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A library for reading Qlik Sense .qvd file format from Python, written in Rust.

Project description

Read Qlik Sense .qvd files 🛠

CI pipeline

A python library for reading Qlik Sense .qvd file format, written in Rust. Files can be read to DataFrame or dictionary.

Install

Install from PyPi https://pypi.org/project/qvd/

pip install qvd

Usage

from qvd import qvd_reader

df = qvd_reader.read('test.qvd')
print(df)

example

Developing

Create a virtual env https://docs.python-guide.org/dev/virtualenvs/ and activate it.

python3 -m venv venv

Then install dev dependencies:

pip install pandas maturin

Afterwards, run

maturin develop --release

to install the generated python lib to the virtual env.

Test

To run the tests, you can use these commands:

cargo test  # runs all Rust unit tests
pytest test_qvd_reader.py  # runs all Python tests

QVD File Structure

A QVD file is split into 3 parts; XML Metdata, Symbols table and the bit stuffed binary indexes.

XML Metadata

This section is at the top of the file and is in human readable XML. This section contains metadata about the file in gneneral such as table name, number of records, size of records as well as data about individual fields including field name, length offset in symbol table.

Symbol table

Directly after the xml section is the symbol table. This is a table of every unique value contained within each column. The columns are in the order described in the metadata fields section. In the metadata we can find the byte offset from the start of the symbols section for each column. Symbol types cannot be determined from the metadata and are instead determined by a flag byte preceding each symbol. These types are:

  • 1 - 4 byte signed int (u32) - little endiand
  • 2 - 8 byte signed float (f64) - little endian
  • 4 - null terminated string
  • 5 - 4 bytes of junk follwed by a null terminated string representing an integer
  • 6 - 8 bytes of junk followed by a null terminated string representing a float

Binary Indexes

After the symbol table are the binary indexes that map to the symbols for each row. They are bit stuffed and reversed binary numbers that point to the index of the symbol in the symbols table for each field.

Project details


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