JournalX
TraderSync
Moodfol.io
Quantro
UltraTrader
Stonk Journal
Mantis Trading Journal
ProfitHelper.app
socketify.py
JournalX is a trading journal for active, self-directed traders who want a real feedback loop on their performance. Log, plan, and analyze every trade in one workspace, then use your own data to work out what is working in your strategy and what is not.
Most journals are a record of what already happened. JournalX starts one step earlier. You write the plan before you take the trade (setup, entry, stop, target, size), take the trade, and the journal reconciles the plan against the execution. Over a few hundred trades, that gap between what you planned and what you did becomes the most useful data you have, and almost nothing else measures it.
Your strategy lives in the product as Gameplans: reusable entry and risk rules you define once, attach to trades, and review for adherence. Pair that with a filter builder that stacks conditions (setup, session, symbol, tag, win or loss) and you can answer a specific question instead of staring at one blended P&L number. An AI assistant works over your own trade history, so you can ask why a month went badly and get an answer grounded in your trades rather than a generic tip.
Trades arrive by broker auto-sync, CSV import with column mapping, or manual entry. Stocks, options, futures, forex, and crypto are all supported, with multi-account and multi-currency tracking.
JournalX socketify.pyJournalX's answer
JournalX started from a problem most traders recognise. You keep a spreadsheet, it grows to forty columns, and at some point you quietly stop updating it. Even when you do keep it current, it tells you what your P&L was without telling you why.
The existing journals solved half of that. They import trades and produce charts. But they still only look backward, at decisions already made and no longer changeable. The idea behind JournalX was that the interesting data is the difference between the trade you planned and the trade you actually took. Capture the plan first and the journal can show you where discipline broke down, not just where money was lost.
So the product was built around that loop: plan, execute, reconcile, review. Everything else, the analytics, the Gameplans, the notes, the AI assistant, the broker sync, exists to make that loop fast enough to run every single day.
JournalX's answer
Most trading journals are a record of what already happened. JournalX starts one step earlier.
You write the plan before you take the trade: setup, entry, stop, target, position size. Then you take the trade, and the journal reconciles the plan against what you actually did. Over a few hundred trades, that gap between the trade you planned and the trade you took is usually where the real problem lives, and almost no other journal measures it.
JournalX's answer
Three reasons.
Pre-trade planning. TradeZella, TraderSync, Tradervue, and Edgewonk are all capable at post-trade analysis. None of them ask you to commit to a plan before entry and then score you against it. That is the habit that actually changes behaviour, and it is what JournalX is built around.
Speed and interface. A journal only works if you use it every day. JournalX is fast, navigable from the keyboard through a command palette, and designed so a daily review takes minutes rather than becoming the chore you skip.
Price and coverage. Starter is $24/mo, or $19/mo billed annually. Pro is $49/mo, or $29/mo billed annually. Stocks, options, futures, forex, and crypto are supported at every tier, with broker auto-sync, CSV import, and manual entry, and there is a 7-day free trial.
JournalX's answer
Active, self-directed retail traders who treat trading as a craft and want a real feedback loop on their performance. That spans day and swing traders, and futures, options, forex, and crypto traders across global markets.
Based on our record, socketify.py seems to be more popular. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
These "benchmarks" are useless, they're not testing anything real world except the performance of uWebsockets. There are copy errors all over the place. And then an advertisement: https://github.com/cirospaciari/socketify.py#briefcase-comme... Is this a professional framework that produces proper, real-world benchmarks and... - Source: Hacker News / over 3 years ago
After starting the project called socketify.py at https://github.com/cirospaciari/socketify.py, I got pretty good results and reviews, but many people asked if socketify.py could be used to create a WSGI and ASGI server. WSGI and ASGI have a lot of overhead, that's is why I choose not to use them in the first place, but adding an ASGI and WSGI server allows a lot of code already written to run faster! Source: over 3 years ago
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