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Python-dotenv is a package that loads environment variables from a .env file into Python applications, helping to manage configuration settings easily and securely.

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Python Flask JSON Guide .cursorrules prompt file

This project is heavily reliant on our custom Drawscape Factorio python module.

Here is code examples of how to use the module:

```
from drawscape_factorio import create as createFactorio
from drawscape_factorio import importFUE5

Load the JSON file coming from the FUE5 MOD

with open('/path/to/exported-entities.json, 'r') as file:
json_data = json.load(file)

Parse the JSON data

data = importFUE5(json_data)

Call the create function with the parsed data and settings

result = createFactorio(data, {
'theme_name': 'default',
'color_scheme': 'main',
'show_layers': ['assets', 'belts', 'walls', 'rails', 'electrical', 'spaceship']
})

Save the SVG file

with open(output_file_name, 'w') as f:
f.write(result['svg_string'])
````

Here is my environment.yml that I'm running the project in

name: drawscape_api
channels:

conda-forge
dependencies:
python=3.12
pip
flask
flask-cors
svgwrite
numpy
python-dotenv
- drawscape-factorio
gunicorn
boto3
pip:
- flask[async]

stack:

Python Flask JSON Guide .cursorrules prompt file

Drawscape

0

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Python GitHub Setup .cursorrules prompt file

{
"general": {
"coding_style": {
"language": "Python",
"use_strict": true,
"indentation": "4 spaces",
"max_line_length": 120,
"comments": {
"style": "# for single-line, ''' for multi-line",
"require_comments": true
}
},
"naming_conventions": {
"variables": "snake_case",
"functions": "snake_case",
"classes": "PascalCase",
"interfaces": "PascalCase",
"files": "snake_case"
},
"error_handling": {
"prefer_try_catch": true,
"log_errors": true},
"testing": {
"require_tests": true,
"test_coverage": "80%",
"test_types": ["unit", "integration"]
},
"documentation": {
"require_docs": true,
"doc_tool": "docstrings",
"style_guide": "Google Python Style Guide"
},
"security": {
"require_https": true,
"sanitize_inputs": true,
"validate_inputs": true,
"use_env_vars": true
},
"configuration_management": {
"config_files": [".env"],
"env_management": "python-dotenv",
"secrets_management": "environment variables"
},
"code_review": {
"require_reviews": true,
"review_tool": "GitHub Pull Requests",
"review_criteria": ["functionality", "code quality", "security"]
},
"version_control": {
"system": "Git",
"branching_strategy": "GitHub Flow",
"commit_message_format": "Conventional Commits"
},
"logging": {
  "logging_tool": "Python logging module",
  "log_levels": ["debug", "info", "warn", "error"],
  "log_retention_policy": "7 days"
  },
  "monitoring": {
  "monitoring_tool": "Not specified",
  "metrics": ["file processing time", "classification accuracy", "error rate"]
  },
  "dependency_management": {
  "package_manager": "pip",
  "versioning_strategy": "Semantic Versioning"
  },
  "accessibility": {
  "standards": ["Not applicable"],
  "testing_tools": ["Not applicable"]
  },
  "internationalization": {
  "i18n_tool": "Not applicable",
  "supported_languages": ["English"],
  "default_language": "English"
  },
  "ci_cd": {
  "ci_tool": "GitHub Actions",
  "cd_tool": "Not specified",
  "pipeline_configuration": ".github/workflows/main.yml"
  },
  "code_formatting": {
  "formatter": "Black",
  "linting_tool": "Pylint",
  "rules": ["PEP 8", "project-specific rules"]
  },
  "architecture": {
    "patterns": ["Modular design"],
    "principles": ["Single Responsibility", "DRY"]
    }
    },
    "project_specific": {
    "use_framework": "None",
    "styling": "Not applicable",
    "testing_framework": "pytest",
    "build_tool": "setuptools",
    "deployment": {
    "environment": "Local machine",
    "automation": "Not specified",
    "strategy": "Manual deployment"
    },
    "performance": {
    "benchmarking_tool": "Not specified",
    "performance_goals": {
    "response_time": "< 5 seconds per file",
    "throughput": "Not specified",
    "error_rate": "< 1%"
    }
    }
    },
    "context": {
      "codebase_overview": "Python-based file organization tool using AI for content analysis and classification",
      "libraries": ["watchdog", "spacy", "PyPDF2", "python-docx", "pandas", "beautifulsoup4", "transformers", "scikit-learn", "joblib", "python-dotenv", "torch", "pytest", "shutil", "logging", "pytest-mock"],
      "coding_practices": {
      "modularity": true,
      "DRY_principle": true,
      "performance_optimization": true
      }
      },
      "behavior": {
      "verbosity": {
      "level": 2,
      "range": [0, 3]
      },
      "handle_incomplete_tasks": "Provide partial solution and explain limitations",
      "ask_for_clarification": true,
      "communication_tone": "Professional and concise"
      }
      }