PM-pinou
85 lines
5.0 KiB
Python
85 lines
5.0 KiB
Python
# Generated by Django 4.2.30 on 2026-07-13 14:36
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from django.db import migrations, models
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import django.db.models.deletion
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class Migration(migrations.Migration):
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initial = True
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dependencies = [
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]
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operations = [
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migrations.CreateModel(
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name='AnalysisRun',
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fields=[
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('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
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('csv_glob', models.CharField(help_text='Glob pattern for CSV files', max_length=1024)),
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('config', models.JSONField(blank=True, default=dict, help_text='YAML config snapshot')),
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('status', models.CharField(choices=[('pending', 'Pending'), ('loading', 'Loading Data'), ('profiling', 'Profiling'), ('aggregating', 'Building Entity Profiles'), ('clustering', 'Clustering'), ('extracting', 'Extracting Features'), ('completed', 'Completed'), ('failed', 'Failed')], default='pending', max_length=32)),
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('created_at', models.DateTimeField(auto_now_add=True)),
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('updated_at', models.DateTimeField(auto_now=True)),
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('error_message', models.TextField(blank=True, default='')),
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('total_flows', models.IntegerField(blank=True, null=True)),
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('entity_count', models.IntegerField(blank=True, null=True)),
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('cluster_count', models.IntegerField(blank=True, null=True)),
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('entity_column', models.CharField(blank=True, default='', help_text='Auto-detected entity column name', max_length=256)),
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],
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options={
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'ordering': ['-created_at'],
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},
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),
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migrations.CreateModel(
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name='ClusterResult',
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fields=[
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('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
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('cluster_label', models.IntegerField(help_text='Cluster label (-1 for noise)')),
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('size', models.IntegerField(help_text='Number of entities in this cluster')),
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('proportion', models.FloatField(blank=True, help_text='Proportion of total entities', null=True)),
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('noise_ratio', models.FloatField(blank=True, help_text='Noise ratio of the clustering', null=True)),
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('silhouette_score', models.FloatField(blank=True, help_text='Silhouette score (sampled if large)', null=True)),
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('run', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='clusters', to='tianxuan_analysis.analysisrun')),
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],
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options={
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'unique_together': {('run', 'cluster_label')},
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},
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),
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migrations.CreateModel(
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name='EntityProfile',
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fields=[
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('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
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('entity_value', models.CharField(help_text='Entity identifier (IP, domain, etc.)', max_length=512)),
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('cluster_label', models.IntegerField(blank=True, help_text='Assigned cluster (-1=noise)', null=True)),
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('feature_json', models.JSONField(blank=True, default=dict, help_text='Aggregated entity features as dict')),
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('embedding_x', models.FloatField(blank=True, help_text='PCA-2D X coordinate', null=True)),
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('embedding_y', models.FloatField(blank=True, help_text='PCA-2D Y coordinate', null=True)),
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('cluster', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='entities', to='tianxuan_analysis.clusterresult')),
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('run', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='entities', to='tianxuan_analysis.analysisrun')),
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],
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options={
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'unique_together': {('run', 'entity_value')},
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},
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),
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migrations.CreateModel(
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name='ClusterFeature',
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fields=[
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('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
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('feature_name', models.CharField(max_length=256)),
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('mean', models.FloatField(blank=True, null=True)),
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('std', models.FloatField(blank=True, null=True)),
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('median', models.FloatField(blank=True, null=True)),
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('p25', models.FloatField(blank=True, null=True)),
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('p75', models.FloatField(blank=True, null=True)),
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('missing_rate', models.FloatField(blank=True, null=True)),
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('distinguishing_score', models.FloatField(blank=True, help_text='Z-score or ANOVA F-score', null=True)),
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('distinguishing_method', models.CharField(default='zscore', max_length=16)),
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('cluster', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='features', to='tianxuan_analysis.clusterresult')),
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],
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options={
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'unique_together': {('cluster', 'feature_name')},
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},
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),
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]
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