AmiBroker VS python xlrd

• Customization
  AmiBroker provides a highly customizable platform with extensive scripting capabilities through AFL (AmiBroker Formula Language), allowing users to create custom indicators, backtest systems, and automated trading strategies.
• Speed
  The platform is optimized for speed and can handle large datasets efficiently, making it suitable for high-frequency trading and backtesting complex strategies.
• Advanced Charting
  AmiBroker offers advanced charting features with multiple time frames, drawing tools, and a wide variety of technical indicators to analyze market trends.
• Data Integration
  The software supports integration with multiple data sources and brokers, providing flexibility in terms of data feeds and execution of trades directly from the platform.
• Cost-Effective
  Compared to other high-end trading platforms, AmiBroker offers a cost-effective solution with a one-time purchase fee, making it accessible for individual traders and small trading firms.

Possible disadvantages

• Learning Curve
  Due to its extensive features and customization options, there is a steep learning curve, especially for those who are new to trading platforms or scripting languages.
• User Interface
  The user interface may seem outdated or non-intuitive compared to newer trading platforms, which can affect user experience and ease of navigation.
• Limited Built-in Data
  AmiBroker does not come with built-in market data, requiring users to subscribe to third-party data providers for real-time or historical data, which can be an additional expense.
• Windows-Only
  The platform is only available for Windows, limiting accessibility for users on MacOS or Linux unless they use virtualization or dual-boot solutions.
• Support
  While AmiBroker has an active community and extensive documentation, official support can be limited, making it challenging for users to get timely assistance for specific issues.

• Simplicity
  xlrd provides a straightforward and easy-to-use API for reading Excel files, making it accessible for beginners and quick implementations.
• Widely Used
  xlrd has been a popular choice for handling Excel files in Python, which means there is a lot of available documentation and community support.
• Efficient Reading
  It is optimized for reading data from Excel files without loading entire data into memory, which is beneficial for handling large files.

Possible disadvantages

• No Write Support
  xlrd is designed solely for reading, and it does not support writing or modifying Excel files.
• Limited to Older Excel Formats
  With version 2.0 and above, xlrd only supports the older .xls Excel file format and does not support .xlsx files.
• Deprecated Features
  Due to changes in dependencies and updates to Excel formats, some features in xlrd have become deprecated or removed, which can limit its functionality.

🚀Amibroker : Beginner's Guide for Indian Traders

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Tracking AmiBroker since Mar 2021.

• I need to read multiple excel files, extract a column from each and compose a new file

  So to get this out of the way first, xlrd has less features than openpyxl and in addition only works with the old '.xls' format, not the newer '.xlsx' format. Even on the xlrd's Github repo it says: 'Please use openpyxl where you can... '. Source: over 4 years ago

• Sending Bulk SMS using Africas Talking, Python and Excel

  There are few alternative libraries for reading and writing excel files: Pandas, Xlrd , openpyxl among others. In the end I settled for openpyxl as I had the most experience Using it and it had support for .xlsx files. - Source: dev.to / over 5 years ago