ai_v/venv/Lib/site-packages/botocore/paginate.py
24024 af7c11d7f9 feat(api): 实现图像生成及后台同步功能
- 新增图像生成接口,支持试用、积分和自定义API Key模式
- 实现生成图片结果异步上传至MinIO存储,带重试机制
- 优化积分预扣除和异常退还逻辑,保障用户积分准确
- 添加获取生成历史记录接口,支持时间范围和分页
- 提供本地字典配置接口,支持模型、比例、提示模板和尺寸
- 实现图片批量上传接口,支持S3兼容对象存储

feat(admin): 增加管理员角色管理与权限分配接口

- 实现角色列表查询、角色创建、更新及删除功能
- 增加权限列表查询接口
- 实现用户角色分配接口,便于统一管理用户权限
- 增加系统字典增删查改接口,支持分类过滤和排序
- 权限控制全面覆盖管理接口,保证安全访问

feat(auth): 完善用户登录注册及权限相关接口与页面

- 实现手机号验证码发送及校验功能,保障注册安全
- 支持手机号注册、登录及退出接口,集成日志记录
- 增加修改密码功能,验证原密码后更新
- 提供动态导航菜单接口,基于权限展示不同菜单
- 实现管理界面路由及日志、角色、字典管理页面访问权限控制
- 添加系统日志查询接口,支持关键词和等级筛选

feat(app): 初始化Flask应用并配置蓝图与数据库

- 创建应用程序工厂,加载配置,初始化数据库和Redis客户端
- 注册认证、API及管理员蓝图,整合路由
- 根路由渲染主页模板
- 应用上下文中自动创建数据库表,保证运行环境准备完毕

feat(database): 提供数据库创建与迁移支持脚本

- 新增数据库创建脚本,支持自动检测是否已存在
- 添加数据库表初始化脚本,支持创建和删除所有表
- 实现RBAC权限初始化,包含基础权限和角色创建
- 新增字段手动修复脚本,添加用户API Key和积分字段
- 强制迁移脚本支持清理连接和修复表结构,初始化默认数据及角色分配

feat(config): 新增系统配置参数

- 配置数据库、Redis、Session和MinIO相关参数
- 添加AI接口地址及试用Key配置
- 集成阿里云短信服务配置及开发模式相关参数

feat(extensions): 初始化数据库、Redis和MinIO客户端

- 创建全局SQLAlchemy数据库实例和Redis客户端
- 配置基于boto3的MinIO兼容S3客户端

chore(logs): 添加示例系统日志文件

- 记录用户请求、验证码发送成功与失败的日志信息
2026-01-12 00:53:31 +08:00

729 lines
27 KiB
Python

# Copyright 2012-2014 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
import base64
import json
import logging
from functools import partial
from itertools import tee
import jmespath
from botocore.context import with_current_context
from botocore.exceptions import PaginationError
from botocore.useragent import register_feature_id
from botocore.utils import merge_dicts, set_value_from_jmespath
log = logging.getLogger(__name__)
class TokenEncoder:
"""Encodes dictionaries into opaque strings.
This for the most part json dumps + base64 encoding, but also supports
having bytes in the dictionary in addition to the types that json can
handle by default.
This is intended for use in encoding pagination tokens, which in some
cases can be complex structures and / or contain bytes.
"""
def encode(self, token):
"""Encodes a dictionary to an opaque string.
:type token: dict
:param token: A dictionary containing pagination information,
particularly the service pagination token(s) but also other boto
metadata.
:rtype: str
:returns: An opaque string
"""
try:
# Try just using json dumps first to avoid having to traverse
# and encode the dict. In 99.9999% of cases this will work.
json_string = json.dumps(token)
except (TypeError, UnicodeDecodeError):
# If normal dumping failed, go through and base64 encode all bytes.
encoded_token, encoded_keys = self._encode(token, [])
# Save the list of all the encoded key paths. We can safely
# assume that no service will ever use this key.
encoded_token['boto_encoded_keys'] = encoded_keys
# Now that the bytes are all encoded, dump the json.
json_string = json.dumps(encoded_token)
# base64 encode the json string to produce an opaque token string.
return base64.b64encode(json_string.encode('utf-8')).decode('utf-8')
def _encode(self, data, path):
"""Encode bytes in given data, keeping track of the path traversed."""
if isinstance(data, dict):
return self._encode_dict(data, path)
elif isinstance(data, list):
return self._encode_list(data, path)
elif isinstance(data, bytes):
return self._encode_bytes(data, path)
else:
return data, []
def _encode_list(self, data, path):
"""Encode any bytes in a list, noting the index of what is encoded."""
new_data = []
encoded = []
for i, value in enumerate(data):
new_path = path + [i]
new_value, new_encoded = self._encode(value, new_path)
new_data.append(new_value)
encoded.extend(new_encoded)
return new_data, encoded
def _encode_dict(self, data, path):
"""Encode any bytes in a dict, noting the index of what is encoded."""
new_data = {}
encoded = []
for key, value in data.items():
new_path = path + [key]
new_value, new_encoded = self._encode(value, new_path)
new_data[key] = new_value
encoded.extend(new_encoded)
return new_data, encoded
def _encode_bytes(self, data, path):
"""Base64 encode a byte string."""
return base64.b64encode(data).decode('utf-8'), [path]
class TokenDecoder:
"""Decodes token strings back into dictionaries.
This performs the inverse operation to the TokenEncoder, accepting
opaque strings and decoding them into a useable form.
"""
def decode(self, token):
"""Decodes an opaque string to a dictionary.
:type token: str
:param token: A token string given by the botocore pagination
interface.
:rtype: dict
:returns: A dictionary containing pagination information,
particularly the service pagination token(s) but also other boto
metadata.
"""
json_string = base64.b64decode(token.encode('utf-8')).decode('utf-8')
decoded_token = json.loads(json_string)
# Remove the encoding metadata as it is read since it will no longer
# be needed.
encoded_keys = decoded_token.pop('boto_encoded_keys', None)
if encoded_keys is None:
return decoded_token
else:
return self._decode(decoded_token, encoded_keys)
def _decode(self, token, encoded_keys):
"""Find each encoded value and decode it."""
for key in encoded_keys:
encoded = self._path_get(token, key)
decoded = base64.b64decode(encoded.encode('utf-8'))
self._path_set(token, key, decoded)
return token
def _path_get(self, data, path):
"""Return the nested data at the given path.
For instance:
data = {'foo': ['bar', 'baz']}
path = ['foo', 0]
==> 'bar'
"""
# jmespath isn't used here because it would be difficult to actually
# create the jmespath query when taking all of the unknowns of key
# structure into account. Gross though this is, it is simple and not
# very error prone.
d = data
for step in path:
d = d[step]
return d
def _path_set(self, data, path, value):
"""Set the value of a key in the given data.
Example:
data = {'foo': ['bar', 'baz']}
path = ['foo', 1]
value = 'bin'
==> data = {'foo': ['bar', 'bin']}
"""
container = self._path_get(data, path[:-1])
container[path[-1]] = value
class PaginatorModel:
def __init__(self, paginator_config):
self._paginator_config = paginator_config['pagination']
def get_paginator(self, operation_name):
try:
single_paginator_config = self._paginator_config[operation_name]
except KeyError:
raise ValueError(
f"Paginator for operation does not exist: {operation_name}"
)
return single_paginator_config
class PageIterator:
"""An iterable object to paginate API results.
Please note it is NOT a python iterator.
Use ``iter`` to wrap this as a generator.
"""
def __init__(
self,
method,
input_token,
output_token,
more_results,
result_keys,
non_aggregate_keys,
limit_key,
max_items,
starting_token,
page_size,
op_kwargs,
):
self._method = method
self._input_token = input_token
self._output_token = output_token
self._more_results = more_results
self._result_keys = result_keys
self._max_items = max_items
self._limit_key = limit_key
self._starting_token = starting_token
self._page_size = page_size
self._op_kwargs = op_kwargs
self._resume_token = None
self._non_aggregate_key_exprs = non_aggregate_keys
self._non_aggregate_part = {}
self._token_encoder = TokenEncoder()
self._token_decoder = TokenDecoder()
@property
def result_keys(self):
return self._result_keys
@property
def resume_token(self):
"""Token to specify to resume pagination."""
return self._resume_token
@resume_token.setter
def resume_token(self, value):
if not isinstance(value, dict):
raise ValueError(f"Bad starting token: {value}")
if 'boto_truncate_amount' in value:
token_keys = sorted(self._input_token + ['boto_truncate_amount'])
else:
token_keys = sorted(self._input_token)
dict_keys = sorted(value.keys())
if token_keys == dict_keys:
self._resume_token = self._token_encoder.encode(value)
else:
raise ValueError(f"Bad starting token: {value}")
@property
def non_aggregate_part(self):
return self._non_aggregate_part
def __iter__(self):
current_kwargs = self._op_kwargs
previous_next_token = None
next_token = {key: None for key in self._input_token}
if self._starting_token is not None:
# If the starting token exists, populate the next_token with the
# values inside it. This ensures that we have the service's
# pagination token on hand if we need to truncate after the
# first response.
next_token = self._parse_starting_token()[0]
# The number of items from result_key we've seen so far.
total_items = 0
first_request = True
primary_result_key = self.result_keys[0]
starting_truncation = 0
self._inject_starting_params(current_kwargs)
while True:
response = self._make_request(current_kwargs)
parsed = self._extract_parsed_response(response)
if first_request:
# The first request is handled differently. We could
# possibly have a resume/starting token that tells us where
# to index into the retrieved page.
if self._starting_token is not None:
starting_truncation = self._handle_first_request(
parsed, primary_result_key, starting_truncation
)
first_request = False
self._record_non_aggregate_key_values(parsed)
else:
# If this isn't the first request, we have already sliced into
# the first request and had to make additional requests after.
# We no longer need to add this to truncation.
starting_truncation = 0
current_response = primary_result_key.search(parsed)
if current_response is None:
current_response = []
num_current_response = len(current_response)
truncate_amount = 0
if self._max_items is not None:
truncate_amount = (
total_items + num_current_response - self._max_items
)
if truncate_amount > 0:
self._truncate_response(
parsed,
primary_result_key,
truncate_amount,
starting_truncation,
next_token,
)
yield response
break
else:
yield response
total_items += num_current_response
next_token = self._get_next_token(parsed)
if all(t is None for t in next_token.values()):
break
if (
self._max_items is not None
and total_items == self._max_items
):
# We're on a page boundary so we can set the current
# next token to be the resume token.
self.resume_token = next_token
break
if (
previous_next_token is not None
and previous_next_token == next_token
):
message = (
f"The same next token was received twice: {next_token}"
)
raise PaginationError(message=message)
self._inject_token_into_kwargs(current_kwargs, next_token)
previous_next_token = next_token
def search(self, expression):
"""Applies a JMESPath expression to a paginator
Each page of results is searched using the provided JMESPath
expression. If the result is not a list, it is yielded
directly. If the result is a list, each element in the result
is yielded individually (essentially implementing a flatmap in
which the JMESPath search is the mapping function).
:type expression: str
:param expression: JMESPath expression to apply to each page.
:return: Returns an iterator that yields the individual
elements of applying a JMESPath expression to each page of
results.
"""
compiled = jmespath.compile(expression)
for page in self:
results = compiled.search(page)
if isinstance(results, list):
yield from results
else:
# Yield result directly if it is not a list.
yield results
@with_current_context(partial(register_feature_id, 'PAGINATOR'))
def _make_request(self, current_kwargs):
return self._method(**current_kwargs)
def _extract_parsed_response(self, response):
return response
def _record_non_aggregate_key_values(self, response):
non_aggregate_keys = {}
for expression in self._non_aggregate_key_exprs:
result = expression.search(response)
set_value_from_jmespath(
non_aggregate_keys, expression.expression, result
)
self._non_aggregate_part = non_aggregate_keys
def _inject_starting_params(self, op_kwargs):
# If the user has specified a starting token we need to
# inject that into the operation's kwargs.
if self._starting_token is not None:
# Don't need to do anything special if there is no starting
# token specified.
next_token = self._parse_starting_token()[0]
self._inject_token_into_kwargs(op_kwargs, next_token)
if self._page_size is not None:
# Pass the page size as the parameter name for limiting
# page size, also known as the limit_key.
op_kwargs[self._limit_key] = self._page_size
def _inject_token_into_kwargs(self, op_kwargs, next_token):
for name, token in next_token.items():
if (token is not None) and (token != 'None'):
op_kwargs[name] = token
elif name in op_kwargs:
del op_kwargs[name]
def _handle_first_request(
self, parsed, primary_result_key, starting_truncation
):
# If the payload is an array or string, we need to slice into it
# and only return the truncated amount.
starting_truncation = self._parse_starting_token()[1]
all_data = primary_result_key.search(parsed)
if isinstance(all_data, (list, str)):
data = all_data[starting_truncation:]
else:
data = None
set_value_from_jmespath(parsed, primary_result_key.expression, data)
# We also need to truncate any secondary result keys
# because they were not truncated in the previous last
# response.
for token in self.result_keys:
if token == primary_result_key:
continue
sample = token.search(parsed)
if isinstance(sample, list):
empty_value = []
elif isinstance(sample, str):
empty_value = ''
elif isinstance(sample, (int, float)):
# Even though we may be resuming from a truncated page, we
# still start from the actual numeric secondary result. For
# DynamoDB's Count/ScannedCount, this will still show how many
# items the server evaluated, even if the client is truncating
# due to a StartingToken.
empty_value = sample
else:
empty_value = None
set_value_from_jmespath(parsed, token.expression, empty_value)
return starting_truncation
def _truncate_response(
self,
parsed,
primary_result_key,
truncate_amount,
starting_truncation,
next_token,
):
original = primary_result_key.search(parsed)
if original is None:
original = []
amount_to_keep = len(original) - truncate_amount
truncated = original[:amount_to_keep]
set_value_from_jmespath(
parsed, primary_result_key.expression, truncated
)
# The issue here is that even though we know how much we've truncated
# we need to account for this globally including any starting
# left truncation. For example:
# Raw response: [0,1,2,3]
# Starting index: 1
# Max items: 1
# Starting left truncation: [1, 2, 3]
# End right truncation for max items: [1]
# However, even though we only kept 1, this is post
# left truncation so the next starting index should be 2, not 1
# (left_truncation + amount_to_keep).
next_token['boto_truncate_amount'] = (
amount_to_keep + starting_truncation
)
self.resume_token = next_token
def _get_next_token(self, parsed):
if self._more_results is not None:
if not self._more_results.search(parsed):
return {}
next_tokens = {}
for output_token, input_key in zip(
self._output_token, self._input_token
):
next_token = output_token.search(parsed)
# We do not want to include any empty strings as actual tokens.
# Treat them as None.
if next_token:
next_tokens[input_key] = next_token
else:
next_tokens[input_key] = None
return next_tokens
def result_key_iters(self):
teed_results = tee(self, len(self.result_keys))
return [
ResultKeyIterator(i, result_key)
for i, result_key in zip(teed_results, self.result_keys)
]
def build_full_result(self):
complete_result = {}
for response in self:
page = response
# We want to try to catch operation object pagination
# and format correctly for those. They come in the form
# of a tuple of two elements: (http_response, parsed_responsed).
# We want the parsed_response as that is what the page iterator
# uses. We can remove it though once operation objects are removed.
if isinstance(response, tuple) and len(response) == 2:
page = response[1]
# We're incrementally building the full response page
# by page. For each page in the response we need to
# inject the necessary components from the page
# into the complete_result.
for result_expression in self.result_keys:
# In order to incrementally update a result key
# we need to search the existing value from complete_result,
# then we need to search the _current_ page for the
# current result key value. Then we append the current
# value onto the existing value, and re-set that value
# as the new value.
result_value = result_expression.search(page)
if result_value is None:
continue
existing_value = result_expression.search(complete_result)
if existing_value is None:
# Set the initial result
set_value_from_jmespath(
complete_result,
result_expression.expression,
result_value,
)
continue
# Now both result_value and existing_value contain something
if isinstance(result_value, list):
existing_value.extend(result_value)
elif isinstance(result_value, (int, float, str)):
# Modify the existing result with the sum or concatenation
set_value_from_jmespath(
complete_result,
result_expression.expression,
existing_value + result_value,
)
merge_dicts(complete_result, self.non_aggregate_part)
if self.resume_token is not None:
complete_result['NextToken'] = self.resume_token
return complete_result
def _parse_starting_token(self):
if self._starting_token is None:
return None
# The starting token is a dict passed as a base64 encoded string.
next_token = self._starting_token
try:
next_token = self._token_decoder.decode(next_token)
index = 0
if 'boto_truncate_amount' in next_token:
index = next_token.get('boto_truncate_amount')
del next_token['boto_truncate_amount']
except (ValueError, TypeError):
next_token, index = self._parse_starting_token_deprecated()
return next_token, index
def _parse_starting_token_deprecated(self):
"""
This handles parsing of old style starting tokens, and attempts to
coerce them into the new style.
"""
log.debug(
"Attempting to fall back to old starting token parser. For token: %s",
self._starting_token,
)
if self._starting_token is None:
return None
parts = self._starting_token.split('___')
next_token = []
index = 0
if len(parts) == len(self._input_token) + 1:
try:
index = int(parts.pop())
except ValueError:
# This doesn't look like a valid old-style token, so we're
# passing it along as an opaque service token.
parts = [self._starting_token]
for part in parts:
if part == 'None':
next_token.append(None)
else:
next_token.append(part)
return self._convert_deprecated_starting_token(next_token), index
def _convert_deprecated_starting_token(self, deprecated_token):
"""
This attempts to convert a deprecated starting token into the new
style.
"""
len_deprecated_token = len(deprecated_token)
len_input_token = len(self._input_token)
if len_deprecated_token > len_input_token:
raise ValueError(f"Bad starting token: {self._starting_token}")
elif len_deprecated_token < len_input_token:
log.debug(
"Old format starting token does not contain all input "
"tokens. Setting the rest, in order, as None."
)
for i in range(len_input_token - len_deprecated_token):
deprecated_token.append(None)
return dict(zip(self._input_token, deprecated_token))
class Paginator:
PAGE_ITERATOR_CLS = PageIterator
def __init__(self, method, pagination_config, model):
self._model = model
self._method = method
self._pagination_cfg = pagination_config
self._output_token = self._get_output_tokens(self._pagination_cfg)
self._input_token = self._get_input_tokens(self._pagination_cfg)
self._more_results = self._get_more_results_token(self._pagination_cfg)
self._non_aggregate_keys = self._get_non_aggregate_keys(
self._pagination_cfg
)
self._result_keys = self._get_result_keys(self._pagination_cfg)
self._limit_key = self._get_limit_key(self._pagination_cfg)
@property
def result_keys(self):
return self._result_keys
def _get_non_aggregate_keys(self, config):
keys = []
for key in config.get('non_aggregate_keys', []):
keys.append(jmespath.compile(key))
return keys
def _get_output_tokens(self, config):
output = []
output_token = config['output_token']
if not isinstance(output_token, list):
output_token = [output_token]
for config in output_token:
output.append(jmespath.compile(config))
return output
def _get_input_tokens(self, config):
input_token = self._pagination_cfg['input_token']
if not isinstance(input_token, list):
input_token = [input_token]
return input_token
def _get_more_results_token(self, config):
more_results = config.get('more_results')
if more_results is not None:
return jmespath.compile(more_results)
def _get_result_keys(self, config):
result_key = config.get('result_key')
if result_key is not None:
if not isinstance(result_key, list):
result_key = [result_key]
result_key = [jmespath.compile(rk) for rk in result_key]
return result_key
def _get_limit_key(self, config):
return config.get('limit_key')
def paginate(self, **kwargs):
"""Create paginator object for an operation.
This returns an iterable object. Iterating over
this object will yield a single page of a response
at a time.
"""
page_params = self._extract_paging_params(kwargs)
return self.PAGE_ITERATOR_CLS(
self._method,
self._input_token,
self._output_token,
self._more_results,
self._result_keys,
self._non_aggregate_keys,
self._limit_key,
page_params['MaxItems'],
page_params['StartingToken'],
page_params['PageSize'],
kwargs,
)
def _extract_paging_params(self, kwargs):
pagination_config = kwargs.pop('PaginationConfig', {})
max_items = pagination_config.get('MaxItems', None)
if max_items is not None:
max_items = int(max_items)
page_size = pagination_config.get('PageSize', None)
if page_size is not None:
if self._limit_key is None:
raise PaginationError(
message="PageSize parameter is not supported for the "
"pagination interface for this operation."
)
input_members = self._model.input_shape.members
limit_key_shape = input_members.get(self._limit_key)
if limit_key_shape.type_name == 'string':
if not isinstance(page_size, str):
page_size = str(page_size)
else:
page_size = int(page_size)
return {
'MaxItems': max_items,
'StartingToken': pagination_config.get('StartingToken', None),
'PageSize': page_size,
}
class ResultKeyIterator:
"""Iterates over the results of paginated responses.
Each iterator is associated with a single result key.
Iterating over this object will give you each element in
the result key list.
:param pages_iterator: An iterator that will give you
pages of results (a ``PageIterator`` class).
:param result_key: The JMESPath expression representing
the result key.
"""
def __init__(self, pages_iterator, result_key):
self._pages_iterator = pages_iterator
self.result_key = result_key
def __iter__(self):
for page in self._pages_iterator:
results = self.result_key.search(page)
if results is None:
results = []
yield from results