104 lines
4.7 KiB
Markdown
104 lines
4.7 KiB
Markdown
# the_works – a publication management tool for writers
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This software project
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* supports managing texts and publications with multiple languages, pseudonyms, genres, publishers, series, editions, and more
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* supports storage of cover images
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* focuses on ease-of-use, safety, and speed
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* written and field-tested by an actual writer
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the_works also is
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* based on common technologies like Python, SQL, and HTML/JavaScript
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* underlying frameworks are Flask and SQLAlchemy
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* includes test coverage (using pytest)
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## Configuration
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The file `.flaskenv` contains the default configuration. Flask reads the file at startup and adds its key-value-pairs to the runtime environment as environment variables. When the Flask app object is being created in `__init__.py`, all environment variables that start with the prefix "FLASK_" get added to the app configuration.
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This is true for any prefixed environment variable, not just the ones from `.flaskenv`. It is therefore possible to set additional config parameters by hand before running the app. Just make sure to prefix the variable name with "FLASK_".
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Configuration values from the runtime environment can be overridden by using Flask's `-e` command line switch to pass a second config file to the app. This file gets processed the same way as `.flaskenv`, which means that all its keys must be prefixed with "FLASK_". These vars take precedence over the default configuration.
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Finally, you can override config settings with Python during the Flask app's instantiation through the factory. To do this, simply pass a dictionary with (unprefixed) key-value-pairs to `create_app()` method as named parameter `config`. Settings passed this way take precedence over those from the default configuration and additional config files.
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## Flask commands
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Execute commands with `python -m flask <command>`. You don't need to specify `--app the_works` as long as the environment variable "FLASK_APP" is set to "the_works"; the default configuration file does this.
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Available commands:
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* `run`: Serve app (don't use for production).
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<!--* `init-db`: Create empty SQLite database `works.sqlite` in project root. BE CAREFUL: If a database already exists, it will be deleted with everything in it. // 5/25: ich hab die Fkt. wieder rausgenommen, aber ich könnte sie eigentlich prima wieder einbauen … -->
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* `shell`: start a shell within the app context (I can i.e. import specific table models and test ORM data structures)
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*
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## Dependencies
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### Python Packages
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Required pip packages
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* flask
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* flask-sqlalchemy
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* python-dotenv
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* Pillow
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* pytest
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Optional pip packages
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* flask-debugtoolbar (optional)
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* sqlacodegen (optional; only used from the command line during development)
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### CSS and Javascript resources
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* any regular (not classless) stylesheet from [PicoCSS](https://picocss.com) for general styling
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* `SwitchColorMode.js` from [Yohn's fork of PicoCSS](https://yohn.github.io/PicoCSS/) to enable color mode switching
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* [DataTables](https://datatables.net/) (JS and CSS components) to enable ordering and filtering result tables
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* DataTables requires [jQuery](https://jquery.com/), which can either be bundled with DataTables itself or installed as a separate resource
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### Icons
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some icons from heroicons.com
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## Other useful stuff
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### Export database schema
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Method 1: `sqlite3 the_works.sqlite .schema > outputfile.sql`
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Method 2: Open DB in SQLitebrowser and use File -> Export -> Database to SQL file …
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* keep original CREATE statements
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* export schema only
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* overwrite old schema (DROP TABLE, then CREATE TABLE)
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### Generate `requirements.txt`
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I use [pipreqs](https://pypi.org/project/pipreqs/) to generate the file `requirements.txt`. The package scans all source files for import statements and uses those to extract all required Pip packages. See `pipreqs -h` for usage info.
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### Outdated: Generate SQLAlchemy code from an existing database
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~~Right now~~ In earlier stages, the_works reflects an existing database in order to infer the underlying data models for SQLAlchemy. Of course, this only works if all the tables already exist in the database. If the_works is run with an empty database (this happens when running tests, for example), the app will create fresh tables in the database. The necessary information about the tables can be generated from an existing database with the help of [sqlacodegen](https://pypi.org/project/sqlacodegen/). Just run this command inside the project's root directory:
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`sqlacodegen --generator tables sqlite:///path/to/good/db.sqlite > ./the_works/tables.py`
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The tool sqlacodegen can also generate Python code declaring the data models directly. This would make the use of reflection obsolete. The command would be:
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`sqlacodegen --generator declarative sqlite:///path/to/good/db.sqlite > outputfile.py`
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