$9/mo billed monthly, or $8.25/mo billed $99 yearly
WakaTime	Premium	$14/mo billed monthly, or $12.83/mo billed $153.96 yearly
WakaTime	Team	$21/dev/mo billed monthly, or $19.25/dev/mo billed $231/dev yearly
WakaTime	Business	$24/dev/mo billed monthly, or $22/dev/mo billed $264/dev yearly
Rize	Basic	$9.99/mo billed annually, or $12.99/month billed monthly
Rize	Pro	$23.99/mo billed annually; for monthly billing, see the vendor’s pricing page
Rize	Max	$39.99/mo billed annually; for monthly billing, see the vendor’s pricing page
Rize	Team	$29.99/seat/month billed annually, or $39.99/seat/month billed monthly
Rize	Enterprise	Custom, contact vendor
Toggl	Free	$0, for up to 3 users
Toggl	Starter	$9 per user per month billed annually, or $12 billed monthly
Toggl	Premium	$16 per user per month billed annually, or $24 billed monthly
Toggl	Enterprise	Contact vendor

The cheapest sensible setup is $0. Use Dayflow with Local AI for the full-day record, and add ActivityWatch or WakaTime Free if you also want app-level or code-level numbers. If you bill clients, the lowest-cost paid step is Timing Professional at $9 per month billed annually for a solo analyst, or Toggl Starter at $9 per user per month billed annually for a team.

The bottom line

If your days are split across notebooks, papers and dashboards and you want a readable record for free, use Dayflow. If you want local, scriptable data across Mac and Linux, use ActivityWatch. If you bill clients, use Timing on a single Mac or Toggl for a team. If code is the only thing you need measured, use WakaTime.

Frequently asked questions

What is the best time tracker for data scientists on a Mac?

For most data scientists, Dayflow is the best fit. It records what is on screen and has AI write the day into a timeline, so it catches notebooks in browser tabs, papers and dashboards. It is free and MIT licensed. If you need billable reports, Timing is stronger. If you want raw local data you can script against, ActivityWatch is the better pick.

Can WakaTime track time in Jupyter notebooks?

WakaTime records coding time through open source plugins for more than 100 editors, IDEs and terminals. Whether it sees your notebook work depends on whether your notebook environment is covered by one of those plugins, so check WakaTime's plugin list first. Time spent reading papers, in meetings or in dashboards outside a supported editor will not appear in WakaTime at all.

Is there a free, open-source time tracker for Mac?

Yes, two. ActivityWatch is free and licensed under MPL-2.0. It records the active app, window titles and away-from-keyboard time, and it stores everything on your device. Dayflow is free and MIT licensed. It records the screen at one frame every 10 seconds and uses AI to write a timeline. Dayflow also has an optional Pro plan at $20 a month.

Which time tracker is best for billing clients for analysis work?

Toggl or Timing, not Dayflow. Dayflow has no invoices, billable rates or team reports. Timing tracks billing status, has customizable reports with rounding and integrates with GrandTotal for invoicing, starting at $9 per month billed annually. Toggl supports billable rates on paid plans, with Starter at $9 per user per month billed annually. Toggl also adds profitability reports and approvals on Premium.

Does Dayflow send my screen recordings to the cloud?

Full screen recordings and the timeline are stored on your Mac. With Local AI, which runs a model through Ollama or LM Studio, screenshot analysis stays on-device. If you choose your own cloud provider or Dayflow Pro, selected screenshots are processed off-device. Under the privacy policy, Pro deletes screenshots after processing and may keep activity data for sync.

Which time tracker works on both Mac and Linux?

ActivityWatch, and here it clearly beats Dayflow, which is Mac only and needs macOS 14 or later. ActivityWatch runs on Windows, Mac, Linux and Android and stores data locally on each device. Sync between devices is still listed as work in progress, so expect separate records per machine for now.

How do I track time spent waiting on a model training run?

First decide whether wait time counts as work. If it does and you want it logged on purpose, start a Toggl timer on the project when the job starts. ActivityWatch records away-from-keyboard time, so you can see when you stepped away. Dayflow's timeline reflects what was on screen, such as a training log, but AI summaries can misread idle stretches, so check them.

Can I analyze my own time tracking data in Python?

Yes. ActivityWatch is the most direct option. It has a local API and supports custom watchers, and the data never leaves your device. Dayflow exports any date range as Markdown from Settings, which works well for text analysis or for feeding an AI assistant. Timing offers a Web API depending on plan, and Rize includes an API and webhooks on Pro and above.

Is Rize or Timing better for analysts on a Mac?

Timing stores tracked time locally unless you opt into sync. It is built around billable records, and plans start at $9 per month billed annually. Rize hosts data on Amazon Web Services and meters AI features in monthly credits. Basic starts at $9.99 per month billed annually. Rize also runs on Windows. If your screen shows sensitive data, Timing's local storage is the easier case to make.