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‎.buildinfo

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# Sphinx build info version 1
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# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
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config: 1d020293d208c2f5ae9d4aa2a27aa227
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tags: 645f666f9bcd5a90fca523b33c5a78b7

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‎_sources/generated/Modules.ModifiedTreeModel.rst.txt

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Modules.ModifiedTreeModel
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=========================
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.. automodule:: Modules.ModifiedTreeModel
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.. rubric:: Classes
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.. autosummary::
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ModifiedTreeClass
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‎_sources/generated/Modules.TreeItem.rst.txt

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Modules.TreeItem
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================
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.. automodule:: Modules.TreeItem
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.. rubric:: Classes
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.. autosummary::
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TreeItem
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‎_sources/generated/Modules.TreeModel.rst.txt

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Modules.TreeModel
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=================
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.. automodule:: Modules.TreeModel
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.. rubric:: Classes
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.. autosummary::
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TreeClass
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‎_sources/generated/Modules.deploy_files.rst.txt

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Modules.deploy\_files
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=====================
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.. automodule:: Modules.deploy_files
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.. rubric:: Functions
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.. autosummary::
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deploy_config
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deploy_schema
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save_config
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save_index
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save_main_index
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‎_sources/generated/Modules.jsonio_lib.rst.txt

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Modules.jsonio\_lib
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===================
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.. automodule:: Modules.jsonio_lib
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.. rubric:: Functions
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.. autosummary::
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decode_function
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py_to_tree
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schema_to_py_gen
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tree_to_py
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type_translation
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validator_files
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validator_vars
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‎_sources/generated/Modules.jsonsearch_lib.rst.txt

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Modules.jsonsearch\_lib
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=======================
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.. automodule:: Modules.jsonsearch_lib
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.. rubric:: Functions
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.. autosummary::
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check_index
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dict_flatten_dict
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f_search
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schema_matching_search
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start_index
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watchdog
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‎_sources/generated/pyJSON.rst.txt

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pyJSON
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======
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.. automodule:: pyJSON
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.. rubric:: Classes
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.. autosummary::
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BackgroundBrushDelegate
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EnumDropDownDelegate
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SearchWindow
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UiRunnerInstance
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‎_sources/index.md.txt

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# The pyJSON Schema Loader and Editor Documentation
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## About
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This is the pyJSON Schema Loader and JSON Editor - a JSON Schema based editor capable of creating a well structured, metadata containing document based on a data schema. With pyJSON, one can create,
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edit, validate and save JSON documents. Furthermore, a simple search function helps keeping track of filesystem-based repositories filled with metadata.
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For a JSON schema creating software that is capable of being integrated in network workflow structures, please have a look at [the ADAMANT web tool](https://github.com/INP-PM/adamant) ([Publication in F1000Research](https://doi.org/10.12688/f1000research.110875.1)).
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pyJSON is licensed under the terms and conditions of [the MIT license](https://opensource.org/license/mit/). The source code is stored in [this Github repository](https://github.com/nplathe/pyJSON-Schema-Loader-and-JSON-Editor).
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## Grant information
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The work was funded by the Federal Ministry of Education and Research (BMBF) under the grant mark 16QK03A and by "Deutsche Forschungsgemeinschaft (DFG)" - Projektnummer 454848899.
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The responsibility for the content of this repository lies with the authors.
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## Requirements
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Head over to the [installation](installation) section of the documentation for details.
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In short, pyJSON requires Python 3.10 or newer, `PySide6` as bindings for Qt6, the `regex` and the `jsonschema` package.
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Furthermore, the `PyInstaller` package is needed, if you want to freeze the environment and distribute pyJSON as an executable for the platform
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of choice. Additional packages are needed for building the documentation. A virtual environment is highly advised.
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```{note}
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pyJSON is unter active development
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```
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```{toctree}
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---
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maxdepth: 2
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caption: Contents
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---
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installation
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usage
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modules
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```
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# Indices and tables
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- {ref}`genindex`
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- {ref}`modindex`
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- {ref}`search`

‎_sources/installation.md.txt

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# Installation
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## Pyinstaller builds
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In order to simplify distribution, you can find packaged one-file builds created with [Pyinstaller](https://pyinstaller.org/en/stable/) via GitHub Actions
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on [the releases page](https://github.com/nplathe/pyJSON-Schema-Loader-and-JSON-Editor/releases).
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If you just want to use pyJSON without looking into the code or dealing with Python, the prebuilt files are the better choice.
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Note that Pyinstaller builds are not extensively tested. If you encounter unusual behaviour, please open [an issue](https://github.com/nplathe/pyJSON-Schema-Loader-and-JSON-Editor/issues).
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## Working with the code
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In order to use pyJSON, at least Python 3.10 is required, alongside a few third-party modules.
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```{warning}
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Due to match cases being used in several parts, pyJSON is explicitly not compatible with versions
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prior to python 3.10! See [PEP 636](https://peps.python.org/pep-0636/) for details.
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```
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Currently, in order to use pyJSON, it is necessary to download the source code. Either use
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```bash
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git clone https://github.com/nplathe/pyJSON-Schema-Loader-and-JSON-Editor
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```
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or use the "Code" -> "Download ZIP" button on the repository page to download the source code.
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For running pyJSON, the following packages are needed:
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| package | version | purpose |
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|------------|-------------|--------------------------------------|
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| jsonschema | ~=4.19.2 | JSON validation via JSON schema |
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| PySide6 | ~=6.5.1.1 | python bindings for the QT framework |
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| regex | ~=2023.10.3 | regular expressions |
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## Prerequisites
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It is highly recommended to create a virtual environment for installation and building an executable. Virtual environments
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keep your main installation free from unneeded packages and introduce a separation of the several packages used, which heavily
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benefits development and avoids unnecessary issues, e.g. package conflicts.
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### A: installing packages via pip
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In order to run pyJSON, run the following command in the repository directory to install the dependencies.
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```bash
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pip install -r requirements.txt
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```
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```{warning}
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As of [PEP 668](https://peps.python.org/pep-0668/), if your base environment is marked as externally managed, you **must**
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use a virtual environment.
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```
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### B: conda managed environment
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[conda](https://docs.conda.io/en/latest/) is an alternative package manager for python. It is capable of creating and managing
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several sources for packages, creating virtual environments and solving dependencies for packages.
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First create a new virtual environment and enter it.
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```bash
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conda create -n <yourenvname> python=3.10.9
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conda activate <yourenvname>
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```
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You can always leave your environment with `conda deactivate`.
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Install the dependencies. Note, that, dependent on your settings and distribution of the conda package manager, you might have
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to specify the channel with the `-c` argument, e.g. `-c conda-forge` for the community-driven [conda-forge repository](https://conda-forge.org/),
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which contains all of the needed packages.
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```bash
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conda install -c conda-forge jsonschema regex pyside6
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```
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## Building the documentation
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If you are interested in building the documentation yourself, you need the following packages:
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| package | version | purpose |
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|-------------|------------|------------------------------------|
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| sphinx | ~=7.7.7 | documentation generation framework |
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| myst-parser | ~=3.0.1 | Markdown parser for sphinx |
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| furo | ~=2024.5.6 | alternative HTML theme for sphinx |
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## Running pyJSON
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In your python environment in the command line, after installing the prerequisites, navigate to the directory pyJSON is located in and execute
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```bash
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python pyJSON.py
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```
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## Building a distributable package
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First, install [PyInstaller](https://pyinstaller.org/en/stable/) into your environment. Make sure to activate your environment, then navigate to the source directory and run
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```bash
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pyinstaller --clean --icon=icon.ico ./pyJSON.py
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```
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to generate a distributable frozen environment containing everything for pyJSON in order to run it without a local python installation.
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You can add the `--onefile` parameter to create an one-file executable instead of a directory tree.

‎_sources/modules.md.txt

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# Modules documentation
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```{eval-rst}
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.. autosummary::
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:toctree: generated
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pyJSON
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Modules.deploy_files
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Modules.jsonio_lib
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Modules.jsonsearch_lib
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Modules.TreeItem
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Modules.TreeModel
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Modules.ModifiedTreeModel
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```

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