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8
Makefile
8
Makefile
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@ -1,5 +1,5 @@
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api:
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uv run granian --interface asgi server.main:app --host 0.0.0.0
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alembic upgrade head && uv run granian --interface asgi server.main:app --host 0.0.0.0
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dog-train:
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uv run ml/dogs.py
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@ -16,3 +16,9 @@ lint:
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pipinstall:
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uv pip sync requirements.txt
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migrate-up:
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alembic upgrade head
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migration-generate:
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git rev-parse --short HEAD | xargs -I {} alembic revision --autogenerate -m "{}"
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@ -0,0 +1,116 @@
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# A generic, single database configuration.
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[alembic]
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# path to migration scripts
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script_location = server/migration
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# template used to generate migration file names; The default value is %%(rev)s_%%(slug)s
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# Uncomment the line below if you want the files to be prepended with date and time
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# see https://alembic.sqlalchemy.org/en/latest/tutorial.html#editing-the-ini-file
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# for all available tokens
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file_template = %%(year)d-%%(month).2d-%%(day).2d-%%(hour).2d%%(minute).2d-%%(rev)s-parent-commit-%%(slug)s
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# sys.path path, will be prepended to sys.path if present.
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# defaults to the current working directory.
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prepend_sys_path = .
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# timezone to use when rendering the date within the migration file
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# as well as the filename.
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# If specified, requires the python-dateutil library that can be
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# installed by adding `alembic[tz]` to the pip requirements
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# string value is passed to dateutil.tz.gettz()
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# leave blank for localtime
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# timezone =
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# max length of characters to apply to the
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# "slug" field
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# truncate_slug_length = 40
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# set to 'true' to run the environment during
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# the 'revision' command, regardless of autogenerate
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# revision_environment = false
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# set to 'true' to allow .pyc and .pyo files without
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# a source .py file to be detected as revisions in the
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# versions/ directory
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# sourceless = false
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# version location specification; This defaults
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# to migration/versions. When using multiple version
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# directories, initial revisions must be specified with --version-path.
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# The path separator used here should be the separator specified by "version_path_separator" below.
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# version_locations = %(here)s/bar:%(here)s/bat:migration/versions
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# version path separator; As mentioned above, this is the character used to split
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# version_locations. The default within new alembic.ini files is "os", which uses os.pathsep.
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# If this key is omitted entirely, it falls back to the legacy behavior of splitting on spaces and/or commas.
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# Valid values for version_path_separator are:
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#
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# version_path_separator = :
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# version_path_separator = ;
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# version_path_separator = space
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version_path_separator = os # Use os.pathsep. Default configuration used for new projects.
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# set to 'true' to search source files recursively
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# in each "version_locations" directory
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# new in Alembic version 1.10
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# recursive_version_locations = false
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# the output encoding used when revision files
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# are written from script.py.mako
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# output_encoding = utf-8
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sqlalchemy.url = driver://user:pass@localhost/dbname
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[post_write_hooks]
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# post_write_hooks defines scripts or Python functions that are run
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# on newly generated revision scripts. See the documentation for further
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# detail and examples
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# format using "black" - use the console_scripts runner, against the "black" entrypoint
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# hooks = black
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# black.type = console_scripts
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# black.entrypoint = black
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# black.options = -l 79 REVISION_SCRIPT_FILENAME
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# lint with attempts to fix using "ruff" - use the exec runner, execute a binary
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# hooks = ruff
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# ruff.type = exec
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# ruff.executable = %(here)s/.venv/bin/ruff
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# ruff.options = --fix REVISION_SCRIPT_FILENAME
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# Logging configuration
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[loggers]
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keys = root,sqlalchemy,alembic
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[handlers]
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keys = console
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[formatters]
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keys = generic
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[logger_root]
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level = WARN
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handlers = console
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qualname =
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[logger_sqlalchemy]
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level = WARN
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handlers =
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qualname = sqlalchemy.engine
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[logger_alembic]
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level = INFO
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handlers =
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qualname = alembic
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[handler_console]
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class = StreamHandler
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args = (sys.stderr,)
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level = NOTSET
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formatter = generic
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[formatter_generic]
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format = %(levelname)-5.5s [%(name)s] %(message)s
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datefmt = %H:%M:%S
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@ -1,11 +1,10 @@
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import json
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from PIL import ImageFile
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import torch.nn as nn
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from torchvision.datasets import ImageFolder # type: ignore
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from PIL import ImageFile
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from torch.utils.data import DataLoader
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from train import get_labels, load_model, get_loaders, train, show, DEVICE # type: ignore
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from torchvision.datasets import ImageFolder # type: ignore
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from train import DEVICE, get_labels, get_loaders, load_model, show, train # type: ignore
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ImageFile.LOAD_TRUNCATED_IMAGES = True
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@ -1,11 +1,10 @@
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import json
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from PIL import ImageFile
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import torch.nn as nn
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from torchvision.datasets import ImageFolder # type: ignore
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from PIL import ImageFile
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from torch.utils.data import DataLoader
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from train import get_labels, load_model, get_loaders, train, show, DEVICE # type: ignore
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from torchvision.datasets import ImageFolder # type: ignore
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from train import DEVICE, get_labels, get_loaders, load_model, show, train # type: ignore
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ImageFile.LOAD_TRUNCATED_IMAGES = True
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|
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@ -1,12 +1,12 @@
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import torch
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from torchvision import transforms # type: ignore
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import torch.nn.functional as F
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from PIL import Image
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import json
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import torch
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import torch.nn.functional as F
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from PIL import Image
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from torchvision import transforms # type: ignore
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# Создание labels_dict для соответствия классов и индексов
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with open("labels.json", "r") as f:
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with open("labels.json") as f:
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data_labels = f.read()
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labels_dict = json.loads(data_labels)
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|
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16
ml/train.py
16
ml/train.py
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@ -1,13 +1,13 @@
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import os
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import matplotlib.pyplot as plt # type: ignore
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import torch
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import torch.nn as nn
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from torchvision.datasets import ImageFolder # type: ignore
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from torch.utils.data import Dataset, DataLoader, random_split
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from torchvision import transforms # type: ignore
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import torchvision
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from torch.utils.data import DataLoader, Dataset, random_split
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from torchvision import transforms # type: ignore
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from torchvision.datasets import ImageFolder # type: ignore
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from torchvision.models import ResNet50_Weights # type: ignore
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from typing import Tuple
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DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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@ -29,7 +29,7 @@ def get_labels(input_dir, img_size):
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return labels_dict, dataset
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def get_loaders(dataset: Dataset) -> Tuple[DataLoader, DataLoader]:
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def get_loaders(dataset: Dataset) -> tuple[DataLoader, DataLoader]:
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# Разделение данных на тренировочные и валидационные
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train_size = int(0.8 * float(len(dataset))) # type: ignore[arg-type]
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val_size = len(dataset) - train_size # type: ignore[arg-type]
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@ -61,7 +61,7 @@ def train(
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model: nn.Module,
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train_loader: DataLoader,
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val_loader: DataLoader,
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) -> Tuple[list[float], list[float], list[float], list[float]]:
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) -> tuple[list[float], list[float], list[float], list[float]]:
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criterion = torch.nn.CrossEntropyLoss()
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optimizer = torch.optim.Adam(model.fc.parameters(), lr=1e-4) # type: ignore[union-attr]
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# История метрик
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@ -96,9 +96,7 @@ def train(
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train_acc = 100.0 * correct / total
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train_loss_history.append(train_loss)
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train_acc_history.append(train_acc)
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print(
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f"Epoch {epoch + 1}/{num_epochs}, Train Loss: {train_loss:.4f}, Train Accuracy: {train_acc:.2f}%"
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)
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print(f"Epoch {epoch + 1}/{num_epochs}, Train Loss: {train_loss:.4f}, Train Accuracy: {train_acc:.2f}%")
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# Оценка на валидационных данных
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model.eval()
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|
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123
pyproject.toml
123
pyproject.toml
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@ -29,6 +29,11 @@ dependencies = [
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"betterconf>=4.5.0",
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"dataclasses-ujson>=0.0.34",
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"asyncpg>=0.31.0",
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"alembic>=1.18.0",
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"aioboto3>=7.0.0",
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"boto3>=1.42.9",
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"python-magic>=0.4.27",
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||||
"psycopg2-binary>=2.9.11",
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||||
]
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||||
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||||
[project.optional-dependencies]
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@ -43,17 +48,117 @@ default = [
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"matplotlib>=3.10.1",
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]
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||||
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[tool.uv.sources]
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torch = [
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{ index = "pytorch-cpu", extra = "default" },
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# MYPY
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[tool.mypy]
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exclude = [
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".venv",
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"venv",
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||||
"tmp",
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"scripts",
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||||
"tests"
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||||
]
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||||
plugins = ["sqlalchemy.ext.mypy.plugin"]
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mypy_path = "./stubs"
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ignore_missing_imports = true
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# RUFF
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[tool.ruff]
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target-version = "py312"
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show-fixes = true
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src = ["app"]
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# Same as Black.
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line-length = 120
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indent-width = 4
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# Exclude a variety of commonly ignored directories.
|
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exclude = [
|
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".bzr",
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".direnv",
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".eggs",
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".git",
|
||||
".git-rewrite",
|
||||
".hg",
|
||||
".ipynb_checkpoints",
|
||||
".mypy_cache",
|
||||
".nox",
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||||
".pants.d",
|
||||
".pyenv",
|
||||
".pytest_cache",
|
||||
".pytype",
|
||||
".ruff_cache",
|
||||
".svn",
|
||||
".tox",
|
||||
".venv",
|
||||
".vscode",
|
||||
"__pypackages__",
|
||||
"_build",
|
||||
"buck-out",
|
||||
"build",
|
||||
"dist",
|
||||
"node_modules",
|
||||
"site-packages",
|
||||
"venv",
|
||||
"stubs",
|
||||
"scripts",
|
||||
]
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||||
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torchvision = [
|
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{ index = "pytorch-cpu", extra = "default" },
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[tool.ruff.lint.isort]
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known-first-party = ["app"]
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[tool.ruff.format]
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# Like Black, use double quotes for strings.
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quote-style = "double"
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# Like Black, indent with spaces, rather than tabs.
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indent-style = "space"
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# Like Black, respect magic trailing commas.
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skip-magic-trailing-comma = false
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# Like Black, automatically detect the appropriate line ending.
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line-ending = "auto"
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[tool.ruff.lint.per-file-ignores]
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"stubs/*" = ["F403"]
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"server/migration/*" = ["E501", "F403"]
|
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"server/config/__init__.py" = ["E501"]
|
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"scripts/*" = ["T201", "E501"]
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"server/admin/*" = ["E501", "E711"]
|
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"vk_api/*"= ["T201", "C416", "A001", "E501"]
|
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"ml/*"= ["T201", "C416", "A001", "E501", "C416", "N812"]
|
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"tests/**/*.py" = [
|
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"E501", "ASYNC230",
|
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# at least this three should be fine in tests:
|
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"S101", # asserts allowed in tests...
|
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"S106", # Possible hardcoded password assigned to argument: "password"
|
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"S110", # consider logging the exception
|
||||
"ARG", # Unused function args -> fixtures nevertheless are functionally relevant...
|
||||
"FBT", # Don't care about booleans as positional arguments in tests, e.g. via @pytest.mark.parametrize()
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||||
# The below are debateable
|
||||
"PLR2004", # Magic value used in comparison, ...
|
||||
"S311", # Standard pseudo-random generators are not suitable for cryptographic purposes
|
||||
"INP001", # File `...` is part of an implicit namespace package. Add an `__init__.py`.
|
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"SLF001", # Private member accessed: `_...`
|
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]
|
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"tests/__init__.py" = ["I001"]
|
||||
|
||||
[[tool.uv.index]]
|
||||
name = "pytorch-cpu"
|
||||
url = "https://download.pytorch.org/whl/cpu"
|
||||
explicit = true
|
||||
[tool.ruff.lint]
|
||||
# https://docs.astral.sh/ruff/rules/
|
||||
select = ["DTZ", "F", "C4", "B", "A", "E", "T", "I", "N", "UP", "ASYNC", "Q"]
|
||||
ignore = ["E712", "B904", "B019", "C417"]
|
||||
|
||||
# Allow fix for all enabled rules (when `--fix`) is provided.
|
||||
fixable = ["ALL"]
|
||||
unfixable = []
|
||||
# Allow unused variables when underscore-prefixed.
|
||||
dummy-variable-rgx = "^(_+|(_+[a-zA-Z0-9_]*[a-zA-Z0-9]+?))$"
|
||||
|
||||
[tool.ruff.lint.mccabe]
|
||||
# https://docs.astral.sh/ruff/settings/#mccabe
|
||||
# Flag errors (`C901`) whenever the complexity level exceeds 5.
|
||||
max-complexity = 12
|
||||
|
||||
[tool.ruff.lint.flake8-pytest-style]
|
||||
# https://docs.astral.sh/ruff/settings/#flake8-pytest-style
|
||||
fixture-parentheses = false
|
||||
mark-parentheses = false
|
||||
|
|
|
|||
|
|
@ -0,0 +1,84 @@
|
|||
import os
|
||||
import random
|
||||
import shutil
|
||||
|
||||
from PIL import Image
|
||||
|
||||
|
||||
def copy_convert_to_webp(
|
||||
source_dir,
|
||||
dest_dir,
|
||||
samples_per_folder=5,
|
||||
size_threshold=1024 * 1024,
|
||||
quality_high=90,
|
||||
quality_low=70,
|
||||
):
|
||||
"""
|
||||
Копирует структуру папок и конвертирует изображения в WebP
|
||||
:param source_dir: Исходная директория с изображениями
|
||||
:param dest_dir: Целевая директория для копирования
|
||||
:param samples_per_folder: Количество изображений для выбора из каждой папки
|
||||
:param size_threshold: Пороговый размер файла (в байтах) для сильного сжатия
|
||||
:param quality_high: Качество для маленьких изображений (0-100)
|
||||
:param quality_low: Качество для больших изображений (0-100)
|
||||
"""
|
||||
image_extensions = (".jpg", ".jpeg", ".png", ".gif", ".bmp", ".tiff", ".webp")
|
||||
|
||||
def is_image_file(filename):
|
||||
return filename.lower().endswith(image_extensions)
|
||||
|
||||
def convert_to_webp(src_path, dest_path, quality):
|
||||
try:
|
||||
with Image.open(src_path) as img:
|
||||
# Сохраняем прозрачность для RGBA
|
||||
if img.mode in ("RGBA", "LA"):
|
||||
img = img.convert("RGBA")
|
||||
img.save(dest_path, "WEBP", quality=quality, lossless=False, method=6)
|
||||
else:
|
||||
# Конвертируем в RGB для JPEG-подобных изображений
|
||||
img = img.convert("RGB")
|
||||
img.save(dest_path, "WEBP", quality=quality, method=6)
|
||||
except Exception as e:
|
||||
print(f"Error converting {src_path}: {e}")
|
||||
return False
|
||||
return True
|
||||
|
||||
# Создаем корневую целевую папку
|
||||
os.makedirs(dest_dir, exist_ok=True)
|
||||
|
||||
for root, dirs, files in os.walk(source_dir):
|
||||
rel_path = os.path.relpath(root, source_dir)
|
||||
target_dir = os.path.join(dest_dir, rel_path)
|
||||
os.makedirs(target_dir, exist_ok=True)
|
||||
|
||||
images = [f for f in files if is_image_file(f)]
|
||||
if not images:
|
||||
continue
|
||||
|
||||
selected = random.sample(images, min(samples_per_folder, len(images)))
|
||||
|
||||
for file in selected:
|
||||
src_path = os.path.join(root, file)
|
||||
base_name = os.path.splitext(file)[0]
|
||||
dest_path = os.path.join(target_dir, f"{base_name}.webp")
|
||||
|
||||
# Определяем качество на основе размера
|
||||
file_size = os.path.getsize(src_path)
|
||||
quality = quality_low if file_size > size_threshold else quality_high
|
||||
|
||||
# Конвертируем в WebP
|
||||
if not convert_to_webp(src_path, dest_path, quality):
|
||||
# Если ошибка конвертации - копируем оригинал
|
||||
shutil.copy2(src_path, dest_path)
|
||||
print(f"Copied original file instead: {file}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
copy_convert_to_webp(
|
||||
source_dir="assets",
|
||||
dest_dir="webp_output",
|
||||
samples_per_folder=5,
|
||||
size_threshold=1 * 1024 * 20, # 1 MB
|
||||
quality_high=70,
|
||||
quality_low=70,
|
||||
)
|
||||
|
|
@ -0,0 +1,167 @@
|
|||
#!/usr/bin/env python3
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
"""
|
||||
import_beerds_sql.py
|
||||
|
||||
Скрипт читает файлы из каталогов:
|
||||
- server/modules/descriptions/repository/breed_descriptions
|
||||
- server/modules/descriptions/repository/breed_signs
|
||||
|
||||
и вместо непосредственной вставки генерирует PostgreSQL‑SQL‑файл, который
|
||||
можно применить через `psql -f <имя_файла.sql>`:
|
||||
|
||||
CREATE TABLE beerds.beerds (
|
||||
id varchar NOT NULL,
|
||||
name text NOT NULL,
|
||||
descriptions text NOT NULL,
|
||||
signs json NOT NULL,
|
||||
alias text NOT NULL,
|
||||
CONSTRAINT beerds_pkey PRIMARY KEY (id)
|
||||
);
|
||||
"""
|
||||
|
||||
import sys
|
||||
import json
|
||||
import hashlib
|
||||
import pathlib
|
||||
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# 2️⃣ Путь к каталогам (можно изменить под свой проект)
|
||||
# ------------------------------------------------------------------
|
||||
BASE_DIR = pathlib.Path(__file__).resolve().parent.parent
|
||||
DESC_DIR = BASE_DIR / "server/modules/descriptions/repository/breed_descriptions"
|
||||
SIGN_DIR = BASE_DIR / "server/modules/descriptions/repository/breed_signs"
|
||||
print(f"DESC_DIR = {DESC_DIR}")
|
||||
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# 3️⃣ Функции чтения файлов
|
||||
# ------------------------------------------------------------------
|
||||
def read_text_file(path: pathlib.Path) -> str:
|
||||
"""Возвращает содержимое текстового файла (unicode)."""
|
||||
with path.open("r", encoding="utf-8") as f:
|
||||
return f.read().strip()
|
||||
|
||||
|
||||
def read_json_file(path: pathlib.Path) -> dict:
|
||||
"""Возвращает JSON‑объект из файла."""
|
||||
with path.open("r", encoding="utf-8") as f:
|
||||
return json.load(f)
|
||||
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# 4️⃣ Формируем словарь: имя → (описание, сигналы)
|
||||
# ------------------------------------------------------------------
|
||||
def build_breed_map(desc_dir: pathlib.Path, sign_dir: pathlib.Path) -> dict:
|
||||
"""Возвращает dict: stem → (description, signs)"""
|
||||
desc_files = {p.stem: p for p in desc_dir.glob("*.txt")}
|
||||
sign_files = {p.stem: p for p in sign_dir.glob("*.txt")}
|
||||
|
||||
common_keys = desc_files.keys() & sign_files.keys()
|
||||
if not common_keys:
|
||||
print("⚠️ Нет общих файлов между каталогами описаний и сигналов.")
|
||||
return {}
|
||||
|
||||
breeds = {}
|
||||
for key in sorted(common_keys):
|
||||
desc_path = desc_files[key]
|
||||
sign_path = sign_files[key]
|
||||
try:
|
||||
description = read_text_file(desc_path)
|
||||
except Exception as e:
|
||||
print(f"❌ Не удалось прочитать описание {desc_path}: {e}")
|
||||
continue
|
||||
try:
|
||||
signs = read_json_file(sign_path)
|
||||
except Exception as e:
|
||||
print(f"❌ Не удалось прочитать сигналы {sign_path}: {e}")
|
||||
continue
|
||||
breeds[key] = (description, signs)
|
||||
return breeds
|
||||
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# 5️⃣ Генерация id (если нужно уникальное)
|
||||
# ------------------------------------------------------------------
|
||||
def generate_id(name: str, alias: str) -> str:
|
||||
"""Генерирует MD5‑hash из `name:alias`."""
|
||||
key = f"{name}:{alias}"
|
||||
return hashlib.md5(key.encode("utf-8")).hexdigest()
|
||||
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# 6️⃣ Генерация SQL‑файла
|
||||
# ------------------------------------------------------------------
|
||||
def write_sql_file(breeds: dict, out_path: pathlib.Path):
|
||||
"""Создаёт один .sql‑файл, содержащий INSERT‑операции для всех пород."""
|
||||
if not breeds:
|
||||
print("⚠️ Нет данных для генерации SQL.")
|
||||
return
|
||||
|
||||
lines = []
|
||||
header = (
|
||||
"-- Автоматически сгенерированный скрипт вставки пород\n"
|
||||
"-- Запустить: psql -f beerds_insert.sql\n\n"
|
||||
"BEGIN;\n"
|
||||
)
|
||||
lines.append(header)
|
||||
|
||||
# Формируем один блок INSERT с несколькими строками VALUES
|
||||
# 1. Столбцы
|
||||
cols = "(id, name, descriptions, signs, alias)"
|
||||
# 2. Генерируем строки VALUES
|
||||
value_lines = []
|
||||
for name, (description, signs) in breeds.items():
|
||||
alias = name # можно изменить при необходимости
|
||||
breed_id = generate_id(name, alias)
|
||||
# Подготовка значений: экранирование апострофов и JSON
|
||||
escaped_name = name.replace("_", " ").replace("'", "''")
|
||||
escaped_alias = alias.replace("'", "''")
|
||||
escaped_desc = description.replace("'", "''")
|
||||
# JSON как строка (в PostgreSQL json можно передавать как текст)
|
||||
json_str = json.dumps(signs, ensure_ascii=False).replace("'", "''")
|
||||
value_line = f"('{breed_id}', '{escaped_name}', '{escaped_desc}', '{json_str}', '{escaped_alias}')"
|
||||
value_lines.append(value_line)
|
||||
|
||||
# Объединяем VALUES через запятую
|
||||
values_section = ",\n".join(value_lines)
|
||||
insert_stmt = (
|
||||
f"INSERT INTO beerds.beerds {cols}\n"
|
||||
f"VALUES\n{values_section}\n"
|
||||
f"ON CONFLICT (id) DO UPDATE\n"
|
||||
f" SET name = EXCLUDED.name,\n"
|
||||
f" descriptions = EXCLUDED.descriptions,\n"
|
||||
f" signs = EXCLUDED.signs,\n"
|
||||
f" alias = EXCLUDED.alias;\n"
|
||||
)
|
||||
lines.append(insert_stmt)
|
||||
lines.append("\nCOMMIT;")
|
||||
|
||||
# Записываем в файл
|
||||
out_path.write_text("\n".join(lines), encoding="utf-8")
|
||||
print(f"✅ SQL‑файл успешно сгенерирован: {out_path}")
|
||||
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# 7️⃣ Основная точка входа
|
||||
# ------------------------------------------------------------------
|
||||
def main():
|
||||
print("🔍 Читаем файлы…")
|
||||
breeds_map = build_breed_map(DESC_DIR, SIGN_DIR)
|
||||
|
||||
if not breeds_map:
|
||||
print("❌ Ничего не найдено. Завершение.")
|
||||
sys.exit(1)
|
||||
|
||||
# Путь для вывода SQL‑файла
|
||||
sql_file_path = BASE_DIR / "beerds_insert.sql"
|
||||
print(f"📝 Записываем INSERT‑операции в файл: {sql_file_path}")
|
||||
write_sql_file(breeds_map, sql_file_path)
|
||||
|
||||
print("🎉 Готово!")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
|
|
@ -0,0 +1,46 @@
|
|||
import json
|
||||
from pathlib import Path
|
||||
|
||||
|
||||
def generate_folder_structure(root_path):
|
||||
result = {}
|
||||
# Поддерживаемые форматы изображений
|
||||
image_ext = {".jpg", ".jpeg", ".png", ".gif", ".bmp", ".webp", ".tiff"}
|
||||
|
||||
# Основные категории (cat и dog)
|
||||
for category in ["cat", "dog"]:
|
||||
category_path = Path(root_path) / category
|
||||
if not category_path.is_dir():
|
||||
continue
|
||||
|
||||
category_dict = {}
|
||||
# Обрабатываем подпапки внутри категории
|
||||
for subfolder in category_path.iterdir():
|
||||
if subfolder.is_dir():
|
||||
# Собираем изображения
|
||||
images = [
|
||||
file.name for file in subfolder.iterdir() if file.is_file() and file.suffix.lower() in image_ext
|
||||
]
|
||||
category_dict[subfolder.name] = sorted(images)
|
||||
|
||||
result[category] = category_dict
|
||||
|
||||
return result
|
||||
|
||||
|
||||
def save_to_json(data, output_file):
|
||||
with open(output_file, "w", encoding="utf-8") as f:
|
||||
json.dump(data, f, ensure_ascii=False, indent=2)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
# Настройки
|
||||
ASSETS_DIR = "server/static/assets"
|
||||
OUTPUT_JSON = "structure.json"
|
||||
|
||||
# Генерация структуры
|
||||
structure = generate_folder_structure(ASSETS_DIR)
|
||||
|
||||
# Сохранение в файл
|
||||
save_to_json(structure, OUTPUT_JSON)
|
||||
print(f"JSON структура сохранена в файл: {OUTPUT_JSON}")
|
||||
|
|
@ -22,11 +22,9 @@ class AppConfig:
|
|||
sentry_dns: str = field("SENTRY_DNS", default="")
|
||||
log_level: str = field("LOG_LEVEL", "INFO")
|
||||
|
||||
db_uri: str = field(
|
||||
"DB_URI", "postgresql+asyncpg://svcuser:svcpass@localhost:5432/svc"
|
||||
)
|
||||
db_uri: str = field("DB_URI", "postgresql+asyncpg://svcuser:svcpass@localhost:5432/svc")
|
||||
db_pass_salt: str = field("DB_PASS_SALT", "")
|
||||
db_search_path: str = field("DB_SEARCH_PATH", "public")
|
||||
db_search_path: str = field("DB_SEARCH_PATH", "beerds")
|
||||
|
||||
fs_local_mount_dir: str = field("FS_LOCAL_MOUNT_DIR", default="./tmp/files")
|
||||
fs_s3_bucket: str = field("FS_S3_BUCKET", "")
|
||||
|
|
|
|||
|
|
@ -1,14 +1,13 @@
|
|||
from abc import ABCMeta, abstractmethod
|
||||
from typing import Optional
|
||||
|
||||
|
||||
class CacheRepository(metaclass=ABCMeta):
|
||||
@abstractmethod
|
||||
async def get(self, key: str) -> Optional[str]:
|
||||
async def get(self, key: str) -> str | None:
|
||||
pass
|
||||
|
||||
@abstractmethod
|
||||
async def set(self, key: str, data: str, _exp_min: Optional[int] = None):
|
||||
async def set(self, key: str, data: str, _exp_min: int | None = None):
|
||||
pass
|
||||
|
||||
@abstractmethod
|
||||
|
|
@ -23,10 +22,10 @@ class LocalCacheRepository(CacheRepository):
|
|||
def __init__(self) -> None:
|
||||
self._data = {}
|
||||
|
||||
async def get(self, key: str) -> Optional[str]:
|
||||
async def get(self, key: str) -> str | None:
|
||||
return self._data.get(key)
|
||||
|
||||
async def set(self, key: str, data: str, _exp_min: Optional[int] = None):
|
||||
async def set(self, key: str, data: str, _exp_min: int | None = None):
|
||||
self._data[key] = data
|
||||
|
||||
async def delete(self, key: str):
|
||||
|
|
|
|||
|
|
@ -1,10 +1,12 @@
|
|||
"""Abstract realiztion for DB"""
|
||||
|
||||
from typing import Any, AsyncContextManager, Awaitable, Callable, TypeAlias
|
||||
from collections.abc import Awaitable, Callable
|
||||
from contextlib import AbstractAsyncContextManager as AsyncContextManager
|
||||
from typing import Any
|
||||
|
||||
from server.config import AppConfig
|
||||
|
||||
ExecuteFun: TypeAlias = Callable[[Any], Awaitable[None]]
|
||||
type ExecuteFun = Callable[[Any], Awaitable[None]]
|
||||
|
||||
|
||||
class ConnectError(Exception):
|
||||
|
|
|
|||
|
|
@ -1,11 +1,9 @@
|
|||
from typing import Type, TypeVar
|
||||
|
||||
from sqlalchemy.orm import registry
|
||||
|
||||
mapper_registry = registry()
|
||||
|
||||
DC = TypeVar("DC")
|
||||
|
||||
|
||||
def dict_to_dataclass(data: dict, class_type: Type[DC]) -> DC:
|
||||
def dict_to_dataclass[T](data: dict, class_type: type[T]) -> T:
|
||||
return class_type(**data)
|
||||
|
|
|
|||
|
|
@ -1,4 +1,5 @@
|
|||
from typing import Any, AsyncContextManager
|
||||
from contextlib import AbstractAsyncContextManager as AsyncContextManager
|
||||
from typing import Any
|
||||
|
||||
from server.config import AppConfig
|
||||
from server.infra.db.abc import AbstractDB, AbstractSession
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
from copy import copy
|
||||
from dataclasses import Field, asdict, dataclass
|
||||
from enum import Enum
|
||||
from typing import Any, ClassVar, Optional, Protocol, assert_never
|
||||
from typing import Any, ClassVar, Protocol, assert_never
|
||||
|
||||
from sqlalchemy import Select, and_, or_
|
||||
|
||||
|
|
@ -28,7 +28,7 @@ class FilterLeftField(Protocol):
|
|||
class Filter:
|
||||
right: Any
|
||||
sign: FilterSign
|
||||
left: Optional[FilterLeftField] = None
|
||||
left: FilterLeftField | None = None
|
||||
|
||||
@staticmethod
|
||||
def not_eq(f1: Any, f2: Any):
|
||||
|
|
@ -79,33 +79,27 @@ class RestrictionField:
|
|||
|
||||
@dataclass
|
||||
class QueryRestriction:
|
||||
filters: Optional[list[Filter]] = None
|
||||
limit: Optional[int] = None
|
||||
offset: Optional[int] = None
|
||||
sort: Optional[list[RestrictionField]] = None
|
||||
filters: list[Filter] | None = None
|
||||
limit: int | None = None
|
||||
offset: int | None = None
|
||||
sort: list[RestrictionField] | None = None
|
||||
|
||||
|
||||
@dataclass(frozen=False)
|
||||
class FilterQuery:
|
||||
filters: list[Filter]
|
||||
limit: Optional[int] = None
|
||||
offset: Optional[int] = None
|
||||
sort: Optional[list[RestrictionField]] = None
|
||||
limit: int | None = None
|
||||
offset: int | None = None
|
||||
sort: list[RestrictionField] | None = None
|
||||
|
||||
@staticmethod
|
||||
def mass_and(fields: list[object], values: list[Any]) -> "FilterQuery":
|
||||
return FilterQuery(
|
||||
filters=[Filter.eq(field, val) for field, val in zip(fields, values)]
|
||||
)
|
||||
return FilterQuery(filters=[Filter.eq(field, val) for field, val in zip(fields, values, strict=True)])
|
||||
|
||||
@staticmethod
|
||||
def mass_or(fields: list[object], values: list[Any]) -> "FilterQuery":
|
||||
return FilterQuery(
|
||||
filters=[
|
||||
Filter.or_(
|
||||
[Filter.eq(field, val) for field, val in zip(fields, values)]
|
||||
)
|
||||
]
|
||||
filters=[Filter.or_([Filter.eq(field, val) for field, val in zip(fields, values, strict=True)])]
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
|
|
@ -119,7 +113,7 @@ class FilterQuery:
|
|||
def add_and(self, field: object, value: Any):
|
||||
self.filters.append(Filter.eq(field, value))
|
||||
|
||||
def add_query_restistions(self, q_restriction: Optional[QueryRestriction] = None):
|
||||
def add_query_restistions(self, q_restriction: QueryRestriction | None = None):
|
||||
if not q_restriction:
|
||||
return None
|
||||
if q_restriction.limit:
|
||||
|
|
@ -137,9 +131,7 @@ class DataclassInstance(Protocol):
|
|||
__dataclass_fields__: ClassVar[dict[str, Field[Any]]]
|
||||
|
||||
|
||||
async def indexes_by_id(
|
||||
input_data: list, values: list[str], id_name="id"
|
||||
) -> Optional[list[int]]:
|
||||
async def indexes_by_id(input_data: list, values: list[str], id_name="id") -> list[int] | None:
|
||||
r_data: list[int] = []
|
||||
for i, _ in enumerate(input_data):
|
||||
if getattr(input_data[i], id_name) in values:
|
||||
|
|
@ -149,9 +141,7 @@ async def indexes_by_id(
|
|||
return r_data
|
||||
|
||||
|
||||
def data_by_filter[T: DataclassInstance](
|
||||
input_data: list[T], q: FilterQuery
|
||||
) -> list[T]:
|
||||
def data_by_filter[T: DataclassInstance](input_data: list[T], q: FilterQuery) -> list[T]:
|
||||
# can't do query AND(OR() + AND())
|
||||
data: list[T] = []
|
||||
data_or: list[T] = []
|
||||
|
|
@ -245,14 +235,10 @@ def sqlalchemy_conditions(q: FilterQuery):
|
|||
conditions = []
|
||||
for f in q.filters:
|
||||
if f.sign == FilterSign.OR:
|
||||
conditions.append(
|
||||
or_(*sqlalchemy_conditions(q=FilterQuery(filters=f.right)))
|
||||
)
|
||||
conditions.append(or_(*sqlalchemy_conditions(q=FilterQuery(filters=f.right))))
|
||||
continue
|
||||
if f.sign == FilterSign.AND:
|
||||
conditions.append(
|
||||
and_(*sqlalchemy_conditions(q=FilterQuery(filters=f.right)))
|
||||
)
|
||||
conditions.append(and_(*sqlalchemy_conditions(q=FilterQuery(filters=f.right))))
|
||||
continue
|
||||
if f.left is None:
|
||||
continue
|
||||
|
|
@ -282,9 +268,7 @@ def sqlalchemy_conditions(q: FilterQuery):
|
|||
return conditions
|
||||
|
||||
|
||||
def sqlalchemy_restrictions(
|
||||
f: FilterQuery, q: Select, dict_to_sort: Optional[dict] = None
|
||||
) -> Select:
|
||||
def sqlalchemy_restrictions(f: FilterQuery, q: Select, dict_to_sort: dict | None = None) -> Select:
|
||||
if f.limit:
|
||||
q = q.limit(f.limit)
|
||||
if f.offset:
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
|||
from server.infra.web.description import DescriptionController
|
||||
from server.infra.web.seo import SeoController
|
||||
from server.infra.web.recognizer import BreedsController
|
||||
from server.infra.web.seo import SeoController
|
||||
|
||||
__all__ = ("DescriptionController", "SeoController", "BreedsController")
|
||||
|
|
|
|||
|
|
@ -34,9 +34,7 @@ class DescriptionController(Controller):
|
|||
async def dogs_characteristics(self) -> Template:
|
||||
characters_service: CharactersService = inject.instance(CharactersService)
|
||||
breeds = await characters_service.get_characters()
|
||||
return Template(
|
||||
template_name="dogs-characteristics.html", context={"breeds": breeds}
|
||||
)
|
||||
return Template(template_name="dogs-characteristics.html", context={"breeds": breeds})
|
||||
|
||||
@get("/dogs-characteristics/{name:str}")
|
||||
async def beer_description(self, name: str) -> Template:
|
||||
|
|
|
|||
|
|
@ -1,10 +1,12 @@
|
|||
from typing import Annotated
|
||||
|
||||
import inject
|
||||
from litestar import (
|
||||
Controller,
|
||||
post,
|
||||
)
|
||||
from litestar.enums import RequestEncodingType
|
||||
from litestar.datastructures import UploadFile
|
||||
from litestar.enums import RequestEncodingType
|
||||
from litestar.params import Body
|
||||
|
||||
from server.modules.recognizer import RecognizerService
|
||||
|
|
@ -14,17 +16,13 @@ class BreedsController(Controller):
|
|||
path = "/beerds"
|
||||
|
||||
@post("/dogs")
|
||||
async def beerds_dogs(
|
||||
self, data: UploadFile = Body(media_type=RequestEncodingType.MULTI_PART)
|
||||
) -> dict:
|
||||
async def beerds_dogs(self, data: Annotated[UploadFile, Body(media_type=RequestEncodingType.MULTI_PART)]) -> dict:
|
||||
recognizer_service: RecognizerService = inject.instance(RecognizerService)
|
||||
body = await data.read()
|
||||
return await recognizer_service.predict_dog_image(body)
|
||||
|
||||
@post("/cats")
|
||||
async def beerds_cats(
|
||||
self, data: UploadFile = Body(media_type=RequestEncodingType.MULTI_PART)
|
||||
) -> dict:
|
||||
async def beerds_cats(self, data: Annotated[UploadFile, Body(media_type=RequestEncodingType.MULTI_PART)]) -> dict:
|
||||
recognizer_service: RecognizerService = inject.instance(RecognizerService)
|
||||
body = await data.read()
|
||||
return await recognizer_service.predict_cat_image(body)
|
||||
|
|
|
|||
|
|
@ -1,11 +1,11 @@
|
|||
import inject
|
||||
from litestar import (
|
||||
Controller,
|
||||
get,
|
||||
MediaType,
|
||||
get,
|
||||
)
|
||||
|
||||
from server.modules.descriptions import CharactersService, Breed
|
||||
from server.modules.descriptions import Breed, CharactersService
|
||||
|
||||
|
||||
class SeoController(Controller):
|
||||
|
|
|
|||
|
|
@ -1,20 +1,20 @@
|
|||
import asyncio
|
||||
from pathlib import Path
|
||||
import os
|
||||
from pathlib import Path
|
||||
|
||||
import inject
|
||||
from litestar import (
|
||||
Litestar,
|
||||
)
|
||||
from litestar.contrib.jinja import JinjaTemplateEngine
|
||||
from litestar.template.config import TemplateConfig
|
||||
from litestar.static_files import create_static_files_router
|
||||
from litestar.template.config import TemplateConfig
|
||||
|
||||
from server.config import get_app_config
|
||||
from server.infra.web import BreedsController, DescriptionController, SeoController
|
||||
from server.infra.db import AsyncDB
|
||||
from server.modules.descriptions import CharactersService, CharactersRepository
|
||||
from server.modules.recognizer import RecognizerService, RecognizerRepository
|
||||
from server.infra.web import BreedsController, DescriptionController, SeoController
|
||||
from server.modules.descriptions import CharactersService, PGCharactersRepository
|
||||
from server.modules.recognizer import RecognizerRepository, RecognizerService
|
||||
|
||||
os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
|
||||
|
||||
|
|
@ -29,7 +29,7 @@ def inject_config(binder: inject.Binder):
|
|||
db = AsyncDB(cnf)
|
||||
loop.run_until_complete(db.connect())
|
||||
binder.bind(RecognizerService, RecognizerService(RecognizerRepository()))
|
||||
binder.bind(CharactersService, CharactersService(CharactersRepository()))
|
||||
binder.bind(CharactersService, CharactersService(PGCharactersRepository(db)))
|
||||
|
||||
|
||||
inject.configure(inject_config)
|
||||
|
|
|
|||
|
|
@ -0,0 +1 @@
|
|||
Generic single-database configuration.
|
||||
|
|
@ -0,0 +1,86 @@
|
|||
from logging.config import fileConfig
|
||||
|
||||
from alembic import context
|
||||
from server.config import get_app_config
|
||||
from server.infra.db.db_mapper import mapper_registry
|
||||
from server.modules.attachments.repository.models import *
|
||||
from server.modules.descriptions.repository.models import *
|
||||
from server.modules.rate.repository.models import *
|
||||
from sqlalchemy import engine_from_config, pool
|
||||
from sqlalchemy.ext.declarative import declarative_base
|
||||
|
||||
# this is the Alembic Config object, which provides
|
||||
# access to the values within the .ini file in use.
|
||||
config = context.config
|
||||
Base = declarative_base()
|
||||
target_metadata = Base.metadata
|
||||
|
||||
for table_name, table in mapper_registry.metadata.tables.items():
|
||||
target_metadata._add_table(table_name, table.schema, table)
|
||||
|
||||
# Interpret the config file for Python logging.
|
||||
# This line sets up loggers basically.
|
||||
if config.config_file_name is not None:
|
||||
fileConfig(config.config_file_name)
|
||||
|
||||
|
||||
def run_migrations_offline() -> None:
|
||||
"""Run migrations in 'offline' mode.
|
||||
|
||||
This configures the context with just a URL
|
||||
and not an Engine, though an Engine is acceptable
|
||||
here as well. By skipping the Engine creation
|
||||
we don't even need a DBAPI to be available.
|
||||
|
||||
Calls to context.execute() here emit the given string to the
|
||||
script output.
|
||||
|
||||
"""
|
||||
url = "{}?options=-c search_path={}".format(
|
||||
str(get_app_config().db_uri).replace("+asyncpg", ""),
|
||||
get_app_config().db_search_path,
|
||||
)
|
||||
context.configure(
|
||||
url=url,
|
||||
target_metadata=target_metadata,
|
||||
literal_binds=True,
|
||||
dialect_opts={"paramstyle": "named"},
|
||||
)
|
||||
|
||||
with context.begin_transaction():
|
||||
context.run_migrations()
|
||||
|
||||
|
||||
def run_migrations_online() -> None:
|
||||
"""Run migrations in 'online' mode.
|
||||
|
||||
In this scenario we need to create an Engine
|
||||
and associate a connection with the context.
|
||||
|
||||
"""
|
||||
alemb_cnf = config.get_section(config.config_ini_section, {})
|
||||
if not alemb_cnf["sqlalchemy.url"] or alemb_cnf["sqlalchemy.url"] == "driver://user:pass@localhost/dbname":
|
||||
alemb_cnf["sqlalchemy.url"] = "{}?options=-c search_path={}".format(
|
||||
str(get_app_config().db_uri).replace("+asyncpg", ""),
|
||||
get_app_config().db_search_path,
|
||||
)
|
||||
connectable = engine_from_config(
|
||||
alemb_cnf,
|
||||
prefix="sqlalchemy.",
|
||||
poolclass=pool.NullPool,
|
||||
)
|
||||
|
||||
with connectable.connect() as connection:
|
||||
context.configure(
|
||||
connection=connection,
|
||||
target_metadata=target_metadata,
|
||||
)
|
||||
|
||||
with context.begin_transaction():
|
||||
context.run_migrations()
|
||||
|
||||
|
||||
if context.is_offline_mode():
|
||||
run_migrations_offline()
|
||||
else:
|
||||
run_migrations_online()
|
||||
|
|
@ -0,0 +1,26 @@
|
|||
"""${message}
|
||||
|
||||
Revision ID: ${up_revision}
|
||||
Revises: ${down_revision | comma,n}
|
||||
Create Date: ${create_date}
|
||||
|
||||
"""
|
||||
from typing import Sequence, Union
|
||||
|
||||
from alembic import op
|
||||
import sqlalchemy as sa
|
||||
${imports if imports else ""}
|
||||
|
||||
# revision identifiers, used by Alembic.
|
||||
revision: str = ${repr(up_revision)}
|
||||
down_revision: Union[str, None] = ${repr(down_revision)}
|
||||
branch_labels: Union[str, Sequence[str], None] = ${repr(branch_labels)}
|
||||
depends_on: Union[str, Sequence[str], None] = ${repr(depends_on)}
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
${upgrades if upgrades else "pass"}
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
${downgrades if downgrades else "pass"}
|
||||
|
|
@ -0,0 +1,71 @@
|
|||
"""a284498
|
||||
|
||||
Revision ID: 474b572b7fe2
|
||||
Revises:
|
||||
Create Date: 2026-01-12 18:28:37.783462
|
||||
|
||||
"""
|
||||
|
||||
import pathlib
|
||||
from collections.abc import Sequence
|
||||
|
||||
import sqlalchemy as sa
|
||||
from alembic import op
|
||||
|
||||
# revision identifiers, used by Alembic.
|
||||
revision: str = "474b572b7fe2"
|
||||
down_revision: str | None = None
|
||||
branch_labels: str | Sequence[str] | None = None
|
||||
depends_on: str | Sequence[str] | None = None
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
op.create_table(
|
||||
"attachments",
|
||||
sa.Column("id", sa.String(), nullable=False),
|
||||
sa.Column("size", sa.BigInteger(), nullable=False),
|
||||
sa.Column("storage_driver_name", sa.String(), nullable=False),
|
||||
sa.Column("path", sa.String(), nullable=False),
|
||||
sa.Column("media_type", sa.String(), nullable=False),
|
||||
sa.Column("content_type", sa.String(), nullable=False),
|
||||
sa.Column("created_at", sa.DateTime(timezone=True), nullable=False),
|
||||
sa.Column("updated_at", sa.DateTime(timezone=True), nullable=False),
|
||||
sa.Column("is_deleted", sa.Boolean(), nullable=False),
|
||||
sa.PrimaryKeyConstraint("id"),
|
||||
)
|
||||
op.create_table(
|
||||
"beerds",
|
||||
sa.Column("id", sa.String(), nullable=False),
|
||||
sa.Column("name", sa.Text(), nullable=False),
|
||||
sa.Column("alias", sa.Text(), nullable=False),
|
||||
sa.Column("descriptions", sa.Text(), nullable=False),
|
||||
sa.Column("signs", sa.JSON(), nullable=False),
|
||||
sa.PrimaryKeyConstraint("id"),
|
||||
)
|
||||
op.create_table(
|
||||
"votes",
|
||||
sa.Column("id", sa.String(), nullable=False),
|
||||
sa.Column("attachemnt_id", sa.String(), nullable=False),
|
||||
sa.Column("beerd_id", sa.String(), nullable=False),
|
||||
sa.Column("rate", sa.BigInteger(), nullable=False),
|
||||
sa.Column("created_at", sa.DateTime(timezone=True), nullable=False),
|
||||
sa.ForeignKeyConstraint(["attachemnt_id"], ["attachments.id"], name="votes_attachemnt_id_fk"),
|
||||
sa.ForeignKeyConstraint(["beerd_id"], ["beerds.id"], name="votes_beerd_id_fk"),
|
||||
sa.PrimaryKeyConstraint("id"),
|
||||
)
|
||||
# ### end Alembic commands ###
|
||||
with open(
|
||||
pathlib.Path(__file__).resolve().parent / "dumps/beerds_insert.sql",
|
||||
encoding="utf-8",
|
||||
) as upgrade_file:
|
||||
sql = upgrade_file.read()
|
||||
op.execute(sql)
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
op.drop_table("votes")
|
||||
op.drop_table("beerds")
|
||||
op.drop_table("attachments")
|
||||
# ### end Alembic commands ###
|
||||
File diff suppressed because it is too large
Load Diff
|
|
@ -3,7 +3,7 @@ Working with media files - uploading, storing, receiving
|
|||
"""
|
||||
|
||||
from server.modules.attachments.domains.attachments import Attachment
|
||||
from server.modules.attachments.repositories.attachments import (
|
||||
from server.modules.attachments.repository.attachments import (
|
||||
AttachmentRepository,
|
||||
DBAttachmentRepository,
|
||||
MockAttachmentRepository,
|
||||
|
|
|
|||
|
|
@ -1,6 +1,5 @@
|
|||
from abc import ABCMeta, abstractmethod
|
||||
from datetime import UTC, datetime
|
||||
from typing import Tuple
|
||||
|
||||
from sqlalchemy import CursorResult, delete, insert, select, update
|
||||
|
||||
|
|
@ -11,9 +10,7 @@ from server.modules.attachments.domains.attachments import Attachment
|
|||
|
||||
class AttachmentRepository(metaclass=ABCMeta):
|
||||
@abstractmethod
|
||||
async def get_by_id(
|
||||
self, session: AbstractSession, attach_id: list[str]
|
||||
) -> list[Attachment]:
|
||||
async def get_by_id(self, session: AbstractSession, attach_id: list[str]) -> list[Attachment]:
|
||||
"""Get Attachment by ID"""
|
||||
pass
|
||||
|
||||
|
|
@ -89,9 +86,7 @@ class MockAttachmentRepository(AttachmentRepository):
|
|||
}
|
||||
self._db = MockDB(get_app_config())
|
||||
|
||||
async def get_by_id(
|
||||
self, session: AbstractSession, attach_id: list[str]
|
||||
) -> list[Attachment]:
|
||||
async def get_by_id(self, session: AbstractSession, attach_id: list[str]) -> list[Attachment]:
|
||||
f: list[Attachment] = []
|
||||
for f_id in attach_id:
|
||||
f_item = self._data.get(f_id)
|
||||
|
|
@ -119,14 +114,12 @@ class DBAttachmentRepository(AttachmentRepository):
|
|||
def __init__(self, db: AsyncDB):
|
||||
self._db = db
|
||||
|
||||
async def get_by_id(
|
||||
self, session: AbstractSession, attach_id: list[str]
|
||||
) -> list[Attachment]:
|
||||
async def get_by_id(self, session: AbstractSession, attach_id: list[str]) -> list[Attachment]:
|
||||
q = select(Attachment).where(
|
||||
Attachment.id.in_(attach_id) # type: ignore
|
||||
)
|
||||
attachment: list[Attachment] = []
|
||||
result: CursorResult[Tuple[Attachment]] = await session.execute(q) # type: ignore
|
||||
result: CursorResult[tuple[Attachment]] = await session.execute(q) # type: ignore
|
||||
for d in result.all():
|
||||
attachment.append(d[0])
|
||||
return attachment
|
||||
|
|
@ -0,0 +1,35 @@
|
|||
from dataclasses import dataclass, field
|
||||
from datetime import UTC, datetime
|
||||
|
||||
from dataclasses_ujson.dataclasses_ujson import UJsonMixin # type: ignore
|
||||
from sqlalchemy import BigInteger, Boolean, Column, DateTime, String
|
||||
|
||||
from server.config import get_app_config
|
||||
from server.infra.db.db_mapper import mapper_registry
|
||||
|
||||
|
||||
@mapper_registry.mapped
|
||||
@dataclass
|
||||
class Attachment(UJsonMixin):
|
||||
__sa_dataclass_metadata_key__ = "sa"
|
||||
__tablename__ = "attachments"
|
||||
|
||||
id: str = field(metadata={"sa": Column(String(), primary_key=True, nullable=False)})
|
||||
size: int = field(metadata={"sa": Column(BigInteger(), nullable=False)})
|
||||
storage_driver_name: str = field(metadata={"sa": Column(String(), nullable=False)})
|
||||
path: str = field(metadata={"sa": Column(String(), nullable=False)})
|
||||
media_type: str = field(metadata={"sa": Column(String(), nullable=False)})
|
||||
content_type: str = field(metadata={"sa": Column(String(), nullable=False)})
|
||||
|
||||
created_at: datetime = field(
|
||||
default=datetime.now(UTC),
|
||||
metadata={"sa": Column(DateTime(timezone=True), nullable=False)},
|
||||
)
|
||||
updated_at: datetime = field(
|
||||
default=datetime.now(UTC),
|
||||
metadata={"sa": Column(DateTime(timezone=True), nullable=False)},
|
||||
)
|
||||
is_deleted: bool = field(default=False, metadata={"sa": Column(Boolean(), nullable=False, default=False)})
|
||||
|
||||
def __str__(self):
|
||||
return f"{get_app_config().app_public_url}/api/v0/attachment/{self.id}.original.ext"
|
||||
|
|
@ -1,12 +1,13 @@
|
|||
import hashlib
|
||||
import os.path
|
||||
import uuid
|
||||
from abc import ABCMeta, abstractmethod
|
||||
from collections.abc import AsyncIterable, AsyncIterator
|
||||
from datetime import UTC, datetime
|
||||
from enum import Enum
|
||||
from io import BytesIO
|
||||
from pathlib import Path
|
||||
from typing import Any, AsyncIterable, AsyncIterator, Optional
|
||||
import uuid
|
||||
from typing import Any
|
||||
|
||||
import aioboto3 # type: ignore
|
||||
import aiofiles
|
||||
|
|
@ -19,7 +20,7 @@ from server.config import AppConfig, get_app_config
|
|||
from server.infra.db import AbstractSession
|
||||
from server.infra.logger import get_logger
|
||||
from server.modules.attachments.domains.attachments import Attachment
|
||||
from server.modules.attachments.repositories.attachments import AttachmentRepository
|
||||
from server.modules.attachments.repository.attachments import AttachmentRepository
|
||||
|
||||
|
||||
class StorageDriversType(str, Enum):
|
||||
|
|
@ -46,7 +47,7 @@ class StorageDriver(metaclass=ABCMeta):
|
|||
pass
|
||||
|
||||
@abstractmethod
|
||||
async def take(self, path: str) -> Optional[bytes]:
|
||||
async def take(self, path: str) -> bytes | None:
|
||||
pass
|
||||
|
||||
@abstractmethod
|
||||
|
|
@ -78,7 +79,7 @@ class LocalStorageDriver(StorageDriver):
|
|||
await f.write(data)
|
||||
return str(path)
|
||||
|
||||
async def take(self, path: str) -> Optional[bytes]:
|
||||
async def take(self, path: str) -> bytes | None:
|
||||
if not os.path.isfile(path):
|
||||
return None
|
||||
async with aiofiles.open(path, "rb") as f:
|
||||
|
|
@ -112,7 +113,7 @@ class MockStorageDriver(StorageDriver):
|
|||
self._store[path] = data
|
||||
return path
|
||||
|
||||
async def take(self, path: str) -> Optional[bytes]:
|
||||
async def take(self, path: str) -> bytes | None:
|
||||
return self._store.get(path)
|
||||
|
||||
async def delete(self, path: str):
|
||||
|
|
@ -138,9 +139,7 @@ class S3StorageDriver(StorageDriver):
|
|||
return self._session.client("s3", endpoint_url=self._cnf.fs_s3_endpoint)
|
||||
|
||||
def _normalize_path(self, path: str) -> str:
|
||||
return f"{S3StorageDriver._prefix}{path}".replace(
|
||||
self._cnf.fs_local_mount_dir, ""
|
||||
)
|
||||
return f"{S3StorageDriver._prefix}{path}".replace(self._cnf.fs_local_mount_dir, "")
|
||||
|
||||
async def put(self, data: bytes) -> str:
|
||||
sign = hashlib.file_digest(BytesIO(data), "sha256").hexdigest()
|
||||
|
|
@ -176,12 +175,10 @@ class S3StorageDriver(StorageDriver):
|
|||
self._logger.error(f"stream client error: {str(e)}, path: {path}")
|
||||
raise FileNotFoundError
|
||||
except Exception as e:
|
||||
self._logger.error(
|
||||
f"stream error: {type(e).__name__} {str(e)}, path: {path}"
|
||||
)
|
||||
self._logger.error(f"stream error: {type(e).__name__} {str(e)}, path: {path}")
|
||||
raise FileNotFoundError
|
||||
|
||||
async def take(self, path: str) -> Optional[bytes]:
|
||||
async def take(self, path: str) -> bytes | None:
|
||||
buffer = BytesIO()
|
||||
async for chunk in self.stream(path):
|
||||
if chunk:
|
||||
|
|
@ -191,9 +188,7 @@ class S3StorageDriver(StorageDriver):
|
|||
|
||||
async def delete(self, path: str) -> None:
|
||||
async with await self._client() as s3:
|
||||
await s3.delete_object(
|
||||
Bucket=self._cnf.fs_s3_bucket, Key=self._normalize_path(path)
|
||||
)
|
||||
await s3.delete_object(Bucket=self._cnf.fs_s3_bucket, Key=self._normalize_path(path))
|
||||
|
||||
|
||||
RESIZE_MAX_SIZE = 100_000
|
||||
|
|
@ -243,9 +238,7 @@ class AtachmentService:
|
|||
return parts.replace("/", "")
|
||||
|
||||
def url(self, attachment_id: str, content_type: str | None = None) -> str:
|
||||
return f"{self._cnf.app_public_url}/api/v0/attachment/{attachment_id}.original.{
|
||||
self.extension(content_type)
|
||||
}"
|
||||
return f"{self._cnf.app_public_url}/api/v0/attachment/{attachment_id}.original.{self.extension(content_type)}"
|
||||
|
||||
async def create(self, file: bytes, user_id: str) -> Attachment:
|
||||
path = await self._driver.put(file)
|
||||
|
|
@ -264,9 +257,7 @@ class AtachmentService:
|
|||
await self._repository.create(attach)
|
||||
return attach
|
||||
|
||||
async def get_info(
|
||||
self, session: AbstractSession | None, attach_id: list[str]
|
||||
) -> list[Attachment]:
|
||||
async def get_info(self, session: AbstractSession | None, attach_id: list[str]) -> list[Attachment]:
|
||||
if not attach_id:
|
||||
return []
|
||||
if session is not None:
|
||||
|
|
@ -277,17 +268,13 @@ class AtachmentService:
|
|||
def get_name(self, attachment: Attachment) -> str:
|
||||
return f"{attachment.id}.{self.extension(attachment.content_type)}"
|
||||
|
||||
async def get_data(
|
||||
self, session: AbstractSession, attach_id: str
|
||||
) -> Optional[bytes]:
|
||||
async def get_data(self, session: AbstractSession, attach_id: str) -> bytes | None:
|
||||
file = await self._repository.get_by_id(session, [attach_id])
|
||||
if not file:
|
||||
return None
|
||||
return await self._driver.take(file[0].path)
|
||||
|
||||
async def get_stream(
|
||||
self, session: AbstractSession | None, attach_id: str
|
||||
) -> AsyncIterator[bytes]:
|
||||
async def get_stream(self, session: AbstractSession | None, attach_id: str) -> AsyncIterator[bytes]:
|
||||
async def _stream_iterator(is_empty: bool):
|
||||
if is_empty:
|
||||
return
|
||||
|
|
@ -343,7 +330,5 @@ class AtachmentService:
|
|||
f"delete:{item.path}",
|
||||
)
|
||||
path = await self._driver.put(d)
|
||||
await self._repository.update(
|
||||
item.id, path=path, content_type="image/jpeg", size=len(d)
|
||||
)
|
||||
await self._repository.update(item.id, path=path, content_type="image/jpeg", size=len(d))
|
||||
await self._driver.delete(item.path)
|
||||
|
|
|
|||
|
|
@ -1,13 +1,11 @@
|
|||
from server.modules.descriptions.repository import (
|
||||
CharactersRepository,
|
||||
ACharactersRepository,
|
||||
)
|
||||
from server.modules.descriptions.service import CharactersService
|
||||
from server.modules.descriptions.domain import Breed
|
||||
from server.modules.descriptions.repository import ACharactersRepository, CharactersRepository, PGCharactersRepository
|
||||
from server.modules.descriptions.service import CharactersService
|
||||
|
||||
__all__ = (
|
||||
"CharactersRepository",
|
||||
"ACharactersRepository",
|
||||
"CharactersService",
|
||||
"PGCharactersRepository",
|
||||
"Breed",
|
||||
)
|
||||
|
|
|
|||
|
|
@ -3,6 +3,7 @@ from dataclasses import dataclass
|
|||
|
||||
@dataclass(frozen=True)
|
||||
class Breed:
|
||||
id: str
|
||||
name: str
|
||||
alias: str
|
||||
description: str
|
||||
|
|
|
|||
|
|
@ -1,6 +1,7 @@
|
|||
from server.modules.descriptions.repository.repository import (
|
||||
CharactersRepository,
|
||||
ACharactersRepository,
|
||||
CharactersRepository,
|
||||
PGCharactersRepository,
|
||||
)
|
||||
|
||||
__all__ = ("CharactersRepository", "ACharactersRepository")
|
||||
__all__ = ("CharactersRepository", "ACharactersRepository", "PGCharactersRepository")
|
||||
|
|
|
|||
|
|
@ -1,107 +0,0 @@
|
|||
|
||||
|
||||
### **Карликовый пинчер: подробное описание породы**
|
||||
|
||||
---
|
||||
|
||||
#### **1. Происхождение и история породы**
|
||||
Карликовый пинчер — компактная, энергичная собака, которая возникла в Германии в XIX веке. Порода была выведена как миниатюрный вариант классического пинчера, который использовался для охоты и охраны. В 1880-х годах селекционеры стремились создать компанию для крупных пинчеров, сохранив их характер и активность, но уменьшив размер.
|
||||
Официально порода признана в 1900 году, а в 1940-х годах она стала популярна как домашний компаньон. Сегодня карликовые пинчеры ценятся за лояльность, ум и жизнерадостность. Их часто называют "пинчерами-малютками" из-за их компактных размеров и динамичного характера.
|
||||
|
||||
---
|
||||
|
||||
#### **2. Физические характеристики**
|
||||
- **Размер**:
|
||||
- Высота в холке: 25–30 см.
|
||||
- Вес: 3–5 кг (в зависимости от пола и генетики).
|
||||
- **Тип шерсти**:
|
||||
- Короткая, гладкая, плотная.
|
||||
- Окрасы: черный, красный, черно-подпалый, белый (иногда с пятнами).
|
||||
- **Физические особенности**:
|
||||
- Мускулистое тело, выразительные глаза, подвижные уши, короткий хвост.
|
||||
- Характерная "квадратная" форма головы и пропорциональное тело.
|
||||
|
||||
---
|
||||
|
||||
#### **3. Характер и поведение**
|
||||
- **Темперамент**:
|
||||
- Лояльный, энергичный, умный и храбрый.
|
||||
- Склонен к обладанию (крадет вещи, защищает территорию).
|
||||
- Чувствителен к эмоциям хозяина.
|
||||
- **Уровень энергии**:
|
||||
- Высокий. Требует регулярной физической активности (прогулки, игры).
|
||||
- **Совместимость с детьми**:
|
||||
- Хорошо ладит с детьми, если воспитан с раннего возраста.
|
||||
- Может проявлять агрессию к младенцам или непоседливым детям.
|
||||
- **Совместимость с другими животными**:
|
||||
- С осторожностью. Может быть агрессивным к крупным собакам.
|
||||
- Лучше знакомить с другими животными в раннем возрасте.
|
||||
- **Опасность без тренировок**:
|
||||
- Без дрессировки может проявлять лай, укус или агрессию.
|
||||
- Нуждается в социализации и умеренном контроле.
|
||||
|
||||
---
|
||||
|
||||
#### **4. Интеллект, способность к обучению, необходимость умственных нагрузок**
|
||||
- **Интеллект**:
|
||||
- Высокий. Быстро учится, но может быть независимым.
|
||||
- Хорошо справляется с командами, но требует терпения.
|
||||
- **Обучение**:
|
||||
- Рекомендуется начинать с 3–4 месяцев.
|
||||
- Нуждается в постоянной стимуляции (игры, тренировки).
|
||||
- **Умственные нагрузки**:
|
||||
- Игры с костями, поиск предметов, тренировки на команды.
|
||||
- Без умственной активности может проявлять деструктивное поведение (грызение мебели, лай).
|
||||
|
||||
---
|
||||
|
||||
#### **5. Уход и содержание**
|
||||
- **Гигиена**:
|
||||
- Регулярное мытье (1 раз в 2–3 недели), чистка ушей, стрижка когтей.
|
||||
- Шерсть легко ухаживать, но требует расчесывания 1–2 раза в неделю.
|
||||
- **Физическая активность**:
|
||||
- Прогулки 2–3 раза в день, игры на площадке.
|
||||
- Не подходит для сидячего образа жизни.
|
||||
- **Кормление**:
|
||||
- Сбалансированный рацион с высоким содержанием белка.
|
||||
- Следить за весом (склонность к ожирению).
|
||||
- **Психологическое благополучие**:
|
||||
- Не оставлять на длительное время одних.
|
||||
- Обеспечить игрушки и внимание.
|
||||
|
||||
---
|
||||
|
||||
#### **6. Здоровье и продолжительность жизни**
|
||||
- **Продолжительность жизни**: 12–15 лет.
|
||||
- **Частые проблемы**:
|
||||
- Болезни суставов (дисплазия), панкреатит, аллергии, проблемы с сердцем.
|
||||
- Склонность к ожирению.
|
||||
- **Рекомендации**:
|
||||
- Регулярные ветеринарные осмотры.
|
||||
- Контроль за питанием и физической активностью.
|
||||
- Прививки по графику, дегельминтизация.
|
||||
|
||||
---
|
||||
|
||||
#### **7. Особенности породы**
|
||||
- **Плюсы**:
|
||||
- Умный, лояльный, компактный, подходит для квартиры.
|
||||
- Хорошо охраняет дом.
|
||||
- **Минусы**:
|
||||
- Склонность к агрессии без тренировок.
|
||||
- Требует времени на воспитание.
|
||||
- Могут быть шумными (часто лают).
|
||||
|
||||
---
|
||||
|
||||
#### **8. Подходит ли карликовый пинчер вам?**
|
||||
- **Для**:
|
||||
- Семьи с детьми, которые готовы к обучению собаки.
|
||||
- Людей, желающих иметь активного компаньона.
|
||||
- **Не подходит**:
|
||||
- Для тех, кто не готов уделять время на воспитание.
|
||||
- Для жителей, у которых нет свободного пространства.
|
||||
|
||||
---
|
||||
|
||||
Карликовый пинчер — это идеальный выбор для тех, кто ценит ум, энергию и лояльность в собаке. Однако его воспитание требует терпения, времени и ответственности. С правильным подходом это питомец станет верным другом на всю жизнь.
|
||||
|
|
@ -1,6 +1,3 @@
|
|||
|
||||
|
||||
```json
|
||||
{
|
||||
"people_friendly": true,
|
||||
"child_friendly": true,
|
||||
|
|
@ -13,5 +10,4 @@
|
|||
"good_health": false,
|
||||
"tolerates_loneliness": false,
|
||||
"hypoallergenic": false
|
||||
}
|
||||
```
|
||||
}
|
||||
|
|
@ -1,6 +1,3 @@
|
|||
|
||||
|
||||
```json
|
||||
{
|
||||
"active": true,
|
||||
"colors": ["blue", "gray", "black"],
|
||||
|
|
@ -9,5 +6,4 @@
|
|||
"smart": true,
|
||||
"good_health": false,
|
||||
"tolerates_loneliness": false
|
||||
}
|
||||
```
|
||||
}
|
||||
|
|
@ -1,6 +1,3 @@
|
|||
|
||||
|
||||
```json
|
||||
{
|
||||
"people_friendly": true,
|
||||
"child_friendly": true,
|
||||
|
|
@ -12,5 +9,4 @@
|
|||
"good_health": false,
|
||||
"tolerates_loneliness": false,
|
||||
"hypoallergenic": false
|
||||
}
|
||||
```
|
||||
}
|
||||
|
|
@ -1,6 +1,3 @@
|
|||
|
||||
|
||||
```json
|
||||
{
|
||||
"people_friendly": true,
|
||||
"child_friendly": true,
|
||||
|
|
@ -16,5 +13,4 @@
|
|||
"good_health": false,
|
||||
"tolerates_loneliness": false,
|
||||
"hypoallergenic": false
|
||||
}
|
||||
```
|
||||
}
|
||||
|
|
@ -1,3 +0,0 @@
|
|||
|
||||
|
||||
It seems like the text you've shared is repeated multiple times, possibly due to an error. Could you clarify your question or specify what you need help with? For example, are you looking for tips on dog care, training, nutrition, or something else? Let me know, and I'll provide a clear, concise response! 🐾
|
||||
|
|
@ -1,6 +1,3 @@
|
|||
|
||||
|
||||
```json
|
||||
{
|
||||
"people_friendly": true,
|
||||
"child_friendly": true,
|
||||
|
|
@ -12,5 +9,4 @@
|
|||
"good_health": false,
|
||||
"tolerates_loneliness": false,
|
||||
"hypoallergenic": false
|
||||
}
|
||||
```
|
||||
}
|
||||
|
|
@ -1,16 +1,7 @@
|
|||
|
||||
|
||||
The Entlebucher Mountain Dog exhibits the following traits based on the provided description:
|
||||
|
||||
- **Child-friendly**: Yes. The text explicitly states, "Прекрасно ладят с детьми" (Great with children).
|
||||
- **High energy**: Yes. The breed requires daily walks, games, and activities, and lacks of stimulation may lead to destructive behavior.
|
||||
- **Friendly**: Yes. The dog is described as "обычно дружелюбны" (usually friendly) with people and other animals, and it is noted that they are good with children.
|
||||
|
||||
Other attributes:
|
||||
- **People-friendly**: Ambiguous. While the breed is friendly with people, the term "people-friendly" is not explicitly mentioned.
|
||||
- **Dog-friendly**: Unclear. The text notes "обычно дружелюбны" (usually friendly) with other animals but mentions a hunting instinct toward small animals, which may not directly apply to dogs.
|
||||
- **Low maintenance**: No. The breed requires regular grooming (brushing) and active socialization/training.
|
||||
- **Hypoallergenic**: No. There is no mention of hypoallergenic traits.
|
||||
|
||||
**Final Answer**:
|
||||
Child-friendly, High energy, Friendly.
|
||||
{
|
||||
"people_friendly": true,
|
||||
"child_friendly": true,
|
||||
"active": true,
|
||||
"need_attentions": true,
|
||||
"good_health": false
|
||||
}
|
||||
|
|
|
|||
|
|
@ -0,0 +1,19 @@
|
|||
from dataclasses import dataclass, field
|
||||
|
||||
from dataclasses_ujson.dataclasses_ujson import UJsonMixin # type: ignore
|
||||
from sqlalchemy import JSON, Column, String, Text
|
||||
|
||||
from server.infra.db.db_mapper import mapper_registry
|
||||
|
||||
|
||||
@mapper_registry.mapped
|
||||
@dataclass
|
||||
class Beerds(UJsonMixin):
|
||||
__sa_dataclass_metadata_key__ = "sa"
|
||||
__tablename__ = "beerds"
|
||||
|
||||
id: str = field(metadata={"sa": Column(String(), primary_key=True, nullable=False)})
|
||||
name: str = field(metadata={"sa": Column(Text(), nullable=False)})
|
||||
alias: str = field(metadata={"sa": Column(Text(), nullable=False)})
|
||||
descriptions: str = field(metadata={"sa": Column(Text(), nullable=False)})
|
||||
signs: dict | None = field(default=None, metadata={"sa": Column(JSON(), nullable=False)})
|
||||
|
|
@ -1,10 +1,12 @@
|
|||
from abc import ABCMeta, abstractmethod
|
||||
from pathlib import Path
|
||||
|
||||
from aiocache import cached, Cache # type: ignore
|
||||
from aiocache import Cache, cached # type: ignore
|
||||
from sqlalchemy import select
|
||||
|
||||
from server.infra.db import AsyncDB
|
||||
from server.modules.descriptions.domain import Breed
|
||||
from server.modules.descriptions.repository import models
|
||||
|
||||
|
||||
class ACharactersRepository(metaclass=ABCMeta):
|
||||
|
|
@ -12,6 +14,7 @@ class ACharactersRepository(metaclass=ABCMeta):
|
|||
async def get_characters(self) -> list[Breed]:
|
||||
pass
|
||||
|
||||
@abstractmethod
|
||||
async def get_character(self, alias: str) -> Breed | None:
|
||||
pass
|
||||
|
||||
|
|
@ -28,11 +31,10 @@ class CharactersRepository(ACharactersRepository):
|
|||
# Идем по каждому текстовому файлу с описанием породы
|
||||
for breed_file in breed_dir.glob("*.txt"):
|
||||
breed_name = breed_file.stem # имя файла без расширения - название породы
|
||||
description = breed_file.read_text(
|
||||
encoding="utf-8"
|
||||
) # читаем описание из файла
|
||||
description = breed_file.read_text(encoding="utf-8") # читаем описание из файла
|
||||
breeds.append(
|
||||
Breed(
|
||||
id=breed_name,
|
||||
name=breed_name.replace("_", " "),
|
||||
alias=breed_file.stem,
|
||||
description=description.strip(),
|
||||
|
|
@ -55,30 +57,71 @@ class PGCharactersRepository(ACharactersRepository):
|
|||
def __init__(self, db: AsyncDB):
|
||||
self._db = db
|
||||
|
||||
@cached(ttl=60, cache=Cache.MEMORY)
|
||||
# ───────────────────────────────────────────────────────────────────── #
|
||||
# 8️⃣ Кешируемый метод, который возвращает **все** породы
|
||||
# ───────────────────────────────────────────────────────────────────── #
|
||||
@cached(ttl=60, cache=Cache.MEMORY) # 1‑мин. кеш
|
||||
async def get_characters(self) -> list[Breed]:
|
||||
breed_dir = Path("server/modules/descriptions/repository/breed_descriptions")
|
||||
breeds: list[Breed] = []
|
||||
"""
|
||||
Читает данные из таблицы `beerds.beerds` и преобразует каждую строку
|
||||
в экземпляр `Breed`. Поле `signs` игнорируется – в `Breed` его нет.
|
||||
"""
|
||||
|
||||
# Идем по каждому текстовому файлу с описанием породы
|
||||
for breed_file in breed_dir.glob("*.txt"):
|
||||
breed_name = breed_file.stem # имя файла без расширения - название породы
|
||||
description = breed_file.read_text(
|
||||
encoding="utf-8"
|
||||
) # читаем описание из файла
|
||||
breeds.append(
|
||||
Breed(
|
||||
name=breed_name.replace("_", " "),
|
||||
alias=breed_file.stem,
|
||||
description=description.strip(),
|
||||
)
|
||||
async with self._db.async_session() as session:
|
||||
# Писем SELECT‑запрос (получаем все строки)
|
||||
stmt = select(
|
||||
models.Beerds.id,
|
||||
models.Beerds.name,
|
||||
models.Beerds.alias,
|
||||
models.Beerds.descriptions,
|
||||
)
|
||||
breeds.sort(key=lambda b: b.name)
|
||||
result = await session.execute(stmt)
|
||||
rows = result.fetchall()
|
||||
|
||||
# Конвертируем в Breed
|
||||
breeds: list[Breed] = [
|
||||
Breed(
|
||||
id=str(row.id),
|
||||
name=row.name.strip(),
|
||||
alias=row.alias.strip(),
|
||||
description=row.descriptions.strip(),
|
||||
)
|
||||
for row in rows
|
||||
]
|
||||
|
||||
# Сортируем по имени, как было в файле‑реализации
|
||||
breeds.sort(key=lambda b: b.name.lower())
|
||||
return breeds
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────── #
|
||||
# 9️⃣ Получить конкретную породу по псевдониму
|
||||
# ───────────────────────────────────────────────────────────────────── #
|
||||
async def get_character(self, alias: str) -> Breed | None:
|
||||
breeds = await self.get_characters()
|
||||
data = [b for b in breeds if b.alias == alias]
|
||||
if len(data) == 0:
|
||||
"""
|
||||
Быстрый запрос без получения всех пород. Если результат
|
||||
пустой – возвращаем `None`.
|
||||
"""
|
||||
|
||||
async with self._db.async_session() as session:
|
||||
stmt = (
|
||||
select(
|
||||
models.Beerds.id,
|
||||
models.Beerds.name,
|
||||
models.Beerds.alias,
|
||||
models.Beerds.descriptions,
|
||||
)
|
||||
.where(models.Beerds.alias == alias)
|
||||
.limit(1)
|
||||
)
|
||||
result = await session.execute(stmt)
|
||||
row = result.fetchone()
|
||||
|
||||
if row is None: # pragma: no cover
|
||||
return None
|
||||
return data[0]
|
||||
|
||||
return Breed(
|
||||
id=str(row.id),
|
||||
name=row.name.strip(),
|
||||
alias=row.alias.strip(),
|
||||
description=row.descriptions.strip(),
|
||||
)
|
||||
|
|
|
|||
|
|
@ -0,0 +1,36 @@
|
|||
from dataclasses import dataclass, field
|
||||
from datetime import UTC, datetime
|
||||
|
||||
from dataclasses_ujson.dataclasses_ujson import UJsonMixin # type: ignore
|
||||
from server.config import get_app_config
|
||||
from server.infra.db.db_mapper import mapper_registry
|
||||
from sqlalchemy import (
|
||||
BigInteger,
|
||||
Column,
|
||||
DateTime,
|
||||
ForeignKeyConstraint,
|
||||
String,
|
||||
)
|
||||
|
||||
|
||||
@mapper_registry.mapped
|
||||
@dataclass
|
||||
class Vote(UJsonMixin):
|
||||
__sa_dataclass_metadata_key__ = "sa"
|
||||
__tablename__ = "votes"
|
||||
__table_args__ = (
|
||||
ForeignKeyConstraint(["attachemnt_id"], ["attachments.id"], "votes_attachemnt_id_fk"),
|
||||
ForeignKeyConstraint(["beerd_id"], ["beerds.id"], "votes_beerd_id_fk"),
|
||||
)
|
||||
|
||||
id: str = field(metadata={"sa": Column(String(), primary_key=True, nullable=False)})
|
||||
attachemnt_id: str = field(metadata={"sa": Column(String(), nullable=False)})
|
||||
beerd_id: str = field(metadata={"sa": Column(String(), nullable=False)})
|
||||
rate: int = field(metadata={"sa": Column(BigInteger(), nullable=False)})
|
||||
created_at: datetime = field(
|
||||
default=datetime.now(UTC),
|
||||
metadata={"sa": Column(DateTime(timezone=True), nullable=False)},
|
||||
)
|
||||
|
||||
def __str__(self):
|
||||
return f"{get_app_config().app_public_url}/api/v0/attachment/{self.id}.original.ext"
|
||||
|
|
@ -1,6 +1,6 @@
|
|||
from server.modules.recognizer.repository import (
|
||||
RecognizerRepository,
|
||||
ARecognizerRepository,
|
||||
RecognizerRepository,
|
||||
)
|
||||
from server.modules.recognizer.service import RecognizerService
|
||||
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
from server.modules.recognizer.repository.repository import (
|
||||
RecognizerRepository,
|
||||
ARecognizerRepository,
|
||||
RecognizerRepository,
|
||||
)
|
||||
|
||||
__all__ = ("RecognizerRepository", "ARecognizerRepository")
|
||||
|
|
|
|||
|
|
@ -481,7 +481,7 @@
|
|||
"n02094114_3667.webp",
|
||||
"n02094114_482.webp"
|
||||
],
|
||||
"японский хин": [
|
||||
"японский_хин": [
|
||||
"japanese_chin_139.webp",
|
||||
"japanese_chin_182.webp",
|
||||
"japanese_chin_25.webp",
|
||||
|
|
@ -628,7 +628,7 @@
|
|||
"n02104029_4696.webp",
|
||||
"n02104029_662.webp"
|
||||
],
|
||||
"пиренейская _горная_собака": [
|
||||
"пиренейская_горная_собака": [
|
||||
"great_pyrenees_124.webp",
|
||||
"great_pyrenees_143.webp",
|
||||
"great_pyrenees_18.webp",
|
||||
|
|
@ -726,7 +726,7 @@
|
|||
"scottish_terrier_185.webp",
|
||||
"scottish_terrier_99.webp"
|
||||
],
|
||||
"австралийский келпи": [
|
||||
"австралийский_келпи": [
|
||||
"n02105412_1757.webp",
|
||||
"n02105412_3786.webp",
|
||||
"n02105412_6770.webp",
|
||||
|
|
@ -803,13 +803,6 @@
|
|||
"n02089078_4098.webp",
|
||||
"n02089078_4508.webp"
|
||||
],
|
||||
"карликовый_пинчер": [
|
||||
"n02107312_1154.webp",
|
||||
"n02107312_2072.webp",
|
||||
"n02107312_3071.webp",
|
||||
"n02107312_3994.webp",
|
||||
"n02107312_5968.webp"
|
||||
],
|
||||
"ирландский_мягкошёрстный_пшеничный_терьер": [
|
||||
"wheaten_terrier_107.webp",
|
||||
"wheaten_terrier_177.webp",
|
||||
|
|
@ -859,7 +852,7 @@
|
|||
"n02099267_4812.webp",
|
||||
"n02099267_4887.webp"
|
||||
],
|
||||
"родезийский риджбек": [
|
||||
"родезийский_риджбек": [
|
||||
"n02087394_3450.webp",
|
||||
"n02087394_4410.webp",
|
||||
"n02087394_4681.webp",
|
||||
|
|
@ -1062,13 +1055,6 @@
|
|||
"n02091831_7237.webp",
|
||||
"n02091831_735.webp"
|
||||
],
|
||||
"карликовый _пинчер": [
|
||||
"miniature_pinscher_130.webp",
|
||||
"miniature_pinscher_149.webp",
|
||||
"miniature_pinscher_153.webp",
|
||||
"miniature_pinscher_53.webp",
|
||||
"miniature_pinscher_55.webp"
|
||||
],
|
||||
"йоркширский_терьер": [
|
||||
"yorkshire_terrier_120.webp",
|
||||
"yorkshire_terrier_148.webp",
|
||||
|
|
@ -1132,7 +1118,7 @@
|
|||
"n02113624_720.webp",
|
||||
"n02113624_942.webp"
|
||||
],
|
||||
"австралийский терьер": [
|
||||
"австралийский_терьер": [
|
||||
"n02096294_1133.webp",
|
||||
"n02096294_3472.webp",
|
||||
"n02096294_3554.webp",
|
||||
|
|
@ -1321,6 +1307,13 @@
|
|||
"n02113978_3249.webp",
|
||||
"n02113978_839.webp"
|
||||
],
|
||||
"карликовый_пинчер": [
|
||||
"n02107312_1154.webp",
|
||||
"n02107312_2072.webp",
|
||||
"n02107312_3071.webp",
|
||||
"n02107312_3994.webp",
|
||||
"n02107312_5968.webp"
|
||||
],
|
||||
"боксер": [
|
||||
"boxer_136.webp",
|
||||
"boxer_142.webp",
|
||||
|
|
|
|||
File diff suppressed because one or more lines are too long
|
|
@ -1,8 +1,8 @@
|
|||
from abc import ABCMeta, abstractmethod
|
||||
from functools import lru_cache
|
||||
|
||||
from aiocache import cached, Cache # type: ignore
|
||||
import ujson
|
||||
from aiocache import Cache, cached # type: ignore
|
||||
|
||||
|
||||
class ARecognizerRepository(metaclass=ABCMeta):
|
||||
|
|
@ -29,26 +29,22 @@ class RecognizerRepository(ARecognizerRepository):
|
|||
|
||||
@cached(ttl=60, cache=Cache.MEMORY)
|
||||
async def images_dogs(self) -> dict:
|
||||
with open("server/modules/recognizer/repository/meta/images.json", "r") as f:
|
||||
with open("server/modules/recognizer/repository/meta/images.json") as f: # noqa: ASYNC230
|
||||
return ujson.loads(f.read())["dog"]
|
||||
|
||||
@cached(ttl=60, cache=Cache.MEMORY)
|
||||
async def images_cats(self) -> dict:
|
||||
with open("server/modules/recognizer/repository/meta/images.json", "r") as f:
|
||||
with open("server/modules/recognizer/repository/meta/images.json") as f: # noqa: ASYNC230
|
||||
return ujson.loads(f.read())["cat"]
|
||||
|
||||
@lru_cache
|
||||
def labels_cats(self) -> dict:
|
||||
with open(
|
||||
"server/modules/recognizer/repository/meta/labels_cats.json", "r"
|
||||
) as f:
|
||||
with open("server/modules/recognizer/repository/meta/labels_cats.json") as f: # noqa: ASYNC230
|
||||
data_labels = f.read()
|
||||
return ujson.loads(data_labels)
|
||||
|
||||
@lru_cache
|
||||
def labels_dogs(self) -> dict:
|
||||
with open(
|
||||
"server/modules/recognizer/repository/meta/labels_dogs.json", "r"
|
||||
) as f:
|
||||
with open("server/modules/recognizer/repository/meta/labels_dogs.json") as f: # noqa: ASYNC230
|
||||
data_labels = f.read()
|
||||
return ujson.loads(data_labels)
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
from typing import NewType, Any
|
||||
import os
|
||||
import io
|
||||
import os
|
||||
from typing import Any, NewType
|
||||
|
||||
from PIL import Image
|
||||
|
||||
|
|
@ -10,7 +10,6 @@ from torchvision import transforms # type: ignore
|
|||
|
||||
from server.modules.recognizer.repository import ARecognizerRepository
|
||||
|
||||
|
||||
TorchModel = NewType("TorchModel", torch.nn.Module)
|
||||
|
||||
|
||||
|
|
@ -49,15 +48,10 @@ class RecognizerService:
|
|||
images.append(
|
||||
{
|
||||
"name": name,
|
||||
"url": [
|
||||
f"/static/assets/dog/{predicted_label}/{i}"
|
||||
for i in images_dogs[predicted_label]
|
||||
],
|
||||
"url": [f"/static/assets/dog/{predicted_label}/{i}" for i in images_dogs[predicted_label]],
|
||||
}
|
||||
)
|
||||
description.setdefault(name, []).append(
|
||||
f"/dogs-characteristics/{name.replace(' ', '_')}"
|
||||
)
|
||||
description.setdefault(name, []).append(f"/dogs-characteristics/{name.replace(' ', '_')}")
|
||||
results[probabilities] = name
|
||||
return {
|
||||
"results": results,
|
||||
|
|
@ -77,10 +71,7 @@ class RecognizerService:
|
|||
images.append(
|
||||
{
|
||||
"name": name,
|
||||
"url": [
|
||||
f"/static/assets/cat/{predicted_label}/{i}"
|
||||
for i in images_cats[predicted_label]
|
||||
],
|
||||
"url": [f"/static/assets/cat/{predicted_label}/{i}" for i in images_cats[predicted_label]],
|
||||
}
|
||||
)
|
||||
results[probabilities] = name
|
||||
|
|
@ -99,9 +90,7 @@ class RecognizerService:
|
|||
]
|
||||
)
|
||||
input_tensor = preprocess(Image.open(io.BytesIO(image)))
|
||||
input_batch = input_tensor.unsqueeze(0).to(
|
||||
device
|
||||
) # Добавляем dimension для батча
|
||||
input_batch = input_tensor.unsqueeze(0).to(device) # Добавляем dimension для батча
|
||||
|
||||
with torch.no_grad():
|
||||
output = model(input_batch)
|
||||
|
|
@ -112,7 +101,5 @@ class RecognizerService:
|
|||
|
||||
predicted_data = []
|
||||
for i in range(k):
|
||||
predicted_data.append(
|
||||
(predicted_idx[i].item(), float(topk_probs[i].item()))
|
||||
)
|
||||
predicted_data.append((predicted_idx[i].item(), float(topk_probs[i].item())))
|
||||
return predicted_data
|
||||
|
|
|
|||
|
|
@ -33,7 +33,7 @@ async function SavePhoto(self) {
|
|||
// Обработка основных результатов
|
||||
for (let key in json.results) {
|
||||
if (json.description != undefined) {
|
||||
text += `<div class='image-block'><div class='image-text'>${json.results[key]} (вероятность: ${Math.round(parseFloat(key) * 100)}%) <br/><a href="/dogs-characteristics/${json.results[key]}" target='_blank'>Описание </a></div>`;
|
||||
text += `<div class='image-block'><div class='image-text'>${json.results[key]} (вероятность: ${Math.round(parseFloat(key) * 100)}%) <br/><a href="${json.description[json.results[key]]}" target='_blank'>Описание </a></div>`;
|
||||
} else {
|
||||
text += `<div class='image-block'><div class='image-text'>${json.results[key]} (вероятность: ${Math.round(parseFloat(key) * 100)}%)</div>`;
|
||||
}
|
||||
|
|
|
|||
|
|
@ -45,6 +45,6 @@
|
|||
{% block form %}{% endblock %}
|
||||
</body>
|
||||
</section>
|
||||
<script src="/static/scripts.js?v=7"></script>
|
||||
<script src="/static/scripts.js?v=8"></script>
|
||||
|
||||
</html>
|
||||
|
|
|
|||
515
uv.lock
515
uv.lock
|
|
@ -12,10 +12,13 @@ name = "ai"
|
|||
version = "0.1.0"
|
||||
source = { virtual = "." }
|
||||
dependencies = [
|
||||
{ name = "aioboto3" },
|
||||
{ name = "aiocache" },
|
||||
{ name = "aiofiles" },
|
||||
{ name = "alembic" },
|
||||
{ name = "asyncpg" },
|
||||
{ name = "betterconf" },
|
||||
{ name = "boto3" },
|
||||
{ name = "botocore" },
|
||||
{ name = "dataclasses-ujson" },
|
||||
{ name = "granian" },
|
||||
|
|
@ -26,7 +29,9 @@ dependencies = [
|
|||
{ name = "mypy" },
|
||||
{ name = "numpy" },
|
||||
{ name = "pillow" },
|
||||
{ name = "psycopg2-binary" },
|
||||
{ name = "pydantic" },
|
||||
{ name = "python-magic" },
|
||||
{ name = "ruff" },
|
||||
{ name = "sqlalchemy" },
|
||||
{ name = "torch" },
|
||||
|
|
@ -52,10 +57,13 @@ default = [
|
|||
|
||||
[package.metadata]
|
||||
requires-dist = [
|
||||
{ name = "aioboto3", specifier = ">=7.0.0" },
|
||||
{ name = "aiocache" },
|
||||
{ name = "aiofiles", specifier = ">=25.1.0" },
|
||||
{ name = "alembic", specifier = ">=1.18.0" },
|
||||
{ name = "asyncpg", specifier = ">=0.31.0" },
|
||||
{ name = "betterconf", specifier = ">=4.5.0" },
|
||||
{ name = "boto3", specifier = ">=1.42.9" },
|
||||
{ name = "botocore", specifier = ">=1.42.9" },
|
||||
{ name = "dataclasses-ujson", specifier = ">=0.0.34" },
|
||||
{ name = "granian", specifier = "==2.5" },
|
||||
|
|
@ -68,8 +76,10 @@ requires-dist = [
|
|||
{ name = "mypy", marker = "extra == 'default'", specifier = ">=1.18" },
|
||||
{ name = "numpy", specifier = "==2.3.4" },
|
||||
{ name = "pillow", specifier = ">=11.1.0" },
|
||||
{ name = "psycopg2-binary", specifier = ">=2.9.11" },
|
||||
{ name = "pydantic", specifier = ">=2.12.4" },
|
||||
{ name = "pyqt5", marker = "extra == 'default'", specifier = ">=5.15.11" },
|
||||
{ name = "python-magic", specifier = ">=0.4.27" },
|
||||
{ name = "requests", marker = "extra == 'default'", specifier = ">=2.32.3" },
|
||||
{ name = "ruff", specifier = ">=0.14.5" },
|
||||
{ name = "ruff", marker = "extra == 'default'", specifier = ">=0.11.5" },
|
||||
|
|
@ -87,6 +97,36 @@ requires-dist = [
|
|||
]
|
||||
provides-extras = ["default"]
|
||||
|
||||
[[package]]
|
||||
name = "aioboto3"
|
||||
version = "7.0.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "aiobotocore" },
|
||||
]
|
||||
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{ url = "https://files.pythonhosted.org/packages/73/ae/b48f95715333080afb75a4504487cbe142cae1268afc482d06692d605ae6/yarl-1.22.0-py3-none-any.whl", hash = "sha256:1380560bdba02b6b6c90de54133c81c9f2a453dee9912fe58c1dcced1edb7cff", size = 46814 },
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]
|
||||
|
|
|
|||
|
|
@ -1,5 +1,6 @@
|
|||
import os
|
||||
import time
|
||||
|
||||
import requests # type: ignore
|
||||
|
||||
# Получить токен чтобы:
|
||||
|
|
@ -12,9 +13,7 @@ group_id = 220240483
|
|||
dir = "../assets/dog"
|
||||
list_labels = [fname for fname in os.listdir(dir)]
|
||||
|
||||
r = requests.get(
|
||||
f"{VK_URL}photos.getAll{postfix}&access_token={TOKEN}&owner_id=-{group_id}&count=200"
|
||||
)
|
||||
r = requests.get(f"{VK_URL}photos.getAll{postfix}&access_token={TOKEN}&owner_id=-{group_id}&count=200")
|
||||
if "error" in r.json():
|
||||
print("error", r.json())
|
||||
exit()
|
||||
|
|
|
|||
Loading…
Reference in New Issue