prospector · Python Simple Repository Browser

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Author: Carl Crowder

Maintainer: Carl Crowder

Requires Python: >=3.9

Classifiers

Development Status

5 - Production/Stable

Environment

Console

Intended Audience

Developers

License

OSI Approved :: GNU General Public License v2 or later (GPLv2+)

Operating System

Unix

Programming Language

Python :: 3 :: Only
Python :: 3.9
Python :: 3.10
Python :: 3.11
Python :: 3.12
Python :: 3.13
Python :: 3.14

Topic

Software Development :: Quality Assurance

About

Prospector is a tool to analyse Python code and output information about errors, potential problems, convention violations and complexity.

It brings together the functionality of other Python analysis tools such as Pylint, pycodestyle, and McCabe complexity. See the Supported Tools documentation section for a complete list.

The primary aim of Prospector is to be useful ‘out of the box’. A common complaint of other Python analysis tools is that it takes a long time to filter through which errors are relevant or interesting to your own coding style. Prospector provides some default profiles, which hopefully will provide a good starting point and will be useful straight away, and adapts the output depending on the libraries your project uses.

Installation

Prospector can be installed from PyPI using pip by running the following command:

pip install prospector

Optional dependencies for Prospector, such as pyroma can also be installed by running:

pip install prospector[with_pyroma]

Some shells (such as Zsh, the default shell of macOS Catalina) require brackets to be escaped:

pip install prospector\[with_pyroma\]

For a list of all of the optional dependencies, see the optional extras section on the ReadTheDocs page on Supported Tools Extras.

For local development, poetry is used. Check out the code, then run:

poetry install

And for extras:

poetry install -E with_everything

For more detailed information on installing the tool, see the installation section of the tool’s main page on ReadTheDocs.

Documentation

Full documentation is available at ReadTheDocs.

Usage

Simply run prospector from the root of your project:

prospector

This will output a list of messages pointing out potential problems or errors, for example:

prospector.tools.base (prospector/tools/base.py):
    L5:0 ToolBase: pylint - R0922
    Abstract class is only referenced 1 times

Options

Run prospector --help for a full list of options and their effects.

Output Format

The default output format of prospector is designed to be human readable. For parsing (for example, for reporting), you can use the --output-format json flag to get JSON-formatted output.

Profiles

Prospector is configurable using “profiles”. These are composable YAML files with directives to disable or enable tools or messages. For more information, read the documentation about profiles.

If your code uses frameworks and libraries

Often tools such as pylint find errors in code which is not an error, for example due to attributes of classes being created at run time by a library or framework used by your project. For example, by default, pylint will generate an error for Django models when accessing objects, as the objects attribute is not part of the Model class definition.

Prospector mitigates this by providing an understanding of these frameworks to the underlying tools.

Prospector will try to intuit which libraries your project uses by detecting dependencies and automatically turning on support for the requisite libraries. You can see which adaptors were run in the metadata section of the report.

If Prospector does not correctly detect your project’s dependencies, you can specify them manually from the commandline:

prospector --uses django celery

Additionally, if Prospector is automatically detecting a library that you do not in fact use, you can turn off autodetection completely:

prospector --no-autodetect

Note that as far as possible, these adaptors have been written as plugins or augmentations for the underlying tools so that they can be used without requiring Prospector. For example, the Django support is available as a pylint plugin.

Strictness

Prospector has a configurable ‘strictness’ level which will determine how harshly it searches for errors:

prospector --strictness high

Possible values are verylow, low, medium, high, veryhigh.

Prospector does not include documentation warnings by default, but you can turn this on using the --doc-warnings flag.

pre-commit

If you’d like Prospector to be run automatically when making changes to files in your Git repository, you can install pre-commit and add the following text to your repositories’ .pre-commit-config.yaml:

repos:
- repo: https://github.com/PyCQA/prospector
  rev: v1.16.1 # The version of Prospector to use, if not 'master' for latest
  hooks:
    - id: prospector

This only installs base prospector - if you also use optional tools, for example bandit and/or mypy, then you can add them to the hook configuration like so:

repos:
- repo: https://github.com/PyCQA/prospector
  rev: v1.16.1
  hooks:
    - id: prospector
      additional_dependencies:
        - ".[with_mypy,with_bandit]"
      args: [
        '--with-tool=mypy',
        '--with-tool=bandit',
        ]

Additional dependencies can be individually configured in your prospector.yml file :

# https://bandit.readthedocs.io/en/latest/config.html
bandit:
options:
    skips:
    - B201
    - B601
    - B610
    - B611
    - B703

# https://mypy.readthedocs.io/en/stable/command_line.html
mypy:
options:
    ignore-missing-imports: true

For prospector options which affect display only - those which are not configurable using a profile - these can be added as command line arguments to the hook. For example:

repos:
- repo: https://github.com/PyCQA/prospector
  rev: v1.16.1
  hooks:
    - id: prospector
      additional_dependencies:
        - ".[with_mypy,with_bandit]"
      args:
        - --with-tool=mypy
        - --with-tool=bandit
        - --summary-only
        - --zero-exit