paradizelost/paperless-ngx
1
0
Fork 0
mirror of https://github.com/paperless-ngx/paperless-ngx.git synced 2025-10-30 03:56:23 -05:00
Code Issues Packages Projects Releases Wiki Activity

missing migrations

Browse Source
This commit is contained in:
Jonas Winkler
2020-10-29 00:54:42 +01:00
parent e4a13156b9
commit 7e9b584905
1 changed files with 32 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

32
src/documents/migrations/1003_auto_20201028_1751.py Normal file
View File

@@ -0,0 +1,32 @@
# Generated by Django 3.1.2 on 2020-10-28 17:51
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('documents', '1002_auto_20180823_1155'),
]
operations = [
migrations.AlterModelOptions(
name='documenttype',
options={'ordering': ('name',)},
),
migrations.AlterField(
model_name='correspondent',
name='matching_algorithm',
field=models.PositiveIntegerField(choices=[(1, 'Any'), (2, 'All'), (3, 'Literal'), (4, 'Regular Expression'), (5, 'Fuzzy Match'), (6, 'Automatic Classification')], default=1, help_text='Which algorithm you want to use when matching text to the OCR\'d PDF. Here, "any" looks for any occurrence of any word provided in the PDF, while "all" requires that every word provided appear in the PDF, albeit not in the order provided. A "literal" match means that the text you enter must appear in the PDF exactly as you\'ve entered it, and "regular expression" uses a regex to match the PDF. (If you don\'t know what a regex is, you probably don\'t want this option.) Finally, a "fuzzy match" looks for words or phrases that are mostly—but not exactly—the same, which can be useful for matching against documents containg imperfections that foil accurate OCR.'),
),
migrations.AlterField(
model_name='documenttype',
name='matching_algorithm',
field=models.PositiveIntegerField(choices=[(1, 'Any'), (2, 'All'), (3, 'Literal'), (4, 'Regular Expression'), (5, 'Fuzzy Match'), (6, 'Automatic Classification')], default=1, help_text='Which algorithm you want to use when matching text to the OCR\'d PDF. Here, "any" looks for any occurrence of any word provided in the PDF, while "all" requires that every word provided appear in the PDF, albeit not in the order provided. A "literal" match means that the text you enter must appear in the PDF exactly as you\'ve entered it, and "regular expression" uses a regex to match the PDF. (If you don\'t know what a regex is, you probably don\'t want this option.) Finally, a "fuzzy match" looks for words or phrases that are mostly—but not exactly—the same, which can be useful for matching against documents containg imperfections that foil accurate OCR.'),
),
migrations.AlterField(
model_name='tag',
name='matching_algorithm',
field=models.PositiveIntegerField(choices=[(1, 'Any'), (2, 'All'), (3, 'Literal'), (4, 'Regular Expression'), (5, 'Fuzzy Match'), (6, 'Automatic Classification')], default=1, help_text='Which algorithm you want to use when matching text to the OCR\'d PDF. Here, "any" looks for any occurrence of any word provided in the PDF, while "all" requires that every word provided appear in the PDF, albeit not in the order provided. A "literal" match means that the text you enter must appear in the PDF exactly as you\'ve entered it, and "regular expression" uses a regex to match the PDF. (If you don\'t know what a regex is, you probably don\'t want this option.) Finally, a "fuzzy match" looks for words or phrases that are mostly—but not exactly—the same, which can be useful for matching against documents containg imperfections that foil accurate OCR.'),
),
]