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It allows pilots, dispatchers, and others\ninterested in flight data to quickly parse the files into Python dictionaries\nor a SQLite database for use in other programs. For example, the parsed data\ncan then be used as a database for flight planning tools.\n\nIf you are interested in seeing the differences between each data cycle, have\na look at [NASRDiff](https://github.com/misterrodg/NASRDiff).\n\n## Versions\n\n| Version | Description                          | Release Date |\n| ------- | ------------------------------------ | ------------ |\n| 1.1.0   | Added `to_str()` methods to records. | 2025-11-12   |\n| 1.0.1   | `__repr()__` Bugfix for enums.       | 2025-11-06   |\n| 1.0.0   | Initial public release.              | 2025-11-06   |\n\nA changelog is available in the [CHANGELOG.md](./CHANGELOG.md) with additional \ndetail and guidance.\n\n## Installation\n\nInstall using `pip`:\n\n```\npip install nasrparse\n```\n\n## Usage\n\nUsage is relatively straightforward. Setting the path to the files can be\nsomewhat finnicky, as it will only accept relative paths. To keep things simple,\nplace the NASR files in subdirectory of your project directory. Otherwise, if\nyou want to go up several folders into a download folder, it might end up\nlooking like `../../../../Downloads/28DaySubscription_Effective_[date]/CSV_Data/[date]_CSV`.\n\nGiven the amount of data, parsing can take a moment. If dumping the data to a\nfile, that can also add time. Dumping every airport to JSON can take around\n10 seconds, and the result file is about 16MB.\n\n### Examples\n\nStart by importing `nasrparse`, setting the path to the NASR CSV directory, and\nthen parsing the data.\n\n```python\nimport nasrparse\n\n# Initialize the parser:\nfrom nasrparse import NASR\n\n# Set the relative path to where you have the NASR CSV files:\nn = NASR(\"./data/CSV_DATA/20_MAR_2025_CSV\")\n\n# Parse the data in the file:\nn.parse()\n```\n\n#### Exporting Data\n\n##### Database\n\nEach object has its own `to_db()` method. This is useful when you would like\nthe data to persist, or query it using standard database methods:\n\n```python\nfrom nasrparse import NASR\n\nn = NASR(\"./data/CSV_DATA/20_MAR_2025_CSV\")\nn.parse()\nn.to_db(\"NASR.db\")\n```\n\n### NASR Objects\n\nThe individual NASR objects are exposed in the package and include the FAA\ndescriptions in the code documentation. More detail can also be found in the\nindividual `[section] DATA LAYOUT.pdf` (e.g. `APT DATA LAYOUT.pdf`) files\nincluded with the CSV files in the same directory.\n\n![Code Documentation](./docs/images/code_doc.png)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmisterrodg%2Fnasrparse","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmisterrodg%2Fnasrparse","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmisterrodg%2Fnasrparse/lists"}