Search_Analysis

Features

Use-Case: Analyze Single Approach

• Get Metrics: Precision, Recall, F-Score
• Find queries that perform especially bad/good
• Analyze false positives, false negatives and true positives
• For every query get score, field value, highlighting

Use-Case Compare Two Approaches

• Visualization of metrics side by side
• Find queries with biggest difference
• Analyze false positives, false negatives, true positives and calculate disjoint sets
• Get scores visualized side by side

(For now it's only possible to work with Elasticsearch)

Requirements

• TODO

Installation

shell

Installation

To build the documents you have to run the nox task responsible for building thte documents

nox --session=docs

Stable release

To install Search Analysis, run this command in your terminal:

$ pip install search_analysis

This is the preferred method to install Search Analysis, as it will always install the most recent stable release.

If you don't have pip installed, this Python installation guide can guide you through the process.

From sources

The sources for Search Analysis can be downloaded from the Github repo.

You can either clone the public repository:

$ git clone git://github.com/pragmalingu/search-analysis

Or download the tarball:

$ curl -OJL https://github.com/pragmalingu/search-analysis/tarball/main

Once you have a copy of the source, you can install it with:

$ python setup.py install

Usage

Contributing

Contributions are very welcome. To learn more, see the Contributor Guide.

License

Distributed under the terms of the MIT license, Search_Analysis is free and open source software.

Issues

If you encounter any problems, please file an issue along with a detailed description.

Help

For questions you can contact us via E-Mail or through our website (https://www.pragmalingu.de/).

Credits

This project was generated from @cjolowicz's Hypermodern Python Cookiecutter template.