At the start of a journal, a few dozen trades pose no problem. You can look at almost everything manually.
Then the weeks pass. The months. Accounts get added. Screenshots pile up. Imports become more numerous. And suddenly, what worked perfectly with 50 trades has to work with 5,000.
That's where another kind of problem appears.
Building for today is easy
Building for the history is different. A journal can seem fast and clean when it holds little data. But that's not real proof.
The real test comes when you start asking: show me only this account; only this period; only this setup; compare these months; find this trade; load the images; recalculate the statistics. And do it without slowing everything else down.
The data has to grow without becoming a mess
That's also where structure decisions become important. A trade must have a clear identity. An account must have a clear identity. A screenshot must be able to attach to the right trade. Imported data must not create a second copy of a trade that already exists.
Each detail seems small when you're building it. But when the history grows, small ambiguities become big problems.
I ran into exactly this problem with duplicates
When several sources can feed the journal, two different files can sometimes represent the same real event in a different way. An add-on can write a trade. A CSV can contain the executions that make up that same trade. If the journal treats both as two different operations, the results become wrong.
So I had to work on much more careful logic. Detect what looks like a duplicate. Compare the information. But above all: never automatically delete something simply because the system thinks it's identical. The trader must be able to check.
This philosophy even shows up in the code: the detection stays deliberately conservative and returns the groups for human review rather than deciding on its own what to delete.
Because wrong data can be worse than missing data
If a journal shows the same trade twice, every statistic after that becomes contaminated. P&L. Win rate. Number of trades. Averages. Streaks. Everything.
So the quality of the history became just as important as its volume.
And that's when I realized something
Making a journal work for a week is one step. Making it work for several years is another.
I didn't want LowFlow to become less useful as the trader accumulates experience. It should be exactly the opposite. The more the history grows, the more interesting it should become.