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7e3c148481dc5590346b302c02684885ab710d45 | 48,147 | py | Python | ui.py | wusuopu/lc-pydns | 4caa6efdcce08d05648f436dc8c845f820ebac6b | [
"Python-2.0"
] | 1 | 2015-09-24T13:11:23.000Z | 2015-09-24T13:11:23.000Z | ui.py | wusuopu/lc-pydns | 4caa6efdcce08d05648f436dc8c845f820ebac6b | [
"Python-2.0"
] | null | null | null | ui.py | wusuopu/lc-pydns | 4caa6efdcce08d05648f436dc8c845f820ebac6b | [
"Python-2.0"
] | null | null | null | #!/usr/bin/env python
#-*- coding:utf-8 -*-
##
# Copyright (C)
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation.
# 本程序是免费软件，基于GPL许可发布。
#
##
# @文件名(file): ui.py
# @作者(author): 龙昌锦(LongChangjin)
# @博客(blog): http://www.xefan.com
# @邮箱(mail): admin@xefan.com
# @QQ: 346202141
# @ICQ: wosuopu@gmail.com
# @时间(date): 2012-03-08
#
login = """
<?xml version="1.0" encoding="UTF-8"?>
<interface>
<requires lib="gtk+" version="2.24"/>
<!-- interface-naming-policy project-wide -->
<object class="GtkWindow" id="window_login">
<property name="width_request">300</property>
<property name="height_request">150</property>
<property name="can_focus">False</property>
<property name="title" translatable="yes">LC-pydns v1.0</property>
<property name="resizable">False</property>
<property name="window_position">center</property>
<property name="icon">logo.ico</property>
<property name="opacity">0.90000000000000002</property>
<signal name="destroy" handler="main_quit" swapped="no"/>
<child>
<object class="GtkFixed" id="fixed_login">
<property name="visible">True</property>
<property name="can_focus">False</property>
<child>
<object class="GtkLabel" id="label_mail">
<property name="width_request">100</property>
<property name="height_request">25</property>
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="label" translatable="yes">邮箱：</property>
</object>
<packing>
<property name="x">15</property>
<property name="y">25</property>
</packing>
</child>
<child>
<object class="GtkLabel" id="label_pswd">
<property name="width_request">100</property>
<property name="height_request">25</property>
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="label" translatable="yes">密码：</property>
</object>
<packing>
<property name="x">15</property>
<property name="y">70</property>
</packing>
</child>
<child>
<object class="GtkEntry" id="entry_mail">
<property name="width_request">150</property>
<property name="height_request">25</property>
<property name="visible">True</property>
<property name="can_focus">True</property>
<property name="invisible_char">●</property>
<property name="primary_icon_activatable">False</property>
<property name="secondary_icon_activatable">False</property>
<property name="primary_icon_sensitive">True</property>
<property name="secondary_icon_sensitive">True</property>
</object>
<packing>
<property name="x">120</property>
<property name="y">25</property>
</packing>
</child>
<child>
<object class="GtkEntry" id="entry_pswd">
<property name="width_request">150</property>
<property name="height_request">25</property>
<property name="visible">True</property>
<property name="can_focus">True</property>
<property name="visibility">False</property>
<property name="invisible_char">●</property>
<property name="primary_icon_activatable">False</property>
<property name="secondary_icon_activatable">False</property>
<property name="primary_icon_sensitive">True</property>
<property name="secondary_icon_sensitive">True</property>
</object>
<packing>
<property name="x">120</property>
<property name="y">70</property>
</packing>
</child>
<child>
<object class="GtkButton" id="button_login">
<property name="label" translatable="yes">登陆</property>
<property name="use_action_appearance">False</property>
<property name="width_request">80</property>
<property name="height_request">25</property>
<property name="visible">True</property>
<property name="can_focus">True</property>
<property name="receives_default">True</property>
<accelerator key="Return" signal="clicked"/>
<signal name="clicked" handler="on_button_login_clicked" swapped="no"/>
</object>
<packing>
<property name="x">113</property>
<property name="y">110</property>
</packing>
</child>
</object>
</child>
</object>
</interface>
"""
ui = """
<?xml version="1.0" encoding="UTF-8"?>
<interface>
<requires lib="gtk+" version="2.24"/>
<!-- interface-naming-policy project-wide -->
<object class="GtkListStore" id="liststore_domain">
<columns>
<!-- column-name id -->
<column type="gchararray"/>
<!-- column-name 标星 -->
<column type="gboolean"/>
<!-- column-name 域名 -->
<column type="gchararray"/>
<!-- column-name 状态 -->
<column type="gchararray"/>
<!-- column-name 备注 -->
<column type="gchararray"/>
</columns>
</object>
<object class="GtkListStore" id="liststore_linetype">
<columns>
<!-- column-name 线路类型 -->
<column type="gchararray"/>
</columns>
<data>
<row>
<col id="0" translatable="yes">默认</col>
</row>
<row>
<col id="0" translatable="yes">电信</col>
</row>
<row>
<col id="0" translatable="yes">联通</col>
</row>
<row>
<col id="0" translatable="yes">教育网</col>
</row>
<row>
<col id="0" translatable="yes">移动</col>
</row>
<row>
<col id="0" translatable="yes">铁通</col>
</row>
<row>
<col id="0" translatable="yes">国内</col>
</row>
<row>
<col id="0" translatable="yes">国外</col>
</row>
<row>
<col id="0" translatable="yes">搜索引擎</col>
</row>
<row>
<col id="0" translatable="yes">百度</col>
</row>
<row>
<col id="0" translatable="yes">Google</col>
</row>
<row>
<col id="0" translatable="yes">有道</col>
</row>
<row>
<col id="0" translatable="yes">必应</col>
</row>
<row>
<col id="0" translatable="yes">搜搜</col>
</row>
<row>
<col id="0" translatable="yes">搜狗</col>
</row>
</data>
</object>
<object class="GtkListStore" id="liststore_record">
<columns>
<!-- column-name rid -->
<column type="gchararray"/>
<!-- column-name 主机 -->
<column type="gchararray"/>
<!-- column-name 记录类型 -->
<column type="gchararray"/>
<!-- column-name 线路类型 -->
<column type="gchararray"/>
<!-- column-name 记录值 -->
<column type="gchararray"/>
<!-- column-name MX优先级 -->
<column type="gchararray"/>
<!-- column-name TTL -->
<column type="gchararray"/>
<!-- column-name 状态 -->
<column type="gchararray"/>
<!-- column-name 备注 -->
<column type="gchararray"/>
</columns>
</object>
<object class="GtkListStore" id="liststore_recordtype">
<columns>
<!-- column-name 记录类型 -->
<column type="gchararray"/>
</columns>
<data>
<row>
<col id="0" translatable="yes">A</col>
</row>
<row>
<col id="0" translatable="yes">CNAME</col>
</row>
<row>
<col id="0" translatable="yes">MX</col>
</row>
<row>
<col id="0" translatable="yes">TXT</col>
</row>
<row>
<col id="0" translatable="yes">NS</col>
</row>
<row>
<col id="0" translatable="yes">AAAA</col>
</row>
<row>
<col id="0" translatable="yes">SRV</col>
</row>
<row>
<col id="0" translatable="yes">URL</col>
</row>
</data>
</object>
<object class="GtkWindow" id="Mainwindow">
<property name="can_focus">False</property>
<property name="title" translatable="yes">LC-pydns v1.0</property>
<property name="window_position">center</property>
<property name="icon">logo.ico</property>
<property name="opacity">0.90000000000000002</property>
<property name="mnemonics_visible">False</property>
<signal name="delete-event" handler="main_quit" swapped="no"/>
<child>
<object class="GtkVBox" id="vbox1">
<property name="visible">True</property>
<property name="can_focus">False</property>
<child>
<object class="GtkVBox" id="vbox2">
<property name="visible">True</property>
<property name="can_focus">False</property>
<child>
<object class="GtkLabel" id="label_info">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="xalign">0.0099999997764825821</property>
<property name="label" translatable="yes"><b>个人信息：</b></property>
<property name="use_markup">True</property>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="position">0</property>
</packing>
</child>
<child>
<object class="GtkHBox" id="hbox1">
<property name="visible">True</property>
<property name="can_focus">False</property>
<child>
<object class="GtkLabel" id="label_email0">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="xalign">0.0099999997764825821</property>
<property name="label" translatable="yes"><b>邮箱：</b></property>
<property name="use_markup">True</property>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="padding">5</property>
<property name="position">0</property>
</packing>
</child>
<child>
<object class="GtkLabel" id="label_info_email">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="xalign">0.10000000149011612</property>
<property name="label" translatable="yes">mail</property>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="padding">5</property>
<property name="position">1</property>
</packing>
</child>
<child>
<object class="GtkLabel" id="label1">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="xalign">0.10000000149011612</property>
<property name="label" translatable="yes"><b>邮箱认证：</b></property>
<property name="use_markup">True</property>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="padding">5</property>
<property name="position">2</property>
</packing>
</child>
<child>
<object class="GtkLabel" id="label_info_mailverified">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="xalign">0.10000000149011612</property>
<property name="label" translatable="yes">mail_verified</property>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="padding">5</property>
<property name="position">3</property>
</packing>
</child>
<child>
<object class="GtkLabel" id="label2">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="xalign">0.10000000149011612</property>
<property name="label" translatable="yes"><b>账号状态：</b></property>
<property name="use_markup">True</property>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="padding">5</property>
<property name="position">4</property>
</packing>
</child>
<child>
<object class="GtkLabel" id="label_info_status">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="xalign">0.10000000149011612</property>
<property name="label" translatable="yes">status</property>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="padding">5</property>
<property name="position">5</property>
</packing>
</child>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="position">1</property>
</packing>
</child>
<child>
<object class="GtkHSeparator" id="hseparator1">
<property name="visible">True</property>
<property name="can_focus">False</property>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">True</property>
<property name="padding">5</property>
<property name="position">2</property>
</packing>
</child>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="position">0</property>
</packing>
</child>
<child>
<object class="GtkHPaned" id="hpaned">
<property name="visible">True</property>
<property name="can_focus">True</property>
<child>
<object class="GtkViewport" id="viewport1">
<property name="visible">True</property>
<property name="can_focus">False</property>
<child>
<object class="GtkVBox" id="vbox3">
<property name="visible">True</property>
<property name="can_focus">False</property>
<child>
<object class="GtkHBox" id="hbox2">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="spacing">5</property>
<child>
<object class="GtkLabel" id="label3">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="label" translatable="yes"><b>我的域名</b></property>
<property name="use_markup">True</property>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="padding">15</property>
<property name="position">0</property>
</packing>
</child>
<child>
<object class="GtkButton" id="button_dpause">
<property name="label" translatable="yes">暂停/启用</property>
<property name="use_action_appearance">False</property>
<property name="visible">True</property>
<property name="can_focus">True</property>
<property name="receives_default">True</property>
<signal name="clicked" handler="on_button_dpause_clicked" swapped="no"/>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="position">1</property>
</packing>
</child>
<child>
<object class="GtkButton" id="button_dfresh">
<property name="label" translatable="yes">刷新</property>
<property name="use_action_appearance">False</property>
<property name="visible">True</property>
<property name="can_focus">True</property>
<property name="receives_default">True</property>
<signal name="clicked" handler="on_button_dfresh_clicked" swapped="no"/>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="position">2</property>
</packing>
</child>
<child>
<object class="GtkButton" id="button_ddel">
<property name="label" translatable="yes">删除</property>
<property name="use_action_appearance">False</property>
<property name="visible">True</property>
<property name="can_focus">True</property>
<property name="receives_default">True</property>
<signal name="clicked" handler="on_button_ddel_clicked" swapped="no"/>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="position">3</property>
</packing>
</child>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="position">0</property>
</packing>
</child>
<child>
<object class="GtkScrolledWindow" id="scrolledwindow1">
<property name="visible">True</property>
<property name="can_focus">True</property>
<property name="hscrollbar_policy">automatic</property>
<property name="vscrollbar_policy">automatic</property>
<child>
<object class="GtkTreeView" id="treeview_domain">
<property name="width_request">220</property>
<property name="height_request">400</property>
<property name="visible">True</property>
<property name="can_focus">True</property>
<property name="model">liststore_domain</property>
<property name="enable_search">False</property>
<property name="search_column">0</property>
<property name="show_expanders">False</property>
<property name="enable_grid_lines">horizontal</property>
<signal name="row-activated" handler="on_treeview_domain_row_activated" swapped="no"/>
</object>
</child>
</object>
<packing>
<property name="expand">True</property>
<property name="fill">True</property>
<property name="position">1</property>
</packing>
</child>
<child>
<object class="GtkHBox" id="hbox4">
<property name="visible">True</property>
<property name="can_focus">False</property>
<child>
<object class="GtkLabel" id="label5">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="label" translatable="yes">输入要解析的域名：</property>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="position">0</property>
</packing>
</child>
<child>
<object class="GtkEntry" id="entry1">
<property name="width_request">110</property>
<property name="visible">True</property>
<property name="can_focus">True</property>
<property name="invisible_char">●</property>
<property name="primary_icon_activatable">False</property>
<property name="secondary_icon_activatable">False</property>
<property name="primary_icon_sensitive">True</property>
<property name="secondary_icon_sensitive">True</property>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="position">1</property>
</packing>
</child>
<child>
<object class="GtkButton" id="button_dadd">
<property name="label" translatable="yes">添加</property>
<property name="use_action_appearance">False</property>
<property name="visible">True</property>
<property name="can_focus">True</property>
<property name="receives_default">True</property>
<signal name="clicked" handler="on_button_dadd_clicked" object="entry1" swapped="no"/>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="position">2</property>
</packing>
</child>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="padding">5</property>
<property name="position">2</property>
</packing>
</child>
<child>
<object class="GtkLabel" id="label4">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="xalign">0</property>
<property name="yalign">0</property>
<property name="xpad">5</property>
<property name="label" translatable="yes">添加域名后再到域名注册的地方将 DNS 修改为：
f1g1ns1.dnspod.net
f1g1ns2.dnspod.net</property>
<property name="selectable">True</property>
<attributes>
<attribute name="foreground" value="#ffff00000000"/>
</attributes>
</object>
<packing>
<property name="expand">True</property>
<property name="fill">True</property>
<property name="position">3</property>
</packing>
</child>
</object>
</child>
</object>
<packing>
<property name="resize">False</property>
<property name="shrink">True</property>
</packing>
</child>
<child>
<object class="GtkViewport" id="viewport2">
<property name="visible">True</property>
<property name="can_focus">False</property>
<child>
<object class="GtkVBox" id="vbox4">
<property name="visible">True</property>
<property name="can_focus">False</property>
<child>
<object class="GtkHBox" id="hbox3">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="spacing">5</property>
<child>
<object class="GtkLabel" id="label_rdomain">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="label" translatable="yes"><请先选择域名></property>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="padding">15</property>
<property name="position">0</property>
</packing>
</child>
<child>
<object class="GtkButton" id="button_rpause">
<property name="label" translatable="yes">暂停/启用</property>
<property name="use_action_appearance">False</property>
<property name="visible">True</property>
<property name="can_focus">True</property>
<property name="receives_default">True</property>
<signal name="clicked" handler="on_button_rpause_clicked" swapped="no"/>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="position">1</property>
</packing>
</child>
<child>
<object class="GtkButton" id="button_rdel">
<property name="label" translatable="yes">删除</property>
<property name="use_action_appearance">False</property>
<property name="visible">True</property>
<property name="can_focus">True</property>
<property name="receives_default">True</property>
<signal name="clicked" handler="on_button_rdel_clicked" swapped="no"/>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="position">2</property>
</packing>
</child>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="position">0</property>
</packing>
</child>
<child>
<object class="GtkScrolledWindow" id="scrolledwindow2">
<property name="visible">True</property>
<property name="can_focus">True</property>
<property name="hscrollbar_policy">automatic</property>
<property name="vscrollbar_policy">automatic</property>
<child>
<object class="GtkTreeView" id="treeview_record">
<property name="width_request">450</property>
<property name="height_request">400</property>
<property name="visible">True</property>
<property name="can_focus">True</property>
<property name="model">liststore_record</property>
<property name="enable_search">False</property>
<property name="search_column">0</property>
<property name="show_expanders">False</property>
<property name="enable_grid_lines">both</property>
</object>
</child>
</object>
<packing>
<property name="expand">True</property>
<property name="fill">True</property>
<property name="position">1</property>
</packing>
</child>
<child>
<object class="GtkTable" id="table1">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="n_rows">3</property>
<property name="n_columns">6</property>
<child>
<object class="GtkLabel" id="label7">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="label" translatable="yes">主机</property>
</object>
<packing>
<property name="top_attach">1</property>
<property name="bottom_attach">2</property>
</packing>
</child>
<child>
<object class="GtkLabel" id="label8">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="label" translatable="yes">记录类型</property>
</object>
<packing>
<property name="left_attach">1</property>
<property name="right_attach">2</property>
<property name="top_attach">1</property>
<property name="bottom_attach">2</property>
</packing>
</child>
<child>
<object class="GtkLabel" id="label9">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="label" translatable="yes">线路类型</property>
</object>
<packing>
<property name="left_attach">2</property>
<property name="right_attach">3</property>
<property name="top_attach">1</property>
<property name="bottom_attach">2</property>
</packing>
</child>
<child>
<object class="GtkLabel" id="label10">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="label" translatable="yes">记录值</property>
</object>
<packing>
<property name="left_attach">3</property>
<property name="right_attach">4</property>
<property name="top_attach">1</property>
<property name="bottom_attach">2</property>
</packing>
</child>
<child>
<object class="GtkLabel" id="label11">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="label" translatable="yes">MX</property>
</object>
<packing>
<property name="left_attach">4</property>
<property name="right_attach">5</property>
<property name="top_attach">1</property>
<property name="bottom_attach">2</property>
</packing>
</child>
<child>
<object class="GtkLabel" id="label12">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="label" translatable="yes">TTL</property>
</object>
<packing>
<property name="left_attach">5</property>
<property name="right_attach">6</property>
<property name="top_attach">1</property>
<property name="bottom_attach">2</property>
</packing>
</child>
<child>
<object class="GtkEntry" id="entry_host">
<property name="width_request">50</property>
<property name="visible">True</property>
<property name="can_focus">True</property>
<property name="invisible_char">●</property>
<property name="primary_icon_activatable">False</property>
<property name="secondary_icon_activatable">False</property>
<property name="primary_icon_sensitive">True</property>
<property name="secondary_icon_sensitive">True</property>
</object>
<packing>
<property name="top_attach">2</property>
<property name="bottom_attach">3</property>
<property name="x_options"></property>
</packing>
</child>
<child>
<object class="GtkEntry" id="entry_value">
<property name="width_request">50</property>
<property name="visible">True</property>
<property name="can_focus">True</property>
<property name="invisible_char">●</property>
<property name="invisible_char_set">True</property>
<property name="primary_icon_activatable">False</property>
<property name="secondary_icon_activatable">False</property>
<property name="primary_icon_sensitive">True</property>
<property name="secondary_icon_sensitive">True</property>
</object>
<packing>
<property name="left_attach">3</property>
<property name="right_attach">4</property>
<property name="top_attach">2</property>
<property name="bottom_attach">3</property>
<property name="x_options"></property>
</packing>
</child>
<child>
<object class="GtkEntry" id="entry_mx">
<property name="width_request">50</property>
<property name="visible">True</property>
<property name="can_focus">True</property>
<property name="invisible_char">●</property>
<property name="text" translatable="yes">5</property>
<property name="invisible_char_set">True</property>
<property name="primary_icon_activatable">False</property>
<property name="secondary_icon_activatable">False</property>
<property name="primary_icon_sensitive">True</property>
<property name="secondary_icon_sensitive">True</property>
</object>
<packing>
<property name="left_attach">4</property>
<property name="right_attach">5</property>
<property name="top_attach">2</property>
<property name="bottom_attach">3</property>
<property name="x_options"></property>
</packing>
</child>
<child>
<object class="GtkEntry" id="entry_ttl">
<property name="width_request">50</property>
<property name="visible">True</property>
<property name="can_focus">True</property>
<property name="invisible_char">●</property>
<property name="text" translatable="yes">600</property>
<property name="invisible_char_set">True</property>
<property name="primary_icon_activatable">False</property>
<property name="secondary_icon_activatable">False</property>
<property name="primary_icon_sensitive">True</property>
<property name="secondary_icon_sensitive">True</property>
</object>
<packing>
<property name="left_attach">5</property>
<property name="right_attach">6</property>
<property name="top_attach">2</property>
<property name="bottom_attach">3</property>
<property name="x_options"></property>
</packing>
</child>
<child>
<object class="GtkLabel" id="label6">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="xalign">0</property>
<property name="label" translatable="yes">添加记录：</property>
<attributes>
<attribute name="weight" value="heavy"/>
</attributes>
</object>
</child>
<child>
<object class="GtkButton" id="button_radd">
<property name="label" translatable="yes">添加</property>
<property name="use_action_appearance">False</property>
<property name="visible">True</property>
<property name="can_focus">True</property>
<property name="receives_default">True</property>
<signal name="clicked" handler="on_button_radd_clicked" swapped="no"/>
</object>
<packing>
<property name="left_attach">4</property>
<property name="right_attach">5</property>
<property name="x_options"></property>
<property name="y_options"></property>
</packing>
</child>
<child>
<object class="GtkComboBox" id="combobox_rtype">
<property name="width_request">80</property>
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="model">liststore_recordtype</property>
<property name="has_entry">True</property>
<property name="entry_text_column">0</property>
</object>
<packing>
<property name="left_attach">1</property>
<property name="right_attach">2</property>
<property name="top_attach">2</property>
<property name="bottom_attach">3</property>
<property name="x_options"></property>
</packing>
</child>
<child>
<object class="GtkComboBox" id="combobox_ltype">
<property name="width_request">80</property>
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="model">liststore_linetype</property>
<property name="has_entry">True</property>
<property name="entry_text_column">0</property>
</object>
<packing>
<property name="left_attach">2</property>
<property name="right_attach">3</property>
<property name="top_attach">2</property>
<property name="bottom_attach">3</property>
<property name="x_options"></property>
</packing>
</child>
<child>
<placeholder/>
</child>
<child>
<placeholder/>
</child>
<child>
<placeholder/>
</child>
<child>
<placeholder/>
</child>
</object>
<packing>
<property name="expand">True</property>
<property name="fill">True</property>
<property name="position">2</property>
</packing>
</child>
</object>
</child>
</object>
<packing>
<property name="resize">True</property>
<property name="shrink">True</property>
</packing>
</child>
</object>
<packing>
<property name="expand">True</property>
<property name="fill">True</property>
<property name="position">1</property>
</packing>
</child>
<child>
<object class="GtkHSeparator" id="hseparator2">
<property name="visible">True</property>
<property name="can_focus">False</property>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">True</property>
<property name="padding">5</property>
<property name="position">2</property>
</packing>
</child>
<child>
<object class="GtkStatusbar" id="statusbar">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="spacing">5</property>
<child>
<object class="GtkLabel" id="label_status">
<property name="visible">True</property>
<property name="can_focus">False</property>
<property name="label" translatable="yes">作者：<b>龙昌</b> 博客：<b>http://www.xefan.com</b></property>
<property name="use_markup">True</property>
<property name="selectable">True</property>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="position">0</property>
</packing>
</child>
</object>
<packing>
<property name="expand">False</property>
<property name="fill">False</property>
<property name="position">3</property>
</packing>
</child>
</object>
</child>
</object>
</interface>
"""
| 49.079511 | 136 | 0.461129 | 3,873 | 48,147 | 5.648593 | 0.08882 | 0.24848 | 0.312657 | 0.123417 | 0.919505 | 0.903917 | 0.885862 | 0.877863 | 0.836084 | 0.831238 | 0 | 0.016194 | 0.412591 | 48,147 | 980 | 137 | 49.129592 | 0.757089 | 0.00864 | 0 | 0.82881 | 0 | 0.006263 | 0.998973 | 0.343164 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 10 |
7e6102e87077415a03fb97771b8d77955e90be73 | 189 | py | Python | CAGG-Molecular-Discovery/objective_func.py | csjtx1021/CAGG | 67fde2f1488ee6e2ff137e87860b5243c5b5fe7c | [
"MIT"
] | 7 | 2020-09-05T01:50:06.000Z | 2021-09-29T13:33:35.000Z | CAGG-Molecular-Discovery/objective_func.py | csjtx1021/CAND | 67fde2f1488ee6e2ff137e87860b5243c5b5fe7c | [
"MIT"
] | null | null | null | CAGG-Molecular-Discovery/objective_func.py | csjtx1021/CAND | 67fde2f1488ee6e2ff137e87860b5243c5b5fe7c | [
"MIT"
] | 1 | 2021-12-07T03:16:24.000Z | 2021-12-07T03:16:24.000Z | #!/usr/bin/env/python
import check_property
#real evaluation function
def evaluate_point(input,target=None):
return check_property.check_property(input["smiles"], target=target)
| 21 | 72 | 0.772487 | 25 | 189 | 5.68 | 0.72 | 0.274648 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.116402 | 189 | 8 | 73 | 23.625 | 0.850299 | 0.232804 | 0 | 0 | 0 | 0 | 0.041958 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | false | 0 | 0.333333 | 0.333333 | 1 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 7 |
7e70b971824a8608a311d77b923989c756d4c624 | 190 | py | Python | profit/dataset/__init__.py | ayushkarnawat/profit | f3c4d601078b52513af6832c3faf75ddafc59ac5 | [
"MIT"
] | null | null | null | profit/dataset/__init__.py | ayushkarnawat/profit | f3c4d601078b52513af6832c3faf75ddafc59ac5 | [
"MIT"
] | 1 | 2021-09-15T13:13:12.000Z | 2021-09-15T13:13:12.000Z | profit/dataset/__init__.py | ayushkarnawat/profit | f3c4d601078b52513af6832c3faf75ddafc59ac5 | [
"MIT"
] | null | null | null | from profit.dataset import parsers
from profit.dataset import preprocessing
from profit.dataset import preprocessors
from profit.dataset import splitters
from profit.dataset import generator | 38 | 40 | 0.873684 | 25 | 190 | 6.64 | 0.36 | 0.301205 | 0.512048 | 0.692771 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.1 | 190 | 5 | 41 | 38 | 0.97076 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 8 |
7e792f65d1e9163646fabd276dc8c3603a62b4cd | 11,735 | py | Python | tests/t_multi.py | carlosefr/python-kyototycoon-ng | 3d1b5d974b50ea44ed95bee0c08bf00d93ac4834 | [
"BSD-3-Clause"
] | null | null | null | tests/t_multi.py | carlosefr/python-kyototycoon-ng | 3d1b5d974b50ea44ed95bee0c08bf00d93ac4834 | [
"BSD-3-Clause"
] | null | null | null | tests/t_multi.py | carlosefr/python-kyototycoon-ng | 3d1b5d974b50ea44ed95bee0c08bf00d93ac4834 | [
"BSD-3-Clause"
] | null | null | null | #!/usr/bin/env python
#
# Copyright 2011, Toru Maesaka
#
# Redistribution and use of this source code is licensed under
# the BSD license. See COPYING file for license description.
#
# Kyoto Tycoon should be started like this:
# $ ktserver one.kch two.kch
import config
import time
import unittest
from kyototycoon import KyotoTycoon, KyotoTycoonException
DB_1 = 0
DB_2 = 1
DB_INVALID = 3
class UnitTest(unittest.TestCase):
def setUp(self):
self.kt_handle_http = KyotoTycoon(binary=False)
self.kt_handle_http.open(port=11978)
self.kt_handle_bin = KyotoTycoon(binary=True)
self.kt_handle_bin.open(port=11978)
self.LARGE_KEY_LEN = 8000
def tearDown(self):
self.kt_handle_http.close()
self.kt_handle_bin.close()
def clear_all(self):
self.assertTrue(self.kt_handle_http.clear(db=DB_1))
self.assertTrue(self.kt_handle_http.clear(db=DB_2))
return True
def test_status(self):
status = self.kt_handle_http.status(DB_1)
assert status is not None
status = self.kt_handle_http.status(DB_2)
assert status is not None
self.assertRaises(KyotoTycoonException, self.kt_handle_http.status, DB_INVALID)
self.assertRaises(KyotoTycoonException, self.kt_handle_http.status, 'non_existent')
def test_set_get(self):
self.assertTrue(self.clear_all())
self.assertTrue(self.kt_handle_http.set('ice', 'cream', db=DB_2))
self.assertRaises(KyotoTycoonException, self.kt_handle_http.set, 'palo', 'alto', db=DB_INVALID)
self.assertEqual(self.kt_handle_http.get('ice'), None)
self.assertEqual(self.kt_handle_http.get('ice', db=DB_1), None)
self.assertRaises(KyotoTycoonException, self.kt_handle_http.get, 'ice', db=DB_INVALID)
self.assertEqual(self.kt_handle_http.get('ice', db=DB_2), 'cream')
self.assertEqual(self.kt_handle_http.count(db=DB_1), 0)
self.assertEqual(self.kt_handle_http.count(db=DB_2), 1)
self.assertTrue(self.kt_handle_http.set('frozen', 'yoghurt', db=DB_1))
self.assertEqual(self.kt_handle_http.count(db=DB_1), 1)
self.assertEqual(self.kt_handle_http.get('frozen'), 'yoghurt')
self.assertEqual(self.kt_handle_http.get('frozen', db=DB_1), 'yoghurt')
self.assertEqual(self.kt_handle_http.get('frozen', db=DB_2), None)
self.assertRaises(KyotoTycoonException, self.kt_handle_http.get, 'frozen', db=DB_INVALID)
self.assertTrue(self.kt_handle_http.clear(db=DB_1))
self.assertEqual(self.kt_handle_http.count(db=DB_1), 0)
self.assertEqual(self.kt_handle_http.count(db=DB_2), 1)
def test_get_multi(self):
self.assertTrue(self.clear_all())
self.assertTrue(self.kt_handle_http.set('a', 'xxxx', db=DB_1))
self.assertTrue(self.kt_handle_http.set_bulk({'b': 'yyyy', 'c': 'zzzz'}, db=DB_1))
self.assertTrue(self.kt_handle_http.set('a1', 'xxxx', db=DB_2))
self.assertTrue(self.kt_handle_http.set_bulk({'b1': 'yyyy', 'c1': 'zzzz'}, db=DB_2))
d = self.kt_handle_http.get_bulk(['a', 'b', 'c'], db=DB_1)
self.assertEqual(len(d), 3)
self.assertEqual(d['a'], 'xxxx')
self.assertEqual(d['b'], 'yyyy')
self.assertEqual(d['c'], 'zzzz')
d = self.kt_handle_http.get_bulk(['a', 'b', 'c'], db=DB_2)
self.assertEqual(len(d), 0)
d = self.kt_handle_http.get_bulk(['a1', 'b1', 'c1'], db=DB_2)
self.assertEqual(len(d), 3)
self.assertEqual(d['a1'], 'xxxx')
self.assertEqual(d['b1'], 'yyyy')
self.assertEqual(d['c1'], 'zzzz')
d = self.kt_handle_http.get_bulk(['a1', 'b1', 'c1'], db=DB_1)
self.assertEqual(len(d), 0)
def test_add(self):
self.assertTrue(self.clear_all())
# Should not conflict due to different databases.
self.assertTrue(self.kt_handle_http.add('key1', 'val1', db=DB_1))
self.assertTrue(self.kt_handle_http.add('key1', 'val1', db=DB_2))
# Now they should.
self.assertRaises(KyotoTycoonException, self.kt_handle_http.add, 'key1', 'val1', db=DB_1)
self.assertRaises(KyotoTycoonException, self.kt_handle_http.add, 'key1', 'val1', db=DB_2)
self.assertRaises(KyotoTycoonException, self.kt_handle_http.add, 'key1', 'val1', db=DB_INVALID)
def test_check(self):
self.assertTrue(self.kt_handle_http.set('check1', 'abc', db=DB_2))
self.assertTrue(self.kt_handle_http.check('check1', db=DB_2))
self.assertFalse(self.kt_handle_http.check('check1', db=DB_1))
def test_seize(self):
self.assertTrue(self.kt_handle_http.set('seize1', 'abc', db=DB_2))
self.assertEqual(self.kt_handle_http.get('seize1', db=DB_2), 'abc')
self.assertEqual(self.kt_handle_http.get('seize1', db=DB_1), None)
self.assertEqual(self.kt_handle_http.seize('seize1', db=DB_2), 'abc')
self.assertEqual(self.kt_handle_http.get('seize1', db=DB_2), None)
def test_replace(self):
self.assertTrue(self.clear_all())
self.assertTrue(self.kt_handle_http.add('key1', 'val1', db=DB_1))
self.assertFalse(self.kt_handle_http.replace('key1', 'val2', db=DB_2))
self.assertTrue(self.kt_handle_http.replace('key1', 'val2', db=DB_1))
self.assertFalse(self.kt_handle_http.replace('key1', 'val2', db=DB_INVALID))
self.assertTrue(self.kt_handle_http.add('key2', 'aaa'))
self.assertTrue(self.kt_handle_http.replace('key2', 'bbb'))
self.assertTrue(self.kt_handle_http.replace('key1', 'zzz'))
self.assertEqual(self.kt_handle_http.get('key2'), 'bbb')
self.assertEqual(self.kt_handle_http.get('key1'), 'zzz')
def test_cas(self):
self.assertTrue(self.clear_all())
self.assertTrue(self.kt_handle_http.set('key', 'xxx'))
self.assertEqual(self.kt_handle_http.get('key', db=DB_2), None)
self.assertRaises(KyotoTycoonException, self.kt_handle_http.cas, 'key', old_val='xxx', new_val='yyy', db=DB_2)
self.assertEqual(self.kt_handle_http.get('key', db=DB_1), 'xxx')
self.assertTrue(self.kt_handle_http.cas('key', old_val='xxx', new_val='yyy', db=DB_1))
self.assertTrue(self.kt_handle_http.cas('key', new_val='xxx', db=DB_2))
def test_remove(self):
self.assertTrue(self.clear_all())
self.assertTrue(self.kt_handle_http.add('key', 'value', db=DB_1))
self.assertTrue(self.kt_handle_http.add('key', 'value', db=DB_2))
self.assertTrue(self.kt_handle_http.remove('key', db=DB_1))
self.assertEqual(self.kt_handle_http.get('key', db=DB_2), 'value')
assert self.kt_handle_http.get('key', db=DB_1) is None
def test_vacuum(self):
self.assertTrue(self.kt_handle_http.vacuum())
self.assertTrue(self.kt_handle_http.vacuum(db=DB_1))
self.assertTrue(self.kt_handle_http.vacuum(db=DB_2))
self.assertRaises(KyotoTycoonException, self.kt_handle_http.vacuum, db=DB_INVALID)
def test_append(self):
self.assertTrue(self.clear_all())
self.assertTrue(self.kt_handle_http.set('key', 'xxx', db=DB_1))
self.assertTrue(self.kt_handle_http.set('key', 'xxx', db=DB_2))
self.assertTrue(self.kt_handle_http.append('key', 'xxx', db=DB_1))
self.assertEqual(self.kt_handle_http.get('key', db=DB_1), 'xxxxxx')
self.assertEqual(self.kt_handle_http.get('key', db=DB_2), 'xxx')
def test_increment(self):
self.assertTrue(self.clear_all())
self.assertEqual(self.kt_handle_http.increment('key', 0, db=DB_1), 0)
self.assertEqual(self.kt_handle_http.increment('key', 0, db=DB_2), 0)
self.assertEqual(self.kt_handle_http.increment('key', 100, db=DB_1), 100)
self.assertEqual(self.kt_handle_http.increment('key', 200, db=DB_2), 200)
self.assertEqual(self.kt_handle_http.increment('key', 100, db=DB_1), 200)
self.assertEqual(self.kt_handle_http.increment('key', 200, db=DB_2), 400)
self.assertEqual(self.kt_handle_http.get_int('key', db=DB_1), 200)
self.assertEqual(self.kt_handle_http.get_int('key', db=DB_2), 400)
def test_match_prefix(self):
self.assertTrue(self.clear_all())
self.assertTrue(self.kt_handle_http.set('abcdef', 'val', db=DB_1))
self.assertTrue(self.kt_handle_http.set('fedcba', 'val', db=DB_2))
list = self.kt_handle_http.match_prefix('abc', db=DB_1)
self.assertEqual(len(list), 1)
self.assertEqual(list[0], 'abcdef')
list = self.kt_handle_http.match_prefix('abc', db=DB_2)
self.assertEqual(len(list), 0)
list = self.kt_handle_http.match_prefix('fed', db=DB_1)
self.assertEqual(len(list), 0)
list = self.kt_handle_http.match_prefix('fed', db=DB_2)
self.assertEqual(len(list), 1)
self.assertEqual(list[0], 'fedcba')
def test_set_get_bin(self):
self.assertTrue(self.clear_all())
self.assertTrue(self.kt_handle_bin.set('ice', 'cream', db=DB_2))
self.assertFalse(self.kt_handle_bin.set('palo', 'alto', db=DB_INVALID))
self.assertEqual(self.kt_handle_bin.get('ice'), None)
self.assertEqual(self.kt_handle_bin.get('ice', db=DB_1), None)
self.assertFalse(self.kt_handle_bin.get('ice', db=DB_INVALID))
self.assertEqual(self.kt_handle_bin.get('ice', db=DB_2), 'cream')
self.assertEqual(self.kt_handle_http.count(db=DB_1), 0)
self.assertEqual(self.kt_handle_http.count(db=DB_2), 1)
self.assertTrue(self.kt_handle_bin.set('frozen', 'yoghurt', db=DB_1))
self.assertEqual(self.kt_handle_http.count(db=DB_1), 1)
self.assertEqual(self.kt_handle_bin.get('frozen'), 'yoghurt')
self.assertEqual(self.kt_handle_bin.get('frozen', db=DB_1), 'yoghurt')
self.assertEqual(self.kt_handle_bin.get('frozen', db=DB_2), None)
self.assertFalse(self.kt_handle_bin.get('frozen', db=DB_INVALID), None)
self.assertTrue(self.kt_handle_http.clear(db=DB_1))
self.assertEqual(self.kt_handle_http.count(db=DB_1), 0)
self.assertEqual(self.kt_handle_http.count(db=DB_2), 1)
def test_get_multi_bin(self):
self.assertTrue(self.clear_all())
self.assertTrue(self.kt_handle_bin.set('a', 'xxxx', db=DB_1))
self.assertTrue(self.kt_handle_bin.set_bulk({'b': 'yyyy', 'c': 'zzzz'}, db=DB_1))
self.assertTrue(self.kt_handle_bin.set('a1', 'xxxx', db=DB_2))
self.assertTrue(self.kt_handle_bin.set_bulk({'b1': 'yyyy', 'c1': 'zzzz'}, db=DB_2))
d = self.kt_handle_bin.get_bulk(['a', 'b', 'c'], db=DB_1, atomic=False)
self.assertEqual(len(d), 3)
self.assertEqual(d['a'], 'xxxx')
self.assertEqual(d['b'], 'yyyy')
self.assertEqual(d['c'], 'zzzz')
d = self.kt_handle_bin.get_bulk(['a', 'b', 'c'], db=DB_2, atomic=False)
self.assertEqual(len(d), 0)
d = self.kt_handle_bin.get_bulk(['a1', 'b1', 'c1'], db=DB_2, atomic=False)
self.assertEqual(len(d), 3)
self.assertEqual(d['a1'], 'xxxx')
self.assertEqual(d['b1'], 'yyyy')
self.assertEqual(d['c1'], 'zzzz')
d = self.kt_handle_bin.get_bulk(['a1', 'b1', 'c1'], db=DB_1, atomic=False)
self.assertEqual(len(d), 0)
def test_remove_bin(self):
self.assertTrue(self.clear_all())
self.assertTrue(self.kt_handle_bin.set('key', 'value', db=DB_1))
self.assertTrue(self.kt_handle_bin.set('key', 'value', db=DB_2))
self.assertTrue(self.kt_handle_bin.remove('key', db=DB_1))
self.assertEqual(self.kt_handle_bin.get('key', db=DB_2), 'value')
assert self.kt_handle_bin.get('key', db=DB_1) is None
if __name__ == '__main__':
unittest.main()
| 45.839844 | 118 | 0.664082 | 1,783 | 11,735 | 4.132361 | 0.084689 | 0.100163 | 0.200326 | 0.208469 | 0.875679 | 0.859799 | 0.853827 | 0.805239 | 0.737921 | 0.661102 | 0 | 0.023861 | 0.175032 | 11,735 | 255 | 119 | 46.019608 | 0.737217 | 0.025991 | 0 | 0.273196 | 0 | 0 | 0.06314 | 0 | 0 | 0 | 0 | 0 | 0.737113 | 1 | 0.097938 | false | 0 | 0.020619 | 0 | 0.128866 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 9 |
7e7f377f9258b4e6efedc0d5406fd637c53d30b4 | 139,936 | py | Python | dlkit/services/learning.py | UOC/dlkit | a9d265db67e81b9e0f405457464e762e2c03f769 | [
"MIT"
] | 2 | 2018-02-23T12:16:11.000Z | 2020-10-08T17:54:24.000Z | dlkit/services/learning.py | UOC/dlkit | a9d265db67e81b9e0f405457464e762e2c03f769 | [
"MIT"
] | 87 | 2017-04-21T18:57:15.000Z | 2021-12-13T19:43:57.000Z | dlkit/services/learning.py | UOC/dlkit | a9d265db67e81b9e0f405457464e762e2c03f769 | [
"MIT"
] | 1 | 2018-03-01T16:44:25.000Z | 2018-03-01T16:44:25.000Z | """DLKit Services implementations of learning service."""
# pylint: disable=no-init
# osid specification includes some 'marker' interfaces.
# pylint: disable=too-many-ancestors
# number of ancestors defined in spec.
# pylint: disable=too-few-public-methods,too-many-public-methods
# number of methods defined in spec. Worse yet, these are aggregates.
# pylint: disable=invalid-name
# method and class names defined in spec.
# pylint: disable=no-self-use,unused-argument
# to catch unimplemented methods.
# pylint: disable=super-init-not-called
# it just isn't.
from . import osid
from .osid_errors import Unimplemented, IllegalState, InvalidArgument
from dlkit.abstract_osid.learning import objects as abc_learning_objects
from dlkit.manager_impls.learning import managers as learning_managers
DEFAULT = 0
COMPARATIVE = 0
PLENARY = 1
FEDERATED = 0
ISOLATED = 1
ANY_STATUS = 0
ACTIVE = 1
UNSEQUESTERED = 0
SEQUESTERED = 1
AUTOMATIC = 0
MANDATORY = 1
DISABLED = -1
class LearningProfile(osid.OsidProfile, learning_managers.LearningProfile):
"""LearningProfile convenience adapter including related Session methods."""
def __init__(self):
self._provider_manager = None
def supports_objective_lookup(self):
"""Pass through to provider supports_objective_lookup"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_objective_lookup()
def supports_objective_query(self):
"""Pass through to provider supports_objective_query"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_objective_query()
def supports_objective_admin(self):
"""Pass through to provider supports_objective_admin"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_objective_admin()
def supports_objective_hierarchy(self):
"""Pass through to provider supports_objective_hierarchy"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_objective_hierarchy()
def supports_objective_hierarchy_design(self):
"""Pass through to provider supports_objective_hierarchy_design"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_objective_hierarchy_design()
def supports_objective_sequencing(self):
"""Pass through to provider supports_objective_sequencing"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_objective_sequencing()
def supports_objective_objective_bank(self):
"""Pass through to provider supports_objective_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_objective_objective_bank()
def supports_objective_objective_bank_assignment(self):
"""Pass through to provider supports_objective_objective_bank_assignment"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_objective_objective_bank_assignment()
def supports_objective_requisite(self):
"""Pass through to provider supports_objective_requisite"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_objective_requisite()
def supports_objective_requisite_assignment(self):
"""Pass through to provider supports_objective_requisite_assignment"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_objective_requisite_assignment()
def supports_activity_lookup(self):
"""Pass through to provider supports_activity_lookup"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_activity_lookup()
def supports_activity_query(self):
"""Pass through to provider supports_activity_query"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_activity_query()
def supports_activity_admin(self):
"""Pass through to provider supports_activity_admin"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_activity_admin()
def supports_activity_objective_bank(self):
"""Pass through to provider supports_activity_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_activity_objective_bank()
def supports_activity_objective_bank_assignment(self):
"""Pass through to provider supports_activity_objective_bank_assignment"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_activity_objective_bank_assignment()
def supports_proficiency_lookup(self):
"""Pass through to provider supports_proficiency_lookup"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_proficiency_lookup()
def supports_proficiency_query(self):
"""Pass through to provider supports_proficiency_query"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_proficiency_query()
def supports_proficiency_admin(self):
"""Pass through to provider supports_proficiency_admin"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_proficiency_admin()
def supports_proficiency_objective_bank_assignment(self):
"""Pass through to provider supports_proficiency_objective_bank_assignment"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_proficiency_objective_bank_assignment()
def supports_objective_bank_lookup(self):
"""Pass through to provider supports_objective_bank_lookup"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_objective_bank_lookup()
def supports_objective_bank_admin(self):
"""Pass through to provider supports_objective_bank_admin"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_objective_bank_admin()
def supports_objective_bank_hierarchy(self):
"""Pass through to provider supports_objective_bank_hierarchy"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_objective_bank_hierarchy()
def supports_objective_bank_hierarchy_design(self):
"""Pass through to provider supports_objective_bank_hierarchy_design"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.supports_resource_lookup
return self._provider_manager.supports_objective_bank_hierarchy_design()
def get_objective_record_types(self):
"""Pass through to provider get_objective_record_types"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.get_resource_record_types
return self._provider_manager.get_objective_record_types()
objective_record_types = property(fget=get_objective_record_types)
def get_objective_search_record_types(self):
"""Pass through to provider get_objective_search_record_types"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.get_resource_record_types
return self._provider_manager.get_objective_search_record_types()
objective_search_record_types = property(fget=get_objective_search_record_types)
def get_activity_record_types(self):
"""Pass through to provider get_activity_record_types"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.get_resource_record_types
return self._provider_manager.get_activity_record_types()
activity_record_types = property(fget=get_activity_record_types)
def get_activity_search_record_types(self):
"""Pass through to provider get_activity_search_record_types"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.get_resource_record_types
return self._provider_manager.get_activity_search_record_types()
activity_search_record_types = property(fget=get_activity_search_record_types)
def get_proficiency_record_types(self):
"""Pass through to provider get_proficiency_record_types"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.get_resource_record_types
return self._provider_manager.get_proficiency_record_types()
proficiency_record_types = property(fget=get_proficiency_record_types)
def get_proficiency_search_record_types(self):
"""Pass through to provider get_proficiency_search_record_types"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.get_resource_record_types
return self._provider_manager.get_proficiency_search_record_types()
proficiency_search_record_types = property(fget=get_proficiency_search_record_types)
def get_objective_bank_record_types(self):
"""Pass through to provider get_objective_bank_record_types"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.get_resource_record_types
return self._provider_manager.get_objective_bank_record_types()
objective_bank_record_types = property(fget=get_objective_bank_record_types)
def get_objective_bank_search_record_types(self):
"""Pass through to provider get_objective_bank_search_record_types"""
# Implemented from kitosid template for -
# osid.resource.ResourceProfile.get_resource_record_types
return self._provider_manager.get_objective_bank_search_record_types()
objective_bank_search_record_types = property(fget=get_objective_bank_search_record_types)
class LearningManager(osid.OsidManager, osid.OsidSession, LearningProfile, learning_managers.LearningManager):
"""LearningManager convenience adapter including related Session methods."""
def __init__(self, proxy=None):
self._runtime = None
self._provider_manager = None
self._provider_sessions = dict()
self._session_management = AUTOMATIC
self._objective_bank_view = DEFAULT
# This is to initialize self._proxy
osid.OsidSession.__init__(self, proxy)
self._sub_package_provider_managers = dict()
def _set_objective_bank_view(self, session):
"""Sets the underlying objective_bank view to match current view"""
if self._objective_bank_view == COMPARATIVE:
try:
session.use_comparative_objective_bank_view()
except AttributeError:
pass
else:
try:
session.use_plenary_objective_bank_view()
except AttributeError:
pass
def _get_provider_session(self, session_name, proxy=None):
"""Gets the session for the provider"""
agent_key = self._get_agent_key(proxy)
if session_name in self._provider_sessions[agent_key]:
return self._provider_sessions[agent_key][session_name]
else:
session = self._instantiate_session('get_' + session_name, self._proxy)
self._set_objective_bank_view(session)
if self._session_management != DISABLED:
self._provider_sessions[agent_key][session_name] = session
return session
def _get_sub_package_provider_manager(self, sub_package_name):
if sub_package_name in self._sub_package_provider_managers:
return self._sub_package_provider_managers[sub_package_name]
config = self._runtime.get_configuration()
parameter_id = Id('parameter:{0}ProviderImpl@dlkit_service'.format(sub_package_name))
provider_impl = config.get_value_by_parameter(parameter_id).get_string_value()
if self._proxy is None:
# need to add version argument
sub_package = self._runtime.get_manager(sub_package_name.upper(), provider_impl)
else:
# need to add version argument
sub_package = self._runtime.get_proxy_manager(sub_package_name.upper(), provider_impl)
self._sub_package_provider_managers[sub_package_name] = sub_package
return sub_package
def _get_sub_package_provider_session(self, sub_package, session_name, proxy=None):
"""Gets the session from a sub-package"""
agent_key = self._get_agent_key(proxy)
if session_name in self._provider_sessions[agent_key]:
return self._provider_sessions[agent_key][session_name]
else:
manager = self._get_sub_package_provider_manager(sub_package)
try:
session = self._instantiate_session('get_' + session_name + '_for_bank',
proxy=self._proxy,
manager=manager)
except AttributeError:
session = self._instantiate_session('get_' + session_name,
proxy=self._proxy,
manager=manager)
self._set_bank_view(session)
if self._session_management != DISABLED:
self._provider_sessions[agent_key][session_name] = session
return session
def _instantiate_session(self, method_name, proxy=None, *args, **kwargs):
"""Instantiates a provider session"""
if 'manager' in kwargs:
session_class = getattr(kwargs['manager'], method_name)
del kwargs['manager']
else:
session_class = getattr(self._provider_manager, method_name)
if proxy is None:
try:
return session_class(bank_id=self._catalog_id, *args, **kwargs)
except AttributeError:
return session_class(*args, **kwargs)
else:
try:
return session_class(bank_id=self._catalog_id, proxy=proxy, *args, **kwargs)
except AttributeError:
return session_class(proxy=proxy, *args, **kwargs)
def initialize(self, runtime):
"""OSID Manager initialize"""
from .primitives import Id
if self._runtime is not None:
raise IllegalState('Manager has already been initialized')
self._runtime = runtime
config = runtime.get_configuration()
parameter_id = Id('parameter:learningProviderImpl@dlkit_service')
provider_impl = config.get_value_by_parameter(parameter_id).get_string_value()
if self._proxy is None:
# need to add version argument
self._provider_manager = runtime.get_manager('LEARNING', provider_impl)
else:
# need to add version argument
self._provider_manager = runtime.get_proxy_manager('LEARNING', provider_impl)
def close_sessions(self):
"""Close all sessions, unless session management is set to MANDATORY"""
if self._session_management != MANDATORY:
self._provider_sessions = dict()
def use_automatic_session_management(self):
"""Session state will be saved unless closed by consumers"""
self._session_management = AUTOMATIC
def use_mandatory_session_management(self):
"""Session state will be saved and can not be closed by consumers"""
self._session_management = MANDATORY
def disable_session_management(self):
"""Session state will never be saved"""
self._session_management = DISABLED
self.close_sessions()
def get_objective_lookup_session(self, *args, **kwargs):
"""Pass through to provider get_objective_lookup_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_catalog_template
return self._provider_manager.get_objective_lookup_session(*args, **kwargs)
objective_lookup_session = property(fget=get_objective_lookup_session)
def get_objective_lookup_session_for_objective_bank(self, *args, **kwargs):
"""Pass through to provider get_objective_lookup_session_for_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_for_bin_catalog_template
return self._provider_manager.get_objective_lookup_session_for_objective_bank(*args, **kwargs)
def get_objective_query_session(self, *args, **kwargs):
"""Pass through to provider get_objective_query_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_catalog_template
return self._provider_manager.get_objective_query_session(*args, **kwargs)
objective_query_session = property(fget=get_objective_query_session)
def get_objective_query_session_for_objective_bank(self, *args, **kwargs):
"""Pass through to provider get_objective_query_session_for_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_for_bin_catalog_template
return self._provider_manager.get_objective_query_session_for_objective_bank(*args, **kwargs)
def get_objective_admin_session(self, *args, **kwargs):
"""Pass through to provider get_objective_admin_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_catalog_template
return self._provider_manager.get_objective_admin_session(*args, **kwargs)
objective_admin_session = property(fget=get_objective_admin_session)
def get_objective_admin_session_for_objective_bank(self, *args, **kwargs):
"""Pass through to provider get_objective_admin_session_for_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_for_bin_catalog_template
return self._provider_manager.get_objective_admin_session_for_objective_bank(*args, **kwargs)
def get_objective_hierarchy_session(self, *args, **kwargs):
"""Pass through to provider get_objective_hierarchy_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_catalog_template
return self._provider_manager.get_objective_hierarchy_session(*args, **kwargs)
objective_hierarchy_session = property(fget=get_objective_hierarchy_session)
def get_objective_hierarchy_session_for_objective_bank(self, *args, **kwargs):
"""Pass through to provider get_objective_hierarchy_session_for_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_for_bin_catalog_template
return self._provider_manager.get_objective_hierarchy_session_for_objective_bank(*args, **kwargs)
def get_objective_hierarchy_design_session(self, *args, **kwargs):
"""Pass through to provider get_objective_hierarchy_design_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_catalog_template
return self._provider_manager.get_objective_hierarchy_design_session(*args, **kwargs)
objective_hierarchy_design_session = property(fget=get_objective_hierarchy_design_session)
def get_objective_hierarchy_design_session_for_objective_bank(self, *args, **kwargs):
"""Pass through to provider get_objective_hierarchy_design_session_for_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_for_bin_catalog_template
return self._provider_manager.get_objective_hierarchy_design_session_for_objective_bank(*args, **kwargs)
def get_objective_sequencing_session(self, *args, **kwargs):
"""Pass through to provider get_objective_sequencing_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_catalog_template
return self._provider_manager.get_objective_sequencing_session(*args, **kwargs)
objective_sequencing_session = property(fget=get_objective_sequencing_session)
def get_objective_sequencing_session_for_objective_bank(self, *args, **kwargs):
"""Pass through to provider get_objective_sequencing_session_for_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_for_bin_catalog_template
return self._provider_manager.get_objective_sequencing_session_for_objective_bank(*args, **kwargs)
def get_objective_objective_bank_session(self, *args, **kwargs):
"""Pass through to provider get_objective_objective_bank_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_manager_template
return self._provider_manager.get_objective_objective_bank_session(*args, **kwargs)
objective_objective_bank_session = property(fget=get_objective_objective_bank_session)
def get_objective_objective_bank_assignment_session(self, *args, **kwargs):
"""Pass through to provider get_objective_objective_bank_assignment_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_manager_template
return self._provider_manager.get_objective_objective_bank_assignment_session(*args, **kwargs)
objective_objective_bank_assignment_session = property(fget=get_objective_objective_bank_assignment_session)
def get_objective_requisite_session(self, *args, **kwargs):
"""Pass through to provider get_objective_requisite_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_catalog_template
return self._provider_manager.get_objective_requisite_session(*args, **kwargs)
objective_requisite_session = property(fget=get_objective_requisite_session)
def get_objective_requisite_session_for_objective_bank(self, *args, **kwargs):
"""Pass through to provider get_objective_requisite_session_for_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_for_bin_catalog_template
return self._provider_manager.get_objective_requisite_session_for_objective_bank(*args, **kwargs)
def get_objective_requisite_assignment_session(self, *args, **kwargs):
"""Pass through to provider get_objective_requisite_assignment_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_catalog_template
return self._provider_manager.get_objective_requisite_assignment_session(*args, **kwargs)
objective_requisite_assignment_session = property(fget=get_objective_requisite_assignment_session)
def get_objective_requisite_assignment_session_for_objective_bank(self, *args, **kwargs):
"""Pass through to provider get_objective_requisite_assignment_session_for_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_for_bin_catalog_template
return self._provider_manager.get_objective_requisite_assignment_session_for_objective_bank(*args, **kwargs)
def get_activity_lookup_session(self, *args, **kwargs):
"""Pass through to provider get_activity_lookup_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_catalog_template
return self._provider_manager.get_activity_lookup_session(*args, **kwargs)
activity_lookup_session = property(fget=get_activity_lookup_session)
def get_activity_lookup_session_for_objective_bank(self, *args, **kwargs):
"""Pass through to provider get_activity_lookup_session_for_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_for_bin_catalog_template
return self._provider_manager.get_activity_lookup_session_for_objective_bank(*args, **kwargs)
def get_activity_query_session(self, *args, **kwargs):
"""Pass through to provider get_activity_query_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_catalog_template
return self._provider_manager.get_activity_query_session(*args, **kwargs)
activity_query_session = property(fget=get_activity_query_session)
def get_activity_query_session_for_objective_bank(self, *args, **kwargs):
"""Pass through to provider get_activity_query_session_for_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_for_bin_catalog_template
return self._provider_manager.get_activity_query_session_for_objective_bank(*args, **kwargs)
def get_activity_admin_session(self, *args, **kwargs):
"""Pass through to provider get_activity_admin_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_catalog_template
return self._provider_manager.get_activity_admin_session(*args, **kwargs)
activity_admin_session = property(fget=get_activity_admin_session)
def get_activity_admin_session_for_objective_bank(self, *args, **kwargs):
"""Pass through to provider get_activity_admin_session_for_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_for_bin_catalog_template
return self._provider_manager.get_activity_admin_session_for_objective_bank(*args, **kwargs)
def get_activity_objective_bank_session(self, *args, **kwargs):
"""Pass through to provider get_activity_objective_bank_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_manager_template
return self._provider_manager.get_activity_objective_bank_session(*args, **kwargs)
activity_objective_bank_session = property(fget=get_activity_objective_bank_session)
def get_activity_objective_bank_assignment_session(self, *args, **kwargs):
"""Pass through to provider get_activity_objective_bank_assignment_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_manager_template
return self._provider_manager.get_activity_objective_bank_assignment_session(*args, **kwargs)
activity_objective_bank_assignment_session = property(fget=get_activity_objective_bank_assignment_session)
def get_proficiency_lookup_session(self, *args, **kwargs):
"""Pass through to provider get_proficiency_lookup_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_catalog_template
return self._provider_manager.get_proficiency_lookup_session(*args, **kwargs)
proficiency_lookup_session = property(fget=get_proficiency_lookup_session)
def get_proficiency_lookup_session_for_objective_bank(self, *args, **kwargs):
"""Pass through to provider get_proficiency_lookup_session_for_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_for_bin_catalog_template
return self._provider_manager.get_proficiency_lookup_session_for_objective_bank(*args, **kwargs)
def get_proficiency_query_session(self, *args, **kwargs):
"""Pass through to provider get_proficiency_query_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_catalog_template
return self._provider_manager.get_proficiency_query_session(*args, **kwargs)
proficiency_query_session = property(fget=get_proficiency_query_session)
def get_proficiency_query_session_for_objective_bank(self, *args, **kwargs):
"""Pass through to provider get_proficiency_query_session_for_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_for_bin_catalog_template
return self._provider_manager.get_proficiency_query_session_for_objective_bank(*args, **kwargs)
def get_proficiency_admin_session(self, *args, **kwargs):
"""Pass through to provider get_proficiency_admin_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_catalog_template
return self._provider_manager.get_proficiency_admin_session(*args, **kwargs)
proficiency_admin_session = property(fget=get_proficiency_admin_session)
def get_proficiency_admin_session_for_objective_bank(self, *args, **kwargs):
"""Pass through to provider get_proficiency_admin_session_for_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_for_bin_catalog_template
return self._provider_manager.get_proficiency_admin_session_for_objective_bank(*args, **kwargs)
def get_proficiency_objective_bank_assignment_session(self, *args, **kwargs):
"""Pass through to provider get_proficiency_objective_bank_assignment_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_manager_template
return self._provider_manager.get_proficiency_objective_bank_assignment_session(*args, **kwargs)
proficiency_objective_bank_assignment_session = property(fget=get_proficiency_objective_bank_assignment_session)
def get_objective_bank_lookup_session(self, *args, **kwargs):
"""Pass through to provider get_objective_bank_lookup_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_manager_template
return self._provider_manager.get_objective_bank_lookup_session(*args, **kwargs)
objective_bank_lookup_session = property(fget=get_objective_bank_lookup_session)
def get_objective_bank_admin_session(self, *args, **kwargs):
"""Pass through to provider get_objective_bank_admin_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_manager_template
return self._provider_manager.get_objective_bank_admin_session(*args, **kwargs)
objective_bank_admin_session = property(fget=get_objective_bank_admin_session)
def get_objective_bank_hierarchy_session(self, *args, **kwargs):
"""Pass through to provider get_objective_bank_hierarchy_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_manager_template
return self._provider_manager.get_objective_bank_hierarchy_session(*args, **kwargs)
objective_bank_hierarchy_session = property(fget=get_objective_bank_hierarchy_session)
def get_objective_bank_hierarchy_design_session(self, *args, **kwargs):
"""Pass through to provider get_objective_bank_hierarchy_design_session"""
# Implemented from kitosid template for -
# osid.resource.ResourceManager.get_resource_lookup_session_manager_template
return self._provider_manager.get_objective_bank_hierarchy_design_session(*args, **kwargs)
objective_bank_hierarchy_design_session = property(fget=get_objective_bank_hierarchy_design_session)
def get_learning_batch_manager(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services')
learning_batch_manager = property(fget=get_learning_batch_manager)
##
# The following methods are from osid.learning.ObjectiveObjectiveBankSession
def can_lookup_objective_objective_bank_mappings(self):
"""Pass through to provider ObjectiveObjectiveBankSession.can_lookup_objective_objective_bank_mappings"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinSession.can_lookup_resource_bin_mappings
return self._get_provider_session('objective_objective_bank_session').can_lookup_objective_objective_bank_mappings()
def use_comparative_objective_bank_view(self):
"""Pass through to provider ObjectiveObjectiveBankSession.use_comparative_objective_bank_view"""
self._objective_bank_view = COMPARATIVE
# self._get_provider_session('objective_objective_bank_session') # To make sure the session is tracked
for session in self._get_provider_sessions():
try:
session.use_comparative_objective_bank_view()
except AttributeError:
pass
def use_plenary_objective_bank_view(self):
"""Pass through to provider ObjectiveObjectiveBankSession.use_plenary_objective_bank_view"""
self._objective_bank_view = PLENARY
# self._get_provider_session('objective_objective_bank_session') # To make sure the session is tracked
for session in self._get_provider_sessions():
try:
session.use_plenary_objective_bank_view()
except AttributeError:
pass
def get_objective_ids_by_objective_bank(self, *args, **kwargs):
"""Pass through to provider ObjectiveObjectiveBankSession.get_objective_ids_by_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinSession.get_resource_ids_by_bin
return self._get_provider_session('objective_objective_bank_session').get_objective_ids_by_objective_bank(*args, **kwargs)
def get_objectives_by_objective_bank(self, *args, **kwargs):
"""Pass through to provider ObjectiveObjectiveBankSession.get_objectives_by_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinSession.get_resources_by_bin
return self._get_provider_session('objective_objective_bank_session').get_objectives_by_objective_bank(*args, **kwargs)
def get_objective_ids_by_objective_banks(self, *args, **kwargs):
"""Pass through to provider ObjectiveObjectiveBankSession.get_objective_ids_by_objective_banks"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinSession.get_resource_ids_by_bins
return self._get_provider_session('objective_objective_bank_session').get_objective_ids_by_objective_banks(*args, **kwargs)
def get_objectives_by_objective_banks(self, *args, **kwargs):
"""Pass through to provider ObjectiveObjectiveBankSession.get_objectives_by_objective_banks"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinSession.get_resources_by_bins
return self._get_provider_session('objective_objective_bank_session').get_objectives_by_objective_banks(*args, **kwargs)
def get_objective_bank_ids_by_objective(self, *args, **kwargs):
"""Pass through to provider ObjectiveObjectiveBankSession.get_objective_bank_ids_by_objective"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinSession.get_bin_ids_by_resource
return self._get_provider_session('objective_objective_bank_session').get_objective_bank_ids_by_objective(*args, **kwargs)
def get_objective_banks_by_objective(self, *args, **kwargs):
"""Pass through to provider ObjectiveObjectiveBankSession.get_objective_banks_by_objective"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinSession.get_bins_by_resource
catalogs = self._get_provider_session('objective_objective_bank_session').get_objective_banks_by_objective(*args, **kwargs)
cat_list = []
for cat in catalogs:
cat_list.append(ObjectiveBank(self._provider_manager, cat, self._runtime, self._proxy))
return ObjectiveBankList(cat_list)
##
# The following methods are from osid.learning.ObjectiveObjectiveBankAssignmentSession
def can_assign_objectives(self):
"""Pass through to provider ObjectiveObjectiveBankAssignmentSession.can_assign_objectives"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinAssignmentSession.can_assign_resources
return self._get_provider_session('objective_objective_bank_assignment_session').can_assign_objectives()
def can_assign_objectives_to_objective_bank(self, *args, **kwargs):
"""Pass through to provider ObjectiveObjectiveBankAssignmentSession.can_assign_objectives_to_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinAssignmentSession.can_assign_resources_to_bin
return self._get_provider_session('objective_objective_bank_assignment_session').can_assign_objectives_to_objective_bank(*args, **kwargs)
def get_assignable_objective_bank_ids(self, *args, **kwargs):
"""Pass through to provider ObjectiveObjectiveBankAssignmentSession.get_assignable_objective_bank_ids"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinAssignmentSession.get_assignable_bin_ids
return self._get_provider_session('objective_objective_bank_assignment_session').get_assignable_objective_bank_ids(*args, **kwargs)
def get_assignable_objective_bank_ids_for_objective(self, *args, **kwargs):
"""Pass through to provider ObjectiveObjectiveBankAssignmentSession.get_assignable_objective_bank_ids_for_objective"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinAssignmentSession.get_assignable_bin_ids_for_resource
return self._get_provider_session('objective_objective_bank_assignment_session').get_assignable_objective_bank_ids_for_objective(*args, **kwargs)
def assign_objective_to_objective_bank(self, *args, **kwargs):
"""Pass through to provider ObjectiveObjectiveBankAssignmentSession.assign_objective_to_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinAssignmentSession.assign_resource_to_bin
self._get_provider_session('objective_objective_bank_assignment_session').assign_objective_to_objective_bank(*args, **kwargs)
def unassign_objective_from_objective_bank(self, *args, **kwargs):
"""Pass through to provider ObjectiveObjectiveBankAssignmentSession.unassign_objective_from_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinAssignmentSession.unassign_resource_from_bin
self._get_provider_session('objective_objective_bank_assignment_session').unassign_objective_from_objective_bank(*args, **kwargs)
def reassign_proficiency_to_objective_bank(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
##
# The following methods are from osid.learning.ActivityObjectiveBankSession
def can_lookup_activity_objective_bank_mappings(self):
"""Pass through to provider ActivityObjectiveBankSession.can_lookup_activity_objective_bank_mappings"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinSession.can_lookup_resource_bin_mappings
return self._get_provider_session('activity_objective_bank_session').can_lookup_activity_objective_bank_mappings()
def get_activity_ids_by_objective_bank(self, *args, **kwargs):
"""Pass through to provider ActivityObjectiveBankSession.get_activity_ids_by_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinSession.get_resource_ids_by_bin
return self._get_provider_session('activity_objective_bank_session').get_activity_ids_by_objective_bank(*args, **kwargs)
def get_activities_by_objective_bank(self, *args, **kwargs):
"""Pass through to provider ActivityObjectiveBankSession.get_activities_by_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinSession.get_resources_by_bin
return self._get_provider_session('activity_objective_bank_session').get_activities_by_objective_bank(*args, **kwargs)
def get_activity_ids_by_objective_banks(self, *args, **kwargs):
"""Pass through to provider ActivityObjectiveBankSession.get_activity_ids_by_objective_banks"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinSession.get_resource_ids_by_bins
return self._get_provider_session('activity_objective_bank_session').get_activity_ids_by_objective_banks(*args, **kwargs)
def get_activities_by_objective_banks(self, *args, **kwargs):
"""Pass through to provider ActivityObjectiveBankSession.get_activities_by_objective_banks"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinSession.get_resources_by_bins
return self._get_provider_session('activity_objective_bank_session').get_activities_by_objective_banks(*args, **kwargs)
def get_objective_bank_ids_by_activity(self, *args, **kwargs):
"""Pass through to provider ActivityObjectiveBankSession.get_objective_bank_ids_by_activity"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinSession.get_bin_ids_by_resource
return self._get_provider_session('activity_objective_bank_session').get_objective_bank_ids_by_activity(*args, **kwargs)
def get_objective_banks_by_activity(self, *args, **kwargs):
"""Pass through to provider ActivityObjectiveBankSession.get_objective_banks_by_activity"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinSession.get_bins_by_resource
catalogs = self._get_provider_session('activity_objective_bank_session').get_objective_banks_by_activity(*args, **kwargs)
cat_list = []
for cat in catalogs:
cat_list.append(ObjectiveBank(self._provider_manager, cat, self._runtime, self._proxy))
return ObjectiveBankList(cat_list)
##
# The following methods are from osid.learning.ActivityObjectiveBankAssignmentSession
def can_assign_activities(self):
"""Pass through to provider ActivityObjectiveBankAssignmentSession.can_assign_activities"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinAssignmentSession.can_assign_resources
return self._get_provider_session('activity_objective_bank_assignment_session').can_assign_activities()
def can_assign_activities_to_objective_bank(self, *args, **kwargs):
"""Pass through to provider ActivityObjectiveBankAssignmentSession.can_assign_activities_to_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinAssignmentSession.can_assign_resources_to_bin
return self._get_provider_session('activity_objective_bank_assignment_session').can_assign_activities_to_objective_bank(*args, **kwargs)
def get_assignable_objective_bank_ids_for_activity(self, *args, **kwargs):
"""Pass through to provider ActivityObjectiveBankAssignmentSession.get_assignable_objective_bank_ids_for_activity"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinAssignmentSession.get_assignable_bin_ids_for_resource
return self._get_provider_session('activity_objective_bank_assignment_session').get_assignable_objective_bank_ids_for_activity(*args, **kwargs)
def assign_activity_to_objective_bank(self, *args, **kwargs):
"""Pass through to provider ActivityObjectiveBankAssignmentSession.assign_activity_to_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinAssignmentSession.assign_resource_to_bin
self._get_provider_session('activity_objective_bank_assignment_session').assign_activity_to_objective_bank(*args, **kwargs)
def unassign_activity_from_objective_bank(self, *args, **kwargs):
"""Pass through to provider ActivityObjectiveBankAssignmentSession.unassign_activity_from_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinAssignmentSession.unassign_resource_from_bin
self._get_provider_session('activity_objective_bank_assignment_session').unassign_activity_from_objective_bank(*args, **kwargs)
def reassign_activity_to_objective_bank(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
##
# The following methods are from osid.learning.ProficiencyObjectiveBankAssignmentSession
def can_assign_proficiencies(self):
"""Pass through to provider ProficiencyObjectiveBankAssignmentSession.can_assign_proficiencies"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinAssignmentSession.can_assign_resources
return self._get_provider_session('proficiency_objective_bank_assignment_session').can_assign_proficiencies()
def can_assign_proficiencies_to_objective_bank(self, *args, **kwargs):
"""Pass through to provider ProficiencyObjectiveBankAssignmentSession.can_assign_proficiencies_to_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinAssignmentSession.can_assign_resources_to_bin
return self._get_provider_session('proficiency_objective_bank_assignment_session').can_assign_proficiencies_to_objective_bank(*args, **kwargs)
def get_assignable_objective_bank_ids_for_proficiency(self, *args, **kwargs):
"""Pass through to provider ProficiencyObjectiveBankAssignmentSession.get_assignable_objective_bank_ids_for_proficiency"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinAssignmentSession.get_assignable_bin_ids_for_resource
return self._get_provider_session('proficiency_objective_bank_assignment_session').get_assignable_objective_bank_ids_for_proficiency(*args, **kwargs)
def assign_proficiency_to_objective_bank(self, *args, **kwargs):
"""Pass through to provider ProficiencyObjectiveBankAssignmentSession.assign_proficiency_to_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinAssignmentSession.assign_resource_to_bin
self._get_provider_session('proficiency_objective_bank_assignment_session').assign_proficiency_to_objective_bank(*args, **kwargs)
def unassign_proficiency_from_objective_bank(self, *args, **kwargs):
"""Pass through to provider ProficiencyObjectiveBankAssignmentSession.unassign_proficiency_from_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.ResourceBinAssignmentSession.unassign_resource_from_bin
self._get_provider_session('proficiency_objective_bank_assignment_session').unassign_proficiency_from_objective_bank(*args, **kwargs)
##
# The following methods are from osid.learning.ObjectiveBankLookupSession
def can_lookup_objective_banks(self):
"""Pass through to provider ObjectiveBankLookupSession.can_lookup_objective_banks"""
# Implemented from kitosid template for -
# osid.resource.BinLookupSession.can_lookup_bins_template
return self._get_provider_session('objective_bank_lookup_session').can_lookup_objective_banks()
def get_objective_bank(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankLookupSession.get_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.BinLookupSession.get_bin
return ObjectiveBank(
self._provider_manager,
self._get_provider_session('objective_bank_lookup_session').get_objective_bank(*args, **kwargs),
self._runtime,
self._proxy)
def get_objective_banks_by_ids(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankLookupSession.get_objective_banks_by_ids"""
# Implemented from kitosid template for -
# osid.resource.BinLookupSession.get_bins_by_ids
catalogs = self._get_provider_session('objective_bank_lookup_session').get_objective_banks_by_ids(*args, **kwargs)
cat_list = []
for cat in catalogs:
cat_list.append(ObjectiveBank(self._provider_manager, cat, self._runtime, self._proxy))
return ObjectiveBankList(cat_list)
def get_objective_banks_by_genus_type(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankLookupSession.get_objective_banks_by_genus_type"""
# Implemented from kitosid template for -
# osid.resource.BinLookupSession.get_bins_by_genus_type
catalogs = self._get_provider_session('objective_bank_lookup_session').get_objective_banks_by_genus_type(*args, **kwargs)
cat_list = []
for cat in catalogs:
cat_list.append(ObjectiveBank(self._provider_manager, cat, self._runtime, self._proxy))
return ObjectiveBankList(cat_list)
def get_objective_banks_by_parent_genus_type(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankLookupSession.get_objective_banks_by_parent_genus_type"""
# Implemented from kitosid template for -
# osid.resource.BinLookupSession.get_bins_by_parent_genus_type
catalogs = self._get_provider_session('objective_bank_lookup_session').get_objective_banks_by_parent_genus_type(*args, **kwargs)
cat_list = []
for cat in catalogs:
cat_list.append(ObjectiveBank(self._provider_manager, cat, self._runtime, self._proxy))
return ObjectiveBankList(cat_list)
def get_objective_banks_by_record_type(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankLookupSession.get_objective_banks_by_record_type"""
# Implemented from kitosid template for -
# osid.resource.BinLookupSession.get_bins_by_record_type
catalogs = self._get_provider_session('objective_bank_lookup_session').get_objective_banks_by_record_type(*args, **kwargs)
cat_list = []
for cat in catalogs:
cat_list.append(ObjectiveBank(self._provider_manager, cat, self._runtime, self._proxy))
return ObjectiveBankList(cat_list)
def get_objective_banks_by_provider(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankLookupSession.get_objective_banks_by_provider"""
# Implemented from kitosid template for -
# osid.resource.BinLookupSession.get_bins_by_provider
catalogs = self._get_provider_session('objective_bank_lookup_session').get_objective_banks_by_provider(*args, **kwargs)
cat_list = []
for cat in catalogs:
cat_list.append(ObjectiveBank(self._provider_manager, cat, self._runtime, self._proxy))
return ObjectiveBankList(cat_list)
def get_objective_banks(self):
"""Pass through to provider ObjectiveBankLookupSession.get_objective_banks"""
# Implemented from kitosid template for -
# osid.resource.BinLookupSession.get_bins_template
catalogs = self._get_provider_session('objective_bank_lookup_session').get_objective_banks()
cat_list = []
for cat in catalogs:
cat_list.append(ObjectiveBank(self._provider_manager, cat, self._runtime, self._proxy))
return ObjectiveBankList(cat_list)
objective_banks = property(fget=get_objective_banks)
##
# The following methods are from osid.learning.ObjectiveBankAdminSession
def can_create_objective_banks(self):
"""Pass through to provider ObjectiveBankAdminSession.can_create_objective_banks"""
# Implemented from kitosid template for -
# osid.resource.BinAdminSession.can_create_bins
return self._get_provider_session('objective_bank_admin_session').can_create_objective_banks()
def can_create_objective_bank_with_record_types(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankAdminSession.can_create_objective_bank_with_record_types"""
# Implemented from kitosid template for -
# osid.resource.BinAdminSession.can_create_bin_with_record_types
return self._get_provider_session('objective_bank_admin_session').can_create_objective_bank_with_record_types(*args, **kwargs)
def get_objective_bank_form_for_create(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankAdminSession.get_objective_bank_form_for_create"""
# Implemented from kitosid template for -
# osid.resource.BinAdminSession.get_bin_form_for_create
return self._get_provider_session('objective_bank_admin_session').get_objective_bank_form_for_create(*args, **kwargs)
def create_objective_bank(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankAdminSession.create_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.BinAdminSession.create_bin
return ObjectiveBank(
self._provider_manager,
self._get_provider_session('objective_bank_admin_session').create_objective_bank(*args, **kwargs),
self._runtime,
self._proxy)
def can_update_objective_banks(self):
"""Pass through to provider ObjectiveBankAdminSession.can_update_objective_banks"""
# Implemented from kitosid template for -
# osid.resource.BinAdminSession.can_update_bins
return self._get_provider_session('objective_bank_admin_session').can_update_objective_banks()
def get_objective_bank_form_for_update(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankAdminSession.get_objective_bank_form_for_update"""
# Implemented from kitosid template for -
# osid.resource.BinAdminSession.get_bin_form_for_update
return self._get_provider_session('objective_bank_admin_session').get_objective_bank_form_for_update(*args, **kwargs)
def get_objective_bank_form(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankAdminSession.get_objective_bank_form_for_update"""
# Implemented from kitosid template for -
# osid.resource.BinAdminSession.get_bin_form_for_update_template
# This method might be a bit sketchy. Time will tell.
if isinstance(args[-1], list) or 'objective_bank_record_types' in kwargs:
return self.get_objective_bank_form_for_create(*args, **kwargs)
else:
return self.get_objective_bank_form_for_update(*args, **kwargs)
def update_objective_bank(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankAdminSession.update_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.BinAdminSession.update_bin
# OSID spec does not require returning updated catalog
return ObjectiveBank(
self._provider_manager,
self._get_provider_session('objective_bank_admin_session').update_objective_bank(*args, **kwargs),
self._runtime,
self._proxy)
def save_objective_bank(self, objective_bank_form, *args, **kwargs):
"""Pass through to provider ObjectiveBankAdminSession.update_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.BinAdminSession.update_bin
if objective_bank_form.is_for_update():
return self.update_objective_bank(objective_bank_form, *args, **kwargs)
else:
return self.create_objective_bank(objective_bank_form, *args, **kwargs)
def can_delete_objective_banks(self):
"""Pass through to provider ObjectiveBankAdminSession.can_delete_objective_banks"""
# Implemented from kitosid template for -
# osid.resource.BinAdminSession.can_delete_bins
return self._get_provider_session('objective_bank_admin_session').can_delete_objective_banks()
def delete_objective_bank(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankAdminSession.delete_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.BinAdminSession.delete_bin
self._get_provider_session('objective_bank_admin_session').delete_objective_bank(*args, **kwargs)
def can_manage_objective_bank_aliases(self):
"""Pass through to provider ObjectiveBankAdminSession.can_manage_objective_bank_aliases"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.can_manage_resource_aliases_template
return self._get_provider_session('objective_bank_admin_session').can_manage_objective_bank_aliases()
def alias_objective_bank(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankAdminSession.alias_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.BinAdminSession.alias_bin
self._get_provider_session('objective_bank_admin_session').alias_objective_bank(*args, **kwargs)
##
# The following methods are from osid.learning.ObjectiveBankHierarchySession
def get_objective_bank_hierarchy_id(self):
"""Pass through to provider ObjectiveBankHierarchySession.get_objective_bank_hierarchy_id"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchySession.get_bin_hierarchy_id
return self._get_provider_session('objective_bank_hierarchy_session').get_objective_bank_hierarchy_id()
objective_bank_hierarchy_id = property(fget=get_objective_bank_hierarchy_id)
def get_objective_bank_hierarchy(self):
"""Pass through to provider ObjectiveBankHierarchySession.get_objective_bank_hierarchy"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchySession.get_bin_hierarchy
return self._get_provider_session('objective_bank_hierarchy_session').get_objective_bank_hierarchy()
objective_bank_hierarchy = property(fget=get_objective_bank_hierarchy)
def can_access_objective_bank_hierarchy(self):
"""Pass through to provider ObjectiveBankHierarchySession.can_access_objective_bank_hierarchy"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchySession.can_access_bin_hierarchy
return self._get_provider_session('objective_bank_hierarchy_session').can_access_objective_bank_hierarchy()
def get_root_objective_bank_ids(self):
"""Pass through to provider ObjectiveBankHierarchySession.get_root_objective_bank_ids"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchySession.get_root_bin_ids
return self._get_provider_session('objective_bank_hierarchy_session').get_root_objective_bank_ids()
root_objective_bank_ids = property(fget=get_root_objective_bank_ids)
def get_root_objective_banks(self):
"""Pass through to provider ObjectiveBankHierarchySession.get_root_objective_banks"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchySession.get_root_bins
return self._get_provider_session('objective_bank_hierarchy_session').get_root_objective_banks()
root_objective_banks = property(fget=get_root_objective_banks)
def has_parent_objective_banks(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankHierarchySession.has_parent_objective_banks"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchySession.has_parent_bins
return self._get_provider_session('objective_bank_hierarchy_session').has_parent_objective_banks(*args, **kwargs)
def is_parent_of_objective_bank(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankHierarchySession.is_parent_of_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchySession.is_parent_of_bin
return self._get_provider_session('objective_bank_hierarchy_session').is_parent_of_objective_bank(*args, **kwargs)
def get_parent_objective_bank_ids(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankHierarchySession.get_parent_objective_bank_ids"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchySession.get_parent_bin_ids
return self._get_provider_session('objective_bank_hierarchy_session').get_parent_objective_bank_ids(*args, **kwargs)
def get_parent_objective_banks(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankHierarchySession.get_parent_objective_banks"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchySession.get_parent_bins
return self._get_provider_session('objective_bank_hierarchy_session').get_parent_objective_banks(*args, **kwargs)
def is_ancestor_of_objective_bank(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankHierarchySession.is_ancestor_of_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchySession.is_ancestor_of_bin
return self._get_provider_session('objective_bank_hierarchy_session').is_ancestor_of_objective_bank(*args, **kwargs)
def has_child_objective_banks(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankHierarchySession.has_child_objective_banks"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchySession.has_child_bins
return self._get_provider_session('objective_bank_hierarchy_session').has_child_objective_banks(*args, **kwargs)
def is_child_of_objective_bank(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankHierarchySession.is_child_of_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchySession.is_child_of_bin
return self._get_provider_session('objective_bank_hierarchy_session').is_child_of_objective_bank(*args, **kwargs)
def get_child_objective_bank_ids(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankHierarchySession.get_child_objective_bank_ids"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchySession.get_child_bin_ids
return self._get_provider_session('objective_bank_hierarchy_session').get_child_objective_bank_ids(*args, **kwargs)
def get_child_objective_banks(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankHierarchySession.get_child_objective_banks"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchySession.get_child_bins
return self._get_provider_session('objective_bank_hierarchy_session').get_child_objective_banks(*args, **kwargs)
def is_descendant_of_objective_bank(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankHierarchySession.is_descendant_of_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchySession.is_descendant_of_bin
return self._get_provider_session('objective_bank_hierarchy_session').is_descendant_of_objective_bank(*args, **kwargs)
def get_objective_bank_node_ids(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankHierarchySession.get_objective_bank_node_ids"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchySession.get_bin_node_ids
return self._get_provider_session('objective_bank_hierarchy_session').get_objective_bank_node_ids(*args, **kwargs)
def get_objective_bank_nodes(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankHierarchySession.get_objective_bank_nodes"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchySession.get_bin_nodes
return self._get_provider_session('objective_bank_hierarchy_session').get_objective_bank_nodes(*args, **kwargs)
##
# The following methods are from osid.learning.ObjectiveBankHierarchyDesignSession
def can_modify_objective_bank_hierarchy(self):
"""Pass through to provider ObjectiveBankHierarchyDesignSession.can_modify_objective_bank_hierarchy"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchyDesignSession.can_modify_bin_hierarchy
return self._get_provider_session('objective_bank_hierarchy_design_session').can_modify_objective_bank_hierarchy()
def create_objective_bank_hierarchy(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankHierarchyDesignSession.can_modify_objective_bank_hierarchy"""
# Patched in by cjshaw@mit.edu, Jul 23, 2014, added by birdland to template on Aug 8, 2014
# Is not part of specs for catalog hierarchy design sessions, but may want to be in hierarchy service instead
# Will not return an actual object, just JSON
# since a BankHierarchy does not seem to be an OSID thing.
return self._get_provider_session('objective_bank_hierarchy_design_session').create_objective_bank_hierarchy(*args, **kwargs)
def delete_objective_bank_hierarchy(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankHierarchyDesignSession.can_modify_objective_bank_hierarchy"""
# Patched in by cjshaw@mit.edu, Jul 23, 2014, added by birdland to template on Aug 8, 2014
# Is not part of specs for catalog hierarchy design sessions, but may want to be in hierarchy service instead
# Will not return an actual object, just JSON
# since a BankHierarchy does not seem to be an OSID thing.
return self._get_provider_session('objective_bank_hierarchy_design_session').delete_objective_bank_hierarchy(*args, **kwargs)
def add_root_objective_bank(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankHierarchyDesignSession.add_root_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchyDesignSession.add_root_bin
self._get_provider_session('objective_bank_hierarchy_design_session').add_root_objective_bank(*args, **kwargs)
def remove_root_objective_bank(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankHierarchyDesignSession.remove_root_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchyDesignSession.remove_root_bin
self._get_provider_session('objective_bank_hierarchy_design_session').remove_root_objective_bank(*args, **kwargs)
def add_child_objective_bank(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankHierarchyDesignSession.add_child_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchyDesignSession.add_child_bin
self._get_provider_session('objective_bank_hierarchy_design_session').add_child_objective_bank(*args, **kwargs)
def remove_child_objective_bank(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankHierarchyDesignSession.remove_child_objective_bank"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchyDesignSession.remove_child_bin
self._get_provider_session('objective_bank_hierarchy_design_session').remove_child_objective_bank(*args, **kwargs)
def remove_child_objective_banks(self, *args, **kwargs):
"""Pass through to provider ObjectiveBankHierarchyDesignSession.remove_child_objective_banks"""
# Implemented from kitosid template for -
# osid.resource.BinHierarchyDesignSession.remove_child_bins
self._get_provider_session('objective_bank_hierarchy_design_session').remove_child_objective_banks(*args, **kwargs)
class LearningProxyManager(osid.OsidProxyManager, LearningProfile, learning_managers.LearningProxyManager):
"""LearningProxyManager convenience adapter including related Session methods."""
def get_objective_lookup_session(self, *args, **kwargs):
"""Sends control to Manager"""
# Implemented from kitosid template for -
# osid.resource.ResourceProxyManager.get_resource_lookup_session_template
return LearningManager.get_objective_lookup_session(*args, **kwargs)
def get_objective_lookup_session_for_objective_bank(self, *args, **kwargs):
"""Sends control to Manager"""
# Implemented from kitosid template for -
# osid.resource.ResourceProxyManager.get_resource_lookup_session_for_bin_template
return LearningManager.get_objective_lookup_session_for_objective_bank(*args, **kwargs)
def get_objective_query_session(self, *args, **kwargs):
"""Sends control to Manager"""
# Implemented from kitosid template for -
# osid.resource.ResourceProxyManager.get_resource_lookup_session_template
return LearningManager.get_objective_query_session(*args, **kwargs)
def get_objective_query_session_for_objective_bank(self, *args, **kwargs):
"""Sends control to Manager"""
# Implemented from kitosid template for -
# osid.resource.ResourceProxyManager.get_resource_lookup_session_for_bin_template
return LearningManager.get_objective_query_session_for_objective_bank(*args, **kwargs)
def get_objective_admin_session(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_objective_admin_session_for_objective_bank(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_objective_hierarchy_session(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_objective_hierarchy_session_for_objective_bank(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_objective_hierarchy_design_session(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_objective_hierarchy_design_session_for_objective_bank(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_objective_sequencing_session(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_objective_sequencing_session_for_objective_bank(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_objective_objective_bank_session(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_objective_objective_bank_assignment_session(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_objective_requisite_session(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_objective_requisite_session_for_objective_bank(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_objective_requisite_assignment_session(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_objective_requisite_assignment_session_for_objective_bank(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_activity_lookup_session(self, *args, **kwargs):
"""Sends control to Manager"""
# Implemented from kitosid template for -
# osid.resource.ResourceProxyManager.get_resource_lookup_session_template
return LearningManager.get_activity_lookup_session(*args, **kwargs)
def get_activity_lookup_session_for_objective_bank(self, *args, **kwargs):
"""Sends control to Manager"""
# Implemented from kitosid template for -
# osid.resource.ResourceProxyManager.get_resource_lookup_session_for_bin_template
return LearningManager.get_activity_lookup_session_for_objective_bank(*args, **kwargs)
def get_activity_query_session(self, *args, **kwargs):
"""Sends control to Manager"""
# Implemented from kitosid template for -
# osid.resource.ResourceProxyManager.get_resource_lookup_session_template
return LearningManager.get_activity_query_session(*args, **kwargs)
def get_activity_query_session_for_objective_bank(self, *args, **kwargs):
"""Sends control to Manager"""
# Implemented from kitosid template for -
# osid.resource.ResourceProxyManager.get_resource_lookup_session_for_bin_template
return LearningManager.get_activity_query_session_for_objective_bank(*args, **kwargs)
def get_activity_admin_session(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_activity_admin_session_for_objective_bank(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_activity_objective_bank_session(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_activity_objective_bank_assignment_session(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_proficiency_lookup_session(self, *args, **kwargs):
"""Sends control to Manager"""
# Implemented from kitosid template for -
# osid.resource.ResourceProxyManager.get_resource_lookup_session_template
return LearningManager.get_proficiency_lookup_session(*args, **kwargs)
def get_proficiency_lookup_session_for_objective_bank(self, *args, **kwargs):
"""Sends control to Manager"""
# Implemented from kitosid template for -
# osid.resource.ResourceProxyManager.get_resource_lookup_session_for_bin_template
return LearningManager.get_proficiency_lookup_session_for_objective_bank(*args, **kwargs)
def get_proficiency_query_session(self, *args, **kwargs):
"""Sends control to Manager"""
# Implemented from kitosid template for -
# osid.resource.ResourceProxyManager.get_resource_lookup_session_template
return LearningManager.get_proficiency_query_session(*args, **kwargs)
def get_proficiency_query_session_for_objective_bank(self, *args, **kwargs):
"""Sends control to Manager"""
# Implemented from kitosid template for -
# osid.resource.ResourceProxyManager.get_resource_lookup_session_for_bin_template
return LearningManager.get_proficiency_query_session_for_objective_bank(*args, **kwargs)
def get_proficiency_admin_session(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_proficiency_admin_session_for_objective_bank(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_proficiency_objective_bank_assignment_session(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_objective_bank_lookup_session(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_objective_bank_admin_session(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_objective_bank_hierarchy_session(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_objective_bank_hierarchy_design_session(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_learning_batch_proxy_manager(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services')
learning_batch_proxy_manager = property(fget=get_learning_batch_proxy_manager)
class ObjectiveBank(abc_learning_objects.ObjectiveBank, osid.OsidSession, osid.OsidCatalog):
"""ObjectiveBank convenience adapter including related Session methods."""
# WILL THIS EVER BE CALLED DIRECTLY - OUTSIDE OF A MANAGER?
def __init__(self, provider_manager, catalog, runtime, proxy, **kwargs):
self._provider_manager = provider_manager
self._catalog = catalog
self._runtime = runtime
osid.OsidObject.__init__(self, self._catalog) # This is to initialize self._object
osid.OsidSession.__init__(self, proxy) # This is to initialize self._proxy
self._catalog_id = catalog.get_id()
self._provider_sessions = kwargs
self._session_management = AUTOMATIC
self._objective_bank_view = DEFAULT
self._object_views = dict()
self._operable_views = dict()
self._containable_views = dict()
def _set_objective_bank_view(self, session):
"""Sets the underlying objective_bank view to match current view"""
if self._objective_bank_view == FEDERATED:
try:
session.use_federated_objective_bank_view()
except AttributeError:
pass
else:
try:
session.use_isolated_objective_bank_view()
except AttributeError:
pass
def _set_object_view(self, session):
"""Sets the underlying object views to match current view"""
for obj_name in self._object_views:
if self._object_views[obj_name] == PLENARY:
try:
getattr(session, 'use_plenary_' + obj_name + '_view')()
except AttributeError:
pass
else:
try:
getattr(session, 'use_comparative_' + obj_name + '_view')()
except AttributeError:
pass
def _set_operable_view(self, session):
"""Sets the underlying operable views to match current view"""
for obj_name in self._operable_views:
if self._operable_views[obj_name] == ACTIVE:
try:
getattr(session, 'use_active_' + obj_name + '_view')()
except AttributeError:
pass
else:
try:
getattr(session, 'use_any_status_' + obj_name + '_view')()
except AttributeError:
pass
def _set_containable_view(self, session):
"""Sets the underlying containable views to match current view"""
for obj_name in self._containable_views:
if self._containable_views[obj_name] == SEQUESTERED:
try:
getattr(session, 'use_sequestered_' + obj_name + '_view')()
except AttributeError:
pass
else:
try:
getattr(session, 'use_unsequestered_' + obj_name + '_view')()
except AttributeError:
pass
def _get_provider_session(self, session_name):
"""Returns the requested provider session.
Instantiates a new one if the named session is not already known.
"""
agent_key = self._get_agent_key()
if session_name in self._provider_sessions[agent_key]:
return self._provider_sessions[agent_key][session_name]
else:
session_class = getattr(self._provider_manager, 'get_' + session_name + '_for_objective_bank')
if self._proxy is None:
if 'notification_session' in session_name:
# Is there something else we should do about the receiver field?
session = session_class('fake receiver', self._catalog.get_id())
else:
session = session_class(self._catalog.get_id())
else:
if 'notification_session' in session_name:
# Is there something else we should do about the receiver field?
session = session_class('fake receiver', self._catalog.get_id(), self._proxy)
else:
session = session_class(self._catalog.get_id(), self._proxy)
self._set_objective_bank_view(session)
self._set_object_view(session)
self._set_operable_view(session)
self._set_containable_view(session)
if self._session_management != DISABLED:
self._provider_sessions[agent_key][session_name] = session
return session
def get_objective_bank_id(self):
"""Gets the Id of this objective_bank."""
return self._catalog_id
def get_objective_bank(self):
"""Strange little method to assure conformance for inherited Sessions."""
return self
def __getattr__(self, name):
if '_catalog' in self.__dict__:
try:
return self._catalog[name]
except AttributeError:
pass
raise AttributeError
def close_sessions(self):
"""Close all sessions currently being managed by this Manager to save memory."""
if self._session_management != MANDATORY:
self._provider_sessions = dict()
else:
raise IllegalState()
def use_automatic_session_management(self):
"""Session state will be saved until closed by consumers."""
self._session_management = AUTOMATIC
def use_mandatory_session_management(self):
"""Session state will always be saved and can not be closed by consumers."""
# Session state will be saved and can not be closed by consumers
self._session_management = MANDATORY
def disable_session_management(self):
"""Session state will never be saved."""
self._session_management = DISABLED
self.close_sessions()
def get_objective_bank_record(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
##
# The following methods are from osid.learning.ObjectiveLookupSession
def can_lookup_objectives(self):
"""Pass through to provider ObjectiveLookupSession.can_lookup_objectives"""
# Implemented from kitosid template for -
# osid.resource.ResourceLookupSession.can_lookup_resources_template
return self._get_provider_session('objective_lookup_session').can_lookup_objectives()
def use_comparative_objective_view(self):
"""Pass through to provider ObjectiveLookupSession.use_comparative_objective_view"""
self._object_views['objective'] = COMPARATIVE
# self._get_provider_session('objective_lookup_session') # To make sure the session is tracked
for session in self._get_provider_sessions():
try:
session.use_comparative_objective_view()
except AttributeError:
pass
def use_plenary_objective_view(self):
"""Pass through to provider ObjectiveLookupSession.use_plenary_objective_view"""
self._object_views['objective'] = PLENARY
# self._get_provider_session('objective_lookup_session') # To make sure the session is tracked
for session in self._get_provider_sessions():
try:
session.use_plenary_objective_view()
except AttributeError:
pass
def use_federated_objective_bank_view(self):
"""Pass through to provider ObjectiveLookupSession.use_federated_objective_bank_view"""
self._objective_bank_view = FEDERATED
# self._get_provider_session('objective_lookup_session') # To make sure the session is tracked
for session in self._get_provider_sessions():
try:
session.use_federated_objective_bank_view()
except AttributeError:
pass
def use_isolated_objective_bank_view(self):
"""Pass through to provider ObjectiveLookupSession.use_isolated_objective_bank_view"""
self._objective_bank_view = ISOLATED
# self._get_provider_session('objective_lookup_session') # To make sure the session is tracked
for session in self._get_provider_sessions():
try:
session.use_isolated_objective_bank_view()
except AttributeError:
pass
def get_objective(self, *args, **kwargs):
"""Pass through to provider ObjectiveLookupSession.get_objective"""
# Implemented from kitosid template for -
# osid.resource.ResourceLookupSession.get_resource_template
return self._get_provider_session('objective_lookup_session').get_objective(*args, **kwargs)
def get_objectives_by_ids(self, *args, **kwargs):
"""Pass through to provider ObjectiveLookupSession.get_objectives_by_ids"""
# Implemented from kitosid template for -
# osid.resource.ResourceLookupSession.get_resources_by_ids_template
return self._get_provider_session('objective_lookup_session').get_objectives_by_ids(*args, **kwargs)
def get_objectives_by_genus_type(self, *args, **kwargs):
"""Pass through to provider ObjectiveLookupSession.get_objectives_by_genus_type"""
# Implemented from kitosid template for -
# osid.resource.ResourceLookupSession.get_resources_by_genus_type_template
return self._get_provider_session('objective_lookup_session').get_objectives_by_genus_type(*args, **kwargs)
def get_objectives_by_parent_genus_type(self, *args, **kwargs):
"""Pass through to provider ObjectiveLookupSession.get_objectives_by_parent_genus_type"""
# Implemented from kitosid template for -
# osid.resource.ResourceLookupSession.get_resources_by_parent_genus_type_template
return self._get_provider_session('objective_lookup_session').get_objectives_by_parent_genus_type(*args, **kwargs)
def get_objectives_by_record_type(self, *args, **kwargs):
"""Pass through to provider ObjectiveLookupSession.get_objectives_by_record_type"""
# Implemented from kitosid template for -
# osid.resource.ResourceLookupSession.get_resources_by_record_type_template
return self._get_provider_session('objective_lookup_session').get_objectives_by_record_type(*args, **kwargs)
def get_objectives(self):
"""Pass through to provider ObjectiveLookupSession.get_objectives"""
# Implemented from kitosid template for -
# osid.resource.ResourceLookupSession.get_resources_template
return self._get_provider_session('objective_lookup_session').get_objectives()
objectives = property(fget=get_objectives)
##
# The following methods are from osid.learning.ObjectiveQuerySession
def can_search_objectives(self):
"""Pass through to provider ObjectiveQuerySession.can_search_objectives"""
# Implemented from kitosid template for -
# osid.resource.ResourceQuerySession.can_search_resources_template
return self._get_provider_session('objective_query_session').can_search_objectives()
def get_objective_query(self):
"""Pass through to provider ObjectiveQuerySession.get_objective_query"""
# Implemented from kitosid template for -
# osid.resource.ResourceQuerySession.get_item_query_template
return self._get_provider_session('objective_query_session').get_objective_query()
objective_query = property(fget=get_objective_query)
def get_objectives_by_query(self, *args, **kwargs):
"""Pass through to provider ObjectiveQuerySession.get_objectives_by_query"""
# Implemented from kitosid template for -
# osid.resource.ResourceQuerySession.get_items_by_query_template
return self._get_provider_session('objective_query_session').get_objectives_by_query(*args, **kwargs)
##
# The following methods are from osid.learning.ObjectiveAdminSession
def can_create_objectives(self):
"""Pass through to provider ObjectiveAdminSession.can_create_objectives"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.can_create_resources
return self._get_provider_session('objective_admin_session').can_create_objectives()
def can_create_objective_with_record_types(self, *args, **kwargs):
"""Pass through to provider ObjectiveAdminSession.can_create_objective_with_record_types"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.can_create_resource_with_record_types
return self._get_provider_session('objective_admin_session').can_create_objective_with_record_types(*args, **kwargs)
def get_objective_form_for_create(self, *args, **kwargs):
"""Pass through to provider ObjectiveAdminSession.get_objective_form_for_create"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.get_resource_form_for_create
return self._get_provider_session('objective_admin_session').get_objective_form_for_create(*args, **kwargs)
def create_objective(self, *args, **kwargs):
"""Pass through to provider ObjectiveAdminSession.create_objective"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.create_resource
return self._get_provider_session('objective_admin_session').create_objective(*args, **kwargs)
def can_update_objectives(self):
"""Pass through to provider ObjectiveAdminSession.can_update_objectives"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.can_update_resources
return self._get_provider_session('objective_admin_session').can_update_objectives()
def get_objective_form_for_update(self, *args, **kwargs):
"""Pass through to provider ObjectiveAdminSession.get_objective_form_for_update"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.get_resource_form_for_update
return self._get_provider_session('objective_admin_session').get_objective_form_for_update(*args, **kwargs)
def get_objective_form(self, *args, **kwargs):
"""Pass through to provider ObjectiveAdminSession.get_objective_form_for_update"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.get_resource_form_for_update
# This method might be a bit sketchy. Time will tell.
if isinstance(args[-1], list) or 'objective_record_types' in kwargs:
return self.get_objective_form_for_create(*args, **kwargs)
else:
return self.get_objective_form_for_update(*args, **kwargs)
def duplicate_objective(self, objective_id):
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.get_resource_form_for_update
return self._get_provider_session('objective_admin_session').duplicate_objective(objective_id)
def update_objective(self, *args, **kwargs):
"""Pass through to provider ObjectiveAdminSession.update_objective"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.update_resource
# Note: The OSID spec does not require returning updated object
return self._get_provider_session('objective_admin_session').update_objective(*args, **kwargs)
def save_objective(self, objective_form, *args, **kwargs):
"""Pass through to provider ObjectiveAdminSession.update_objective"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.update_resource
if objective_form.is_for_update():
return self.update_objective(objective_form, *args, **kwargs)
else:
return self.create_objective(objective_form, *args, **kwargs)
def can_delete_objectives(self):
"""Pass through to provider ObjectiveAdminSession.can_delete_objectives"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.can_delete_resources
return self._get_provider_session('objective_admin_session').can_delete_objectives()
def delete_objective(self, *args, **kwargs):
"""Pass through to provider ObjectiveAdminSession.delete_objective"""
# Implemented from kitosid template for -
# osid.learning.ObjectiveAdminSession.delete_objective
self._get_provider_session('objective_admin_session').delete_objective(*args, **kwargs)
def can_manage_objective_aliases(self):
"""Pass through to provider ObjectiveAdminSession.can_manage_objective_aliases"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.can_manage_resource_aliases_template
return self._get_provider_session('objective_admin_session').can_manage_objective_aliases()
def alias_objective(self, *args, **kwargs):
"""Pass through to provider ObjectiveAdminSession.alias_objective"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.alias_resources
self._get_provider_session('objective_admin_session').alias_objective(*args, **kwargs)
##
# The following methods are from osid.learning.ObjectiveHierarchySession
def get_objective_hierarchy_id(self):
return self._get_provider_session('objective_hierarchy_session').get_objective_hierarchy_id()
objective_hierarchy_id = property(fget=get_objective_hierarchy_id)
def get_objective_hierarchy(self):
return self._get_provider_session('objective_hierarchy_session').get_objective_hierarchy()
objective_hierarchy = property(fget=get_objective_hierarchy)
def can_access_objective_hierarchy(self):
"""Pass through to provider ObjectiveHierarchySession.can_access_objective_hierarchy"""
# Implemented from kitosid template for -
# osid.ontology.SubjectHierarchySession.can_access_subject_hierarchy_template
return self._get_provider_session('objective_hierarchy_session').can_access_objective_hierarchy()
def get_root_objective_ids(self):
"""Pass through to provider ObjectiveHierarchySession.get_root_objective_ids"""
# Implemented from kitosid template for -
# osid.ontology.SubjectHierarchySession.get_root_subject_ids_template
return self._get_provider_session('objective_hierarchy_session').get_root_objective_ids()
root_objective_ids = property(fget=get_root_objective_ids)
def get_root_objectives(self):
"""Pass through to provider ObjectiveHierarchySession.get_root_objectives"""
# Implemented from kitosid template for -
# osid.ontology.SubjectHierarchySession.get_root_subjects_template
return self._get_provider_session('objective_hierarchy_session').get_root_objectives()
root_objectives = property(fget=get_root_objectives)
def has_parent_objectives(self, *args, **kwargs):
"""Pass through to provider ObjectiveHierarchySession.has_parent_objectives"""
# Implemented from kitosid template for -
# osid.ontology.SubjectHierarchySession.has_parent_subjects_template
return self._get_provider_session('objective_hierarchy_session').has_parent_objectives(*args, **kwargs)
def is_parent_of_objective(self, *args, **kwargs):
"""Pass through to provider ObjectiveHierarchySession.is_parent_of_objective"""
# Implemented from kitosid template for -
# osid.ontology.SubjectHierarchySession.is_parent_of_subject_template
return self._get_provider_session('objective_hierarchy_session').is_parent_of_objective(*args, **kwargs)
def get_parent_objective_ids(self, *args, **kwargs):
"""Pass through to provider ObjectiveHierarchySession.get_parent_objective_ids"""
# Implemented from kitosid template for -
# osid.ontology.SubjectHierarchySession.get_parent_subject_ids_template
return self._get_provider_session('objective_hierarchy_session').get_parent_objective_ids(*args, **kwargs)
def get_parent_objectives(self, *args, **kwargs):
"""Pass through to provider ObjectiveHierarchySession.get_parent_objectives"""
# Implemented from kitosid template for -
# osid.ontology.SubjectHierarchySession.get_parent_subjects_template
return self._get_provider_session('objective_hierarchy_session').get_parent_objectives(*args, **kwargs)
def is_ancestor_of_objective(self, *args, **kwargs):
"""Pass through to provider ObjectiveHierarchySession.is_ancestor_of_objective"""
# Implemented from kitosid template for -
# osid.ontology.SubjectHierarchySession.is_ancestor_of_subject_template
return self._get_provider_session('objective_hierarchy_session').is_ancestor_of_objective(*args, **kwargs)
def has_child_objectives(self, *args, **kwargs):
"""Pass through to provider ObjectiveHierarchySession.has_child_objectives"""
# Implemented from kitosid template for -
# osid.ontology.SubjectHierarchySession.has_child_subjects_template
return self._get_provider_session('objective_hierarchy_session').has_child_objectives(*args, **kwargs)
def is_child_of_objective(self, *args, **kwargs):
"""Pass through to provider ObjectiveHierarchySession.is_child_of_objective"""
# Implemented from kitosid template for -
# osid.ontology.SubjectHierarchySession.is_child_of_subject_template
return self._get_provider_session('objective_hierarchy_session').is_child_of_objective(*args, **kwargs)
def get_child_objective_ids(self, *args, **kwargs):
"""Pass through to provider ObjectiveHierarchySession.get_child_objective_ids"""
# Implemented from kitosid template for -
# osid.ontology.SubjectHierarchySession.get_child_subject_ids_template
return self._get_provider_session('objective_hierarchy_session').get_child_objective_ids(*args, **kwargs)
def get_child_objectives(self, *args, **kwargs):
"""Pass through to provider ObjectiveHierarchySession.get_child_objectives"""
# Implemented from kitosid template for -
# osid.ontology.SubjectHierarchySession.get_child_subjects_template
return self._get_provider_session('objective_hierarchy_session').get_child_objectives(*args, **kwargs)
def is_descendant_of_objective(self, *args, **kwargs):
"""Pass through to provider ObjectiveHierarchySession.is_descendant_of_objective"""
# Implemented from kitosid template for -
# osid.ontology.SubjectHierarchySession.is_descendant_of_subject_template
return self._get_provider_session('objective_hierarchy_session').is_descendant_of_objective(*args, **kwargs)
def get_objective_node_ids(self, *args, **kwargs):
"""Pass through to provider ObjectiveHierarchySession.get_objective_node_ids"""
# Implemented from kitosid template for -
# osid.ontology.SubjectHierarchySession.get_subject_node_ids_template
return self._get_provider_session('objective_hierarchy_session').get_objective_node_ids(*args, **kwargs)
def get_objective_nodes(self, *args, **kwargs):
"""Pass through to provider ObjectiveHierarchySession.get_objective_nodes"""
# Implemented from kitosid template for -
# osid.ontology.SubjectHierarchySession.get_subject_nodes_template
return self._get_provider_session('objective_hierarchy_session').get_objective_nodes(*args, **kwargs)
##
# The following methods are from osid.learning.ObjectiveHierarchyDesignSession
def can_modify_objective_hierarchy(self):
"""Pass through to provider ObjectiveHierarchyDesignSession.can_modify_objective_hierarchy"""
# Implemented from kitosid template for -
# osid.ontology.SubjectHierarchyDesignSession.can_modify_subject_hierarchy
return self._get_provider_session('objective_hierarchy_design_session').can_modify_objective_hierarchy()
def add_root_objective(self, *args, **kwargs):
"""Pass through to provider ObjectiveHierarchyDesignSession.add_root_objective"""
# Implemented from kitosid template for -
# osid.ontology.SubjectHierarchyDesignSession.add_root_subject
self._get_provider_session('objective_hierarchy_design_session').add_root_objective(*args, **kwargs)
def remove_root_objective(self, *args, **kwargs):
"""Pass through to provider ObjectiveHierarchyDesignSession.remove_root_objective"""
# Implemented from kitosid template for -
# osid.ontology.SubjectHierarchyDesignSession.remove_root_subject
self._get_provider_session('objective_hierarchy_design_session').remove_root_objective(*args, **kwargs)
def add_child_objective(self, *args, **kwargs):
"""Pass through to provider ObjectiveHierarchyDesignSession.add_child_objective"""
# Implemented from kitosid template for -
# osid.ontology.SubjectHierarchyDesignSession.add_child_subject
self._get_provider_session('objective_hierarchy_design_session').add_child_objective(*args, **kwargs)
def remove_child_objective(self, *args, **kwargs):
"""Pass through to provider ObjectiveHierarchyDesignSession.remove_child_objective"""
# Implemented from kitosid template for -
# osid.ontology.SubjectHierarchyDesignSession.remove_child_subject
self._get_provider_session('objective_hierarchy_design_session').remove_child_objective(*args, **kwargs)
def remove_child_objectives(self, *args, **kwargs):
"""Pass through to provider ObjectiveHierarchyDesignSession.remove_child_objectives"""
# Implemented from kitosid template for -
# osid.ontology.SubjectHierarchyDesignSession.remove_child_subjects_template
self._get_provider_session('objective_hierarchy_design_session').remove_child_objectives(*args, **kwargs)
##
# The following methods are from osid.learning.ObjectiveSequencingSession
def can_sequence_objectives(self):
"""Pass through to provider method"""
return self._get_provider_session('objective_sequencing_session').can_sequence_objectives()
def move_objective_ahead(self, *args, **kwargs):
"""Pass through to provider method"""
return self._get_provider_session('objective_sequencing_session').move_objective_ahead(*args, **kwargs)
def move_objective_behind(self, *args, **kwargs):
"""Pass through to provider method"""
return self._get_provider_session('objective_sequencing_session').move_objective_behind(*args, **kwargs)
def sequence_objectives(self, *args, **kwargs):
"""Pass through to provider method"""
return self._get_provider_session('objective_sequencing_session').sequence_objectives(*args, **kwargs)
##
# The following methods are from osid.learning.ObjectiveRequisiteSession
def can_lookup_objective_prerequisites(self):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services')
def get_requisite_objectives(self, *args, **kwargs):
"""Pass through to provider ObjectiveRequisiteSession.get_requisite_objectives"""
# Implemented from kitosid template for -
# osid.learning.ObjectiveRequisiteSession.get_requisite_objectives
return self._get_provider_session('objective_requisite_session').get_requisite_objectives(*args, **kwargs)
def get_all_requisite_objectives(self, *args, **kwargs):
"""Pass through to provider ObjectiveRequisiteSession.get_all_requisite_objectives"""
# Implemented from kitosid template for -
# osid.learning.ObjectiveRequisiteSession.get_all_requisite_objectives
return self._get_provider_session('objective_requisite_session').get_all_requisite_objectives(*args, **kwargs)
def get_dependent_objectives(self, *args, **kwargs):
"""Pass through to provider ObjectiveRequisiteSession.get_dependent_objectives"""
# Implemented from kitosid template for -
# osid.learning.ObjectiveRequisiteSession.get_dependent_objectives
return self._get_provider_session('objective_requisite_session').get_dependent_objectives(*args, **kwargs)
def is_objective_required(self, *args, **kwargs):
"""Pass through to provider ObjectiveRequisiteSession.is_objective_required"""
# Implemented from kitosid template for -
# osid.learning.ObjectiveRequisiteSession.is_objective_required
return self._get_provider_session('objective_requisite_session').is_objective_required(*args, **kwargs)
def get_equivalent_objectives(self, *args, **kwargs):
"""Pass through to provider ObjectiveRequisiteSession.get_equivalent_objectives"""
# Implemented from kitosid template for -
# osid.learning.ObjectiveRequisiteSession.get_equivalent_objectives
return self._get_provider_session('objective_requisite_session').get_equivalent_objectives(*args, **kwargs)
##
# The following methods are from osid.learning.ObjectiveRequisiteAssignmentSession
def can_assign_requisites(self):
"""Pass through to provider ObjectiveRequisiteAssignmentSession.can_assign_requisites"""
# Implemented from kitosid template for -
# osid.learning.ObjectiveRequisiteAssignmentSession.can_assign_requisites
return self._get_provider_session('objective_requisite_assignment_session').can_assign_requisites()
def assign_objective_requisite(self, *args, **kwargs):
"""Pass through to provider ObjectiveRequisiteAssignmentSession.assign_objective_requisite"""
# Implemented from kitosid template for -
# osid.learning.ObjectiveRequisiteAssignmentSession.assign_objective_requisite
return self._get_provider_session('objective_requisite_assignment_session').assign_objective_requisite(*args, **kwargs)
def unassign_objective_requisite(self, *args, **kwargs):
"""Pass through to provider ObjectiveRequisiteAssignmentSession.unassign_objective_requisite"""
# Implemented from kitosid template for -
# osid.learning.ObjectiveRequisiteAssignmentSession.unassign_objective_requisite
return self._get_provider_session('objective_requisite_assignment_session').unassign_objective_requisite(*args, **kwargs)
def assign_equivalent_objective(self, *args, **kwargs):
"""Pass through to provider ObjectiveRequisiteAssignmentSession.assign_equivalent_objective"""
# Implemented from kitosid template for -
# osid.learning.ObjectiveRequisiteAssignmentSession.assign_equivalent_objective
return self._get_provider_session('objective_requisite_assignment_session').assign_equivalent_objective(*args, **kwargs)
def unassign_equivalent_objective(self, *args, **kwargs):
"""Pass through to provider ObjectiveRequisiteAssignmentSession.unassign_equivalent_objective"""
# Implemented from kitosid template for -
# osid.learning.ObjectiveRequisiteAssignmentSession.unassign_equivalent_objective
return self._get_provider_session('objective_requisite_assignment_session').unassign_equivalent_objective(*args, **kwargs)
##
# The following methods are from osid.learning.ActivityLookupSession
def can_lookup_activities(self):
"""Pass through to provider ActivityLookupSession.can_lookup_activities"""
# Implemented from kitosid template for -
# osid.resource.ResourceLookupSession.can_lookup_resources_template
return self._get_provider_session('activity_lookup_session').can_lookup_activities()
def use_comparative_activity_view(self):
"""Pass through to provider ActivityLookupSession.use_comparative_activity_view"""
self._object_views['activity'] = COMPARATIVE
# self._get_provider_session('activity_lookup_session') # To make sure the session is tracked
for session in self._get_provider_sessions():
try:
session.use_comparative_activity_view()
except AttributeError:
pass
def use_plenary_activity_view(self):
"""Pass through to provider ActivityLookupSession.use_plenary_activity_view"""
self._object_views['activity'] = PLENARY
# self._get_provider_session('activity_lookup_session') # To make sure the session is tracked
for session in self._get_provider_sessions():
try:
session.use_plenary_activity_view()
except AttributeError:
pass
def get_activity(self, *args, **kwargs):
"""Pass through to provider ActivityLookupSession.get_activity"""
# Implemented from kitosid template for -
# osid.resource.ResourceLookupSession.get_resource_template
return self._get_provider_session('activity_lookup_session').get_activity(*args, **kwargs)
def get_activities_by_ids(self, *args, **kwargs):
"""Pass through to provider ActivityLookupSession.get_activities_by_ids"""
# Implemented from kitosid template for -
# osid.resource.ResourceLookupSession.get_resources_by_ids_template
return self._get_provider_session('activity_lookup_session').get_activities_by_ids(*args, **kwargs)
def get_activities_by_genus_type(self, *args, **kwargs):
"""Pass through to provider ActivityLookupSession.get_activities_by_genus_type"""
# Implemented from kitosid template for -
# osid.resource.ResourceLookupSession.get_resources_by_genus_type_template
return self._get_provider_session('activity_lookup_session').get_activities_by_genus_type(*args, **kwargs)
def get_activities_by_parent_genus_type(self, *args, **kwargs):
"""Pass through to provider ActivityLookupSession.get_activities_by_parent_genus_type"""
# Implemented from kitosid template for -
# osid.resource.ResourceLookupSession.get_resources_by_parent_genus_type_template
return self._get_provider_session('activity_lookup_session').get_activities_by_parent_genus_type(*args, **kwargs)
def get_activities_by_record_type(self, *args, **kwargs):
"""Pass through to provider ActivityLookupSession.get_activities_by_record_type"""
# Implemented from kitosid template for -
# osid.resource.ResourceLookupSession.get_resources_by_record_type_template
return self._get_provider_session('activity_lookup_session').get_activities_by_record_type(*args, **kwargs)
def get_activities_for_objective(self, *args, **kwargs):
"""Pass through to provider ActivityLookupSession.get_activities_for_objective"""
# Implemented from kitosid template for -
# osid.resource.ActivityLookupSession.get_activities_for_objective
return self._get_provider_session('activity_lookup_session').get_activities_for_objective(*args, **kwargs)
def get_activities_for_objectives(self, *args, **kwargs):
"""Pass through to provider ActivityLookupSession.get_activities_for_objectives"""
# Implemented from kitosid template for -
# osid.resource.ActivityLookupSession.get_activities_for_objectives
return self._get_provider_session('activity_lookup_session').get_activities_for_objectives(*args, **kwargs)
def get_activities_by_asset(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_activities_by_assets(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_activities(self):
"""Pass through to provider ActivityLookupSession.get_activities"""
# Implemented from kitosid template for -
# osid.resource.ResourceLookupSession.get_resources_template
return self._get_provider_session('activity_lookup_session').get_activities()
activities = property(fget=get_activities)
##
# The following methods are from osid.learning.ActivityQuerySession
def can_search_activities(self):
"""Pass through to provider ActivityQuerySession.can_search_activities"""
# Implemented from kitosid template for -
# osid.resource.ResourceQuerySession.can_search_resources_template
return self._get_provider_session('activity_query_session').can_search_activities()
def get_activity_query(self):
"""Pass through to provider ActivityQuerySession.get_activity_query"""
# Implemented from kitosid template for -
# osid.resource.ResourceQuerySession.get_item_query_template
return self._get_provider_session('activity_query_session').get_activity_query()
activity_query = property(fget=get_activity_query)
def get_activities_by_query(self, *args, **kwargs):
"""Pass through to provider ActivityQuerySession.get_activities_by_query"""
# Implemented from kitosid template for -
# osid.resource.ResourceQuerySession.get_items_by_query_template
return self._get_provider_session('activity_query_session').get_activities_by_query(*args, **kwargs)
##
# The following methods are from osid.learning.ActivityAdminSession
def can_create_activities(self):
"""Pass through to provider ActivityAdminSession.can_create_activities"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.can_create_resources
return self._get_provider_session('activity_admin_session').can_create_activities()
def can_create_activity_with_record_types(self, *args, **kwargs):
"""Pass through to provider ActivityAdminSession.can_create_activity_with_record_types"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.can_create_resource_with_record_types
return self._get_provider_session('activity_admin_session').can_create_activity_with_record_types(*args, **kwargs)
def get_activity_form_for_create(self, *args, **kwargs):
"""Pass through to provider ActivityAdminSession.get_activity_form_for_create"""
# Implemented from -
# osid.learning.ActivityAdminSession.get_activity_form_for_create_template
return self._get_provider_session('activity_admin_session').get_activity_form_for_create(*args, **kwargs)
def create_activity(self, *args, **kwargs):
"""Pass through to provider ActivityAdminSession.create_activity"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.create_resource
return self._get_provider_session('activity_admin_session').create_activity(*args, **kwargs)
def can_update_activities(self):
"""Pass through to provider ActivityAdminSession.can_update_activities"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.can_update_resources
return self._get_provider_session('activity_admin_session').can_update_activities()
def get_activity_form_for_update(self, *args, **kwargs):
"""Pass through to provider ActivityAdminSession.get_activity_form_for_update"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.get_resource_form_for_update
return self._get_provider_session('activity_admin_session').get_activity_form_for_update(*args, **kwargs)
def get_activity_form(self, *args, **kwargs):
"""Pass through to provider ActivityAdminSession.get_activity_form_for_update"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.get_resource_form_for_update
# This method might be a bit sketchy. Time will tell.
if isinstance(args[-1], list) or 'activity_record_types' in kwargs:
return self.get_activity_form_for_create(*args, **kwargs)
else:
return self.get_activity_form_for_update(*args, **kwargs)
def duplicate_activity(self, activity_id):
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.get_resource_form_for_update
return self._get_provider_session('activity_admin_session').duplicate_activity(activity_id)
def update_activity(self, *args, **kwargs):
"""Pass through to provider ActivityAdminSession.update_activity"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.update_resource
# Note: The OSID spec does not require returning updated object
return self._get_provider_session('activity_admin_session').update_activity(*args, **kwargs)
def save_activity(self, activity_form, *args, **kwargs):
"""Pass through to provider ActivityAdminSession.update_activity"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.update_resource
if activity_form.is_for_update():
return self.update_activity(activity_form, *args, **kwargs)
else:
return self.create_activity(activity_form, *args, **kwargs)
def can_delete_activities(self):
"""Pass through to provider ActivityAdminSession.can_delete_activities"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.can_delete_resources
return self._get_provider_session('activity_admin_session').can_delete_activities()
def delete_activity(self, *args, **kwargs):
"""Pass through to provider ActivityAdminSession.delete_activity"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.delete_resource
self._get_provider_session('activity_admin_session').delete_activity(*args, **kwargs)
def can_manage_activity_aliases(self):
"""Pass through to provider ActivityAdminSession.can_manage_activity_aliases"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.can_manage_resource_aliases_template
return self._get_provider_session('activity_admin_session').can_manage_activity_aliases()
def alias_activity(self, *args, **kwargs):
"""Pass through to provider ActivityAdminSession.alias_activity"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.alias_resources
self._get_provider_session('activity_admin_session').alias_activity(*args, **kwargs)
##
# The following methods are from osid.learning.ProficiencyLookupSession
def can_lookup_proficiencies(self):
"""Pass through to provider ProficiencyLookupSession.can_lookup_proficiencies"""
# Implemented from kitosid template for -
# osid.resource.ResourceLookupSession.can_lookup_resources_template
return self._get_provider_session('proficiency_lookup_session').can_lookup_proficiencies()
def use_comparative_proficiency_view(self):
"""Pass through to provider ProficiencyLookupSession.use_comparative_proficiency_view"""
self._object_views['proficiency'] = COMPARATIVE
# self._get_provider_session('proficiency_lookup_session') # To make sure the session is tracked
for session in self._get_provider_sessions():
try:
session.use_comparative_proficiency_view()
except AttributeError:
pass
def use_plenary_proficiency_view(self):
"""Pass through to provider ProficiencyLookupSession.use_plenary_proficiency_view"""
self._object_views['proficiency'] = PLENARY
# self._get_provider_session('proficiency_lookup_session') # To make sure the session is tracked
for session in self._get_provider_sessions():
try:
session.use_plenary_proficiency_view()
except AttributeError:
pass
def use_effective_proficiency_view(self):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services')
def use_any_effective_proficiency_view(self):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services')
def get_proficiency(self, *args, **kwargs):
"""Pass through to provider ProficiencyLookupSession.get_proficiency"""
# Implemented from kitosid template for -
# osid.resource.ResourceLookupSession.get_resource_template
return self._get_provider_session('proficiency_lookup_session').get_proficiency(*args, **kwargs)
def get_proficiencies_by_ids(self, *args, **kwargs):
"""Pass through to provider ProficiencyLookupSession.get_proficiencies_by_ids"""
# Implemented from kitosid template for -
# osid.resource.ResourceLookupSession.get_resources_by_ids_template
return self._get_provider_session('proficiency_lookup_session').get_proficiencies_by_ids(*args, **kwargs)
def get_proficiencies_by_genus_type(self, *args, **kwargs):
"""Pass through to provider ProficiencyLookupSession.get_proficiencies_by_genus_type"""
# Implemented from kitosid template for -
# osid.resource.ResourceLookupSession.get_resources_by_genus_type_template
return self._get_provider_session('proficiency_lookup_session').get_proficiencies_by_genus_type(*args, **kwargs)
def get_proficiencies_by_parent_genus_type(self, *args, **kwargs):
"""Pass through to provider ProficiencyLookupSession.get_proficiencies_by_parent_genus_type"""
# Implemented from kitosid template for -
# osid.resource.ResourceLookupSession.get_resources_by_parent_genus_type_template
return self._get_provider_session('proficiency_lookup_session').get_proficiencies_by_parent_genus_type(*args, **kwargs)
def get_proficiencies_by_record_type(self, *args, **kwargs):
"""Pass through to provider ProficiencyLookupSession.get_proficiencies_by_record_type"""
# Implemented from kitosid template for -
# osid.resource.ResourceLookupSession.get_resources_by_record_type_template
return self._get_provider_session('proficiency_lookup_session').get_proficiencies_by_record_type(*args, **kwargs)
def get_proficiencies_on_date(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_proficiencies_by_genus_type_on_date(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_proficiencies_for_objective(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_proficiencies_for_objective_on_date(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_proficiencies_by_genus_type_for_objective(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_proficiencies_by_genus_type_for_objective_on_date(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_proficiencies_for_objectives(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_proficiencies_for_resource(self, *args, **kwargs):
"""Pass through to provider ProficiencyLookupSession.get_proficiencies_for_resource"""
# Implemented from kitosid template for -
# osid.relationship.RelationshipLookupSession.get_relationships_for_source_template
return self._get_provider_session('proficiency_lookup_session').get_proficiencies_for_resource(*args, **kwargs)
def get_proficiencies_for_resource_on_date(self, *args, **kwargs):
"""Pass through to provider ProficiencyLookupSession.get_proficiencies_for_resource_on_date"""
# Implemented from kitosid template for -
# osid.relationship.RelationshipLookupSession.get_relationships_for_source_on_date_template
return self._get_provider_session('proficiency_lookup_session').get_proficiencies_for_resource_on_date(*args, **kwargs)
def get_proficiencies_by_genus_type_for_resource(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_proficiencies_by_genus_type_for_resource_on_date(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_proficiencies_for_resources(self, *args, **kwargs):
"""Pass through to provider ProficiencyLookupSession.get_proficiencies_for_resources"""
# Implemented from kitosid template for -
# osid.relationship.RelationshipLookupSession.get_relationships_for_source_template
return self._get_provider_session('proficiency_lookup_session').get_proficiencies_for_resources(*args, **kwargs)
def get_proficiencies_for_objective_and_resource(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_proficiencies_for_objective_and_resource_on_date(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_proficiencies_by_genus_type_for_objective_and_resource(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_proficiencies_by_genus_type_for_objective_and_resource_on_date(self, *args, **kwargs):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services - args=' + str(args) + ', kwargs=' + str(kwargs))
def get_proficiencies(self):
"""Pass through to provider ProficiencyLookupSession.get_proficiencies"""
# Implemented from kitosid template for -
# osid.resource.ResourceLookupSession.get_resources_template
return self._get_provider_session('proficiency_lookup_session').get_proficiencies()
proficiencies = property(fget=get_proficiencies)
##
# The following methods are from osid.learning.ProficiencyQuerySession
def can_search_proficiencies(self):
"""Pass through to provider ProficiencyQuerySession.can_search_proficiencies"""
# Implemented from kitosid template for -
# osid.resource.ResourceQuerySession.can_search_resources_template
return self._get_provider_session('proficiency_query_session').can_search_proficiencies()
def get_proficiency_query(self):
"""Pass through to provider ProficiencyQuerySession.get_proficiency_query"""
# Implemented from kitosid template for -
# osid.resource.ResourceQuerySession.get_item_query_template
return self._get_provider_session('proficiency_query_session').get_proficiency_query()
proficiency_query = property(fget=get_proficiency_query)
def get_proficiencies_by_query(self, *args, **kwargs):
"""Pass through to provider ProficiencyQuerySession.get_proficiencies_by_query"""
# Implemented from kitosid template for -
# osid.resource.ResourceQuerySession.get_items_by_query_template
return self._get_provider_session('proficiency_query_session').get_proficiencies_by_query(*args, **kwargs)
##
# The following methods are from osid.learning.ProficiencyAdminSession
def can_create_proficiencies(self):
"""Pass through to provider ProficiencyAdminSession.can_create_proficiencies"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.can_create_resources
return self._get_provider_session('proficiency_admin_session').can_create_proficiencies()
def can_create_proficiency_with_record_types(self, *args, **kwargs):
"""Pass through to provider ProficiencyAdminSession.can_create_proficiency_with_record_types"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.can_create_resource_with_record_types
return self._get_provider_session('proficiency_admin_session').can_create_proficiency_with_record_types(*args, **kwargs)
def get_proficiency_form_for_create(self, *args, **kwargs):
"""Pass through to provider ProficiencyAdminSession.get_proficiency_form_for_create"""
# Implemented from kitosid template for -
# osid.relationship.RelationshipAdminSession.get_relationship_form_for_create_template
return self._get_provider_session('proficiency_admin_session').get_proficiency_form_for_create(*args, **kwargs)
def create_proficiency(self, *args, **kwargs):
"""Pass through to provider ProficiencyAdminSession.create_proficiency"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.create_resource
return self._get_provider_session('proficiency_admin_session').create_proficiency(*args, **kwargs)
def can_update_proficiencies(self):
"""Pass through to provider ProficiencyAdminSession.can_update_proficiencies"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.can_update_resources
return self._get_provider_session('proficiency_admin_session').can_update_proficiencies()
def get_proficiency_form_for_update(self, *args, **kwargs):
"""Pass through to provider ProficiencyAdminSession.get_proficiency_form_for_update"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.get_resource_form_for_update
return self._get_provider_session('proficiency_admin_session').get_proficiency_form_for_update(*args, **kwargs)
def get_proficiency_form(self, *args, **kwargs):
"""Pass through to provider ProficiencyAdminSession.get_proficiency_form_for_update"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.get_resource_form_for_update
# This method might be a bit sketchy. Time will tell.
if isinstance(args[-1], list) or 'proficiency_record_types' in kwargs:
return self.get_proficiency_form_for_create(*args, **kwargs)
else:
return self.get_proficiency_form_for_update(*args, **kwargs)
def duplicate_proficiency(self, proficiency_id):
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.get_resource_form_for_update
return self._get_provider_session('proficiency_admin_session').duplicate_proficiency(proficiency_id)
def update_proficiency(self, *args, **kwargs):
"""Pass through to provider ProficiencyAdminSession.update_proficiency"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.update_resource
# Note: The OSID spec does not require returning updated object
return self._get_provider_session('proficiency_admin_session').update_proficiency(*args, **kwargs)
def save_proficiency(self, proficiency_form, *args, **kwargs):
"""Pass through to provider ProficiencyAdminSession.update_proficiency"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.update_resource
if proficiency_form.is_for_update():
return self.update_proficiency(proficiency_form, *args, **kwargs)
else:
return self.create_proficiency(proficiency_form, *args, **kwargs)
def can_delete_proficiencies(self):
"""Pass through to provider ProficiencyAdminSession.can_delete_proficiencies"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.can_delete_resources
return self._get_provider_session('proficiency_admin_session').can_delete_proficiencies()
def delete_proficiency(self, *args, **kwargs):
"""Pass through to provider ProficiencyAdminSession.delete_proficiency"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.delete_resource
self._get_provider_session('proficiency_admin_session').delete_proficiency(*args, **kwargs)
def delete_proficiencies(self):
"""Pass through to provider unimplemented"""
raise Unimplemented('Unimplemented in dlkit.services')
def can_manage_proficiency_aliases(self):
"""Pass through to provider ProficiencyAdminSession.can_manage_proficiency_aliases"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.can_manage_resource_aliases_template
return self._get_provider_session('proficiency_admin_session').can_manage_proficiency_aliases()
def alias_proficiency(self, *args, **kwargs):
"""Pass through to provider ProficiencyAdminSession.alias_proficiency"""
# Implemented from kitosid template for -
# osid.resource.ResourceAdminSession.alias_resources
self._get_provider_session('proficiency_admin_session').alias_proficiency(*args, **kwargs)
class ObjectiveBankList(abc_learning_objects.ObjectiveBankList, osid.OsidList):
"""ObjectiveBankList convenience adapter including related Session methods."""
def get_next_objective_bank(self):
"""Gets next object"""
# Implemented from kitosid template for -
# osid.resource.ResourceList.get_next_resource
try:
next_item = next(self)
except StopIteration:
raise IllegalState('no more elements available in this list')
else:
return next_item
def next(self):
"""next method for enumerator"""
# Implemented from kitosid template for -
# osid.resource.ResourceList.get_next_resource
next_item = osid.OsidList.next(self)
return next_item
__next__ = next
next_objective_bank = property(fget=get_next_objective_bank)
def get_next_objective_banks(self, n):
"""gets next n objects from list"""
# Implemented from kitosid template for -
# osid.resource.ResourceList.get_next_resources
if n > self.available():
# !!! This is not quite as specified (see method docs) !!!
raise IllegalState('not enough elements available in this list')
else:
next_list = []
i = 0
while i < n:
try:
next_list.append(next(self))
except StopIteration:
break
i += 1
return next_list
| 56.539798 | 157 | 0.745934 | 15,589 | 139,936 | 6.314388 | 0.024697 | 0.048255 | 0.041205 | 0.066562 | 0.918982 | 0.888312 | 0.847046 | 0.798852 | 0.756509 | 0.709819 | 0 | 0.000355 | 0.174351 | 139,936 | 2,474 | 158 | 56.562652 | 0.851616 | 0.39711 | 0 | 0.324651 | 0 | 0 | 0.099946 | 0.067038 | 0 | 0 | 0 | 0 | 0 | 1 | 0.332093 | false | 0.019535 | 0.004651 | 0.004651 | 0.64093 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 8 |
0e2dfbd8910c1ee5cc589408b726ef27f299a13c | 549 | py | Python | pytorch_myself/tensor_basic.py | 94JuHo/study_for_deeplearning | ababf482b6a24d94b5f860ea9a68e34fe324d182 | [
"MIT"
] | null | null | null | pytorch_myself/tensor_basic.py | 94JuHo/study_for_deeplearning | ababf482b6a24d94b5f860ea9a68e34fe324d182 | [
"MIT"
] | null | null | null | pytorch_myself/tensor_basic.py | 94JuHo/study_for_deeplearning | ababf482b6a24d94b5f860ea9a68e34fe324d182 | [
"MIT"
] | null | null | null | import torch
x = torch.tensor([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
print(x)
print("Size:", x.size())
print("Shape:", x.shape)
print("Rank:",x.ndimension())
x = torch.unsqueeze(x, 0)
print(x)
print("Size:", x.size())
print("Shape:", x.shape)
print("Rank:",x.ndimension())
x = torch.squeeze(x)
print(x)
print("Size:", x.size())
print("Shape:", x.shape)
print("Rank:",x.ndimension())
x = x.view(9)
print(x)
print("Size:", x.size())
print("Shape:", x.shape)
print("Rank:",x.ndimension())
try:
x = x.view(2, 4)
except Exception as e:
print(e)
| 17.709677 | 51 | 0.599271 | 95 | 549 | 3.463158 | 0.284211 | 0.091185 | 0.133739 | 0.182371 | 0.726444 | 0.726444 | 0.726444 | 0.726444 | 0.726444 | 0.726444 | 0 | 0.02714 | 0.127505 | 549 | 30 | 52 | 18.3 | 0.659708 | 0 | 0 | 0.64 | 0 | 0 | 0.116576 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.04 | 0 | 0.04 | 0.68 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 7 |
0e5ed790daabb0eda61cd93338f38f8bae9c9ce7 | 114 | py | Python | vestlus/search_indexes/__init__.py | lehvitus/vestlus | 6d9c8b1de7821e544e0c7c99f42d60f8f3805557 | [
"BSD-3-Clause"
] | 12 | 2020-07-02T23:36:02.000Z | 2020-12-15T07:29:20.000Z | vestlus/search_indexes/__init__.py | lehvitus/vestlus | 6d9c8b1de7821e544e0c7c99f42d60f8f3805557 | [
"BSD-3-Clause"
] | null | null | null | vestlus/search_indexes/__init__.py | lehvitus/vestlus | 6d9c8b1de7821e544e0c7c99f42d60f8f3805557 | [
"BSD-3-Clause"
] | null | null | null | from .channel import ChannelIndex
from .message import PrivateMessageIndex
from .message import GroupMessageIndex
| 28.5 | 40 | 0.868421 | 12 | 114 | 8.25 | 0.583333 | 0.222222 | 0.343434 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.105263 | 114 | 3 | 41 | 38 | 0.970588 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
0e831bf1c22a83ba6c4e1123beb7df5d6dcc4a96 | 154 | py | Python | hebpipe/lib/xrenner/__init__.py | amir-zeldes/HebPipe | a3eb95abd2dd9588806b545eba7b28f57e589973 | [
"Apache-2.0"
] | 21 | 2019-02-04T16:27:37.000Z | 2022-03-22T11:45:05.000Z | hebpipe/lib/xrenner/__init__.py | amir-zeldes/HebPipe | a3eb95abd2dd9588806b545eba7b28f57e589973 | [
"Apache-2.0"
] | 12 | 2020-01-02T15:56:31.000Z | 2022-03-31T10:35:16.000Z | hebpipe/lib/xrenner/__init__.py | amir-zeldes/HebPipe | a3eb95abd2dd9588806b545eba7b28f57e589973 | [
"Apache-2.0"
] | 5 | 2020-01-01T20:51:35.000Z | 2021-12-21T12:56:53.000Z | ## xrenner init ##
import sys
if sys.version_info[0] < 3:
from modules.xrenner_xrenner import Xrenner
else:
from .modules.xrenner_xrenner import Xrenner | 25.666667 | 45 | 0.785714 | 23 | 154 | 5.130435 | 0.521739 | 0.186441 | 0.305085 | 0.423729 | 0.644068 | 0.644068 | 0 | 0 | 0 | 0 | 0 | 0.014925 | 0.12987 | 154 | 6 | 45 | 25.666667 | 0.865672 | 0.077922 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.6 | 0 | 0.6 | 0 | 1 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
7eba47dc78322e6f5149d7cfcee2d62d8722c3a6 | 9,701 | py | Python | webapp/apps/btax/migrations/0001_initial.py | codekansas/PolicyBrain | 83c459db883536bae70cc78ca92ebdcff554ac2d | [
"MIT"
] | null | null | null | webapp/apps/btax/migrations/0001_initial.py | codekansas/PolicyBrain | 83c459db883536bae70cc78ca92ebdcff554ac2d | [
"MIT"
] | null | null | null | webapp/apps/btax/migrations/0001_initial.py | codekansas/PolicyBrain | 83c459db883536bae70cc78ca92ebdcff554ac2d | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
import datetime
import jsonfield.fields
from django.conf import settings
import uuidfield.fields
import webapp.apps.taxbrain.models
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
]
operations = [
migrations.CreateModel(
name='BTaxOutputUrl',
fields=[
('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)),
('model_pk', models.IntegerField(default=None, null=True)),
('exp_comp_datetime', models.DateTimeField(default=datetime.datetime(2015, 1, 1, 0, 0))),
('uuid', uuidfield.fields.UUIDField(null=True, default=None, editable=False, max_length=32, blank=True, unique=True)),
('btax_vers', models.CharField(default=None, max_length=50, null=True, blank=True)),
('taxcalc_vers', models.CharField(default=None, max_length=50, null=True, blank=True)),
],
),
migrations.CreateModel(
name='BTaxSaveInputs',
fields=[
('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)),
('btax_betr_corp', webapp.apps.taxbrain.models.CommaSeparatedField(default=None, max_length=200, null=True, blank=True)),
('btax_betr_entity_Switch', models.NullBooleanField(default=None)),
('btax_betr_pass', webapp.apps.taxbrain.models.CommaSeparatedField(default=None, max_length=200, null=True, blank=True)),
('btax_depr_allyr', models.CharField(default=None, max_length=50, null=True, blank=True)),
('btax_depr_3yr', models.CharField(default=None, max_length=50, null=True, blank=True)),
('btax_depr_5yr', models.CharField(default=None, max_length=50, null=True, blank=True)),
('btax_depr_7yr', models.CharField(default=None, max_length=50, null=True, blank=True)),
('btax_depr_10yr', models.CharField(default=None, max_length=50, null=True, blank=True)),
('btax_depr_15yr', models.CharField(default=None, max_length=50, null=True, blank=True)),
('btax_depr_20yr', models.CharField(default=None, max_length=50, null=True, blank=True)),
('btax_depr_25yr', models.CharField(default=None, max_length=50, null=True, blank=True)),
('btax_depr_27_5yr', models.CharField(default=None, max_length=50, null=True, blank=True)),
('btax_depr_39yr', models.CharField(default=None, max_length=50, null=True, blank=True)),
('btax_depr_allyr_gds_Switch', models.CharField(default=b'True', max_length=50, null=True, blank=True)),
('btax_depr_3yr_gds_Switch', models.CharField(default=b'True', max_length=50, null=True, blank=True)),
('btax_depr_5yr_gds_Switch', models.CharField(default=b'True', max_length=50, null=True, blank=True)),
('btax_depr_7yr_gds_Switch', models.CharField(default=b'True', max_length=50, null=True, blank=True)),
('btax_depr_10yr_gds_Switch', models.CharField(default=b'True', max_length=50, null=True, blank=True)),
('btax_depr_15yr_gds_Switch', models.CharField(default=b'True', max_length=50, null=True, blank=True)),
('btax_depr_20yr_gds_Switch', models.CharField(default=b'True', max_length=50, null=True, blank=True)),
('btax_depr_25yr_gds_Switch', models.CharField(default=b'True', max_length=50, null=True, blank=True)),
('btax_depr_27_5yr_gds_Switch', models.CharField(default=b'True', max_length=50, null=True, blank=True)),
('btax_depr_39yr_gds_Switch', models.CharField(default=b'True', max_length=50, null=True, blank=True)),
('btax_depr_allyr_ads_Switch', models.CharField(default=b'False', max_length=50, null=True, blank=True)),
('btax_depr_3yr_ads_Switch', models.CharField(default=b'False', max_length=50, null=True, blank=True)),
('btax_depr_5yr_ads_Switch', models.CharField(default=b'False', max_length=50, null=True, blank=True)),
('btax_depr_7yr_ads_Switch', models.CharField(default=b'False', max_length=50, null=True, blank=True)),
('btax_depr_10yr_ads_Switch', models.CharField(default=b'False', max_length=50, null=True, blank=True)),
('btax_depr_15yr_ads_Switch', models.CharField(default=b'False', max_length=50, null=True, blank=True)),
('btax_depr_20yr_ads_Switch', models.CharField(default=b'False', max_length=50, null=True, blank=True)),
('btax_depr_25yr_ads_Switch', models.CharField(default=b'False', max_length=50, null=True, blank=True)),
('btax_depr_27_5yr_ads_Switch', models.CharField(default=b'False', max_length=50, null=True, blank=True)),
('btax_depr_39yr_ads_Switch', models.CharField(default=b'False', max_length=50, null=True, blank=True)),
('btax_depr_allyr_tax_Switch', models.CharField(default=b'False', max_length=50, null=True, blank=True)),
('btax_depr_3yr_tax_Switch', models.CharField(default=b'False', max_length=50, null=True, blank=True)),
('btax_depr_5yr_tax_Switch', models.CharField(default=b'False', max_length=50, null=True, blank=True)),
('btax_depr_7yr_tax_Switch', models.CharField(default=b'False', max_length=50, null=True, blank=True)),
('btax_depr_10yr_tax_Switch', models.CharField(default=b'False', max_length=50, null=True, blank=True)),
('btax_depr_15yr_tax_Switch', models.CharField(default=b'False', max_length=50, null=True, blank=True)),
('btax_depr_20yr_tax_Switch', models.CharField(default=b'False', max_length=50, null=True, blank=True)),
('btax_depr_25yr_tax_Switch', models.CharField(default=b'False', max_length=50, null=True, blank=True)),
('btax_depr_27_5yr_tax_Switch', models.CharField(default=b'False', max_length=50, null=True, blank=True)),
('btax_depr_39yr_tax_Switch', models.CharField(default=b'False', max_length=50, null=True, blank=True)),
('btax_depr_allyr_exp', webapp.apps.taxbrain.models.CommaSeparatedField(default=None, max_length=200, null=True, blank=True)),
('btax_depr_3yr_exp', webapp.apps.taxbrain.models.CommaSeparatedField(default=None, max_length=200, null=True, blank=True)),
('btax_depr_5yr_exp', webapp.apps.taxbrain.models.CommaSeparatedField(default=None, max_length=200, null=True, blank=True)),
('btax_depr_7yr_exp', webapp.apps.taxbrain.models.CommaSeparatedField(default=None, max_length=200, null=True, blank=True)),
('btax_depr_10yr_exp', webapp.apps.taxbrain.models.CommaSeparatedField(default=None, max_length=200, null=True, blank=True)),
('btax_depr_15yr_exp', webapp.apps.taxbrain.models.CommaSeparatedField(default=None, max_length=200, null=True, blank=True)),
('btax_depr_20yr_exp', webapp.apps.taxbrain.models.CommaSeparatedField(default=None, max_length=200, null=True, blank=True)),
('btax_depr_25yr_exp', webapp.apps.taxbrain.models.CommaSeparatedField(default=None, max_length=200, null=True, blank=True)),
('btax_depr_27_5yr_exp', webapp.apps.taxbrain.models.CommaSeparatedField(default=None, max_length=200, null=True, blank=True)),
('btax_depr_39yr_exp', webapp.apps.taxbrain.models.CommaSeparatedField(default=None, max_length=200, null=True, blank=True)),
('btax_other_hair', webapp.apps.taxbrain.models.CommaSeparatedField(default=None, max_length=200, null=True, blank=True)),
('btax_other_corpeq', webapp.apps.taxbrain.models.CommaSeparatedField(default=None, max_length=200, null=True, blank=True)),
('btax_other_proptx', webapp.apps.taxbrain.models.CommaSeparatedField(default=None, max_length=200, null=True, blank=True)),
('btax_other_invest', webapp.apps.taxbrain.models.CommaSeparatedField(default=None, max_length=200, null=True, blank=True)),
('btax_econ_nomint', webapp.apps.taxbrain.models.CommaSeparatedField(default=None, max_length=200, null=True, blank=True)),
('btax_econ_inflat', webapp.apps.taxbrain.models.CommaSeparatedField(default=None, max_length=200, null=True, blank=True)),
('job_ids', webapp.apps.taxbrain.models.SeparatedValuesField(default=None, null=True, blank=True)),
('jobs_not_ready', webapp.apps.taxbrain.models.SeparatedValuesField(default=None, null=True, blank=True)),
('first_year', models.IntegerField(default=None, null=True)),
('tax_result', jsonfield.fields.JSONField(default=None, null=True, blank=True)),
('creation_date', models.DateTimeField(default=datetime.datetime(2015, 1, 1, 0, 0))),
],
options={
'permissions': (('view_inputs', 'Allowed to view Taxbrain.'),),
},
),
migrations.AddField(
model_name='btaxoutputurl',
name='unique_inputs',
field=models.ForeignKey(default=None, to='btax.BTaxSaveInputs'),
),
migrations.AddField(
model_name='btaxoutputurl',
name='user',
field=models.ForeignKey(default=None, to=settings.AUTH_USER_MODEL, null=True),
),
]
| 85.096491 | 143 | 0.67024 | 1,227 | 9,701 | 5.066015 | 0.09617 | 0.086229 | 0.131757 | 0.172297 | 0.873713 | 0.873713 | 0.832207 | 0.82722 | 0.826898 | 0.826898 | 0 | 0.030111 | 0.18864 | 9,701 | 113 | 144 | 85.849558 | 0.759624 | 0.002165 | 0 | 0.149533 | 0 | 0 | 0.166047 | 0.079872 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.009346 | 0.065421 | 0 | 0.093458 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
7ee0a5ca756112a988e770b9a1fd6ad6f9dca9b1 | 65,722 | py | Python | sdk/python/pulumi_gcp/certificateauthority/authority.py | sisisin/pulumi-gcp | af6681d70ea457843409110c1324817fe55f68ad | [
"ECL-2.0",
"Apache-2.0"
] | null | null | null | sdk/python/pulumi_gcp/certificateauthority/authority.py | sisisin/pulumi-gcp | af6681d70ea457843409110c1324817fe55f68ad | [
"ECL-2.0",
"Apache-2.0"
] | null | null | null | sdk/python/pulumi_gcp/certificateauthority/authority.py | sisisin/pulumi-gcp | af6681d70ea457843409110c1324817fe55f68ad | [
"ECL-2.0",
"Apache-2.0"
] | null | null | null | # coding=utf-8
# *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from .. import _utilities
from . import outputs
from ._inputs import *
__all__ = ['AuthorityArgs', 'Authority']
@pulumi.input_type
class AuthorityArgs:
def __init__(__self__, *,
certificate_authority_id: pulumi.Input[str],
config: pulumi.Input['AuthorityConfigArgs'],
key_spec: pulumi.Input['AuthorityKeySpecArgs'],
location: pulumi.Input[str],
pool: pulumi.Input[str],
gcs_bucket: Optional[pulumi.Input[str]] = None,
ignore_active_certificates_on_deletion: Optional[pulumi.Input[bool]] = None,
labels: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,
lifetime: Optional[pulumi.Input[str]] = None,
project: Optional[pulumi.Input[str]] = None,
type: Optional[pulumi.Input[str]] = None):
"""
The set of arguments for constructing a Authority resource.
:param pulumi.Input[str] certificate_authority_id: The user provided Resource ID for this Certificate Authority.
:param pulumi.Input['AuthorityConfigArgs'] config: The config used to create a self-signed X.509 certificate or CSR.
Structure is documented below.
:param pulumi.Input['AuthorityKeySpecArgs'] key_spec: Used when issuing certificates for this CertificateAuthority. If this CertificateAuthority
is a self-signed CertificateAuthority, this key is also used to sign the self-signed CA
certificate. Otherwise, it is used to sign a CSR.
Structure is documented below.
:param pulumi.Input[str] location: Location of the CertificateAuthority. A full list of valid locations can be found by
running `gcloud privateca locations list`.
:param pulumi.Input[str] pool: The name of the CaPool this Certificate Authority belongs to.
:param pulumi.Input[str] gcs_bucket: The name of a Cloud Storage bucket where this CertificateAuthority will publish content,
such as the CA certificate and CRLs. This must be a bucket name, without any prefixes
(such as `gs://`) or suffixes (such as `.googleapis.com`). For example, to use a bucket named
my-bucket, you would simply specify `my-bucket`. If not specified, a managed bucket will be
created.
:param pulumi.Input[bool] ignore_active_certificates_on_deletion: This field allows the CA to be deleted even if the CA has active certs. Active certs include both unrevoked and unexpired certs.
Use with care. Defaults to `false`.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] labels: Labels with user-defined metadata.
An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass":
"1.3kg", "count": "3" }.
:param pulumi.Input[str] lifetime: The desired lifetime of the CA certificate. Used to create the "notBeforeTime" and
"notAfterTime" fields inside an X.509 certificate. A duration in seconds with up to nine
fractional digits, terminated by 's'. Example: "3.5s".
:param pulumi.Input[str] project: The ID of the project in which the resource belongs.
If it is not provided, the provider project is used.
:param pulumi.Input[str] type: The Type of this CertificateAuthority.
> **Note:** For `SUBORDINATE` Certificate Authorities, they need to
be manually activated (via Cloud Console of `gcloud`) before they can
issue certificates.
Default value is `SELF_SIGNED`.
Possible values are `SELF_SIGNED` and `SUBORDINATE`.
"""
pulumi.set(__self__, "certificate_authority_id", certificate_authority_id)
pulumi.set(__self__, "config", config)
pulumi.set(__self__, "key_spec", key_spec)
pulumi.set(__self__, "location", location)
pulumi.set(__self__, "pool", pool)
if gcs_bucket is not None:
pulumi.set(__self__, "gcs_bucket", gcs_bucket)
if ignore_active_certificates_on_deletion is not None:
pulumi.set(__self__, "ignore_active_certificates_on_deletion", ignore_active_certificates_on_deletion)
if labels is not None:
pulumi.set(__self__, "labels", labels)
if lifetime is not None:
pulumi.set(__self__, "lifetime", lifetime)
if project is not None:
pulumi.set(__self__, "project", project)
if type is not None:
pulumi.set(__self__, "type", type)
@property
@pulumi.getter(name="certificateAuthorityId")
def certificate_authority_id(self) -> pulumi.Input[str]:
"""
The user provided Resource ID for this Certificate Authority.
"""
return pulumi.get(self, "certificate_authority_id")
@certificate_authority_id.setter
def certificate_authority_id(self, value: pulumi.Input[str]):
pulumi.set(self, "certificate_authority_id", value)
@property
@pulumi.getter
def config(self) -> pulumi.Input['AuthorityConfigArgs']:
"""
The config used to create a self-signed X.509 certificate or CSR.
Structure is documented below.
"""
return pulumi.get(self, "config")
@config.setter
def config(self, value: pulumi.Input['AuthorityConfigArgs']):
pulumi.set(self, "config", value)
@property
@pulumi.getter(name="keySpec")
def key_spec(self) -> pulumi.Input['AuthorityKeySpecArgs']:
"""
Used when issuing certificates for this CertificateAuthority. If this CertificateAuthority
is a self-signed CertificateAuthority, this key is also used to sign the self-signed CA
certificate. Otherwise, it is used to sign a CSR.
Structure is documented below.
"""
return pulumi.get(self, "key_spec")
@key_spec.setter
def key_spec(self, value: pulumi.Input['AuthorityKeySpecArgs']):
pulumi.set(self, "key_spec", value)
@property
@pulumi.getter
def location(self) -> pulumi.Input[str]:
"""
Location of the CertificateAuthority. A full list of valid locations can be found by
running `gcloud privateca locations list`.
"""
return pulumi.get(self, "location")
@location.setter
def location(self, value: pulumi.Input[str]):
pulumi.set(self, "location", value)
@property
@pulumi.getter
def pool(self) -> pulumi.Input[str]:
"""
The name of the CaPool this Certificate Authority belongs to.
"""
return pulumi.get(self, "pool")
@pool.setter
def pool(self, value: pulumi.Input[str]):
pulumi.set(self, "pool", value)
@property
@pulumi.getter(name="gcsBucket")
def gcs_bucket(self) -> Optional[pulumi.Input[str]]:
"""
The name of a Cloud Storage bucket where this CertificateAuthority will publish content,
such as the CA certificate and CRLs. This must be a bucket name, without any prefixes
(such as `gs://`) or suffixes (such as `.googleapis.com`). For example, to use a bucket named
my-bucket, you would simply specify `my-bucket`. If not specified, a managed bucket will be
created.
"""
return pulumi.get(self, "gcs_bucket")
@gcs_bucket.setter
def gcs_bucket(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "gcs_bucket", value)
@property
@pulumi.getter(name="ignoreActiveCertificatesOnDeletion")
def ignore_active_certificates_on_deletion(self) -> Optional[pulumi.Input[bool]]:
"""
This field allows the CA to be deleted even if the CA has active certs. Active certs include both unrevoked and unexpired certs.
Use with care. Defaults to `false`.
"""
return pulumi.get(self, "ignore_active_certificates_on_deletion")
@ignore_active_certificates_on_deletion.setter
def ignore_active_certificates_on_deletion(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "ignore_active_certificates_on_deletion", value)
@property
@pulumi.getter
def labels(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]:
"""
Labels with user-defined metadata.
An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass":
"1.3kg", "count": "3" }.
"""
return pulumi.get(self, "labels")
@labels.setter
def labels(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]):
pulumi.set(self, "labels", value)
@property
@pulumi.getter
def lifetime(self) -> Optional[pulumi.Input[str]]:
"""
The desired lifetime of the CA certificate. Used to create the "notBeforeTime" and
"notAfterTime" fields inside an X.509 certificate. A duration in seconds with up to nine
fractional digits, terminated by 's'. Example: "3.5s".
"""
return pulumi.get(self, "lifetime")
@lifetime.setter
def lifetime(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "lifetime", value)
@property
@pulumi.getter
def project(self) -> Optional[pulumi.Input[str]]:
"""
The ID of the project in which the resource belongs.
If it is not provided, the provider project is used.
"""
return pulumi.get(self, "project")
@project.setter
def project(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "project", value)
@property
@pulumi.getter
def type(self) -> Optional[pulumi.Input[str]]:
"""
The Type of this CertificateAuthority.
> **Note:** For `SUBORDINATE` Certificate Authorities, they need to
be manually activated (via Cloud Console of `gcloud`) before they can
issue certificates.
Default value is `SELF_SIGNED`.
Possible values are `SELF_SIGNED` and `SUBORDINATE`.
"""
return pulumi.get(self, "type")
@type.setter
def type(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "type", value)
@pulumi.input_type
class _AuthorityState:
def __init__(__self__, *,
access_urls: Optional[pulumi.Input[Sequence[pulumi.Input['AuthorityAccessUrlArgs']]]] = None,
certificate_authority_id: Optional[pulumi.Input[str]] = None,
config: Optional[pulumi.Input['AuthorityConfigArgs']] = None,
create_time: Optional[pulumi.Input[str]] = None,
gcs_bucket: Optional[pulumi.Input[str]] = None,
ignore_active_certificates_on_deletion: Optional[pulumi.Input[bool]] = None,
key_spec: Optional[pulumi.Input['AuthorityKeySpecArgs']] = None,
labels: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,
lifetime: Optional[pulumi.Input[str]] = None,
location: Optional[pulumi.Input[str]] = None,
name: Optional[pulumi.Input[str]] = None,
pem_ca_certificates: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
pool: Optional[pulumi.Input[str]] = None,
project: Optional[pulumi.Input[str]] = None,
state: Optional[pulumi.Input[str]] = None,
type: Optional[pulumi.Input[str]] = None,
update_time: Optional[pulumi.Input[str]] = None):
"""
Input properties used for looking up and filtering Authority resources.
:param pulumi.Input[Sequence[pulumi.Input['AuthorityAccessUrlArgs']]] access_urls: URLs for accessing content published by this CA, such as the CA certificate and CRLs.
:param pulumi.Input[str] certificate_authority_id: The user provided Resource ID for this Certificate Authority.
:param pulumi.Input['AuthorityConfigArgs'] config: The config used to create a self-signed X.509 certificate or CSR.
Structure is documented below.
:param pulumi.Input[str] create_time: The time at which this CertificateAuthority was created. A timestamp in RFC3339 UTC "Zulu" format, with nanosecond
resolution and up to nine fractional digits. Examples: "2014-10-02T15:01:23Z" and "2014-10-02T15:01:23.045123456Z".
:param pulumi.Input[str] gcs_bucket: The name of a Cloud Storage bucket where this CertificateAuthority will publish content,
such as the CA certificate and CRLs. This must be a bucket name, without any prefixes
(such as `gs://`) or suffixes (such as `.googleapis.com`). For example, to use a bucket named
my-bucket, you would simply specify `my-bucket`. If not specified, a managed bucket will be
created.
:param pulumi.Input[bool] ignore_active_certificates_on_deletion: This field allows the CA to be deleted even if the CA has active certs. Active certs include both unrevoked and unexpired certs.
Use with care. Defaults to `false`.
:param pulumi.Input['AuthorityKeySpecArgs'] key_spec: Used when issuing certificates for this CertificateAuthority. If this CertificateAuthority
is a self-signed CertificateAuthority, this key is also used to sign the self-signed CA
certificate. Otherwise, it is used to sign a CSR.
Structure is documented below.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] labels: Labels with user-defined metadata.
An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass":
"1.3kg", "count": "3" }.
:param pulumi.Input[str] lifetime: The desired lifetime of the CA certificate. Used to create the "notBeforeTime" and
"notAfterTime" fields inside an X.509 certificate. A duration in seconds with up to nine
fractional digits, terminated by 's'. Example: "3.5s".
:param pulumi.Input[str] location: Location of the CertificateAuthority. A full list of valid locations can be found by
running `gcloud privateca locations list`.
:param pulumi.Input[str] name: The resource name for this CertificateAuthority in the format projects/*/locations/*/certificateAuthorities/*.
:param pulumi.Input[Sequence[pulumi.Input[str]]] pem_ca_certificates: This CertificateAuthority's certificate chain, including the current CertificateAuthority's certificate. Ordered such
that the root issuer is the final element (consistent with RFC 5246). For a self-signed CA, this will only list the
current CertificateAuthority's certificate.
:param pulumi.Input[str] pool: The name of the CaPool this Certificate Authority belongs to.
:param pulumi.Input[str] project: The ID of the project in which the resource belongs.
If it is not provided, the provider project is used.
:param pulumi.Input[str] state: The State for this CertificateAuthority.
:param pulumi.Input[str] type: The Type of this CertificateAuthority.
> **Note:** For `SUBORDINATE` Certificate Authorities, they need to
be manually activated (via Cloud Console of `gcloud`) before they can
issue certificates.
Default value is `SELF_SIGNED`.
Possible values are `SELF_SIGNED` and `SUBORDINATE`.
:param pulumi.Input[str] update_time: The time at which this CertificateAuthority was updated. A timestamp in RFC3339 UTC "Zulu" format, with nanosecond
resolution and up to nine fractional digits. Examples: "2014-10-02T15:01:23Z" and "2014-10-02T15:01:23.045123456Z".
"""
if access_urls is not None:
pulumi.set(__self__, "access_urls", access_urls)
if certificate_authority_id is not None:
pulumi.set(__self__, "certificate_authority_id", certificate_authority_id)
if config is not None:
pulumi.set(__self__, "config", config)
if create_time is not None:
pulumi.set(__self__, "create_time", create_time)
if gcs_bucket is not None:
pulumi.set(__self__, "gcs_bucket", gcs_bucket)
if ignore_active_certificates_on_deletion is not None:
pulumi.set(__self__, "ignore_active_certificates_on_deletion", ignore_active_certificates_on_deletion)
if key_spec is not None:
pulumi.set(__self__, "key_spec", key_spec)
if labels is not None:
pulumi.set(__self__, "labels", labels)
if lifetime is not None:
pulumi.set(__self__, "lifetime", lifetime)
if location is not None:
pulumi.set(__self__, "location", location)
if name is not None:
pulumi.set(__self__, "name", name)
if pem_ca_certificates is not None:
pulumi.set(__self__, "pem_ca_certificates", pem_ca_certificates)
if pool is not None:
pulumi.set(__self__, "pool", pool)
if project is not None:
pulumi.set(__self__, "project", project)
if state is not None:
pulumi.set(__self__, "state", state)
if type is not None:
pulumi.set(__self__, "type", type)
if update_time is not None:
pulumi.set(__self__, "update_time", update_time)
@property
@pulumi.getter(name="accessUrls")
def access_urls(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['AuthorityAccessUrlArgs']]]]:
"""
URLs for accessing content published by this CA, such as the CA certificate and CRLs.
"""
return pulumi.get(self, "access_urls")
@access_urls.setter
def access_urls(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['AuthorityAccessUrlArgs']]]]):
pulumi.set(self, "access_urls", value)
@property
@pulumi.getter(name="certificateAuthorityId")
def certificate_authority_id(self) -> Optional[pulumi.Input[str]]:
"""
The user provided Resource ID for this Certificate Authority.
"""
return pulumi.get(self, "certificate_authority_id")
@certificate_authority_id.setter
def certificate_authority_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "certificate_authority_id", value)
@property
@pulumi.getter
def config(self) -> Optional[pulumi.Input['AuthorityConfigArgs']]:
"""
The config used to create a self-signed X.509 certificate or CSR.
Structure is documented below.
"""
return pulumi.get(self, "config")
@config.setter
def config(self, value: Optional[pulumi.Input['AuthorityConfigArgs']]):
pulumi.set(self, "config", value)
@property
@pulumi.getter(name="createTime")
def create_time(self) -> Optional[pulumi.Input[str]]:
"""
The time at which this CertificateAuthority was created. A timestamp in RFC3339 UTC "Zulu" format, with nanosecond
resolution and up to nine fractional digits. Examples: "2014-10-02T15:01:23Z" and "2014-10-02T15:01:23.045123456Z".
"""
return pulumi.get(self, "create_time")
@create_time.setter
def create_time(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "create_time", value)
@property
@pulumi.getter(name="gcsBucket")
def gcs_bucket(self) -> Optional[pulumi.Input[str]]:
"""
The name of a Cloud Storage bucket where this CertificateAuthority will publish content,
such as the CA certificate and CRLs. This must be a bucket name, without any prefixes
(such as `gs://`) or suffixes (such as `.googleapis.com`). For example, to use a bucket named
my-bucket, you would simply specify `my-bucket`. If not specified, a managed bucket will be
created.
"""
return pulumi.get(self, "gcs_bucket")
@gcs_bucket.setter
def gcs_bucket(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "gcs_bucket", value)
@property
@pulumi.getter(name="ignoreActiveCertificatesOnDeletion")
def ignore_active_certificates_on_deletion(self) -> Optional[pulumi.Input[bool]]:
"""
This field allows the CA to be deleted even if the CA has active certs. Active certs include both unrevoked and unexpired certs.
Use with care. Defaults to `false`.
"""
return pulumi.get(self, "ignore_active_certificates_on_deletion")
@ignore_active_certificates_on_deletion.setter
def ignore_active_certificates_on_deletion(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "ignore_active_certificates_on_deletion", value)
@property
@pulumi.getter(name="keySpec")
def key_spec(self) -> Optional[pulumi.Input['AuthorityKeySpecArgs']]:
"""
Used when issuing certificates for this CertificateAuthority. If this CertificateAuthority
is a self-signed CertificateAuthority, this key is also used to sign the self-signed CA
certificate. Otherwise, it is used to sign a CSR.
Structure is documented below.
"""
return pulumi.get(self, "key_spec")
@key_spec.setter
def key_spec(self, value: Optional[pulumi.Input['AuthorityKeySpecArgs']]):
pulumi.set(self, "key_spec", value)
@property
@pulumi.getter
def labels(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]:
"""
Labels with user-defined metadata.
An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass":
"1.3kg", "count": "3" }.
"""
return pulumi.get(self, "labels")
@labels.setter
def labels(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]):
pulumi.set(self, "labels", value)
@property
@pulumi.getter
def lifetime(self) -> Optional[pulumi.Input[str]]:
"""
The desired lifetime of the CA certificate. Used to create the "notBeforeTime" and
"notAfterTime" fields inside an X.509 certificate. A duration in seconds with up to nine
fractional digits, terminated by 's'. Example: "3.5s".
"""
return pulumi.get(self, "lifetime")
@lifetime.setter
def lifetime(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "lifetime", value)
@property
@pulumi.getter
def location(self) -> Optional[pulumi.Input[str]]:
"""
Location of the CertificateAuthority. A full list of valid locations can be found by
running `gcloud privateca locations list`.
"""
return pulumi.get(self, "location")
@location.setter
def location(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "location", value)
@property
@pulumi.getter
def name(self) -> Optional[pulumi.Input[str]]:
"""
The resource name for this CertificateAuthority in the format projects/*/locations/*/certificateAuthorities/*.
"""
return pulumi.get(self, "name")
@name.setter
def name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "name", value)
@property
@pulumi.getter(name="pemCaCertificates")
def pem_ca_certificates(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
"""
This CertificateAuthority's certificate chain, including the current CertificateAuthority's certificate. Ordered such
that the root issuer is the final element (consistent with RFC 5246). For a self-signed CA, this will only list the
current CertificateAuthority's certificate.
"""
return pulumi.get(self, "pem_ca_certificates")
@pem_ca_certificates.setter
def pem_ca_certificates(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]):
pulumi.set(self, "pem_ca_certificates", value)
@property
@pulumi.getter
def pool(self) -> Optional[pulumi.Input[str]]:
"""
The name of the CaPool this Certificate Authority belongs to.
"""
return pulumi.get(self, "pool")
@pool.setter
def pool(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "pool", value)
@property
@pulumi.getter
def project(self) -> Optional[pulumi.Input[str]]:
"""
The ID of the project in which the resource belongs.
If it is not provided, the provider project is used.
"""
return pulumi.get(self, "project")
@project.setter
def project(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "project", value)
@property
@pulumi.getter
def state(self) -> Optional[pulumi.Input[str]]:
"""
The State for this CertificateAuthority.
"""
return pulumi.get(self, "state")
@state.setter
def state(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "state", value)
@property
@pulumi.getter
def type(self) -> Optional[pulumi.Input[str]]:
"""
The Type of this CertificateAuthority.
> **Note:** For `SUBORDINATE` Certificate Authorities, they need to
be manually activated (via Cloud Console of `gcloud`) before they can
issue certificates.
Default value is `SELF_SIGNED`.
Possible values are `SELF_SIGNED` and `SUBORDINATE`.
"""
return pulumi.get(self, "type")
@type.setter
def type(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "type", value)
@property
@pulumi.getter(name="updateTime")
def update_time(self) -> Optional[pulumi.Input[str]]:
"""
The time at which this CertificateAuthority was updated. A timestamp in RFC3339 UTC "Zulu" format, with nanosecond
resolution and up to nine fractional digits. Examples: "2014-10-02T15:01:23Z" and "2014-10-02T15:01:23.045123456Z".
"""
return pulumi.get(self, "update_time")
@update_time.setter
def update_time(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "update_time", value)
class Authority(pulumi.CustomResource):
@overload
def __init__(__self__,
resource_name: str,
opts: Optional[pulumi.ResourceOptions] = None,
certificate_authority_id: Optional[pulumi.Input[str]] = None,
config: Optional[pulumi.Input[pulumi.InputType['AuthorityConfigArgs']]] = None,
gcs_bucket: Optional[pulumi.Input[str]] = None,
ignore_active_certificates_on_deletion: Optional[pulumi.Input[bool]] = None,
key_spec: Optional[pulumi.Input[pulumi.InputType['AuthorityKeySpecArgs']]] = None,
labels: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,
lifetime: Optional[pulumi.Input[str]] = None,
location: Optional[pulumi.Input[str]] = None,
pool: Optional[pulumi.Input[str]] = None,
project: Optional[pulumi.Input[str]] = None,
type: Optional[pulumi.Input[str]] = None,
__props__=None):
"""
A CertificateAuthority represents an individual Certificate Authority. A
CertificateAuthority can be used to create Certificates.
To get more information about CertificateAuthority, see:
* [API documentation](https://cloud.google.com/certificate-authority-service/docs/reference/rest)
* How-to Guides
* [Official Documentation](https://cloud.google.com/certificate-authority-service)
## Example Usage
### Privateca Certificate Authority Basic
```python
import pulumi
import pulumi_gcp as gcp
default = gcp.certificateauthority.Authority("default",
certificate_authority_id="my-certificate-authority",
config=gcp.certificateauthority.AuthorityConfigArgs(
subject_config=gcp.certificateauthority.AuthorityConfigSubjectConfigArgs(
subject=gcp.certificateauthority.AuthorityConfigSubjectConfigSubjectArgs(
common_name="my-certificate-authority",
organization="HashiCorp",
),
subject_alt_name=gcp.certificateauthority.AuthorityConfigSubjectConfigSubjectAltNameArgs(
dns_names=["hashicorp.com"],
),
),
x509_config=gcp.certificateauthority.AuthorityConfigX509ConfigArgs(
ca_options=gcp.certificateauthority.AuthorityConfigX509ConfigCaOptionsArgs(
is_ca=True,
max_issuer_path_length=10,
),
key_usage=gcp.certificateauthority.AuthorityConfigX509ConfigKeyUsageArgs(
base_key_usage=gcp.certificateauthority.AuthorityConfigX509ConfigKeyUsageBaseKeyUsageArgs(
cert_sign=True,
content_commitment=True,
crl_sign=True,
data_encipherment=True,
decipher_only=True,
digital_signature=True,
key_agreement=True,
key_encipherment=False,
),
extended_key_usage=gcp.certificateauthority.AuthorityConfigX509ConfigKeyUsageExtendedKeyUsageArgs(
client_auth=False,
code_signing=True,
email_protection=True,
server_auth=True,
time_stamping=True,
),
),
),
),
key_spec=gcp.certificateauthority.AuthorityKeySpecArgs(
algorithm="RSA_PKCS1_4096_SHA256",
),
lifetime="86400s",
location="us-central1",
pool="ca-pool")
```
### Privateca Certificate Authority Subordinate
```python
import pulumi
import pulumi_gcp as gcp
default = gcp.certificateauthority.Authority("default",
certificate_authority_id="my-certificate-authority",
config=gcp.certificateauthority.AuthorityConfigArgs(
subject_config=gcp.certificateauthority.AuthorityConfigSubjectConfigArgs(
subject=gcp.certificateauthority.AuthorityConfigSubjectConfigSubjectArgs(
common_name="my-subordinate-authority",
organization="HashiCorp",
),
subject_alt_name=gcp.certificateauthority.AuthorityConfigSubjectConfigSubjectAltNameArgs(
dns_names=["hashicorp.com"],
),
),
x509_config=gcp.certificateauthority.AuthorityConfigX509ConfigArgs(
ca_options=gcp.certificateauthority.AuthorityConfigX509ConfigCaOptionsArgs(
is_ca=True,
max_issuer_path_length=0,
),
key_usage=gcp.certificateauthority.AuthorityConfigX509ConfigKeyUsageArgs(
base_key_usage=gcp.certificateauthority.AuthorityConfigX509ConfigKeyUsageBaseKeyUsageArgs(
cert_sign=True,
content_commitment=True,
crl_sign=True,
data_encipherment=True,
decipher_only=True,
digital_signature=True,
key_agreement=True,
key_encipherment=False,
),
extended_key_usage=gcp.certificateauthority.AuthorityConfigX509ConfigKeyUsageExtendedKeyUsageArgs(
client_auth=False,
code_signing=True,
email_protection=True,
server_auth=True,
time_stamping=True,
),
),
),
),
key_spec=gcp.certificateauthority.AuthorityKeySpecArgs(
algorithm="RSA_PKCS1_4096_SHA256",
),
lifetime="86400s",
location="us-central1",
pool="ca-pool",
type="SUBORDINATE")
```
### Privateca Certificate Authority Byo Key
```python
import pulumi
import pulumi_gcp as gcp
privateca_sa = gcp.projects.ServiceIdentity("privatecaSa", service="privateca.googleapis.com")
privateca_sa_keyuser_signerverifier = gcp.kms.CryptoKeyIAMBinding("privatecaSaKeyuserSignerverifier",
crypto_key_id="projects/keys-project/locations/us-central1/keyRings/key-ring/cryptoKeys/crypto-key",
role="roles/cloudkms.signerVerifier",
members=[privateca_sa.email.apply(lambda email: f"serviceAccount:{email}")])
privateca_sa_keyuser_viewer = gcp.kms.CryptoKeyIAMBinding("privatecaSaKeyuserViewer",
crypto_key_id="projects/keys-project/locations/us-central1/keyRings/key-ring/cryptoKeys/crypto-key",
role="roles/viewer",
members=[privateca_sa.email.apply(lambda email: f"serviceAccount:{email}")])
default = gcp.certificateauthority.Authority("default",
pool="ca-pool",
certificate_authority_id="my-certificate-authority",
location="us-central1",
key_spec=gcp.certificateauthority.AuthorityKeySpecArgs(
cloud_kms_key_version="projects/keys-project/locations/us-central1/keyRings/key-ring/cryptoKeys/crypto-key/cryptoKeyVersions/1",
),
config=gcp.certificateauthority.AuthorityConfigArgs(
subject_config=gcp.certificateauthority.AuthorityConfigSubjectConfigArgs(
subject=gcp.certificateauthority.AuthorityConfigSubjectConfigSubjectArgs(
organization="Example, Org.",
common_name="Example Authority",
),
),
x509_config=gcp.certificateauthority.AuthorityConfigX509ConfigArgs(
ca_options=gcp.certificateauthority.AuthorityConfigX509ConfigCaOptionsArgs(
is_ca=True,
max_issuer_path_length=10,
),
key_usage=gcp.certificateauthority.AuthorityConfigX509ConfigKeyUsageArgs(
base_key_usage=gcp.certificateauthority.AuthorityConfigX509ConfigKeyUsageBaseKeyUsageArgs(
cert_sign=True,
crl_sign=True,
),
extended_key_usage=gcp.certificateauthority.AuthorityConfigX509ConfigKeyUsageExtendedKeyUsageArgs(
server_auth=False,
),
),
),
),
opts=pulumi.ResourceOptions(depends_on=[
privateca_sa_keyuser_signerverifier,
privateca_sa_keyuser_viewer,
]))
```
## Import
CertificateAuthority can be imported using any of these accepted formats
```sh
$ pulumi import gcp:certificateauthority/authority:Authority default projects/{{project}}/locations/{{location}}/caPools/{{pool}}/certificateAuthorities/{{certificate_authority_id}}
```
```sh
$ pulumi import gcp:certificateauthority/authority:Authority default {{project}}/{{location}}/{{pool}}/{{certificate_authority_id}}
```
```sh
$ pulumi import gcp:certificateauthority/authority:Authority default {{location}}/{{pool}}/{{certificate_authority_id}}
```
:param str resource_name: The name of the resource.
:param pulumi.ResourceOptions opts: Options for the resource.
:param pulumi.Input[str] certificate_authority_id: The user provided Resource ID for this Certificate Authority.
:param pulumi.Input[pulumi.InputType['AuthorityConfigArgs']] config: The config used to create a self-signed X.509 certificate or CSR.
Structure is documented below.
:param pulumi.Input[str] gcs_bucket: The name of a Cloud Storage bucket where this CertificateAuthority will publish content,
such as the CA certificate and CRLs. This must be a bucket name, without any prefixes
(such as `gs://`) or suffixes (such as `.googleapis.com`). For example, to use a bucket named
my-bucket, you would simply specify `my-bucket`. If not specified, a managed bucket will be
created.
:param pulumi.Input[bool] ignore_active_certificates_on_deletion: This field allows the CA to be deleted even if the CA has active certs. Active certs include both unrevoked and unexpired certs.
Use with care. Defaults to `false`.
:param pulumi.Input[pulumi.InputType['AuthorityKeySpecArgs']] key_spec: Used when issuing certificates for this CertificateAuthority. If this CertificateAuthority
is a self-signed CertificateAuthority, this key is also used to sign the self-signed CA
certificate. Otherwise, it is used to sign a CSR.
Structure is documented below.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] labels: Labels with user-defined metadata.
An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass":
"1.3kg", "count": "3" }.
:param pulumi.Input[str] lifetime: The desired lifetime of the CA certificate. Used to create the "notBeforeTime" and
"notAfterTime" fields inside an X.509 certificate. A duration in seconds with up to nine
fractional digits, terminated by 's'. Example: "3.5s".
:param pulumi.Input[str] location: Location of the CertificateAuthority. A full list of valid locations can be found by
running `gcloud privateca locations list`.
:param pulumi.Input[str] pool: The name of the CaPool this Certificate Authority belongs to.
:param pulumi.Input[str] project: The ID of the project in which the resource belongs.
If it is not provided, the provider project is used.
:param pulumi.Input[str] type: The Type of this CertificateAuthority.
> **Note:** For `SUBORDINATE` Certificate Authorities, they need to
be manually activated (via Cloud Console of `gcloud`) before they can
issue certificates.
Default value is `SELF_SIGNED`.
Possible values are `SELF_SIGNED` and `SUBORDINATE`.
"""
...
@overload
def __init__(__self__,
resource_name: str,
args: AuthorityArgs,
opts: Optional[pulumi.ResourceOptions] = None):
"""
A CertificateAuthority represents an individual Certificate Authority. A
CertificateAuthority can be used to create Certificates.
To get more information about CertificateAuthority, see:
* [API documentation](https://cloud.google.com/certificate-authority-service/docs/reference/rest)
* How-to Guides
* [Official Documentation](https://cloud.google.com/certificate-authority-service)
## Example Usage
### Privateca Certificate Authority Basic
```python
import pulumi
import pulumi_gcp as gcp
default = gcp.certificateauthority.Authority("default",
certificate_authority_id="my-certificate-authority",
config=gcp.certificateauthority.AuthorityConfigArgs(
subject_config=gcp.certificateauthority.AuthorityConfigSubjectConfigArgs(
subject=gcp.certificateauthority.AuthorityConfigSubjectConfigSubjectArgs(
common_name="my-certificate-authority",
organization="HashiCorp",
),
subject_alt_name=gcp.certificateauthority.AuthorityConfigSubjectConfigSubjectAltNameArgs(
dns_names=["hashicorp.com"],
),
),
x509_config=gcp.certificateauthority.AuthorityConfigX509ConfigArgs(
ca_options=gcp.certificateauthority.AuthorityConfigX509ConfigCaOptionsArgs(
is_ca=True,
max_issuer_path_length=10,
),
key_usage=gcp.certificateauthority.AuthorityConfigX509ConfigKeyUsageArgs(
base_key_usage=gcp.certificateauthority.AuthorityConfigX509ConfigKeyUsageBaseKeyUsageArgs(
cert_sign=True,
content_commitment=True,
crl_sign=True,
data_encipherment=True,
decipher_only=True,
digital_signature=True,
key_agreement=True,
key_encipherment=False,
),
extended_key_usage=gcp.certificateauthority.AuthorityConfigX509ConfigKeyUsageExtendedKeyUsageArgs(
client_auth=False,
code_signing=True,
email_protection=True,
server_auth=True,
time_stamping=True,
),
),
),
),
key_spec=gcp.certificateauthority.AuthorityKeySpecArgs(
algorithm="RSA_PKCS1_4096_SHA256",
),
lifetime="86400s",
location="us-central1",
pool="ca-pool")
```
### Privateca Certificate Authority Subordinate
```python
import pulumi
import pulumi_gcp as gcp
default = gcp.certificateauthority.Authority("default",
certificate_authority_id="my-certificate-authority",
config=gcp.certificateauthority.AuthorityConfigArgs(
subject_config=gcp.certificateauthority.AuthorityConfigSubjectConfigArgs(
subject=gcp.certificateauthority.AuthorityConfigSubjectConfigSubjectArgs(
common_name="my-subordinate-authority",
organization="HashiCorp",
),
subject_alt_name=gcp.certificateauthority.AuthorityConfigSubjectConfigSubjectAltNameArgs(
dns_names=["hashicorp.com"],
),
),
x509_config=gcp.certificateauthority.AuthorityConfigX509ConfigArgs(
ca_options=gcp.certificateauthority.AuthorityConfigX509ConfigCaOptionsArgs(
is_ca=True,
max_issuer_path_length=0,
),
key_usage=gcp.certificateauthority.AuthorityConfigX509ConfigKeyUsageArgs(
base_key_usage=gcp.certificateauthority.AuthorityConfigX509ConfigKeyUsageBaseKeyUsageArgs(
cert_sign=True,
content_commitment=True,
crl_sign=True,
data_encipherment=True,
decipher_only=True,
digital_signature=True,
key_agreement=True,
key_encipherment=False,
),
extended_key_usage=gcp.certificateauthority.AuthorityConfigX509ConfigKeyUsageExtendedKeyUsageArgs(
client_auth=False,
code_signing=True,
email_protection=True,
server_auth=True,
time_stamping=True,
),
),
),
),
key_spec=gcp.certificateauthority.AuthorityKeySpecArgs(
algorithm="RSA_PKCS1_4096_SHA256",
),
lifetime="86400s",
location="us-central1",
pool="ca-pool",
type="SUBORDINATE")
```
### Privateca Certificate Authority Byo Key
```python
import pulumi
import pulumi_gcp as gcp
privateca_sa = gcp.projects.ServiceIdentity("privatecaSa", service="privateca.googleapis.com")
privateca_sa_keyuser_signerverifier = gcp.kms.CryptoKeyIAMBinding("privatecaSaKeyuserSignerverifier",
crypto_key_id="projects/keys-project/locations/us-central1/keyRings/key-ring/cryptoKeys/crypto-key",
role="roles/cloudkms.signerVerifier",
members=[privateca_sa.email.apply(lambda email: f"serviceAccount:{email}")])
privateca_sa_keyuser_viewer = gcp.kms.CryptoKeyIAMBinding("privatecaSaKeyuserViewer",
crypto_key_id="projects/keys-project/locations/us-central1/keyRings/key-ring/cryptoKeys/crypto-key",
role="roles/viewer",
members=[privateca_sa.email.apply(lambda email: f"serviceAccount:{email}")])
default = gcp.certificateauthority.Authority("default",
pool="ca-pool",
certificate_authority_id="my-certificate-authority",
location="us-central1",
key_spec=gcp.certificateauthority.AuthorityKeySpecArgs(
cloud_kms_key_version="projects/keys-project/locations/us-central1/keyRings/key-ring/cryptoKeys/crypto-key/cryptoKeyVersions/1",
),
config=gcp.certificateauthority.AuthorityConfigArgs(
subject_config=gcp.certificateauthority.AuthorityConfigSubjectConfigArgs(
subject=gcp.certificateauthority.AuthorityConfigSubjectConfigSubjectArgs(
organization="Example, Org.",
common_name="Example Authority",
),
),
x509_config=gcp.certificateauthority.AuthorityConfigX509ConfigArgs(
ca_options=gcp.certificateauthority.AuthorityConfigX509ConfigCaOptionsArgs(
is_ca=True,
max_issuer_path_length=10,
),
key_usage=gcp.certificateauthority.AuthorityConfigX509ConfigKeyUsageArgs(
base_key_usage=gcp.certificateauthority.AuthorityConfigX509ConfigKeyUsageBaseKeyUsageArgs(
cert_sign=True,
crl_sign=True,
),
extended_key_usage=gcp.certificateauthority.AuthorityConfigX509ConfigKeyUsageExtendedKeyUsageArgs(
server_auth=False,
),
),
),
),
opts=pulumi.ResourceOptions(depends_on=[
privateca_sa_keyuser_signerverifier,
privateca_sa_keyuser_viewer,
]))
```
## Import
CertificateAuthority can be imported using any of these accepted formats
```sh
$ pulumi import gcp:certificateauthority/authority:Authority default projects/{{project}}/locations/{{location}}/caPools/{{pool}}/certificateAuthorities/{{certificate_authority_id}}
```
```sh
$ pulumi import gcp:certificateauthority/authority:Authority default {{project}}/{{location}}/{{pool}}/{{certificate_authority_id}}
```
```sh
$ pulumi import gcp:certificateauthority/authority:Authority default {{location}}/{{pool}}/{{certificate_authority_id}}
```
:param str resource_name: The name of the resource.
:param AuthorityArgs args: The arguments to use to populate this resource's properties.
:param pulumi.ResourceOptions opts: Options for the resource.
"""
...
def __init__(__self__, resource_name: str, *args, **kwargs):
resource_args, opts = _utilities.get_resource_args_opts(AuthorityArgs, pulumi.ResourceOptions, *args, **kwargs)
if resource_args is not None:
__self__._internal_init(resource_name, opts, **resource_args.__dict__)
else:
__self__._internal_init(resource_name, *args, **kwargs)
def _internal_init(__self__,
resource_name: str,
opts: Optional[pulumi.ResourceOptions] = None,
certificate_authority_id: Optional[pulumi.Input[str]] = None,
config: Optional[pulumi.Input[pulumi.InputType['AuthorityConfigArgs']]] = None,
gcs_bucket: Optional[pulumi.Input[str]] = None,
ignore_active_certificates_on_deletion: Optional[pulumi.Input[bool]] = None,
key_spec: Optional[pulumi.Input[pulumi.InputType['AuthorityKeySpecArgs']]] = None,
labels: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,
lifetime: Optional[pulumi.Input[str]] = None,
location: Optional[pulumi.Input[str]] = None,
pool: Optional[pulumi.Input[str]] = None,
project: Optional[pulumi.Input[str]] = None,
type: Optional[pulumi.Input[str]] = None,
__props__=None):
if opts is None:
opts = pulumi.ResourceOptions()
if not isinstance(opts, pulumi.ResourceOptions):
raise TypeError('Expected resource options to be a ResourceOptions instance')
if opts.version is None:
opts.version = _utilities.get_version()
if opts.id is None:
if __props__ is not None:
raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource')
__props__ = AuthorityArgs.__new__(AuthorityArgs)
if certificate_authority_id is None and not opts.urn:
raise TypeError("Missing required property 'certificate_authority_id'")
__props__.__dict__["certificate_authority_id"] = certificate_authority_id
if config is None and not opts.urn:
raise TypeError("Missing required property 'config'")
__props__.__dict__["config"] = config
__props__.__dict__["gcs_bucket"] = gcs_bucket
__props__.__dict__["ignore_active_certificates_on_deletion"] = ignore_active_certificates_on_deletion
if key_spec is None and not opts.urn:
raise TypeError("Missing required property 'key_spec'")
__props__.__dict__["key_spec"] = key_spec
__props__.__dict__["labels"] = labels
__props__.__dict__["lifetime"] = lifetime
if location is None and not opts.urn:
raise TypeError("Missing required property 'location'")
__props__.__dict__["location"] = location
if pool is None and not opts.urn:
raise TypeError("Missing required property 'pool'")
__props__.__dict__["pool"] = pool
__props__.__dict__["project"] = project
__props__.__dict__["type"] = type
__props__.__dict__["access_urls"] = None
__props__.__dict__["create_time"] = None
__props__.__dict__["name"] = None
__props__.__dict__["pem_ca_certificates"] = None
__props__.__dict__["state"] = None
__props__.__dict__["update_time"] = None
super(Authority, __self__).__init__(
'gcp:certificateauthority/authority:Authority',
resource_name,
__props__,
opts)
@staticmethod
def get(resource_name: str,
id: pulumi.Input[str],
opts: Optional[pulumi.ResourceOptions] = None,
access_urls: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['AuthorityAccessUrlArgs']]]]] = None,
certificate_authority_id: Optional[pulumi.Input[str]] = None,
config: Optional[pulumi.Input[pulumi.InputType['AuthorityConfigArgs']]] = None,
create_time: Optional[pulumi.Input[str]] = None,
gcs_bucket: Optional[pulumi.Input[str]] = None,
ignore_active_certificates_on_deletion: Optional[pulumi.Input[bool]] = None,
key_spec: Optional[pulumi.Input[pulumi.InputType['AuthorityKeySpecArgs']]] = None,
labels: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,
lifetime: Optional[pulumi.Input[str]] = None,
location: Optional[pulumi.Input[str]] = None,
name: Optional[pulumi.Input[str]] = None,
pem_ca_certificates: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
pool: Optional[pulumi.Input[str]] = None,
project: Optional[pulumi.Input[str]] = None,
state: Optional[pulumi.Input[str]] = None,
type: Optional[pulumi.Input[str]] = None,
update_time: Optional[pulumi.Input[str]] = None) -> 'Authority':
"""
Get an existing Authority resource's state with the given name, id, and optional extra
properties used to qualify the lookup.
:param str resource_name: The unique name of the resulting resource.
:param pulumi.Input[str] id: The unique provider ID of the resource to lookup.
:param pulumi.ResourceOptions opts: Options for the resource.
:param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['AuthorityAccessUrlArgs']]]] access_urls: URLs for accessing content published by this CA, such as the CA certificate and CRLs.
:param pulumi.Input[str] certificate_authority_id: The user provided Resource ID for this Certificate Authority.
:param pulumi.Input[pulumi.InputType['AuthorityConfigArgs']] config: The config used to create a self-signed X.509 certificate or CSR.
Structure is documented below.
:param pulumi.Input[str] create_time: The time at which this CertificateAuthority was created. A timestamp in RFC3339 UTC "Zulu" format, with nanosecond
resolution and up to nine fractional digits. Examples: "2014-10-02T15:01:23Z" and "2014-10-02T15:01:23.045123456Z".
:param pulumi.Input[str] gcs_bucket: The name of a Cloud Storage bucket where this CertificateAuthority will publish content,
such as the CA certificate and CRLs. This must be a bucket name, without any prefixes
(such as `gs://`) or suffixes (such as `.googleapis.com`). For example, to use a bucket named
my-bucket, you would simply specify `my-bucket`. If not specified, a managed bucket will be
created.
:param pulumi.Input[bool] ignore_active_certificates_on_deletion: This field allows the CA to be deleted even if the CA has active certs. Active certs include both unrevoked and unexpired certs.
Use with care. Defaults to `false`.
:param pulumi.Input[pulumi.InputType['AuthorityKeySpecArgs']] key_spec: Used when issuing certificates for this CertificateAuthority. If this CertificateAuthority
is a self-signed CertificateAuthority, this key is also used to sign the self-signed CA
certificate. Otherwise, it is used to sign a CSR.
Structure is documented below.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] labels: Labels with user-defined metadata.
An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass":
"1.3kg", "count": "3" }.
:param pulumi.Input[str] lifetime: The desired lifetime of the CA certificate. Used to create the "notBeforeTime" and
"notAfterTime" fields inside an X.509 certificate. A duration in seconds with up to nine
fractional digits, terminated by 's'. Example: "3.5s".
:param pulumi.Input[str] location: Location of the CertificateAuthority. A full list of valid locations can be found by
running `gcloud privateca locations list`.
:param pulumi.Input[str] name: The resource name for this CertificateAuthority in the format projects/*/locations/*/certificateAuthorities/*.
:param pulumi.Input[Sequence[pulumi.Input[str]]] pem_ca_certificates: This CertificateAuthority's certificate chain, including the current CertificateAuthority's certificate. Ordered such
that the root issuer is the final element (consistent with RFC 5246). For a self-signed CA, this will only list the
current CertificateAuthority's certificate.
:param pulumi.Input[str] pool: The name of the CaPool this Certificate Authority belongs to.
:param pulumi.Input[str] project: The ID of the project in which the resource belongs.
If it is not provided, the provider project is used.
:param pulumi.Input[str] state: The State for this CertificateAuthority.
:param pulumi.Input[str] type: The Type of this CertificateAuthority.
> **Note:** For `SUBORDINATE` Certificate Authorities, they need to
be manually activated (via Cloud Console of `gcloud`) before they can
issue certificates.
Default value is `SELF_SIGNED`.
Possible values are `SELF_SIGNED` and `SUBORDINATE`.
:param pulumi.Input[str] update_time: The time at which this CertificateAuthority was updated. A timestamp in RFC3339 UTC "Zulu" format, with nanosecond
resolution and up to nine fractional digits. Examples: "2014-10-02T15:01:23Z" and "2014-10-02T15:01:23.045123456Z".
"""
opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id))
__props__ = _AuthorityState.__new__(_AuthorityState)
__props__.__dict__["access_urls"] = access_urls
__props__.__dict__["certificate_authority_id"] = certificate_authority_id
__props__.__dict__["config"] = config
__props__.__dict__["create_time"] = create_time
__props__.__dict__["gcs_bucket"] = gcs_bucket
__props__.__dict__["ignore_active_certificates_on_deletion"] = ignore_active_certificates_on_deletion
__props__.__dict__["key_spec"] = key_spec
__props__.__dict__["labels"] = labels
__props__.__dict__["lifetime"] = lifetime
__props__.__dict__["location"] = location
__props__.__dict__["name"] = name
__props__.__dict__["pem_ca_certificates"] = pem_ca_certificates
__props__.__dict__["pool"] = pool
__props__.__dict__["project"] = project
__props__.__dict__["state"] = state
__props__.__dict__["type"] = type
__props__.__dict__["update_time"] = update_time
return Authority(resource_name, opts=opts, __props__=__props__)
@property
@pulumi.getter(name="accessUrls")
def access_urls(self) -> pulumi.Output[Sequence['outputs.AuthorityAccessUrl']]:
"""
URLs for accessing content published by this CA, such as the CA certificate and CRLs.
"""
return pulumi.get(self, "access_urls")
@property
@pulumi.getter(name="certificateAuthorityId")
def certificate_authority_id(self) -> pulumi.Output[str]:
"""
The user provided Resource ID for this Certificate Authority.
"""
return pulumi.get(self, "certificate_authority_id")
@property
@pulumi.getter
def config(self) -> pulumi.Output['outputs.AuthorityConfig']:
"""
The config used to create a self-signed X.509 certificate or CSR.
Structure is documented below.
"""
return pulumi.get(self, "config")
@property
@pulumi.getter(name="createTime")
def create_time(self) -> pulumi.Output[str]:
"""
The time at which this CertificateAuthority was created. A timestamp in RFC3339 UTC "Zulu" format, with nanosecond
resolution and up to nine fractional digits. Examples: "2014-10-02T15:01:23Z" and "2014-10-02T15:01:23.045123456Z".
"""
return pulumi.get(self, "create_time")
@property
@pulumi.getter(name="gcsBucket")
def gcs_bucket(self) -> pulumi.Output[Optional[str]]:
"""
The name of a Cloud Storage bucket where this CertificateAuthority will publish content,
such as the CA certificate and CRLs. This must be a bucket name, without any prefixes
(such as `gs://`) or suffixes (such as `.googleapis.com`). For example, to use a bucket named
my-bucket, you would simply specify `my-bucket`. If not specified, a managed bucket will be
created.
"""
return pulumi.get(self, "gcs_bucket")
@property
@pulumi.getter(name="ignoreActiveCertificatesOnDeletion")
def ignore_active_certificates_on_deletion(self) -> pulumi.Output[Optional[bool]]:
"""
This field allows the CA to be deleted even if the CA has active certs. Active certs include both unrevoked and unexpired certs.
Use with care. Defaults to `false`.
"""
return pulumi.get(self, "ignore_active_certificates_on_deletion")
@property
@pulumi.getter(name="keySpec")
def key_spec(self) -> pulumi.Output['outputs.AuthorityKeySpec']:
"""
Used when issuing certificates for this CertificateAuthority. If this CertificateAuthority
is a self-signed CertificateAuthority, this key is also used to sign the self-signed CA
certificate. Otherwise, it is used to sign a CSR.
Structure is documented below.
"""
return pulumi.get(self, "key_spec")
@property
@pulumi.getter
def labels(self) -> pulumi.Output[Optional[Mapping[str, str]]]:
"""
Labels with user-defined metadata.
An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass":
"1.3kg", "count": "3" }.
"""
return pulumi.get(self, "labels")
@property
@pulumi.getter
def lifetime(self) -> pulumi.Output[Optional[str]]:
"""
The desired lifetime of the CA certificate. Used to create the "notBeforeTime" and
"notAfterTime" fields inside an X.509 certificate. A duration in seconds with up to nine
fractional digits, terminated by 's'. Example: "3.5s".
"""
return pulumi.get(self, "lifetime")
@property
@pulumi.getter
def location(self) -> pulumi.Output[str]:
"""
Location of the CertificateAuthority. A full list of valid locations can be found by
running `gcloud privateca locations list`.
"""
return pulumi.get(self, "location")
@property
@pulumi.getter
def name(self) -> pulumi.Output[str]:
"""
The resource name for this CertificateAuthority in the format projects/*/locations/*/certificateAuthorities/*.
"""
return pulumi.get(self, "name")
@property
@pulumi.getter(name="pemCaCertificates")
def pem_ca_certificates(self) -> pulumi.Output[Sequence[str]]:
"""
This CertificateAuthority's certificate chain, including the current CertificateAuthority's certificate. Ordered such
that the root issuer is the final element (consistent with RFC 5246). For a self-signed CA, this will only list the
current CertificateAuthority's certificate.
"""
return pulumi.get(self, "pem_ca_certificates")
@property
@pulumi.getter
def pool(self) -> pulumi.Output[str]:
"""
The name of the CaPool this Certificate Authority belongs to.
"""
return pulumi.get(self, "pool")
@property
@pulumi.getter
def project(self) -> pulumi.Output[str]:
"""
The ID of the project in which the resource belongs.
If it is not provided, the provider project is used.
"""
return pulumi.get(self, "project")
@property
@pulumi.getter
def state(self) -> pulumi.Output[str]:
"""
The State for this CertificateAuthority.
"""
return pulumi.get(self, "state")
@property
@pulumi.getter
def type(self) -> pulumi.Output[Optional[str]]:
"""
The Type of this CertificateAuthority.
> **Note:** For `SUBORDINATE` Certificate Authorities, they need to
be manually activated (via Cloud Console of `gcloud`) before they can
issue certificates.
Default value is `SELF_SIGNED`.
Possible values are `SELF_SIGNED` and `SUBORDINATE`.
"""
return pulumi.get(self, "type")
@property
@pulumi.getter(name="updateTime")
def update_time(self) -> pulumi.Output[str]:
"""
The time at which this CertificateAuthority was updated. A timestamp in RFC3339 UTC "Zulu" format, with nanosecond
resolution and up to nine fractional digits. Examples: "2014-10-02T15:01:23Z" and "2014-10-02T15:01:23.045123456Z".
"""
return pulumi.get(self, "update_time")
| 50.361686 | 202 | 0.63335 | 7,006 | 65,722 | 5.781188 | 0.057237 | 0.05649 | 0.047009 | 0.038022 | 0.941757 | 0.927117 | 0.908723 | 0.895292 | 0.886305 | 0.871812 | 0 | 0.012743 | 0.276422 | 65,722 | 1,304 | 203 | 50.400307 | 0.838965 | 0.555552 | 0 | 0.684536 | 1 | 0 | 0.114816 | 0.040441 | 0 | 0 | 0 | 0 | 0 | 1 | 0.164948 | false | 0.002062 | 0.014433 | 0 | 0.280412 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
7ee40b5e26936ed1beda4ff941c748c29781b364 | 24,467 | py | Python | sdk/python/pulumi_aws/route53/resolver_firewall_rule_group_association.py | rapzo/pulumi-aws | 390a098221315d98a54ba97d1559e750dc3053b7 | [
"ECL-2.0",
"Apache-2.0"
] | 260 | 2018-06-18T14:57:00.000Z | 2022-03-29T11:41:03.000Z | sdk/python/pulumi_aws/route53/resolver_firewall_rule_group_association.py | rapzo/pulumi-aws | 390a098221315d98a54ba97d1559e750dc3053b7 | [
"ECL-2.0",
"Apache-2.0"
] | 1,154 | 2018-06-19T20:38:20.000Z | 2022-03-31T19:48:16.000Z | sdk/python/pulumi_aws/route53/resolver_firewall_rule_group_association.py | rapzo/pulumi-aws | 390a098221315d98a54ba97d1559e750dc3053b7 | [
"ECL-2.0",
"Apache-2.0"
] | 115 | 2018-06-28T03:20:27.000Z | 2022-03-29T11:41:06.000Z | # coding=utf-8
# *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from .. import _utilities
__all__ = ['ResolverFirewallRuleGroupAssociationArgs', 'ResolverFirewallRuleGroupAssociation']
@pulumi.input_type
class ResolverFirewallRuleGroupAssociationArgs:
def __init__(__self__, *,
firewall_rule_group_id: pulumi.Input[str],
priority: pulumi.Input[int],
vpc_id: pulumi.Input[str],
mutation_protection: Optional[pulumi.Input[str]] = None,
name: Optional[pulumi.Input[str]] = None,
tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None):
"""
The set of arguments for constructing a ResolverFirewallRuleGroupAssociation resource.
:param pulumi.Input[str] firewall_rule_group_id: The unique identifier of the firewall rule group.
:param pulumi.Input[int] priority: The setting that determines the processing order of the rule group among the rule groups that you associate with the specified VPC. DNS Firewall filters VPC traffic starting from the rule group with the lowest numeric priority setting.
:param pulumi.Input[str] vpc_id: The unique identifier of the VPC that you want to associate with the rule group.
:param pulumi.Input[str] mutation_protection: If enabled, this setting disallows modification or removal of the association, to help prevent against accidentally altering DNS firewall protections. Valid values: `ENABLED`, `DISABLED`.
:param pulumi.Input[str] name: A name that lets you identify the rule group association, to manage and use it.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] tags: Key-value map of resource tags. .If configured with a provider `default_tags` configuration block present, tags with matching keys will overwrite those defined at the provider-level.
"""
pulumi.set(__self__, "firewall_rule_group_id", firewall_rule_group_id)
pulumi.set(__self__, "priority", priority)
pulumi.set(__self__, "vpc_id", vpc_id)
if mutation_protection is not None:
pulumi.set(__self__, "mutation_protection", mutation_protection)
if name is not None:
pulumi.set(__self__, "name", name)
if tags is not None:
pulumi.set(__self__, "tags", tags)
@property
@pulumi.getter(name="firewallRuleGroupId")
def firewall_rule_group_id(self) -> pulumi.Input[str]:
"""
The unique identifier of the firewall rule group.
"""
return pulumi.get(self, "firewall_rule_group_id")
@firewall_rule_group_id.setter
def firewall_rule_group_id(self, value: pulumi.Input[str]):
pulumi.set(self, "firewall_rule_group_id", value)
@property
@pulumi.getter
def priority(self) -> pulumi.Input[int]:
"""
The setting that determines the processing order of the rule group among the rule groups that you associate with the specified VPC. DNS Firewall filters VPC traffic starting from the rule group with the lowest numeric priority setting.
"""
return pulumi.get(self, "priority")
@priority.setter
def priority(self, value: pulumi.Input[int]):
pulumi.set(self, "priority", value)
@property
@pulumi.getter(name="vpcId")
def vpc_id(self) -> pulumi.Input[str]:
"""
The unique identifier of the VPC that you want to associate with the rule group.
"""
return pulumi.get(self, "vpc_id")
@vpc_id.setter
def vpc_id(self, value: pulumi.Input[str]):
pulumi.set(self, "vpc_id", value)
@property
@pulumi.getter(name="mutationProtection")
def mutation_protection(self) -> Optional[pulumi.Input[str]]:
"""
If enabled, this setting disallows modification or removal of the association, to help prevent against accidentally altering DNS firewall protections. Valid values: `ENABLED`, `DISABLED`.
"""
return pulumi.get(self, "mutation_protection")
@mutation_protection.setter
def mutation_protection(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "mutation_protection", value)
@property
@pulumi.getter
def name(self) -> Optional[pulumi.Input[str]]:
"""
A name that lets you identify the rule group association, to manage and use it.
"""
return pulumi.get(self, "name")
@name.setter
def name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "name", value)
@property
@pulumi.getter
def tags(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]:
"""
Key-value map of resource tags. .If configured with a provider `default_tags` configuration block present, tags with matching keys will overwrite those defined at the provider-level.
"""
return pulumi.get(self, "tags")
@tags.setter
def tags(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]):
pulumi.set(self, "tags", value)
@pulumi.input_type
class _ResolverFirewallRuleGroupAssociationState:
def __init__(__self__, *,
arn: Optional[pulumi.Input[str]] = None,
firewall_rule_group_id: Optional[pulumi.Input[str]] = None,
mutation_protection: Optional[pulumi.Input[str]] = None,
name: Optional[pulumi.Input[str]] = None,
priority: Optional[pulumi.Input[int]] = None,
tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,
tags_all: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,
vpc_id: Optional[pulumi.Input[str]] = None):
"""
Input properties used for looking up and filtering ResolverFirewallRuleGroupAssociation resources.
:param pulumi.Input[str] arn: The ARN (Amazon Resource Name) of the firewall rule group association.
:param pulumi.Input[str] firewall_rule_group_id: The unique identifier of the firewall rule group.
:param pulumi.Input[str] mutation_protection: If enabled, this setting disallows modification or removal of the association, to help prevent against accidentally altering DNS firewall protections. Valid values: `ENABLED`, `DISABLED`.
:param pulumi.Input[str] name: A name that lets you identify the rule group association, to manage and use it.
:param pulumi.Input[int] priority: The setting that determines the processing order of the rule group among the rule groups that you associate with the specified VPC. DNS Firewall filters VPC traffic starting from the rule group with the lowest numeric priority setting.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] tags: Key-value map of resource tags. .If configured with a provider `default_tags` configuration block present, tags with matching keys will overwrite those defined at the provider-level.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] tags_all: A map of tags assigned to the resource, including those inherited from the provider .
:param pulumi.Input[str] vpc_id: The unique identifier of the VPC that you want to associate with the rule group.
"""
if arn is not None:
pulumi.set(__self__, "arn", arn)
if firewall_rule_group_id is not None:
pulumi.set(__self__, "firewall_rule_group_id", firewall_rule_group_id)
if mutation_protection is not None:
pulumi.set(__self__, "mutation_protection", mutation_protection)
if name is not None:
pulumi.set(__self__, "name", name)
if priority is not None:
pulumi.set(__self__, "priority", priority)
if tags is not None:
pulumi.set(__self__, "tags", tags)
if tags_all is not None:
pulumi.set(__self__, "tags_all", tags_all)
if vpc_id is not None:
pulumi.set(__self__, "vpc_id", vpc_id)
@property
@pulumi.getter
def arn(self) -> Optional[pulumi.Input[str]]:
"""
The ARN (Amazon Resource Name) of the firewall rule group association.
"""
return pulumi.get(self, "arn")
@arn.setter
def arn(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "arn", value)
@property
@pulumi.getter(name="firewallRuleGroupId")
def firewall_rule_group_id(self) -> Optional[pulumi.Input[str]]:
"""
The unique identifier of the firewall rule group.
"""
return pulumi.get(self, "firewall_rule_group_id")
@firewall_rule_group_id.setter
def firewall_rule_group_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "firewall_rule_group_id", value)
@property
@pulumi.getter(name="mutationProtection")
def mutation_protection(self) -> Optional[pulumi.Input[str]]:
"""
If enabled, this setting disallows modification or removal of the association, to help prevent against accidentally altering DNS firewall protections. Valid values: `ENABLED`, `DISABLED`.
"""
return pulumi.get(self, "mutation_protection")
@mutation_protection.setter
def mutation_protection(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "mutation_protection", value)
@property
@pulumi.getter
def name(self) -> Optional[pulumi.Input[str]]:
"""
A name that lets you identify the rule group association, to manage and use it.
"""
return pulumi.get(self, "name")
@name.setter
def name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "name", value)
@property
@pulumi.getter
def priority(self) -> Optional[pulumi.Input[int]]:
"""
The setting that determines the processing order of the rule group among the rule groups that you associate with the specified VPC. DNS Firewall filters VPC traffic starting from the rule group with the lowest numeric priority setting.
"""
return pulumi.get(self, "priority")
@priority.setter
def priority(self, value: Optional[pulumi.Input[int]]):
pulumi.set(self, "priority", value)
@property
@pulumi.getter
def tags(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]:
"""
Key-value map of resource tags. .If configured with a provider `default_tags` configuration block present, tags with matching keys will overwrite those defined at the provider-level.
"""
return pulumi.get(self, "tags")
@tags.setter
def tags(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]):
pulumi.set(self, "tags", value)
@property
@pulumi.getter(name="tagsAll")
def tags_all(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]:
"""
A map of tags assigned to the resource, including those inherited from the provider .
"""
return pulumi.get(self, "tags_all")
@tags_all.setter
def tags_all(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]):
pulumi.set(self, "tags_all", value)
@property
@pulumi.getter(name="vpcId")
def vpc_id(self) -> Optional[pulumi.Input[str]]:
"""
The unique identifier of the VPC that you want to associate with the rule group.
"""
return pulumi.get(self, "vpc_id")
@vpc_id.setter
def vpc_id(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "vpc_id", value)
class ResolverFirewallRuleGroupAssociation(pulumi.CustomResource):
@overload
def __init__(__self__,
resource_name: str,
opts: Optional[pulumi.ResourceOptions] = None,
firewall_rule_group_id: Optional[pulumi.Input[str]] = None,
mutation_protection: Optional[pulumi.Input[str]] = None,
name: Optional[pulumi.Input[str]] = None,
priority: Optional[pulumi.Input[int]] = None,
tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,
vpc_id: Optional[pulumi.Input[str]] = None,
__props__=None):
"""
Provides a Route 53 Resolver DNS Firewall rule group association resource.
## Example Usage
```python
import pulumi
import pulumi_aws as aws
example_resolver_firewall_rule_group = aws.route53.ResolverFirewallRuleGroup("exampleResolverFirewallRuleGroup")
example_resolver_firewall_rule_group_association = aws.route53.ResolverFirewallRuleGroupAssociation("exampleResolverFirewallRuleGroupAssociation",
firewall_rule_group_id=example_resolver_firewall_rule_group.id,
priority=100,
vpc_id=aws_vpc["example"]["id"])
```
## Import
Route 53 Resolver DNS Firewall rule group associations can be imported using the Route 53 Resolver DNS Firewall rule group association ID, e.g.
```sh
$ pulumi import aws:route53/resolverFirewallRuleGroupAssociation:ResolverFirewallRuleGroupAssociation example rslvr-frgassoc-0123456789abcdef
```
:param str resource_name: The name of the resource.
:param pulumi.ResourceOptions opts: Options for the resource.
:param pulumi.Input[str] firewall_rule_group_id: The unique identifier of the firewall rule group.
:param pulumi.Input[str] mutation_protection: If enabled, this setting disallows modification or removal of the association, to help prevent against accidentally altering DNS firewall protections. Valid values: `ENABLED`, `DISABLED`.
:param pulumi.Input[str] name: A name that lets you identify the rule group association, to manage and use it.
:param pulumi.Input[int] priority: The setting that determines the processing order of the rule group among the rule groups that you associate with the specified VPC. DNS Firewall filters VPC traffic starting from the rule group with the lowest numeric priority setting.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] tags: Key-value map of resource tags. .If configured with a provider `default_tags` configuration block present, tags with matching keys will overwrite those defined at the provider-level.
:param pulumi.Input[str] vpc_id: The unique identifier of the VPC that you want to associate with the rule group.
"""
...
@overload
def __init__(__self__,
resource_name: str,
args: ResolverFirewallRuleGroupAssociationArgs,
opts: Optional[pulumi.ResourceOptions] = None):
"""
Provides a Route 53 Resolver DNS Firewall rule group association resource.
## Example Usage
```python
import pulumi
import pulumi_aws as aws
example_resolver_firewall_rule_group = aws.route53.ResolverFirewallRuleGroup("exampleResolverFirewallRuleGroup")
example_resolver_firewall_rule_group_association = aws.route53.ResolverFirewallRuleGroupAssociation("exampleResolverFirewallRuleGroupAssociation",
firewall_rule_group_id=example_resolver_firewall_rule_group.id,
priority=100,
vpc_id=aws_vpc["example"]["id"])
```
## Import
Route 53 Resolver DNS Firewall rule group associations can be imported using the Route 53 Resolver DNS Firewall rule group association ID, e.g.
```sh
$ pulumi import aws:route53/resolverFirewallRuleGroupAssociation:ResolverFirewallRuleGroupAssociation example rslvr-frgassoc-0123456789abcdef
```
:param str resource_name: The name of the resource.
:param ResolverFirewallRuleGroupAssociationArgs args: The arguments to use to populate this resource's properties.
:param pulumi.ResourceOptions opts: Options for the resource.
"""
...
def __init__(__self__, resource_name: str, *args, **kwargs):
resource_args, opts = _utilities.get_resource_args_opts(ResolverFirewallRuleGroupAssociationArgs, pulumi.ResourceOptions, *args, **kwargs)
if resource_args is not None:
__self__._internal_init(resource_name, opts, **resource_args.__dict__)
else:
__self__._internal_init(resource_name, *args, **kwargs)
def _internal_init(__self__,
resource_name: str,
opts: Optional[pulumi.ResourceOptions] = None,
firewall_rule_group_id: Optional[pulumi.Input[str]] = None,
mutation_protection: Optional[pulumi.Input[str]] = None,
name: Optional[pulumi.Input[str]] = None,
priority: Optional[pulumi.Input[int]] = None,
tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,
vpc_id: Optional[pulumi.Input[str]] = None,
__props__=None):
if opts is None:
opts = pulumi.ResourceOptions()
if not isinstance(opts, pulumi.ResourceOptions):
raise TypeError('Expected resource options to be a ResourceOptions instance')
if opts.version is None:
opts.version = _utilities.get_version()
if opts.id is None:
if __props__ is not None:
raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource')
__props__ = ResolverFirewallRuleGroupAssociationArgs.__new__(ResolverFirewallRuleGroupAssociationArgs)
if firewall_rule_group_id is None and not opts.urn:
raise TypeError("Missing required property 'firewall_rule_group_id'")
__props__.__dict__["firewall_rule_group_id"] = firewall_rule_group_id
__props__.__dict__["mutation_protection"] = mutation_protection
__props__.__dict__["name"] = name
if priority is None and not opts.urn:
raise TypeError("Missing required property 'priority'")
__props__.__dict__["priority"] = priority
__props__.__dict__["tags"] = tags
if vpc_id is None and not opts.urn:
raise TypeError("Missing required property 'vpc_id'")
__props__.__dict__["vpc_id"] = vpc_id
__props__.__dict__["arn"] = None
__props__.__dict__["tags_all"] = None
super(ResolverFirewallRuleGroupAssociation, __self__).__init__(
'aws:route53/resolverFirewallRuleGroupAssociation:ResolverFirewallRuleGroupAssociation',
resource_name,
__props__,
opts)
@staticmethod
def get(resource_name: str,
id: pulumi.Input[str],
opts: Optional[pulumi.ResourceOptions] = None,
arn: Optional[pulumi.Input[str]] = None,
firewall_rule_group_id: Optional[pulumi.Input[str]] = None,
mutation_protection: Optional[pulumi.Input[str]] = None,
name: Optional[pulumi.Input[str]] = None,
priority: Optional[pulumi.Input[int]] = None,
tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,
tags_all: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,
vpc_id: Optional[pulumi.Input[str]] = None) -> 'ResolverFirewallRuleGroupAssociation':
"""
Get an existing ResolverFirewallRuleGroupAssociation resource's state with the given name, id, and optional extra
properties used to qualify the lookup.
:param str resource_name: The unique name of the resulting resource.
:param pulumi.Input[str] id: The unique provider ID of the resource to lookup.
:param pulumi.ResourceOptions opts: Options for the resource.
:param pulumi.Input[str] arn: The ARN (Amazon Resource Name) of the firewall rule group association.
:param pulumi.Input[str] firewall_rule_group_id: The unique identifier of the firewall rule group.
:param pulumi.Input[str] mutation_protection: If enabled, this setting disallows modification or removal of the association, to help prevent against accidentally altering DNS firewall protections. Valid values: `ENABLED`, `DISABLED`.
:param pulumi.Input[str] name: A name that lets you identify the rule group association, to manage and use it.
:param pulumi.Input[int] priority: The setting that determines the processing order of the rule group among the rule groups that you associate with the specified VPC. DNS Firewall filters VPC traffic starting from the rule group with the lowest numeric priority setting.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] tags: Key-value map of resource tags. .If configured with a provider `default_tags` configuration block present, tags with matching keys will overwrite those defined at the provider-level.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] tags_all: A map of tags assigned to the resource, including those inherited from the provider .
:param pulumi.Input[str] vpc_id: The unique identifier of the VPC that you want to associate with the rule group.
"""
opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id))
__props__ = _ResolverFirewallRuleGroupAssociationState.__new__(_ResolverFirewallRuleGroupAssociationState)
__props__.__dict__["arn"] = arn
__props__.__dict__["firewall_rule_group_id"] = firewall_rule_group_id
__props__.__dict__["mutation_protection"] = mutation_protection
__props__.__dict__["name"] = name
__props__.__dict__["priority"] = priority
__props__.__dict__["tags"] = tags
__props__.__dict__["tags_all"] = tags_all
__props__.__dict__["vpc_id"] = vpc_id
return ResolverFirewallRuleGroupAssociation(resource_name, opts=opts, __props__=__props__)
@property
@pulumi.getter
def arn(self) -> pulumi.Output[str]:
"""
The ARN (Amazon Resource Name) of the firewall rule group association.
"""
return pulumi.get(self, "arn")
@property
@pulumi.getter(name="firewallRuleGroupId")
def firewall_rule_group_id(self) -> pulumi.Output[str]:
"""
The unique identifier of the firewall rule group.
"""
return pulumi.get(self, "firewall_rule_group_id")
@property
@pulumi.getter(name="mutationProtection")
def mutation_protection(self) -> pulumi.Output[str]:
"""
If enabled, this setting disallows modification or removal of the association, to help prevent against accidentally altering DNS firewall protections. Valid values: `ENABLED`, `DISABLED`.
"""
return pulumi.get(self, "mutation_protection")
@property
@pulumi.getter
def name(self) -> pulumi.Output[str]:
"""
A name that lets you identify the rule group association, to manage and use it.
"""
return pulumi.get(self, "name")
@property
@pulumi.getter
def priority(self) -> pulumi.Output[int]:
"""
The setting that determines the processing order of the rule group among the rule groups that you associate with the specified VPC. DNS Firewall filters VPC traffic starting from the rule group with the lowest numeric priority setting.
"""
return pulumi.get(self, "priority")
@property
@pulumi.getter
def tags(self) -> pulumi.Output[Optional[Mapping[str, str]]]:
"""
Key-value map of resource tags. .If configured with a provider `default_tags` configuration block present, tags with matching keys will overwrite those defined at the provider-level.
"""
return pulumi.get(self, "tags")
@property
@pulumi.getter(name="tagsAll")
def tags_all(self) -> pulumi.Output[Mapping[str, str]]:
"""
A map of tags assigned to the resource, including those inherited from the provider .
"""
return pulumi.get(self, "tags_all")
@property
@pulumi.getter(name="vpcId")
def vpc_id(self) -> pulumi.Output[str]:
"""
The unique identifier of the VPC that you want to associate with the rule group.
"""
return pulumi.get(self, "vpc_id")
| 50.551653 | 278 | 0.679609 | 2,952 | 24,467 | 5.446477 | 0.072493 | 0.077311 | 0.06879 | 0.042543 | 0.854957 | 0.83692 | 0.817017 | 0.802152 | 0.793755 | 0.776278 | 0 | 0.002816 | 0.230678 | 24,467 | 483 | 279 | 50.656315 | 0.851352 | 0.421261 | 0 | 0.664179 | 1 | 0 | 0.09593 | 0.032233 | 0 | 0 | 0 | 0 | 0 | 1 | 0.160448 | false | 0.048507 | 0.018657 | 0 | 0.276119 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
bc0d103c643e738a9bf6f4d08b076079f1f027f0 | 5,280 | py | Python | server/openapi_server/test/test_model_controller.py | mintproject/MINT-ModelCatalogIngestionAPI | 026d3495483a3e48ea3c1364d0dda09beeea69e4 | [
"Apache-2.0"
] | 2 | 2019-05-30T21:33:43.000Z | 2019-09-27T21:04:38.000Z | server/openapi_server/test/test_model_controller.py | mintproject/MINT-ModelCatalogIngestionAPI | 026d3495483a3e48ea3c1364d0dda09beeea69e4 | [
"Apache-2.0"
] | 25 | 2019-03-28T14:44:57.000Z | 2019-07-25T00:20:09.000Z | server/openapi_server/test/test_model_controller.py | mintproject/MINT-ModelCatalogIngestionAPI | 026d3495483a3e48ea3c1364d0dda09beeea69e4 | [
"Apache-2.0"
] | null | null | null | # coding: utf-8
from __future__ import absolute_import
import logging
import unittest
from flask import json
from six import BytesIO
from openapi_server.models import Model
from openapi_server.test import BaseTestCase
MINT_USERNAME = "mint@isi.edu"
class TestModel(BaseTestCase):
"""Model integration test stubs"""
logger = logging.getLogger("TestModel")
def test_models_get(self):
"""Test case for models_get
List all Model entities
"""
query_string = [('username', self.get_username)]
headers = {
'Accept': 'application/json',
}
response = self.client.open(
'/v1.8.0/modelconfigurations',
method='GET',
headers=headers,
query_string=query_string)
self.logger.info("Response length {}".format(len(response.json)))
self.assert200(response,
'Response body is : ' + response.data.decode('utf-8'))
self.assertTrue(response.json)
for _item in response.json:
keys = _item.keys()
for key in keys:
self.check_key(key)
def test_model_custom_index_get(self):
"""Test case for model_get
List all Models entities
"""
query_string = [('username', MINT_USERNAME),
('label', 'flooding')]
headers = {
'Accept': 'application/json',
}
response = self.client.open(
'/v1.8.0/custom/models/variable',
method='GET',
headers=headers,
query_string=query_string)
self.logger.info("Response length {}".format(len(response.json)))
for item in response.json:
self.assertIsInstance(Model.from_dict(item), Model)
self.assert200(response,
'Response body is : ' + response.data.decode('utf-8'))
def test_model_custom_intervention_get(self):
"""Test case for model_get
List all Models entities
"""
query_string = [('username', MINT_USERNAME),
('label', 'Fertilizer')]
headers = {
'Accept': 'application/json',
}
response = self.client.open(
'/v1.8.0/custom/model/intervention',
method='GET',
headers=headers,
query_string=query_string)
self.logger.info("Response length {}".format(len(response.json)))
for item in response.json:
self.assertIsInstance(Model.from_dict(item), Model)
self.assert200(response,
'Response body is : ' + response.data.decode('utf-8'))
def test_model_custom_region_get(self):
"""Test case for model_get
List all Models entities
"""
query_string = [('username', MINT_USERNAME),
('label', 'baro')]
headers = {
'Accept': 'application/json',
}
response = self.client.open(
'/v1.8.0/custom/model/region',
method='GET',
headers=headers,
query_string=query_string)
self.logger.info("Response length {}".format(len(response.json)))
for item in response.json:
self.assertIsInstance(Model.from_dict(item), Model)
self.assert200(response,
'Response body is : ' + response.data.decode('utf-8'))
for _item in response.json:
keys = _item.keys()
for key in keys:
self.check_key(key)
def test_model_custom_variable_get(self):
"""Test case for model_get
List all Models entities
"""
query_string = [('username', MINT_USERNAME),
('label', 'crop')]
headers = {
'Accept': 'application/json',
}
response = self.client.open(
'/v1.8.0/custom/models/variable',
method='GET',
headers=headers,
query_string=query_string)
self.logger.info("Response length {}".format(len(response.json)))
for item in response.json:
self.assertIsInstance(Model.from_dict(item), Model)
self.assert200(response,
'Response body is : ' + response.data.decode('utf-8'))
def test_model_custom_standard_variable_get(self):
"""Test case for model_get
List all Models entities
"""
query_string = [('username', MINT_USERNAME),
('label', 'crop')]
headers = {
'Accept': 'application/json',
}
response = self.client.open(
'/v1.8.0/custom/models/standard_variable',
method='GET',
headers=headers,
query_string=query_string)
self.logger.info("Response length {}".format(len(response.json)))
for item in response.json:
self.assertIsInstance(Model.from_dict(item), Model)
self.assert200(response,
'Response body is : ' + response.data.decode('utf-8'))
for _item in response.json:
keys = _item.keys()
for key in keys:
self.check_key(key)
if __name__ == '__main__':
unittest.main()
| 33 | 77 | 0.557386 | 552 | 5,280 | 5.179348 | 0.144928 | 0.069255 | 0.025184 | 0.047569 | 0.827562 | 0.821266 | 0.821266 | 0.817069 | 0.817069 | 0.817069 | 0 | 0.012092 | 0.326515 | 5,280 | 159 | 78 | 33.207547 | 0.791901 | 0.064962 | 0 | 0.720339 | 0 | 0 | 0.150031 | 0.038758 | 0 | 0 | 0 | 0 | 0.101695 | 1 | 0.050847 | false | 0 | 0.059322 | 0 | 0.127119 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
bc307db5b30ba05ce1bf6c5a3174210c86d82796 | 30 | py | Python | src/BearSki/install_data.py | Sirius1942/BearFramework | 333b6f98c00441b3606d116625faabd0d66c2a37 | [
"MIT"
] | null | null | null | src/BearSki/install_data.py | Sirius1942/BearFramework | 333b6f98c00441b3606d116625faabd0d66c2a37 | [
"MIT"
] | null | null | null | src/BearSki/install_data.py | Sirius1942/BearFramework | 333b6f98c00441b3606d116625faabd0d66c2a37 | [
"MIT"
] | null | null | null | def testRun():
return "OK" | 15 | 15 | 0.6 | 4 | 30 | 4.5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.233333 | 30 | 2 | 15 | 15 | 0.782609 | 0 | 0 | 0 | 0 | 0 | 0.064516 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.5 | true | 0 | 0 | 0.5 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 7 |
70fd15c7839e62af7a2ea01b37774a8f23087692 | 62,256 | py | Python | src/pyrad_proc/pyrad/proc/process_monitoring.py | jfigui/pyrad | 7811d593bb09a7f8a621c0e8ae3f32c2b85a0254 | [
"BSD-3-Clause"
] | 41 | 2016-12-01T08:46:06.000Z | 2021-06-24T21:14:33.000Z | src/pyrad_proc/pyrad/proc/process_monitoring.py | jfigui/pyrad | 7811d593bb09a7f8a621c0e8ae3f32c2b85a0254 | [
"BSD-3-Clause"
] | 42 | 2017-02-23T14:52:49.000Z | 2021-02-01T10:43:52.000Z | src/pyrad_proc/pyrad/proc/process_monitoring.py | jfigui/pyrad | 7811d593bb09a7f8a621c0e8ae3f32c2b85a0254 | [
"BSD-3-Clause"
] | 21 | 2016-08-25T15:02:12.000Z | 2021-05-27T04:09:40.000Z | """
pyrad.proc.process_monitoring
=============================
Functions for monitoring of the polarimetric variables
.. autosummary::
:toctree: generated/
process_selfconsistency_kdp_phidp
process_selfconsistency_bias
process_selfconsistency_bias2
process_estimate_phidp0
process_rhohv_rain
process_zdr_precip
process_zdr_snow
process_monitoring
"""
from copy import deepcopy
from warnings import warn
import numpy as np
import pyart
from ..io.io_aux import get_datatype_fields, get_fieldname_pyart
from ..io.read_data_other import read_selfconsistency
from ..io.read_data_radar import interpol_field
from ..util.radar_utils import get_histogram_bins
from ..util.stat_utils import ratio_bootstrapping
def process_selfconsistency_kdp_phidp(procstatus, dscfg, radar_list=None):
"""
Computes specific differential phase and differential phase in rain using
the selfconsistency between Zdr, Zh and KDP
Parameters
----------
procstatus : int
Processing status: 0 initializing, 1 processing volume,
2 post-processing
dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords::
datatype : list of strings. Dataset keyword
The input data types
parametrization : str
The type of parametrization for the self-consistency curves. Can
be 'None', 'Gourley', 'Wolfensberger', 'Louf', 'Gorgucci' or
'Vaccarono'
'None' will use tables from config files. Default 'None'.
rsmooth : float. Dataset keyword
length of the smoothing window [m]. Default 2000.
min_rhohv : float. Dataset keyword
minimum valid RhoHV. Default 0.92
filter_rain : Bool. Dataset keyword
If True the hydrometeor classification is used to filter out gates
that are not rain. Default True
max_phidp : float. Dataset keyword
maximum valid PhiDP [deg]. Default 20.
ml_thickness : float. Dataset keyword
assumed melting layer thickness [m]. Default 700.
fzl : float. Dataset keyword
The default freezing level height. It will be used if no
temperature field name is specified or the temperature field is
not in the radar object. Default 2000.
frequency : float. Dataset keyword
the radar frequency [Hz]. If None that of the key
frequency in attribute instrument_parameters of the radar
object will be used. If the key or the attribute are not present
the selfconsistency will not be computed
radar_list : list of Radar objects
Optional. list of radar objects
Returns
-------
new_dataset : dict
dictionary containing the output
ind_rad : int
radar index
"""
if procstatus != 1:
return None, None
temp = None
iso0 = None
hydro = None
for datatypedescr in dscfg['datatype']:
radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr)
if datatype == 'dBZc':
refl = 'corrected_reflectivity'
if datatype == 'dBZ':
refl = 'reflectivity'
if datatype == 'ZDRc':
zdr = 'corrected_differential_reflectivity'
if datatype == 'ZDR':
zdr = 'differential_reflectivity'
if datatype == 'PhiDPc':
phidp = 'corrected_differential_phase'
if datatype == 'PhiDP':
phidp = 'differential_phase'
if datatype == 'TEMP':
temp = 'temperature'
if datatype == 'H_ISO0':
iso0 = 'height_over_iso0'
if datatype == 'hydro':
hydro = 'radar_echo_classification'
if datatype == 'RhoHV':
rhohv = 'cross_correlation_ratio'
if datatype == 'RhoHVc':
rhohv = 'corrected_cross_correlation_ratio'
if datatype == 'uRhoHV':
rhohv = 'uncorrected_cross_correlation_ratio'
ind_rad = int(radarnr[5:8])-1
if radar_list[ind_rad] is None:
warn('No valid radar')
return None, None
radar = radar_list[ind_rad]
if ((refl not in radar.fields) or
(zdr not in radar.fields) or
(phidp not in radar.fields) or
(rhohv not in radar.fields)):
warn('Unable to estimate PhiDP/KDP using selfconsistency. ' +
'Missing data')
return None, None
# determine which freezing level reference
if temp is not None:
if temp in radar.fields:
temp_ref = 'temperature'
else:
warn('COSMO temperature field not available. ' +
'Using fixed freezing level height to determine liquid phase')
temp_ref = 'fixed_fzl'
elif iso0 is not None:
if iso0 in radar.fields:
temp_ref = 'height_over_iso0'
else:
warn('Height over iso0 field not available. ' +
'Using fixed freezing level height to determine liquid phase')
temp_ref = 'fixed_fzl'
else:
warn('Field to obtain the freezing level was not specified. ' +
'Using fixed freezing level height')
temp_ref = 'fixed_fzl'
# determine freezing level height if necessary
fzl = None
if temp_ref == 'fixed_fzl':
if 'fzl' in dscfg:
fzl = dscfg['fzl']
else:
fzl = 2000.
warn('Freezing level height not defined. Using default ' +
str(fzl)+' m')
# get self-consistency parametrization or curves
parametrization = dscfg.get('parametrization', 'None')
if dscfg['initialized'] == 0:
# get frequency band
freq = dscfg.get('frequency', None)
if freq is None:
if (radar.instrument_parameters is not None and
'frequency' in radar.instrument_parameters):
freq = radar.instrument_parameters['frequency']['data'][0]
else:
warn('Unable to estimate Zh bias using ' +
'self-consistency. Unknown radar frequency')
return None, None
freq_band = pyart.retrieve.get_freq_band(freq)
if parametrization == 'None':
# find unique elevations
el_vec = np.unique(
(10.*np.round(radar.elevation['data'], decimals=1)).astype(int))
zdr_kdpzh_list = list()
el_list = list()
for el in el_vec:
fname = (
dscfg['configpath'] + 'selfconsistency/' +
'selfconsistency_zdr_zhkdp_'+freq_band+'band_temp10_elev' +
'{:03d}'.format(el)+'_mu05.txt')
zdr_kdpzh_table = read_selfconsistency(fname)
if zdr_kdpzh_table is not None:
zdr_kdpzh_list.append(zdr_kdpzh_table)
el_list.append((el/10.).astype(int))
if not el_list:
warn('Unable to retrieve PhiDP and KDP using self-consistency. ' +
'No selfconsistency files for the radar elevations.')
return None, None
zdr_kdpzh_dict = {'zdr_kdpzh': zdr_kdpzh_list,
'elev': el_list,
'freq_band': freq_band}
else:
zdr_kdpzh_dict = {'zdr_kdpzh': None,
'elev': None,
'freq_band': freq_band}
dscfg['global_data'] = zdr_kdpzh_dict
dscfg['initialized'] = 1
if dscfg['initialized'] == 1:
# get user defined values
rsmooth = dscfg.get('rsmooth', 2000.)
min_rhohv = dscfg.get('min_rhohv', 0.92)
filter_rain = dscfg.get('filter_rain', True)
max_phidp = dscfg.get('max_phidp', 20.)
ml_thickness = dscfg.get('ml_thickness', 700.)
kdpsim_field = 'specific_differential_phase'
phidpsim_field = 'differential_phase'
r_res = radar.range['data'][1]-radar.range['data'][0]
smooth_wind_len = int(rsmooth/r_res)
kdpsim, phidpsim = pyart.correct.selfconsistency_kdp_phidp(
radar, dscfg['global_data'], min_rhohv=min_rhohv,
filter_rain=filter_rain, max_phidp=max_phidp,
smooth_wind_len=smooth_wind_len, doc=15, fzl=fzl,
thickness=ml_thickness, parametrization=parametrization,
refl_field=refl, phidp_field=phidp, zdr_field=zdr,
temp_field=temp, iso0_field=iso0, hydro_field=hydro,
rhohv_field=rhohv, kdpsim_field=kdpsim_field,
phidpsim_field=phidpsim_field, temp_ref=temp_ref)
# prepare for exit
new_dataset = {'radar_out': deepcopy(radar)}
new_dataset['radar_out'].fields = dict()
new_dataset['radar_out'].add_field(kdpsim_field, kdpsim)
new_dataset['radar_out'].add_field(phidpsim_field, phidpsim)
return new_dataset, ind_rad
def process_selfconsistency_bias(procstatus, dscfg, radar_list=None):
"""
Estimates the reflectivity bias by means of the selfconsistency
algorithm by Gourley
Parameters
----------
procstatus : int
Processing status: 0 initializing, 1 processing volume,
2 post-processing
dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords::
datatype : list of string. Dataset keyword
The input data types
parametrization : str
The type of parametrization for the self-consistency curves. Can
be 'None', 'Gourley', 'Wolfensberger', 'Louf', 'Gorgucci' or
'Vaccarono'
'None' will use tables from config files. Default 'None'.
fzl : float. Dataset keyword
Default freezing level height. Default 2000.
rsmooth : float. Dataset keyword
length of the smoothing window [m]. Default 2000.
min_rhohv : float. Dataset keyword
minimum valid RhoHV. Default 0.92
filter_rain : Bool. Dataset keyword
If True the hydrometeor classification is used to filter out gates
that are not rain. Default True
max_phidp : float. Dataset keyword
maximum valid PhiDP [deg]. Default 20.
ml_thickness : float. Dataset keyword
Melting layer thickness [m]. Default 700.
rcell : float. Dataset keyword
length of continuous precipitation to consider the precipitation
cell a valid phidp segment [m]. Default 15000.
dphidp_min : float. Dataset keyword
minimum phase shift [deg]. Default 2.
dphidp_max : float. Dataset keyword
maximum phase shift [deg]. Default 16.
frequency : float. Dataset keyword
the radar frequency [Hz]. If None that of the key
frequency in attribute instrument_parameters of the radar
object will be used. If the key or the attribute are not present
the selfconsistency will not be computed
check_wet_radome : Bool. Dataset keyword
if True the average reflectivity of the closest gates to the radar
is going to be check to find out whether there is rain over the
radome. If there is rain no bias will be computed. Default True.
wet_radome_refl : Float. Dataset keyword
Average reflectivity [dBZ] of the gates close to the radar to
consider the radome as wet. Default 25.
wet_radome_rng_min, wet_radome_rng_max : Float. Dataset keyword
Min and max range [m] of the disk around the radar used to compute
the average reflectivity to determine whether the radome is wet.
Default 2000 and 4000.
wet_radome_ngates_min : int
Minimum number of valid gates to consider that the radome is wet.
Default 180
valid_gates_only : Bool
If True the reflectivity bias obtained for each valid ray is going
to be assigned only to gates of the segment used. That will give
more weight to longer segments when computing the total bias.
Default False
keep_points : Bool
If True the ZDR, ZH and KDP of the gates used in the self-
consistency algorithm are going to be stored for further analysis.
Default False
rkdp : float
The length of the window used to compute KDP with the single
window least square method [m]. Default 6000.
radar_list : list of Radar objects
Optional. list of radar objects
Returns
-------
new_dataset : dict
dictionary containing the output
ind_rad : int
radar index
"""
if procstatus == 0:
return None, None
keep_points = dscfg.get('keep_points', False)
if procstatus == 2:
if not keep_points or dscfg['initialized'] == 0:
return None, None
return (
{'selfconsistency_points':
dscfg['global_data']['selfconsistency_points']}, None)
temp = None
iso0 = None
hydro = None
for datatypedescr in dscfg['datatype']:
radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr)
if datatype == 'dBZc':
refl = 'corrected_reflectivity'
if datatype == 'dBZ':
refl = 'reflectivity'
if datatype == 'ZDRc':
zdr = 'corrected_differential_reflectivity'
if datatype == 'ZDR':
zdr = 'differential_reflectivity'
if datatype == 'PhiDPc':
phidp = 'corrected_differential_phase'
if datatype == 'PhiDP':
phidp = 'differential_phase'
if datatype == 'TEMP':
temp = 'temperature'
if datatype == 'H_ISO0':
iso0 = 'height_over_iso0'
if datatype == 'hydro':
hydro = 'radar_echo_classification'
if datatype == 'RhoHV':
rhohv = 'cross_correlation_ratio'
if datatype == 'RhoHVc':
rhohv = 'corrected_cross_correlation_ratio'
if datatype == 'uRhoHV':
rhohv = 'uncorrected_cross_correlation_ratio'
ind_rad = int(radarnr[5:8])-1
if radar_list[ind_rad] is None:
warn('No valid radar')
return None, None
radar = radar_list[ind_rad]
if ((refl not in radar.fields) or
(zdr not in radar.fields) or
(phidp not in radar.fields) or
(rhohv not in radar.fields)):
warn('Unable to estimate reflectivity bias using selfconsistency. ' +
'Missing data')
return None, None
# determine which freezing level reference
if temp is not None:
if temp in radar.fields:
temp_ref = 'temperature'
else:
warn('COSMO temperature field not available. ' +
'Using fixed freezing level height to determine liquid phase')
temp_ref = 'fixed_fzl'
elif iso0 is not None:
if iso0 in radar.fields:
temp_ref = 'height_over_iso0'
else:
warn('Height over iso0 field not available. ' +
'Using fixed freezing level height to determine liquid phase')
temp_ref = 'fixed_fzl'
else:
warn('Field to obtain the freezing level was not specified. ' +
'Using fixed freezing level height')
temp_ref = 'fixed_fzl'
# determine freezing level height if necessary
fzl = None
if temp_ref == 'fixed_fzl':
if 'fzl' in dscfg:
fzl = dscfg['fzl']
else:
fzl = 2000.
warn('Freezing level height not defined. Using default ' +
str(fzl)+' m')
# get self-consistency parametrization or curves
parametrization = dscfg.get('parametrization', 'None')
if dscfg['initialized'] == 0:
# get frequency band
freq = dscfg.get('frequency', None)
if freq is None:
if (radar.instrument_parameters is not None and
'frequency' in radar.instrument_parameters):
freq = radar.instrument_parameters['frequency']['data'][0]
else:
warn('Unable to estimate Zh bias using ' +
'self-consistency. Unknown radar frequency')
return None, None
freq_band = pyart.retrieve.get_freq_band(freq)
if parametrization == 'None':
# find unique elevations
el_vec = np.unique(
(10.*np.round(radar.elevation['data'], decimals=1)).astype(int))
zdr_kdpzh_list = list()
el_list = list()
for el in el_vec:
fname = (
dscfg['configpath'] + 'selfconsistency/' +
'selfconsistency_zdr_zhkdp_'+freq_band+'band_temp10_elev' +
'{:03d}'.format(el)+'_mu05.txt')
zdr_kdpzh_table = read_selfconsistency(fname)
if zdr_kdpzh_table is not None:
zdr_kdpzh_list.append(zdr_kdpzh_table)
el_list.append((el/10.).astype(int))
if not el_list:
warn('Unable to retrieve Zh bias using self-consistency. ' +
'No selfconsistency files for the radar elevations.')
return None, None
zdr_kdpzh_dict = {'zdr_kdpzh': zdr_kdpzh_list,
'elev': el_list,
'freq_band': freq_band}
else:
zdr_kdpzh_dict = {'zdr_kdpzh': None,
'elev': None,
'freq_band': freq_band}
dscfg['global_data'] = {'zdr_kdpzh_dict': zdr_kdpzh_dict}
if keep_points:
dscfg['global_data'].update({'selfconsistency_points': {
'zdr': [],
'kdp': [],
'zh': [],
'timeinfo': dscfg['timeinfo'],
'parametrization': parametrization,
'zdr_kdpzh_dict': zdr_kdpzh_dict
}})
dscfg['initialized'] = 1
if dscfg['initialized'] == 1:
# get user defined values
rsmooth = dscfg.get('rsmooth', 2000.)
min_rhohv = dscfg.get('min_rhohv', 0.92)
filter_rain = dscfg.get('filter_rain', True)
max_phidp = dscfg.get('max_phidp', 20.)
ml_thickness = dscfg.get('ml_thickness', 700.)
rcell = dscfg.get('rcell', 15000.)
dphidp_min = dscfg.get('dphidp_min', 2.)
dphidp_max = dscfg.get('dphidp_max', 16.)
check_wet_radome = dscfg.get('check_wet_radome', True)
wet_radome_refl = dscfg.get('wet_radome_refl', 25.)
wet_radome_rng_min = dscfg.get('wet_radome_rng_min', 2000.)
wet_radome_rng_max = dscfg.get('wet_radome_rng_max', 4000.)
wet_radome_ngates_min = dscfg.get('wet_radome_ngates_min', 180)
valid_gates_only = dscfg.get('valid_gates_only', False)
rkdp = dscfg.get('rkdp', 6000.)
r_res = radar.range['data'][1]-radar.range['data'][0]
smooth_wind_len = int(rsmooth/r_res)
kdp_wind_len = int(rkdp/r_res)
min_rcons = int(rcell/r_res)
wet_radome_len_min = int(wet_radome_rng_min/r_res)
wet_radome_len_max = int(wet_radome_rng_max/r_res)
refl_bias, selfconsistency_dict = pyart.correct.selfconsistency_bias(
radar, dscfg['global_data']['zdr_kdpzh_dict'],
min_rhohv=min_rhohv, filter_rain=filter_rain, max_phidp=max_phidp,
smooth_wind_len=smooth_wind_len, doc=15, fzl=fzl,
thickness=ml_thickness, min_rcons=min_rcons,
dphidp_min=dphidp_min, dphidp_max=dphidp_max,
parametrization=parametrization, refl_field=refl,
phidp_field=phidp, zdr_field=zdr, temp_field=temp,
iso0_field=iso0, hydro_field=hydro, rhohv_field=rhohv,
temp_ref=temp_ref, check_wet_radome=check_wet_radome,
wet_radome_refl=wet_radome_refl,
wet_radome_len_min=wet_radome_len_min,
wet_radome_len_max=wet_radome_len_max,
valid_gates_only=valid_gates_only, keep_points=keep_points,
kdp_wind_len=kdp_wind_len)
if keep_points:
if selfconsistency_dict is not None:
dscfg['global_data']['selfconsistency_points']['zdr'].extend(
selfconsistency_dict['zdr'])
dscfg['global_data']['selfconsistency_points']['zh'].extend(
selfconsistency_dict['zh'])
dscfg['global_data']['selfconsistency_points']['kdp'].extend(
selfconsistency_dict['kdp'])
# prepare for exit
new_dataset = {'radar_out': deepcopy(radar)}
new_dataset['radar_out'].fields = dict()
new_dataset['radar_out'].add_field('reflectivity_bias', refl_bias)
return new_dataset, ind_rad
def process_selfconsistency_bias2(procstatus, dscfg, radar_list=None):
"""
Estimates the reflectivity bias by means of the selfconsistency
algorithm by Gourley
Parameters
----------
procstatus : int
Processing status: 0 initializing, 1 processing volume,
2 post-processing
dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords::
datatype : list of string. Dataset keyword
The input data types
parametrization : str
The type of parametrization for the self-consistency curves. Can
be 'None', 'Gourley', 'Wolfensberger', 'Louf', 'Gorgucci' or
'Vaccarono'
'None' will use tables from config files. Default 'None'.
fzl : float. Dataset keyword
Default freezing level height. Default 2000.
rsmooth : float. Dataset keyword
length of the smoothing window [m]. Default 2000.
min_rhohv : float. Dataset keyword
minimum valid RhoHV. Default 0.92
filter_rain : Bool. Dataset keyword
If True the hydrometeor classification is used to filter out gates
that are not rain. Default True
max_phidp : float. Dataset keyword
maximum valid PhiDP [deg]. Default 20.
ml_thickness : float. Dataset keyword
Melting layer thickness [m]. Default 700.
rcell : float. Dataset keyword
length of continuous precipitation to consider the precipitation
cell a valid phidp segment [m]. Default 15000.
frequency : float. Dataset keyword
the radar frequency [Hz]. If None that of the key
frequency in attribute instrument_parameters of the radar
object will be used. If the key or the attribute are not present
the selfconsistency will not be computed
check_wet_radome : Bool. Dataset keyword
if True the average reflectivity of the closest gates to the radar
is going to be check to find out whether there is rain over the
radome. If there is rain no bias will be computed. Default True.
wet_radome_refl : Float. Dataset keyword
Average reflectivity [dBZ] of the gates close to the radar to
consider the radome as wet. Default 25.
wet_radome_rng_min, wet_radome_rng_max : Float. Dataset keyword
Min and max range [m] of the disk around the radar used to compute
the average reflectivity to determine whether the radome is wet.
Default 2000 and 4000.
wet_radome_ngates_min : int
Minimum number of valid gates to consider that the radome is wet.
Default 180
keep_points : Bool
If True the ZDR, ZH and KDP of the gates used in the self-
consistency algorithm are going to be stored for further analysis.
Default False
bias_per_gate : Bool
If True the bias per gate will be computed
radar_list : list of Radar objects
Optional. list of radar objects
Returns
-------
new_dataset : dict
dictionary containing the output
ind_rad : int
radar index
"""
if procstatus == 0:
return None, None
keep_points = dscfg.get('keep_points', False)
bias_type = dscfg.get('bias_type', 'cumulative')
provide_confidence = dscfg.get('provide_confidence', False)
nsamples_confidence = dscfg.get('nsamples_confidence', 1000)
if procstatus == 2:
if dscfg['initialized'] == 0:
return None, None
dataset = None
if bias_type == 'cumulative':
kdp_obs = np.ma.array(
dscfg['global_data']['kdp_data_dict']['kdp_obs'])
kdp_sim = np.ma.array(
dscfg['global_data']['kdp_data_dict']['kdp_sim'])
reflectivity_bias = {
'value': 10.*np.ma.log10(
np.ma.sum(kdp_sim)/np.ma.sum(kdp_obs)),
'npoints': kdp_obs.size,
'timeinfo': dscfg['global_data']['kdp_data_dict']['timeinfo'],
'bias_type': 'cumulative'}
if provide_confidence:
samples = ratio_bootstrapping(
kdp_sim, kdp_obs, nsamples=nsamples_confidence)
reflectivity_bias.update(
{'samples': 10.*np.ma.log10(samples)})
dataset = {'reflectivity_bias': reflectivity_bias}
if keep_points:
if dataset is None:
dataset = {'selfconsistency_points':
dscfg['global_data']['selfconsistency_points']}
else:
dataset.update(
{'selfconsistency_points':
dscfg['global_data']['selfconsistency_points']})
return dataset, None
temp = None
iso0 = None
hydro = None
phidp = None
for datatypedescr in dscfg['datatype']:
radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr)
if datatype == 'dBZc':
refl = 'corrected_reflectivity'
if datatype == 'dBZ':
refl = 'reflectivity'
if datatype == 'ZDRc':
zdr = 'corrected_differential_reflectivity'
if datatype == 'ZDR':
zdr = 'differential_reflectivity'
if datatype == 'PhiDPc':
phidp = 'corrected_differential_phase'
if datatype == 'PhiDP':
phidp = 'differential_phase'
if datatype == 'KDPc':
kdp = 'corrected_specific_differential_phase'
if datatype == 'KDP':
kdp = 'specific_differential_phase'
if datatype == 'TEMP':
temp = 'temperature'
if datatype == 'H_ISO0':
iso0 = 'height_over_iso0'
if datatype == 'hydro':
hydro = 'radar_echo_classification'
if datatype == 'RhoHV':
rhohv = 'cross_correlation_ratio'
if datatype == 'RhoHVc':
rhohv = 'corrected_cross_correlation_ratio'
if datatype == 'uRhoHV':
rhohv = 'uncorrected_cross_correlation_ratio'
ind_rad = int(radarnr[5:8])-1
if radar_list[ind_rad] is None:
warn('No valid radar')
return None, None
radar = radar_list[ind_rad]
if ((refl not in radar.fields) or
(zdr not in radar.fields) or
(kdp not in radar.fields) or
(rhohv not in radar.fields)):
warn('Unable to estimate reflectivity bias using selfconsistency. ' +
'Missing data')
return None, None
# determine which freezing level reference
if temp is not None:
if temp in radar.fields:
temp_ref = 'temperature'
else:
warn('COSMO temperature field not available. ' +
'Using fixed freezing level height to determine liquid phase')
temp_ref = 'fixed_fzl'
elif iso0 is not None:
if iso0 in radar.fields:
temp_ref = 'height_over_iso0'
else:
warn('Height over iso0 field not available. ' +
'Using fixed freezing level height to determine liquid phase')
temp_ref = 'fixed_fzl'
else:
warn('Field to obtain the freezing level was not specified. ' +
'Using fixed freezing level height')
temp_ref = 'fixed_fzl'
# determine freezing level height if necessary
fzl = None
if temp_ref == 'fixed_fzl':
if 'fzl' in dscfg:
fzl = dscfg['fzl']
else:
fzl = 2000.
warn('Freezing level height not defined. Using default ' +
str(fzl)+' m')
# get self-consistency parametrization or curves
parametrization = dscfg.get('parametrization', 'None')
if dscfg['initialized'] == 0:
# get frequency band
freq = dscfg.get('frequency', None)
if freq is None:
if (radar.instrument_parameters is not None and
'frequency' in radar.instrument_parameters):
freq = radar.instrument_parameters['frequency']['data'][0]
else:
warn('Unable to estimate Zh bias using ' +
'self-consistency. Unknown radar frequency')
return None, None
freq_band = pyart.retrieve.get_freq_band(freq)
if parametrization == 'None':
# find unique elevations
el_vec = np.unique(
(10.*np.round(radar.elevation['data'], decimals=1)).astype(int))
zdr_kdpzh_list = list()
el_list = list()
for el in el_vec:
fname = (
dscfg['configpath'] + 'selfconsistency/' +
'selfconsistency_zdr_zhkdp_'+freq_band+'band_temp10_elev' +
'{:03d}'.format(el)+'_mu05.txt')
zdr_kdpzh_table = read_selfconsistency(fname)
if zdr_kdpzh_table is not None:
zdr_kdpzh_list.append(zdr_kdpzh_table)
el_list.append((el/10.).astype(int))
if not el_list:
warn('Unable to retrieve Zh bias using self-consistency. ' +
'No selfconsistency files for the radar elevations.')
return None, None
zdr_kdpzh_dict = {'zdr_kdpzh': zdr_kdpzh_list,
'elev': el_list,
'freq_band': freq_band}
else:
zdr_kdpzh_dict = {'zdr_kdpzh': None,
'elev': None,
'freq_band': freq_band}
dscfg['global_data'] = {'zdr_kdpzh_dict': zdr_kdpzh_dict}
dscfg['global_data'].update({'kdp_data_dict': {
'kdp_obs': [],
'kdp_sim': [],
'timeinfo': dscfg['timeinfo']
}})
if keep_points:
dscfg['global_data'].update({'selfconsistency_points': {
'zdr': [],
'kdp': [],
'zh': [],
'timeinfo': dscfg['timeinfo'],
'parametrization': parametrization,
'zdr_kdpzh_dict': zdr_kdpzh_dict
}})
dscfg['initialized'] = 1
if dscfg['initialized'] == 1:
# get user defined values
rsmooth = dscfg.get('rsmooth', 2000.)
min_rhohv = dscfg.get('min_rhohv', 0.92)
min_zdr = dscfg.get('min_zdr', 0.2)
filter_rain = dscfg.get('filter_rain', True)
max_phidp = dscfg.get('max_phidp', 20.)
ml_thickness = dscfg.get('ml_thickness', 700.)
rcell = dscfg.get('rcell', 15000.)
check_wet_radome = dscfg.get('check_wet_radome', True)
wet_radome_refl = dscfg.get('wet_radome_refl', 25.)
wet_radome_rng_min = dscfg.get('wet_radome_rng_min', 2000.)
wet_radome_rng_max = dscfg.get('wet_radome_rng_max', 4000.)
wet_radome_ngates_min = dscfg.get('wet_radome_ngates_min', 180)
bias_per_gate = dscfg.get('bias_per_gate', False)
r_res = radar.range['data'][1]-radar.range['data'][0]
smooth_wind_len = int(rsmooth/r_res)
min_rcons = int(rcell/r_res)
wet_radome_len_min = int(wet_radome_rng_min/r_res)
wet_radome_len_max = int(wet_radome_rng_max/r_res)
kdp_data_dict, refl_bias, selfcons_dict = pyart.correct.selfconsistency_bias2(
radar, dscfg['global_data']['zdr_kdpzh_dict'],
min_rhohv=min_rhohv, min_zdr=min_zdr, filter_rain=filter_rain,
max_phidp=max_phidp, smooth_wind_len=smooth_wind_len, doc=15,
fzl=fzl, thickness=ml_thickness, min_rcons=min_rcons,
parametrization=parametrization, refl_field=refl,
phidp_field=phidp, zdr_field=zdr, temp_field=temp,
iso0_field=iso0, hydro_field=hydro, rhohv_field=rhohv,
kdp_field=kdp, temp_ref=temp_ref,
check_wet_radome=check_wet_radome,
wet_radome_refl=wet_radome_refl,
wet_radome_len_min=wet_radome_len_min,
wet_radome_len_max=wet_radome_len_max, keep_points=keep_points,
bias_per_gate=bias_per_gate)
if keep_points:
if selfcons_dict is not None:
dscfg['global_data']['selfconsistency_points']['zdr'].extend(
selfcons_dict['zdr'])
dscfg['global_data']['selfconsistency_points']['zh'].extend(
selfcons_dict['zh'])
dscfg['global_data']['selfconsistency_points']['kdp'].extend(
selfcons_dict['kdp'])
if kdp_data_dict is not None:
dscfg['global_data']['kdp_data_dict']['kdp_sim'].extend(
kdp_data_dict['kdp_sim'])
dscfg['global_data']['kdp_data_dict']['kdp_obs'].extend(
kdp_data_dict['kdp_obs'])
# prepare for exit
dataset = None
if bias_type == 'instant':
reflectivity_bias = {
'value': np.ma.masked,
'npoints': 0,
'timeinfo': dscfg['timeinfo'],
'bias_type': 'instant'}
if kdp_data_dict is not None:
kdp_obs = np.ma.array(kdp_data_dict['kdp_obs'])
kdp_sim = np.ma.array(kdp_data_dict['kdp_sim'])
reflectivity_bias['value'] = 10.*np.ma.log10(
np.ma.sum(kdp_sim)/np.ma.sum(kdp_obs))
reflectivity_bias['npoints'] = kdp_obs.size
if provide_confidence:
samples = ratio_bootstrapping(
kdp_sim, kdp_obs, iter=nsamples_confidence)
reflectivity_bias.update(
{'samples': 10.*np.ma.log10(samples)})
dataset = {'reflectivity_bias': reflectivity_bias}
if bias_per_gate:
if refl_bias is not None:
if dataset is None:
dataset = {'radar_out': deepcopy(radar)}
else:
dataset.update({'radar_out': deepcopy(radar)})
dataset['radar_out'].fields = dict()
dataset['radar_out'].add_field(
'reflectivity_bias', refl_bias)
return dataset, ind_rad
def process_estimate_phidp0(procstatus, dscfg, radar_list=None):
"""
estimates the system differential phase offset at each ray
Parameters
----------
procstatus : int
Processing status: 0 initializing, 1 processing volume,
2 post-processing
dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords::
datatype : list of string. Dataset keyword
The input data types
rmin : float. Dataset keyword
The minimum range where to look for valid data [m]
rmax : float. Dataset keyword
The maximum range where to look for valid data [m]
rcell : float. Dataset keyword
The length of a continuous cell to consider it valid precip [m]
Zmin : float. Dataset keyword
The minimum reflectivity [dBZ]
Zmax : float. Dataset keyword
The maximum reflectivity [dBZ]
radar_list : list of Radar objects
Optional. list of radar objects
Returns
-------
new_dataset : dict
dictionary containing the output
ind_rad : int
radar index
"""
if procstatus != 1:
return None, None
for datatypedescr in dscfg['datatype']:
radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr)
if datatype == 'dBZ':
refl_field = 'reflectivity'
if datatype == 'dBZc':
refl_field = 'corrected_reflectivity'
if datatype == 'PhiDP':
psidp_field = 'differential_phase'
if datatype == 'PhiDPc':
psidp_field = 'corrected_differential_phase'
if datatype == 'uPhiDP':
psidp_field = 'uncorrected_differential_phase'
ind_rad = int(radarnr[5:8])-1
if radar_list[ind_rad] is None:
warn('No valid radar')
return None, None
radar = radar_list[ind_rad]
if (refl_field not in radar.fields) or (psidp_field not in radar.fields):
warn('Unable to estimate PhiDP system offset. Missing data')
return None, None
ind_rmin = np.where(radar.range['data'] > dscfg['rmin'])[0][0]
ind_rmax = np.where(radar.range['data'] < dscfg['rmax'])[0][-1]
r_res = radar.range['data'][1]-radar.range['data'][0]
min_rcons = int(dscfg['rcell']/r_res)
phidp0, first_gates = pyart.correct.det_sys_phase_ray(
radar, ind_rmin=ind_rmin, ind_rmax=ind_rmax, min_rcons=min_rcons,
zmin=dscfg['Zmin'], zmax=dscfg['Zmax'], phidp_field=psidp_field,
refl_field=refl_field)
# prepare for exit
new_dataset = {'radar_out': deepcopy(radar)}
new_dataset['radar_out'].fields = dict()
new_dataset['radar_out'].add_field('system_differential_phase', phidp0)
new_dataset['radar_out'].add_field(
'first_gate_differential_phase', first_gates)
return new_dataset, ind_rad
def process_rhohv_rain(procstatus, dscfg, radar_list=None):
"""
Keeps only suitable data to evaluate the 80 percentile of RhoHV in rain
Parameters
----------
procstatus : int
Processing status: 0 initializing, 1 processing volume,
2 post-processing
dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords::
datatype : list of string. Dataset keyword
The input data types
rmin : float. Dataset keyword
minimum range where to look for rain [m]. Default 1000.
rmax : float. Dataset keyword
maximum range where to look for rain [m]. Default 50000.
Zmin : float. Dataset keyword
minimum reflectivity to consider the bin as precipitation [dBZ].
Default 20.
Zmax : float. Dataset keyword
maximum reflectivity to consider the bin as precipitation [dBZ]
Default 40.
ml_thickness : float. Dataset keyword
assumed thickness of the melting layer. Default 700.
fzl : float. Dataset keyword
The default freezing level height. It will be used if no
temperature field name is specified or the temperature field is
not in the radar object. Default 2000.
radar_list : list of Radar objects
Optional. list of radar objects
Returns
-------
new_dataset : dict
dictionary containing the output
ind_rad : int
radar index
"""
if procstatus != 1:
return None, None
temp_field = None
iso0_field = None
for datatypedescr in dscfg['datatype']:
radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr)
if datatype == 'RhoHV':
rhohv_field = 'cross_correlation_ratio'
if datatype == 'RhoHVc':
rhohv_field = 'corrected_cross_correlation_ratio'
if datatype == 'uRhoHV':
rhohv_field = 'uncorrected_cross_correlation_ratio'
if datatype == 'dBZc':
refl_field = 'corrected_reflectivity'
if datatype == 'dBZ':
refl_field = 'reflectivity'
if datatype == 'TEMP':
temp_field = 'temperature'
if datatype == 'H_ISO0':
iso0_field = 'height_over_iso0'
ind_rad = int(radarnr[5:8])-1
if radar_list[ind_rad] is None:
warn('No valid radar')
return None, None
radar = radar_list[ind_rad]
if ((refl_field not in radar.fields) or
(rhohv_field not in radar.fields)):
warn('Unable to estimate RhoHV in rain. Missing data')
return None, None
# determine which freezing level reference
temp_ref = 'temperature'
if temp_field is None and iso0_field is None:
warn('Field to obtain the freezing level was not specified. ' +
'Using fixed freezing level height')
temp_ref = 'fixed_fzl'
elif temp_field is not None:
if temp_field not in radar.fields:
warn('COSMO temperature field not available. ' +
'Using fixed freezing level height')
temp_ref = 'fixed_fzl'
elif iso0_field is not None:
if iso0_field not in radar.fields:
warn('Height over iso0 field not available. ' +
'Using fixed freezing level height')
temp_ref = 'fixed_fzl'
else:
temp_ref = 'height_over_iso0'
# determine freezing level height if necessary
fzl = None
if temp_ref == 'fixed_fzl':
if 'fzl' in dscfg:
fzl = dscfg['fzl']
else:
fzl = 2000.
warn('Freezing level height not defined. Using default ' +
str(fzl)+' m')
# default values
rmin = 1000.
rmax = 50000.
zmin = 20.
zmax = 40.
thickness = 700.
# user defined values
if 'rmin' in dscfg:
rmin = dscfg['rmin']
if 'rmax' in dscfg:
rmax = dscfg['rmax']
if 'Zmin' in dscfg:
zmin = dscfg['Zmin']
if 'Zmax' in dscfg:
zmax = dscfg['Zmax']
if 'ml_thickness' in dscfg:
thickness = dscfg['ml_thickness']
ind_rmin = np.where(radar.range['data'] > rmin)[0][0]
ind_rmax = np.where(radar.range['data'] < rmax)[0][-1]
rhohv_rain = pyart.correct.est_rhohv_rain(
radar, ind_rmin=ind_rmin, ind_rmax=ind_rmax, zmin=zmin,
zmax=zmax, thickness=thickness, doc=15, fzl=fzl,
rhohv_field=rhohv_field, temp_field=temp_field, iso0_field=iso0_field,
refl_field=refl_field, temp_ref=temp_ref)
# prepare for exit
new_dataset = {'radar_out': deepcopy(radar)}
new_dataset['radar_out'].fields = dict()
new_dataset['radar_out'].add_field(
'cross_correlation_ratio_in_rain', rhohv_rain)
return new_dataset, ind_rad
def process_zdr_precip(procstatus, dscfg, radar_list=None):
"""
Keeps only suitable data to evaluate the differential reflectivity in
moderate rain or precipitation (for vertical scans)
Parameters
----------
procstatus : int
Processing status: 0 initializing, 1 processing volume,
2 post-processing
dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords::
datatype : list of string. Dataset keyword
The input data types
ml_filter : boolean. Dataset keyword
indicates if a filter on data in and above the melting layer is
applied. Default True.
rmin : float. Dataset keyword
minimum range where to look for rain [m]. Default 1000.
rmax : float. Dataset keyword
maximum range where to look for rain [m]. Default 50000.
Zmin : float. Dataset keyword
minimum reflectivity to consider the bin as precipitation [dBZ].
Default 20.
Zmax : float. Dataset keyword
maximum reflectivity to consider the bin as precipitation [dBZ]
Default 22.
RhoHVmin : float. Dataset keyword
minimum RhoHV to consider the bin as precipitation
Default 0.97
PhiDPmax : float. Dataset keyword
maximum PhiDP to consider the bin as precipitation [deg]
Default 10.
elmax : float. Dataset keyword
maximum elevation angle where to look for precipitation [deg]
Default None.
ml_thickness : float. Dataset keyword
assumed thickness of the melting layer. Default 700.
fzl : float. Dataset keyword
The default freezing level height. It will be used if no
temperature field name is specified or the temperature field is
not in the radar object. Default 2000.
radar_list : list of Radar objects
Optional. list of radar objects
Returns
-------
new_dataset : dict
dictionary containing the output
ind_rad : int
radar index
"""
if procstatus != 1:
return None, None
temp_field = None
iso0_field = None
for datatypedescr in dscfg['datatype']:
radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr)
if datatype == 'ZDR':
zdr_field = 'differential_reflectivity'
if datatype == 'ZDRc':
zdr_field = 'corrected_differential_reflectivity'
if datatype == 'PhiDP':
phidp_field = 'differential_phase'
if datatype == 'PhiDPc':
phidp_field = 'corrected_differential_phase'
if datatype == 'RhoHV':
rhohv_field = 'cross_correlation_ratio'
if datatype == 'RhoHVc':
rhohv_field = 'corrected_cross_correlation_ratio'
if datatype == 'uRhoHV':
rhohv_field = 'uncorrected_cross_correlation_ratio'
if datatype == 'dBZc':
refl_field = 'corrected_reflectivity'
if datatype == 'dBZ':
refl_field = 'reflectivity'
if datatype == 'TEMP':
temp_field = 'temperature'
if datatype == 'H_ISO0':
iso0_field = 'height_over_iso0'
ind_rad = int(radarnr[5:8])-1
if radar_list[ind_rad] is None:
warn('No valid radar')
return None, None
radar = radar_list[ind_rad]
if ((refl_field not in radar.fields) or
(rhohv_field not in radar.fields) or
(zdr_field not in radar.fields) or
(phidp_field not in radar.fields)):
warn('Unable to estimate ZDR in rain. Missing data')
return None, None
# if data in and above the melting layer has to be filtered determine the
# field to use
fzl = None
ml_filter = True
if 'ml_filter' in dscfg:
ml_filter = dscfg['ml_filter']
if ml_filter:
# determine which freezing level reference
temp_ref = 'temperature'
if temp_field is None and iso0_field is None:
warn('Field to obtain the freezing level was not specified. ' +
'Using fixed freezing level height')
temp_ref = 'fixed_fzl'
elif temp_field is not None:
if temp_field not in radar.fields:
warn('COSMO temperature field not available. ' +
'Using fixed freezing level height')
temp_ref = 'fixed_fzl'
elif iso0_field is not None:
if iso0_field not in radar.fields:
warn('Height over iso0 field not available. ' +
'Using fixed freezing level height')
temp_ref = 'fixed_fzl'
else:
temp_ref = 'height_over_iso0'
# determine freezing level height if necessary
if temp_ref == 'fixed_fzl':
if 'fzl' in dscfg:
fzl = dscfg['fzl']
else:
fzl = 2000.
warn('Freezing level height not defined. Using default ' +
str(fzl)+' m')
else:
temp_ref = None
# default values
rmin = 1000.
rmax = 50000.
zmin = 20.
zmax = 22.
rhohvmin = 0.97
phidpmax = 10.
elmax = None
thickness = 700.
# user defined values
if 'rmin' in dscfg:
rmin = dscfg['rmin']
if 'rmax' in dscfg:
rmax = dscfg['rmax']
if 'Zmin' in dscfg:
zmin = dscfg['Zmin']
if 'Zmax' in dscfg:
zmax = dscfg['Zmax']
if 'RhoHVmin' in dscfg:
rhohvmin = dscfg['RhoHVmin']
if 'PhiDPmax' in dscfg:
phidpmax = dscfg['PhiDPmax']
if 'elmax' in dscfg:
elmax = dscfg['elmax']
if 'ml_thickness' in dscfg:
thickness = dscfg['ml_thickness']
ind_rmin = np.where(radar.range['data'] > rmin)[0][0]
ind_rmax = np.where(radar.range['data'] < rmax)[0][-1]
zdr_precip = pyart.correct.est_zdr_precip(
radar, ind_rmin=ind_rmin, ind_rmax=ind_rmax, zmin=zmin,
zmax=zmax, rhohvmin=rhohvmin, phidpmax=phidpmax, elmax=elmax,
thickness=thickness, doc=15, fzl=fzl, zdr_field=zdr_field,
rhohv_field=rhohv_field, phidp_field=phidp_field,
temp_field=temp_field, iso0_field=iso0_field, refl_field=refl_field,
temp_ref=temp_ref)
# prepare for exit
new_dataset = {'radar_out': deepcopy(radar)}
new_dataset['radar_out'].fields = dict()
new_dataset['radar_out'].add_field(
'differential_reflectivity_in_precipitation', zdr_precip)
return new_dataset, ind_rad
def process_zdr_snow(procstatus, dscfg, radar_list=None):
"""
Keeps only suitable data to evaluate the differential reflectivity in
snow
Parameters
----------
procstatus : int
Processing status: 0 initializing, 1 processing volume,
2 post-processing
dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords::
datatype : list of string. Dataset keyword
The input data types
rmin : float. Dataset keyword
minimum range where to look for rain [m]. Default 1000.
rmax : float. Dataset keyword
maximum range where to look for rain [m]. Default 50000.
Zmin : float. Dataset keyword
minimum reflectivity to consider the bin as snow [dBZ].
Default 0.
Zmax : float. Dataset keyword
maximum reflectivity to consider the bin as snow [dBZ]
Default 30.
SNRmin : float. Dataset keyword
minimum SNR to consider the bin as snow [dB].
Default 10.
SNRmax : float. Dataset keyword
maximum SNR to consider the bin as snow [dB]
Default 50.
RhoHVmin : float. Dataset keyword
minimum RhoHV to consider the bin as snow
Default 0.97
PhiDPmax : float. Dataset keyword
maximum PhiDP to consider the bin as snow [deg]
Default 10.
elmax : float. Dataset keyword
maximum elevation angle where to look for snow [deg]
Default None.
KDPmax : float. Dataset keyword
maximum KDP to consider the bin as snow [deg]
Default None
TEMPmin : float. Dataset keyword
minimum temperature to consider the bin as snow [deg C].
Default None
TEMPmax : float. Dataset keyword
maximum temperature to consider the bin as snow [deg C]
Default None
hydroclass : list of ints. Dataset keyword
list of hydrometeor classes to keep for the analysis
Default [2] (dry snow)
radar_list : list of Radar objects
Optional. list of radar objects
Returns
-------
new_dataset : dict
dictionary containing the output
ind_rad : int
radar index
"""
if procstatus != 1:
return None, None
temp_field = None
kdp_field = None
for datatypedescr in dscfg['datatype']:
radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr)
if datatype == 'ZDR':
zdr_field = 'differential_reflectivity'
if datatype == 'ZDRc':
zdr_field = 'corrected_differential_reflectivity'
if datatype == 'PhiDP':
phidp_field = 'differential_phase'
if datatype == 'PhiDPc':
phidp_field = 'corrected_differential_phase'
if datatype == 'RhoHV':
rhohv_field = 'cross_correlation_ratio'
if datatype == 'RhoHVc':
rhohv_field = 'corrected_cross_correlation_ratio'
if datatype == 'uRhoHV':
rhohv_field = 'uncorrected_cross_correlation_ratio'
if datatype == 'dBZc':
refl_field = 'corrected_reflectivity'
if datatype == 'dBZ':
refl_field = 'reflectivity'
if datatype == 'TEMP':
temp_field = 'temperature'
if datatype == 'PhiDP':
kdp_field = 'specific_differential_phase'
if datatype == 'PhiDPc':
kdp_field = 'corrected_specific_differential_phase'
if datatype == 'SNRh':
snr_field = 'signal_to_noise_ratio_hh'
if datatype == 'SNRv':
snr_field = 'signal_to_noise_ratio_vv'
if datatype == 'hydro':
hydro_field = 'radar_echo_classification'
ind_rad = int(radarnr[5:8])-1
if radar_list[ind_rad] is None:
warn('No valid radar')
return None, None
radar = radar_list[ind_rad]
if ((refl_field not in radar.fields) or
(rhohv_field not in radar.fields) or
(zdr_field not in radar.fields) or
(phidp_field not in radar.fields) or
(hydro_field not in radar.fields)):
warn('Unable to estimate ZDR in snow. Missing data')
return None, None
# User defined values
rmin = dscfg.get('rmin', 1000.)
rmax = dscfg.get('rmax', 50000.)
zmin = dscfg.get('Zmin', 0.)
zmax = dscfg.get('Zmax', 30.)
snrmin = dscfg.get('SNRmin', 10.)
snrmax = dscfg.get('SNRmax', 50.)
rhohvmin = dscfg.get('RhoHVmin', 0.97)
phidpmax = dscfg.get('PhiDPmax', 10.)
elmax = dscfg.get('elmax', None)
kdpmax = dscfg.get('KDPmax', None)
tempmin = dscfg.get('TEMPmin', None)
tempmax = dscfg.get('TEMPmax', None)
hydroclass = dscfg.get('hydroclass', [2])
ind_rmin = np.where(radar.range['data'] > rmin)[0][0]
ind_rmax = np.where(radar.range['data'] < rmax)[0][-1]
zdr_snow = pyart.correct.est_zdr_snow(
radar, ind_rmin=ind_rmin, ind_rmax=ind_rmax, zmin=zmin, zmax=zmax,
snrmin=snrmin, snrmax=snrmax, rhohvmin=rhohvmin,
kept_values=hydroclass, phidpmax=phidpmax, kdpmax=kdpmax,
tempmin=tempmin, tempmax=tempmax, elmax=elmax, zdr_field=zdr_field,
rhohv_field=rhohv_field, phidp_field=phidp_field,
temp_field=temp_field, snr_field=snr_field, hydro_field=hydro_field,
kdp_field=kdp_field, refl_field=refl_field)
# prepare for exit
new_dataset = {'radar_out': deepcopy(radar)}
new_dataset['radar_out'].fields = dict()
new_dataset['radar_out'].add_field(
'differential_reflectivity_in_snow', zdr_snow)
return new_dataset, ind_rad
def process_monitoring(procstatus, dscfg, radar_list=None):
"""
computes monitoring statistics
Parameters
----------
procstatus : int
Processing status: 0 initializing, 1 processing volume,
2 post-processing
dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords::
datatype : list of string. Dataset keyword
The input data types
step : float. Dataset keyword
The width of the histogram bin. Default is None. In that case the
default step in function get_histogram_bins is used
max_rays : int. Dataset keyword
The maximum number of rays per sweep used when computing the
histogram. If set above 0 the number of rays per sweep will be
checked and if above max_rays the last rays of the sweep will be
removed
radar_list : list of Radar objects
Optional. list of radar objects
Returns
-------
new_dataset : Radar
radar object containing histogram data
ind_rad : int
radar index
"""
if procstatus == 0:
return None, None
if procstatus == 1:
for datatypedescr in dscfg['datatype']:
radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr)
field_name = get_fieldname_pyart(datatype)
break
ind_rad = int(radarnr[5:8])-1
if radar_list[ind_rad] is None:
warn('No valid radar')
return None, None
radar = radar_list[ind_rad]
if field_name not in radar.fields:
warn(field_name+' not available.')
return None, None
step = dscfg.get('step', None)
max_rays = dscfg.get('max_rays', 0)
bin_edges = get_histogram_bins(field_name, step=step)
nbins = len(bin_edges)-1
step = bin_edges[1]-bin_edges[0]
bin_centers = bin_edges[:-1]+step/2.
radar_aux = deepcopy(radar)
if max_rays > 0:
# remove excess of rays
ind_above_max = np.where(
radar.rays_per_sweep['data'] > max_rays)[0]
if ind_above_max.size > 0:
radar_aux.rays_per_sweep['data'][ind_above_max] = max_rays
for ind in ind_above_max:
excess_rays = radar.rays_per_sweep['data'][ind]-max_rays
radar_aux.sweep_end_ray_index['data'][ind:] -= (
excess_rays)
if ind < radar.nsweeps-1:
radar_aux.sweep_start_ray_index['data'][ind+1:] = (
radar_aux.sweep_end_ray_index['data'][ind:-1]+1)
radar_aux.nrays = np.sum(radar_aux.rays_per_sweep['data'])
radar_aux.fields[field_name]['data'] = np.ma.masked_all(
(radar_aux.nrays, radar_aux.ngates),
dtype=radar.fields[field_name]['data'].dtype)
radar_aux.azimuth['data'] = np.empty(
radar_aux.nrays, dtype=radar.azimuth['data'].dtype)
radar_aux.elevation['data'] = np.empty(
radar_aux.nrays, dtype=radar.elevation['data'].dtype)
radar_aux.time['data'] = np.empty(
radar_aux.nrays, dtype=radar.time['data'].dtype)
for sweep in range(radar.nsweeps):
ind_start_old = radar.sweep_start_ray_index['data'][sweep]
nrays_sweep = radar_aux.rays_per_sweep['data'][sweep]
ind_start_new = radar_aux.sweep_start_ray_index['data'][
sweep]
ind_end_new = radar_aux.sweep_end_ray_index['data'][sweep]
radar_aux.fields[field_name]['data'][
ind_start_new:ind_end_new+1, :] = (
radar.fields[field_name]['data'][
ind_start_old:ind_start_old+nrays_sweep, :])
radar_aux.azimuth['data'][ind_start_new:ind_end_new+1] = (
radar.azimuth['data'][
ind_start_old:ind_start_old+nrays_sweep])
radar_aux.elevation['data'][
ind_start_new:ind_end_new+1] = (
radar.elevation['data'][
ind_start_old:ind_start_old+nrays_sweep])
radar_aux.time['data'][ind_start_new:ind_end_new+1] = (
radar.time['data'][
ind_start_old:ind_start_old+nrays_sweep])
radar_hist = deepcopy(radar_aux)
radar_hist.fields = dict()
radar_hist.range['data'] = bin_centers
radar_hist.ngates = nbins
field_dict = pyart.config.get_metadata(field_name)
field_dict['data'] = np.ma.zeros((radar_aux.nrays, nbins), dtype=int)
field = deepcopy(radar_aux.fields[field_name]['data'])
# put gates with values off limits to limit
mask = np.ma.getmaskarray(field)
ind = np.where(np.logical_and(mask == False, field < bin_centers[0]))
field[ind] = bin_centers[0]
ind = np.where(np.logical_and(mask == False, field > bin_centers[-1]))
field[ind] = bin_centers[-1]
for ray in range(radar_aux.nrays):
field_dict['data'][ray, :], bin_edges = np.histogram(
field[ray, :].compressed(), bins=bin_edges)
radar_hist.add_field(field_name, field_dict)
start_time = pyart.graph.common.generate_radar_time_begin(radar_hist)
# keep histogram in Memory or add to existing histogram
if dscfg['initialized'] == 0:
dscfg['global_data'] = {'hist_obj': radar_hist,
'timeinfo': start_time}
dscfg['initialized'] = 1
else:
field_interp = interpol_field(
dscfg['global_data']['hist_obj'], radar_hist, field_name,
fill_value=0)
dscfg['global_data']['hist_obj'].fields[field_name]['data'] += (
field_interp['data'].filled(fill_value=0)).astype('int64')
# dscfg['global_data']['timeinfo'] = dscfg['timeinfo']
dataset = dict()
dataset.update({'hist_obj': radar_hist})
dataset.update({'hist_type': 'instant'})
dataset.update({'timeinfo': start_time})
return dataset, ind_rad
if procstatus == 2:
if dscfg['initialized'] == 0:
return None, None
for datatypedescr in dscfg['datatype']:
radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr)
field_name = get_fieldname_pyart(datatype)
break
ind_rad = int(radarnr[5:8])-1
dataset = dict()
dataset.update({'hist_obj': dscfg['global_data']['hist_obj']})
dataset.update({'hist_type': 'cumulative'})
dataset.update({'timeinfo': dscfg['global_data']['timeinfo']})
return dataset, ind_rad
| 38.861423 | 86 | 0.597083 | 7,327 | 62,256 | 4.878668 | 0.061144 | 0.021261 | 0.03136 | 0.013428 | 0.821938 | 0.80644 | 0.78336 | 0.765009 | 0.750909 | 0.732502 | 0 | 0.013434 | 0.314893 | 62,256 | 1,601 | 87 | 38.885696 | 0.824651 | 0.272183 | 0 | 0.716942 | 1 | 0 | 0.196345 | 0.047838 | 0 | 0 | 0 | 0 | 0 | 1 | 0.008264 | false | 0 | 0.009298 | 0 | 0.063017 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
cb1fb11d71097166f5d564ef924aa75e741f9d9a | 2,902 | py | Python | Plugins/UnrealEnginePython/Binaries/Win64/Lib/site-packages/tensorflow/_api/v1/linalg/__init__.py | JustinACoder/H22-GR3-UnrealAI | 361eb9ef1147f8a2991e5f98c4118cd823184adf | [
"MIT"
] | 6 | 2022-02-04T18:12:24.000Z | 2022-03-21T23:57:12.000Z | Lib/site-packages/tensorflow/_api/v1/linalg/__init__.py | shfkdroal/Robot-Learning-in-Mixed-Adversarial-and-Collaborative-Settings | 1fa4cd6a566c8745f455fc3d2273208f21f88ced | [
"bzip2-1.0.6"
] | null | null | null | Lib/site-packages/tensorflow/_api/v1/linalg/__init__.py | shfkdroal/Robot-Learning-in-Mixed-Adversarial-and-Collaborative-Settings | 1fa4cd6a566c8745f455fc3d2273208f21f88ced | [
"bzip2-1.0.6"
] | 1 | 2022-02-08T03:53:23.000Z | 2022-02-08T03:53:23.000Z | # This file is MACHINE GENERATED! Do not edit.
# Generated by: tensorflow/python/tools/api/generator/create_python_api.py script.
"""Operations for linear algebra.
"""
from __future__ import print_function
from tensorflow.python import cholesky
from tensorflow.python import cholesky_solve
from tensorflow.python import cross
from tensorflow.python import diag as tensor_diag
from tensorflow.python import diag_part as tensor_diag_part
from tensorflow.python import einsum
from tensorflow.python import eye
from tensorflow.python import global_norm
from tensorflow.python import log_matrix_determinant as slogdet
from tensorflow.python import matmul
from tensorflow.python import matrix_band_part as band_part
from tensorflow.python import matrix_determinant as det
from tensorflow.python import matrix_diag as diag
from tensorflow.python import matrix_diag_part as diag_part
from tensorflow.python import matrix_inverse as inv
from tensorflow.python import matrix_logarithm as logm
from tensorflow.python import matrix_set_diag as set_diag
from tensorflow.python import matrix_solve as solve
from tensorflow.python import matrix_solve_ls as lstsq
from tensorflow.python import matrix_transpose as transpose
from tensorflow.python import matrix_triangular_solve as triangular_solve
from tensorflow.python import norm
from tensorflow.python import qr
from tensorflow.python import self_adjoint_eig as eigh
from tensorflow.python import self_adjoint_eigvals as eigvalsh
from tensorflow.python import svd
from tensorflow.python import tensordot
from tensorflow.python import trace
from tensorflow.python.ops.linalg.linalg import LinearOperator
from tensorflow.python.ops.linalg.linalg import LinearOperatorBlockDiag
from tensorflow.python.ops.linalg.linalg import LinearOperatorCirculant
from tensorflow.python.ops.linalg.linalg import LinearOperatorCirculant2D
from tensorflow.python.ops.linalg.linalg import LinearOperatorCirculant3D
from tensorflow.python.ops.linalg.linalg import LinearOperatorComposition
from tensorflow.python.ops.linalg.linalg import LinearOperatorDiag
from tensorflow.python.ops.linalg.linalg import LinearOperatorFullMatrix
from tensorflow.python.ops.linalg.linalg import LinearOperatorIdentity
from tensorflow.python.ops.linalg.linalg import LinearOperatorKronecker
from tensorflow.python.ops.linalg.linalg import LinearOperatorLowRankUpdate
from tensorflow.python.ops.linalg.linalg import LinearOperatorLowerTriangular
from tensorflow.python.ops.linalg.linalg import LinearOperatorScaledIdentity
from tensorflow.python.ops.linalg.linalg import LinearOperatorZeros
from tensorflow.python.ops.linalg.linalg import adjoint
from tensorflow.python.ops.linalg.linalg import logdet
from tensorflow.python.ops.linalg.linalg import matrix_exponential as expm
from tensorflow.python.ops.nn import l2_normalize
del print_function
| 51.821429 | 83 | 0.855617 | 383 | 2,902 | 6.373368 | 0.224543 | 0.30807 | 0.376895 | 0.298238 | 0.595658 | 0.424007 | 0.285539 | 0 | 0 | 0 | 0 | 0.001153 | 0.103722 | 2,902 | 55 | 84 | 52.763636 | 0.937332 | 0.054101 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.979167 | 0 | 0.979167 | 0.041667 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
cb3dfb6191946d73c05959de5c99b8ee9660001a | 178 | py | Python | src/sqlIntuitive/exceptions/parameterExceptions/subexceptions/__init__.py | einfachIrgendwer0815/SqlIntuitive | 11a0548ac2d6cfce295952bbf0f09a4faa4c42af | [
"MIT"
] | 6 | 2021-09-10T10:34:47.000Z | 2022-03-09T13:50:39.000Z | src/sqlIntuitive/exceptions/parameterExceptions/subexceptions/__init__.py | einfachIrgendwer0815/SqlIntuitive | 11a0548ac2d6cfce295952bbf0f09a4faa4c42af | [
"MIT"
] | 1 | 2021-11-25T07:10:16.000Z | 2021-11-26T12:18:14.000Z | src/sqlIntuitive/exceptions/parameterExceptions/subexceptions/__init__.py | einfachIrgendwer0815/SqlIntuitive | 11a0548ac2d6cfce295952bbf0f09a4faa4c42af | [
"MIT"
] | null | null | null | from sqlIntuitive.exceptions.parameterExceptions.subexceptions.invalidConstraintExceptions import *
from sqlIntuitive.exceptions.parameterExceptions.subexceptions.other import *
| 59.333333 | 99 | 0.898876 | 14 | 178 | 11.428571 | 0.571429 | 0.2 | 0.325 | 0.5625 | 0.725 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.044944 | 178 | 2 | 100 | 89 | 0.941176 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 1 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 8 |
cb8ab5949ae70e4dece989275017f23b82f3adbc | 171 | py | Python | physDBD/gauss/__init__.py | smrfeld/phys_dbd | 38743d753a8a0fe9259453da6fce7260ec175364 | [
"MIT"
] | null | null | null | physDBD/gauss/__init__.py | smrfeld/phys_dbd | 38743d753a8a0fe9259453da6fce7260ec175364 | [
"MIT"
] | null | null | null | physDBD/gauss/__init__.py | smrfeld/phys_dbd | 38743d753a8a0fe9259453da6fce7260ec175364 | [
"MIT"
] | null | null | null | from .dparams0_traj import *
from .dparams0 import *
from .net import *
from .params_traj import *
from .params import *
from .params0_traj import *
from .params0 import * | 24.428571 | 28 | 0.760234 | 24 | 171 | 5.291667 | 0.291667 | 0.472441 | 0.330709 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.027778 | 0.157895 | 171 | 7 | 29 | 24.428571 | 0.854167 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
cbdff8a6104a7ffe10627c3836cbce07ec0bb989 | 1,556 | py | Python | dpa_chile/models.py | epineda/django-dpa-chile | aeb00b1d113d6e7bc896426552e4507afd166ef3 | [
"MIT"
] | 1 | 2019-03-08T03:20:55.000Z | 2019-03-08T03:20:55.000Z | dpa_chile/models.py | epineda/django-dpa-chile | aeb00b1d113d6e7bc896426552e4507afd166ef3 | [
"MIT"
] | null | null | null | dpa_chile/models.py | epineda/django-dpa-chile | aeb00b1d113d6e7bc896426552e4507afd166ef3 | [
"MIT"
] | 4 | 2019-03-08T03:34:32.000Z | 2021-04-21T13:57:28.000Z | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models
from django.utils.encoding import python_2_unicode_compatible
@python_2_unicode_compatible
class Region(models.Model):
"""
Region object
"""
codigo = models.CharField(max_length=10, primary_key=True)
tipo = models.CharField(max_length=10)
nombre = models.CharField(max_length=255)
lat = models.CharField(max_length=50)
lng = models.CharField(max_length=50)
url = models.URLField(max_length=200)
def __str__(self):
return self.nombre
@python_2_unicode_compatible
class Provincia(models.Model):
"""
Provincia object
"""
codigo = models.CharField(max_length=10, primary_key=True)
tipo = models.CharField(max_length=10)
nombre = models.CharField(max_length=255)
lat = models.CharField(max_length=50)
lng = models.CharField(max_length=50)
url = models.URLField(max_length=200)
region = models.ForeignKey('Region')
def __str__(self):
return self.nombre
@python_2_unicode_compatible
class Comuna(models.Model):
"""
Comuna object
"""
codigo = models.CharField(max_length=10, primary_key=True)
tipo = models.CharField(max_length=10)
nombre = models.CharField(max_length=255)
lat = models.CharField(max_length=50)
lng = models.CharField(max_length=50)
url = models.URLField(max_length=200)
region = models.ForeignKey('Region')
provincia = models.ForeignKey('Provincia')
def __str__(self):
return self.nombre
| 27.785714 | 62 | 0.709512 | 199 | 1,556 | 5.296482 | 0.221106 | 0.1537 | 0.256167 | 0.341556 | 0.78463 | 0.757116 | 0.732448 | 0.732448 | 0.732448 | 0.732448 | 0 | 0.036863 | 0.180591 | 1,556 | 55 | 63 | 28.290909 | 0.789804 | 0.043059 | 0 | 0.805556 | 0 | 0 | 0.014553 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.083333 | false | 0 | 0.083333 | 0.083333 | 0.916667 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 9 |
6985e9241e1e8f0bddaeed11e0fa925f03e9e79b | 79 | py | Python | app/models/__init__.py | eddy0/todolist | e0b01961271120631eb53dc5364f0fbf15db5d2f | [
"Apache-2.0"
] | null | null | null | app/models/__init__.py | eddy0/todolist | e0b01961271120631eb53dc5364f0fbf15db5d2f | [
"Apache-2.0"
] | null | null | null | app/models/__init__.py | eddy0/todolist | e0b01961271120631eb53dc5364f0fbf15db5d2f | [
"Apache-2.0"
] | null | null | null | from app.models.item_model import Item
from app.models.user_model import User
| 19.75 | 38 | 0.835443 | 14 | 79 | 4.571429 | 0.5 | 0.21875 | 0.40625 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.113924 | 79 | 3 | 39 | 26.333333 | 0.914286 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
6992ca99d13da8801d97284f7680e10b4e4644b9 | 3,011 | py | Python | Lab3/q2_a.py | ViniciusRCortez/Monitoria-de-metodos-numericos-com-python | 85678fe8907752533d0dc97dc83550411ba079f0 | [
"MIT"
] | null | null | null | Lab3/q2_a.py | ViniciusRCortez/Monitoria-de-metodos-numericos-com-python | 85678fe8907752533d0dc97dc83550411ba079f0 | [
"MIT"
] | null | null | null | Lab3/q2_a.py | ViniciusRCortez/Monitoria-de-metodos-numericos-com-python | 85678fe8907752533d0dc97dc83550411ba079f0 | [
"MIT"
] | null | null | null | """
Objetivo: Resolver questão 2a do terceiro laboratorio.
é exatamente o mesmo codigo da questão anterior porém mudando a função a ser passada e o palpite
"""
import matplotlib.pyplot as plt
import numpy as np
from Newton_Raphson import newton_raphson
#PARA X0 = 1
y = lambda x: 180*x**3 - 117*x**2 - 80*x + 52 # f(x) = 180x^3 - 117x^2 - 80x + 52
y_linha = lambda x: 540*x**2 - 234*x - 80 # f'(x) = 540x^2 - 234x - 80
ini = 1 # ponto inicial
#Verificar o arquivo Nexton-Raphson.py para entender o funcionamento dessa função
resp = newton_raphson(ini, y, y_linha, 'q2')
print(f'Para essa X0 = 1 levamos {resp["iterações"] - 1} iterações e temos como valor de f(x) = {resp["modulo"]}')
print('Abaixo seguem os graficos dos valores de f(x) e dos erros, respectivamente:')
# Grafico com os valores de f(x)
x_a = np.linspace(-1.2, 1.2, 30) # valores escolhidos para melhor visualização do grafico
y_a = [y(i) for i in x_a]
plt.style.use('ggplot')
plt.figure(figsize=(7, 5))
plt.title(f'F(x) por X\ncom X0 = 1')
plt.xlabel('Valores de x')
plt.ylabel('Valores de f(x)')
# função com valores entre 0.4 e 0.8
plt.plot(x_a, y_a, label='Função exata')
# Nossa aproximação Newton-Raphson por iteração
plt.plot(resp['valores'], resp['valores_função'], label='Valores de Newton-Raphson por iteração')
plt.tight_layout()
plt.legend(loc='best')
plt.show()
# Grafico com os valores dos erros
plt.style.use('ggplot')
plt.figure(figsize=(7, 5))
plt.title('Erro por Iterações')
plt.xlabel('Numero de iterações')
plt.ylabel('Valores dos erros')
plt.plot([i for i in range(1, resp['iterações'])], resp['erros'])
plt.tight_layout()
plt.show()
#PARA X0 = -1
y = lambda x: 180*x**3 - 117*x**2 - 80*x + 52 # f(x) = 180x^3 - 117x^2 - 80x + 52
y_linha = lambda x: 540*x**2 - 234*x - 80 # f'(x) = 540x^2 - 234x - 80
ini = -1 # ponto inicial
#Verificar o arquivo Nexton-Raphson.py para entender o funcionamento dessa função
resp = newton_raphson(ini, y, y_linha, 'q2')
print(f'Para essa X0 = -1 levamos {resp["iterações"] - 1} iterações e temos como valor de f(x) = {resp["modulo"]}')
print('Abaixo seguem os graficos dos valores de f(x) e dos erros, respectivamente:')
# Grafico com os valores de f(x)
x_a = np.linspace(-1.2, 1.2, 30) # valores escolhidos para melhor visualização do grafico
y_a = [y(i) for i in x_a]
plt.style.use('ggplot')
plt.figure(figsize=(7, 5))
plt.title(f'F(x) por X\ncom X0 = -1')
plt.xlabel('Valores de x')
plt.ylabel('Valores de f(x)')
# função com valores entre 0.4 e 0.8
plt.plot(x_a, y_a, label='Função exata')
# Nossa aproximação Newton-Raphson por iteração
plt.plot(resp['valores'], resp['valores_função'], label='Valores de Newton-Raphson por iteração')
plt.tight_layout()
plt.legend(loc='best')
plt.show()
# Grafico com os valores dos erros
plt.style.use('ggplot')
plt.figure(figsize=(7, 5))
plt.title('Erro por Iterações')
plt.xlabel('Numero de iterações')
plt.ylabel('Valores dos erros')
plt.plot([i for i in range(1, resp['iterações'])], resp['erros'])
plt.tight_layout()
plt.show()
| 38.602564 | 115 | 0.698439 | 546 | 3,011 | 3.807692 | 0.225275 | 0.013468 | 0.015392 | 0.031746 | 0.902357 | 0.902357 | 0.902357 | 0.902357 | 0.902357 | 0.902357 | 0 | 0.051751 | 0.146463 | 3,011 | 77 | 116 | 39.103896 | 0.757198 | 0.295251 | 0 | 0.836364 | 0 | 0.036364 | 0.368496 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.054545 | 0 | 0.054545 | 0.072727 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
699fe19a53dcca152156ecb428694f3408e21869 | 4,637 | py | Python | fittingjob/fittingjob/test_datadog.py | cyberagent-oss/intelligent-hpa | 3b9db9101a885a3b7c54e0e237ad343bde17e9f4 | [
"Apache-2.0"
] | 27 | 2020-06-13T05:17:05.000Z | 2022-03-02T05:27:47.000Z | fittingjob/fittingjob/test_datadog.py | cyberagent-oss/intelligent-hpa | 3b9db9101a885a3b7c54e0e237ad343bde17e9f4 | [
"Apache-2.0"
] | 2 | 2020-06-14T05:54:38.000Z | 2021-04-30T21:27:13.000Z | fittingjob/fittingjob/test_datadog.py | cyberagent-oss/intelligent-hpa | 3b9db9101a885a3b7c54e0e237ad343bde17e9f4 | [
"Apache-2.0"
] | null | null | null | #!/usr/bin/env python3
from datetime import datetime
import pytest
from fittingjob import datadog
@pytest.mark.parametrize(
'tags, expected', [
(
{'key': 'value'},
'key:value'
),
(
{'key1': 'value1', 'key2': 'value2', 'key3': 'value3'},
'key1:value1,key2:value2,key3:value3'
),
(
{},
''
)
]
)
def test_tags_string(tags, expected):
assert datadog.tags_string(tags) == expected
@pytest.mark.parametrize(
'end, days, hours, minutes, expected', [
(
datetime(year=2019, month=12, day=25),
5,
0,
0,
[
{
'start': datetime(year=2019, month=12, day=20),
'end': datetime(year=2019, month=12, day=21)
},
{
'start': datetime(year=2019, month=12, day=21),
'end': datetime(year=2019, month=12, day=22)
},
{
'start': datetime(year=2019, month=12, day=22),
'end': datetime(year=2019, month=12, day=23)
},
{
'start': datetime(year=2019, month=12, day=23),
'end': datetime(year=2019, month=12, day=24)
},
{
'start': datetime(year=2019, month=12, day=24),
'end': datetime(year=2019, month=12, day=25)
},
]
),
(
datetime(year=2019, month=12, day=25, hour=3),
5,
12,
0,
[
{
'start': datetime(year=2019, month=12, day=19, hour=15),
'end': datetime(year=2019, month=12, day=20, hour=15)
},
{
'start': datetime(year=2019, month=12, day=20, hour=15),
'end': datetime(year=2019, month=12, day=21, hour=15)
},
{
'start': datetime(year=2019, month=12, day=21, hour=15),
'end': datetime(year=2019, month=12, day=22, hour=15)
},
{
'start': datetime(year=2019, month=12, day=22, hour=15),
'end': datetime(year=2019, month=12, day=23, hour=15)
},
{
'start': datetime(year=2019, month=12, day=23, hour=15),
'end': datetime(year=2019, month=12, day=24, hour=15)
},
{
'start': datetime(year=2019, month=12, day=24, hour=15),
'end': datetime(year=2019, month=12, day=25, hour=3)
},
]
),
(
datetime(year=2019, month=12, day=25),
5,
36,
10,
[
{
'start': datetime(year=2019, month=12, day=18, hour=11, minute=50),
'end': datetime(year=2019, month=12, day=19, hour=11, minute=50)
},
{
'start': datetime(year=2019, month=12, day=19, hour=11, minute=50),
'end': datetime(year=2019, month=12, day=20, hour=11, minute=50)
},
{
'start': datetime(year=2019, month=12, day=20, hour=11, minute=50),
'end': datetime(year=2019, month=12, day=21, hour=11, minute=50)
},
{
'start': datetime(year=2019, month=12, day=21, hour=11, minute=50),
'end': datetime(year=2019, month=12, day=22, hour=11, minute=50)
},
{
'start': datetime(year=2019, month=12, day=22, hour=11, minute=50),
'end': datetime(year=2019, month=12, day=23, hour=11, minute=50)
},
{
'start': datetime(year=2019, month=12, day=23, hour=11, minute=50),
'end': datetime(year=2019, month=12, day=24, hour=11, minute=50)
},
{
'start': datetime(year=2019, month=12, day=24, hour=11, minute=50),
'end': datetime(year=2019, month=12, day=25)
},
]
)
]
)
def test_separate_date_range_per_days(end, days, hours, minutes, expected):
assert datadog.separate_date_range_per_days(
end, days, hours, minutes) == expected
| 35.128788 | 87 | 0.418805 | 475 | 4,637 | 4.063158 | 0.122105 | 0.242487 | 0.323316 | 0.424352 | 0.873057 | 0.859067 | 0.827979 | 0.811917 | 0.61399 | 0.36114 | 0 | 0.158602 | 0.43843 | 4,637 | 131 | 88 | 35.396947 | 0.582565 | 0.004529 | 0 | 0.129032 | 0 | 0 | 0.059588 | 0.007584 | 0 | 0 | 0 | 0 | 0.016129 | 1 | 0.016129 | false | 0 | 0.024194 | 0 | 0.040323 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
69ad5864332d2ea6177ae5bd31905f17a9391f01 | 108 | py | Python | PaGraph/partition/__init__.py | lzhangbv/PaGraph | 2686a4e2ffcba7de3af1e6bb015b8a4d211160b8 | [
"MIT"
] | 13 | 2021-06-25T23:55:12.000Z | 2022-02-16T22:40:18.000Z | PaGraph/partition/__init__.py | lzhangbv/PaGraph | 2686a4e2ffcba7de3af1e6bb015b8a4d211160b8 | [
"MIT"
] | null | null | null | PaGraph/partition/__init__.py | lzhangbv/PaGraph | 2686a4e2ffcba7de3af1e6bb015b8a4d211160b8 | [
"MIT"
] | 6 | 2021-05-15T13:51:43.000Z | 2022-03-17T07:06:30.000Z | from .partition import kl_2partition
from .refine import build_train_graph
from .refine import wrap_neighbor | 36 | 37 | 0.87037 | 16 | 108 | 5.625 | 0.6875 | 0.222222 | 0.355556 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.010309 | 0.101852 | 108 | 3 | 38 | 36 | 0.917526 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
69e653292be8a77869622bf4d3a708932f857957 | 2,526 | py | Python | tests/test_mission/test_channel_tracker.py | matan1008/srsran-controller | 8389a78976efb7dfe3ef5dc17f5ac14adcae732c | [
"MIT"
] | null | null | null | tests/test_mission/test_channel_tracker.py | matan1008/srsran-controller | 8389a78976efb7dfe3ef5dc17f5ac14adcae732c | [
"MIT"
] | null | null | null | tests/test_mission/test_channel_tracker.py | matan1008/srsran-controller | 8389a78976efb7dfe3ef5dc17f5ac14adcae732c | [
"MIT"
] | null | null | null | from srsran_controller.mission.channel_tracker import ChannelTracker, RA_RESPONSE_NAME, ATTACH_REQUEST_NAME, \
ATTACH_ACCEPT_NAME
def test_create_channel():
tracker = ChannelTracker()
tracker.handle_uu_event({'c-rnti': 20, 'ta': 5, 'event': RA_RESPONSE_NAME})
event = {'rnti': 20}
tracker.enrich_event(event)
assert event == {'rnti': 20, 'ta': 5}
def test_attach_request():
tracker = ChannelTracker()
tracker.handle_uu_event({'c-rnti': 20, 'ta': 5, 'event': RA_RESPONSE_NAME})
tracker.handle_uu_event({'rnti': 20, 'imsi': '001010123456789', 'event': ATTACH_REQUEST_NAME})
event = {'rnti': 20}
tracker.enrich_event(event)
assert event == {'rnti': 20, 'ta': 5, 'imsi': '001010123456789'}
def test_attach_accept():
tracker = ChannelTracker()
tracker.handle_uu_event({'c-rnti': 20, 'ta': 3, 'event': RA_RESPONSE_NAME})
tracker.handle_uu_event({'rnti': 20, 'imsi': '001010123456789', 'event': ATTACH_REQUEST_NAME})
tracker.handle_uu_event({'rnti': 20, 'tmsi': '0x53d764bc', 'event': ATTACH_ACCEPT_NAME, 'ip': '172.16.0.2'})
event = {'rnti': 20}
tracker.enrich_event(event)
assert event == {'rnti': 20, 'ta': 3, 'imsi': '001010123456789', 'ip': '172.16.0.2'}
def test_imsi_to_ip():
tracker = ChannelTracker()
# Test receiving the correct IP.
tracker.handle_uu_event({'c-rnti': 20, 'ta': 3, 'event': RA_RESPONSE_NAME})
tracker.handle_uu_event({'rnti': 20, 'imsi': '001010123456789', 'event': ATTACH_REQUEST_NAME})
tracker.handle_uu_event({'rnti': 20, 'tmsi': '0x53d764bc', 'event': ATTACH_ACCEPT_NAME, 'ip': '172.16.0.2'})
assert tracker.imsi_to_ip('001010123456789') == '172.16.0.2'
# Test receiving the correct IP after other subsribers attach.
tracker.handle_uu_event({'c-rnti': 21, 'ta': 3, 'event': RA_RESPONSE_NAME})
tracker.handle_uu_event({'rnti': 21, 'imsi': '001010123456788', 'event': ATTACH_REQUEST_NAME})
tracker.handle_uu_event({'rnti': 21, 'tmsi': '0x53d764bd', 'event': ATTACH_ACCEPT_NAME, 'ip': '172.16.0.3'})
assert tracker.imsi_to_ip('001010123456789') == '172.16.0.2'
# Test receiving the correct IP after assigning new IP.
tracker.handle_uu_event({'c-rnti': 24, 'ta': 3, 'event': RA_RESPONSE_NAME})
tracker.handle_uu_event({'rnti': 24, 'imsi': '001010123456789', 'event': ATTACH_REQUEST_NAME})
tracker.handle_uu_event({'rnti': 24, 'tmsi': '0x53d764bc', 'event': ATTACH_ACCEPT_NAME, 'ip': '172.16.0.4'})
assert tracker.imsi_to_ip('001010123456789') == '172.16.0.4'
| 51.55102 | 112 | 0.680523 | 349 | 2,526 | 4.679083 | 0.146132 | 0.119412 | 0.137783 | 0.183711 | 0.807103 | 0.787508 | 0.772198 | 0.749541 | 0.731782 | 0.677893 | 0 | 0.129374 | 0.140143 | 2,526 | 48 | 113 | 52.625 | 0.622468 | 0.057403 | 0 | 0.567568 | 0 | 0 | 0.215818 | 0 | 0 | 0 | 0.016828 | 0 | 0.162162 | 1 | 0.108108 | false | 0 | 0.027027 | 0 | 0.135135 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
69e9b0d0cfd3b4ba1ecd1565324b82b3aec20c53 | 109 | py | Python | src/reset_hardware.py | foxdb/raspi-chill | f699c584fc40e15e16faa2c9eee24365fea661ba | [
"MIT"
] | 1 | 2021-08-12T11:24:43.000Z | 2021-08-12T11:24:43.000Z | src/reset_hardware.py | foxdb/raspi-chill | f699c584fc40e15e16faa2c9eee24365fea661ba | [
"MIT"
] | 2 | 2018-10-15T13:11:48.000Z | 2018-11-11T22:30:11.000Z | src/reset_hardware.py | foxdb/raspi-chill | f699c584fc40e15e16faa2c9eee24365fea661ba | [
"MIT"
] | null | null | null | from buzzer import turn_buzzer_off
from cooler import turn_cooling_off
turn_cooling_off()
turn_buzzer_off()
| 18.166667 | 35 | 0.862385 | 18 | 109 | 4.777778 | 0.388889 | 0.232558 | 0.302326 | 0.418605 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.100917 | 109 | 5 | 36 | 21.8 | 0.877551 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 7 |
69edfd510cfd9f2799c4eaed33a5649eec5a3ce6 | 15,808 | py | Python | convertCallData.py | supernovahs/multisig | 8de1362d84c0f61cb1efc00319c9362eb4379f37 | [
"MIT"
] | null | null | null | convertCallData.py | supernovahs/multisig | 8de1362d84c0f61cb1efc00319c9362eb4379f37 | [
"MIT"
] | null | null | null | convertCallData.py | supernovahs/multisig | 8de1362d84c0f61cb1efc00319c9362eb4379f37 | [
"MIT"
] | null | null | null |
import traceback
import sys
from functools import lru_cache
from web3 import Web3
from web3.auto import w3
from web3.contract import Contract
from web3._utils.events import get_event_data
from web3._utils.abi import exclude_indexed_event_inputs, get_abi_input_names, get_indexed_event_inputs, normalize_event_input_types
from web3.exceptions import MismatchedABI, LogTopicError
from web3.types import ABIEvent
from eth_utils import event_abi_to_log_topic, to_hex
from hexbytes import HexBytes
import json
import re
def decode_tuple(t, target_field):
output = dict()
for i in range(len(t)):
if isinstance(t[i], (bytes, bytearray)):
output[target_field[i]['name']] = to_hex(t[i])
elif isinstance(t[i], (tuple)):
output[target_field[i]['name']] = decode_tuple(t[i], target_field[i]['components'])
else:
output[target_field[i]['name']] = t[i]
return output
def decode_list_tuple(l, target_field):
output = l
for i in range(len(l)):
output[i] = decode_tuple(l[i], target_field)
return output
def decode_list(l):
output = l
for i in range(len(l)):
if isinstance(l[i], (bytes, bytearray)):
output[i] = to_hex(l[i])
else:
output[i] = l[i]
return output
def convert_to_hex(arg, target_schema):
"""
utility function to convert byte codes into human readable and json serializable data structures
"""
output = dict()
for k in arg:
if isinstance(arg[k], (bytes, bytearray)):
output[k] = to_hex(arg[k])
elif isinstance(arg[k], (list)) and len(arg[k]) > 0:
target = [a for a in target_schema if 'name' in a and a['name'] == k][0]
if target['type'] == 'tuple[]':
target_field = target['components']
output[k] = decode_list_tuple(arg[k], target_field)
else:
output[k] = decode_list(arg[k])
elif isinstance(arg[k], (tuple)):
target_field = [a['components'] for a in target_schema if 'name' in a and a['name'] == k][0]
output[k] = decode_tuple(arg[k], target_field)
else:
output[k] = arg[k]
return output
@lru_cache(maxsize=None)
def _get_contract(address, abi):
"""
This helps speed up execution of decoding across a large dataset by caching the contract object
It assumes that we are decoding a small set, on the order of thousands, of target smart contracts
"""
if isinstance(abi, (str)):
abi = json.loads(abi)
contract = w3.eth.contract(address=Web3.toChecksumAddress(address), abi=abi)
return (contract, abi)
def decode_tx(address, input_data, abi):
if abi is not None:
try:
(contract, abi) = _get_contract(address, abi)
func_obj, func_params = contract.decode_function_input(input_data)
target_schema = [a['inputs'] for a in abi if 'name' in a and a['name'] == func_obj.fn_name][0]
decoded_func_params = convert_to_hex(func_params, target_schema)
return (func_obj.fn_name, json.dumps(decoded_func_params), json.dumps(target_schema))
except:
e = sys.exc_info()[0]
return ('decode error', repr(e), None)
else:
return ('no matching abi', None, None)
sample_abi = '[{"inputs":[{"internalType":"address","name":"_factory","type":"address"},{"internalType":"address","name":"_WETH","type":"address"}],"stateMutability":"nonpayable","type":"constructor"},{"inputs":[],"name":"WETH","outputs":[{"internalType":"address","name":"","type":"address"}],"stateMutability":"view","type":"function"},{"inputs":[{"internalType":"address","name":"tokenA","type":"address"},{"internalType":"address","name":"tokenB","type":"address"},{"internalType":"uint256","name":"amountADesired","type":"uint256"},{"internalType":"uint256","name":"amountBDesired","type":"uint256"},{"internalType":"uint256","name":"amountAMin","type":"uint256"},{"internalType":"uint256","name":"amountBMin","type":"uint256"},{"internalType":"address","name":"to","type":"address"},{"internalType":"uint256","name":"deadline","type":"uint256"}],"name":"addLiquidity","outputs":[{"internalType":"uint256","name":"amountA","type":"uint256"},{"internalType":"uint256","name":"amountB","type":"uint256"},{"internalType":"uint256","name":"liquidity","type":"uint256"}],"stateMutability":"nonpayable","type":"function"},{"inputs":[{"internalType":"address","name":"token","type":"address"},{"internalType":"uint256","name":"amountTokenDesired","type":"uint256"},{"internalType":"uint256","name":"amountTokenMin","type":"uint256"},{"internalType":"uint256","name":"amountETHMin","type":"uint256"},{"internalType":"address","name":"to","type":"address"},{"internalType":"uint256","name":"deadline","type":"uint256"}],"name":"addLiquidityETH","outputs":[{"internalType":"uint256","name":"amountToken","type":"uint256"},{"internalType":"uint256","name":"amountETH","type":"uint256"},{"internalType":"uint256","name":"liquidity","type":"uint256"}],"stateMutability":"payable","type":"function"},{"inputs":[],"name":"factory","outputs":[{"internalType":"address","name":"","type":"address"}],"stateMutability":"view","type":"function"},{"inputs":[{"internalType":"uint256","name":"amountOut","type":"uint256"},{"internalType":"uint256","name":"reserveIn","type":"uint256"},{"internalType":"uint256","name":"reserveOut","type":"uint256"}],"name":"getAmountIn","outputs":[{"internalType":"uint256","name":"amountIn","type":"uint256"}],"stateMutability":"pure","type":"function"},{"inputs":[{"internalType":"uint256","name":"amountIn","type":"uint256"},{"internalType":"uint256","name":"reserveIn","type":"uint256"},{"internalType":"uint256","name":"reserveOut","type":"uint256"}],"name":"getAmountOut","outputs":[{"internalType":"uint256","name":"amountOut","type":"uint256"}],"stateMutability":"pure","type":"function"},{"inputs":[{"internalType":"uint256","name":"amountOut","type":"uint256"},{"internalType":"address[]","name":"path","type":"address[]"}],"name":"getAmountsIn","outputs":[{"internalType":"uint256[]","name":"amounts","type":"uint256[]"}],"stateMutability":"view","type":"function"},{"inputs":[{"internalType":"uint256","name":"amountIn","type":"uint256"},{"internalType":"address[]","name":"path","type":"address[]"}],"name":"getAmountsOut","outputs":[{"internalType":"uint256[]","name":"amounts","type":"uint256[]"}],"stateMutability":"view","type":"function"},{"inputs":[{"internalType":"uint256","name":"amountA","type":"uint256"},{"internalType":"uint256","name":"reserveA","type":"uint256"},{"internalType":"uint256","name":"reserveB","type":"uint256"}],"name":"quote","outputs":[{"internalType":"uint256","name":"amountB","type":"uint256"}],"stateMutability":"pure","type":"function"},{"inputs":[{"internalType":"address","name":"tokenA","type":"address"},{"internalType":"address","name":"tokenB","type":"address"},{"internalType":"uint256","name":"liquidity","type":"uint256"},{"internalType":"uint256","name":"amountAMin","type":"uint256"},{"internalType":"uint256","name":"amountBMin","type":"uint256"},{"internalType":"address","name":"to","type":"address"},{"internalType":"uint256","name":"deadline","type":"uint256"}],"name":"removeLiquidity","outputs":[{"internalType":"uint256","name":"amountA","type":"uint256"},{"internalType":"uint256","name":"amountB","type":"uint256"}],"stateMutability":"nonpayable","type":"function"},{"inputs":[{"internalType":"address","name":"token","type":"address"},{"internalType":"uint256","name":"liquidity","type":"uint256"},{"internalType":"uint256","name":"amountTokenMin","type":"uint256"},{"internalType":"uint256","name":"amountETHMin","type":"uint256"},{"internalType":"address","name":"to","type":"address"},{"internalType":"uint256","name":"deadline","type":"uint256"}],"name":"removeLiquidityETH","outputs":[{"internalType":"uint256","name":"amountToken","type":"uint256"},{"internalType":"uint256","name":"amountETH","type":"uint256"}],"stateMutability":"nonpayable","type":"function"},{"inputs":[{"internalType":"address","name":"token","type":"address"},{"internalType":"uint256","name":"liquidity","type":"uint256"},{"internalType":"uint256","name":"amountTokenMin","type":"uint256"},{"internalType":"uint256","name":"amountETHMin","type":"uint256"},{"internalType":"address","name":"to","type":"address"},{"internalType":"uint256","name":"deadline","type":"uint256"}],"name":"removeLiquidityETHSupportingFeeOnTransferTokens","outputs":[{"internalType":"uint256","name":"amountETH","type":"uint256"}],"stateMutability":"nonpayable","type":"function"},{"inputs":[{"internalType":"address","name":"token","type":"address"},{"internalType":"uint256","name":"liquidity","type":"uint256"},{"internalType":"uint256","name":"amountTokenMin","type":"uint256"},{"internalType":"uint256","name":"amountETHMin","type":"uint256"},{"internalType":"address","name":"to","type":"address"},{"internalType":"uint256","name":"deadline","type":"uint256"},{"internalType":"bool","name":"approveMax","type":"bool"},{"internalType":"uint8","name":"v","type":"uint8"},{"internalType":"bytes32","name":"r","type":"bytes32"},{"internalType":"bytes32","name":"s","type":"bytes32"}],"name":"removeLiquidityETHWithPermit","outputs":[{"internalType":"uint256","name":"amountToken","type":"uint256"},{"internalType":"uint256","name":"amountETH","type":"uint256"}],"stateMutability":"nonpayable","type":"function"},{"inputs":[{"internalType":"address","name":"token","type":"address"},{"internalType":"uint256","name":"liquidity","type":"uint256"},{"internalType":"uint256","name":"amountTokenMin","type":"uint256"},{"internalType":"uint256","name":"amountETHMin","type":"uint256"},{"internalType":"address","name":"to","type":"address"},{"internalType":"uint256","name":"deadline","type":"uint256"},{"internalType":"bool","name":"approveMax","type":"bool"},{"internalType":"uint8","name":"v","type":"uint8"},{"internalType":"bytes32","name":"r","type":"bytes32"},{"internalType":"bytes32","name":"s","type":"bytes32"}],"name":"removeLiquidityETHWithPermitSupportingFeeOnTransferTokens","outputs":[{"internalType":"uint256","name":"amountETH","type":"uint256"}],"stateMutability":"nonpayable","type":"function"},{"inputs":[{"internalType":"address","name":"tokenA","type":"address"},{"internalType":"address","name":"tokenB","type":"address"},{"internalType":"uint256","name":"liquidity","type":"uint256"},{"internalType":"uint256","name":"amountAMin","type":"uint256"},{"internalType":"uint256","name":"amountBMin","type":"uint256"},{"internalType":"address","name":"to","type":"address"},{"internalType":"uint256","name":"deadline","type":"uint256"},{"internalType":"bool","name":"approveMax","type":"bool"},{"internalType":"uint8","name":"v","type":"uint8"},{"internalType":"bytes32","name":"r","type":"bytes32"},{"internalType":"bytes32","name":"s","type":"bytes32"}],"name":"removeLiquidityWithPermit","outputs":[{"internalType":"uint256","name":"amountA","type":"uint256"},{"internalType":"uint256","name":"amountB","type":"uint256"}],"stateMutability":"nonpayable","type":"function"},{"inputs":[{"internalType":"uint256","name":"amountOut","type":"uint256"},{"internalType":"address[]","name":"path","type":"address[]"},{"internalType":"address","name":"to","type":"address"},{"internalType":"uint256","name":"deadline","type":"uint256"}],"name":"swapETHForExactTokens","outputs":[{"internalType":"uint256[]","name":"amounts","type":"uint256[]"}],"stateMutability":"payable","type":"function"},{"inputs":[{"internalType":"uint256","name":"amountOutMin","type":"uint256"},{"internalType":"address[]","name":"path","type":"address[]"},{"internalType":"address","name":"to","type":"address"},{"internalType":"uint256","name":"deadline","type":"uint256"}],"name":"swapExactETHForTokens","outputs":[{"internalType":"uint256[]","name":"amounts","type":"uint256[]"}],"stateMutability":"payable","type":"function"},{"inputs":[{"internalType":"uint256","name":"amountOutMin","type":"uint256"},{"internalType":"address[]","name":"path","type":"address[]"},{"internalType":"address","name":"to","type":"address"},{"internalType":"uint256","name":"deadline","type":"uint256"}],"name":"swapExactETHForTokensSupportingFeeOnTransferTokens","outputs":[],"stateMutability":"payable","type":"function"},{"inputs":[{"internalType":"uint256","name":"amountIn","type":"uint256"},{"internalType":"uint256","name":"amountOutMin","type":"uint256"},{"internalType":"address[]","name":"path","type":"address[]"},{"internalType":"address","name":"to","type":"address"},{"internalType":"uint256","name":"deadline","type":"uint256"}],"name":"swapExactTokensForETH","outputs":[{"internalType":"uint256[]","name":"amounts","type":"uint256[]"}],"stateMutability":"nonpayable","type":"function"},{"inputs":[{"internalType":"uint256","name":"amountIn","type":"uint256"},{"internalType":"uint256","name":"amountOutMin","type":"uint256"},{"internalType":"address[]","name":"path","type":"address[]"},{"internalType":"address","name":"to","type":"address"},{"internalType":"uint256","name":"deadline","type":"uint256"}],"name":"swapExactTokensForETHSupportingFeeOnTransferTokens","outputs":[],"stateMutability":"nonpayable","type":"function"},{"inputs":[{"internalType":"uint256","name":"amountIn","type":"uint256"},{"internalType":"uint256","name":"amountOutMin","type":"uint256"},{"internalType":"address[]","name":"path","type":"address[]"},{"internalType":"address","name":"to","type":"address"},{"internalType":"uint256","name":"deadline","type":"uint256"}],"name":"swapExactTokensForTokens","outputs":[{"internalType":"uint256[]","name":"amounts","type":"uint256[]"}],"stateMutability":"nonpayable","type":"function"},{"inputs":[{"internalType":"uint256","name":"amountIn","type":"uint256"},{"internalType":"uint256","name":"amountOutMin","type":"uint256"},{"internalType":"address[]","name":"path","type":"address[]"},{"internalType":"address","name":"to","type":"address"},{"internalType":"uint256","name":"deadline","type":"uint256"}],"name":"swapExactTokensForTokensSupportingFeeOnTransferTokens","outputs":[],"stateMutability":"nonpayable","type":"function"},{"inputs":[{"internalType":"uint256","name":"amountOut","type":"uint256"},{"internalType":"uint256","name":"amountInMax","type":"uint256"},{"internalType":"address[]","name":"path","type":"address[]"},{"internalType":"address","name":"to","type":"address"},{"internalType":"uint256","name":"deadline","type":"uint256"}],"name":"swapTokensForExactETH","outputs":[{"internalType":"uint256[]","name":"amounts","type":"uint256[]"}],"stateMutability":"nonpayable","type":"function"},{"inputs":[{"internalType":"uint256","name":"amountOut","type":"uint256"},{"internalType":"uint256","name":"amountInMax","type":"uint256"},{"internalType":"address[]","name":"path","type":"address[]"},{"internalType":"address","name":"to","type":"address"},{"internalType":"uint256","name":"deadline","type":"uint256"}],"name":"swapTokensForExactTokens","outputs":[{"internalType":"uint256[]","name":"amounts","type":"uint256[]"}],"stateMutability":"nonpayable","type":"function"},{"stateMutability":"payable","type":"receive"}]'
output = decode_tx('0x7a250d5630b4cf539739df2c5dacb4c659f2488d', '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', sample_abi)
print('function called: ', output[0])
print('arguments: ', json.dumps(json.loads(output[1]), indent=2))
view rawdecode_transaction.py hosted with ❤ by GitHub | 164.666667 | 11,890 | 0.692561 | 1,610 | 15,808 | 6.747826 | 0.130435 | 0.113402 | 0.201123 | 0.102172 | 0.699558 | 0.678203 | 0.668354 | 0.661727 | 0.647183 | 0.630707 | 0 | 0.075799 | 0.038588 | 15,808 | 96 | 11,891 | 164.666667 | 0.638966 | 0 | 0 | 0.189873 | 0 | 0.012658 | 0.816128 | 0.807218 | 0 | 0 | 0.040545 | 0 | 0 | 0 | null | null | 0 | 0.177215 | null | null | 0.025316 | 0 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
0e0bc40fd5d6f9970419fa055801ba082976dcb8 | 17,454 | py | Python | bloscpickle/test.py | robbmcleod/bloscpickle | 8ab0a92a82de4bd4f699d0412973fac3321ba88e | [
"BSD-2-Clause"
] | 1 | 2021-12-30T08:16:11.000Z | 2021-12-30T08:16:11.000Z | bloscpickle/test.py | robbmcleod/bloscpickle | 8ab0a92a82de4bd4f699d0412973fac3321ba88e | [
"BSD-2-Clause"
] | null | null | null | bloscpickle/test.py | robbmcleod/bloscpickle | 8ab0a92a82de4bd4f699d0412973fac3321ba88e | [
"BSD-2-Clause"
] | null | null | null | # coding=UTF-8
"""
Created on Wed Dec 28 11:47:37 2016
@author: Robert A. McLeod
"""
import bloscpickle
import json
import ujson
import rapidjson
import pickle
import marshal
import msgpack
import os, os.path
import uuid
from time import time
MB = 2**20
from itertools import count; COUNTER = count()
import matplotlib.pyplot as plt
import numpy as np
####### MODULE TESTS #######
#from memory_profiler import profile
#@profile
def testUUID():
"""
UUIDs are more or less random ascii codes, so they represent a difficult
target for data compression.
"""
write = {}
read = {}
sizes = {}
testDict = {}
testDict['name'] = "Foo"
testDict['id'] = next(COUNTER)
testDict['uuCount'] = 2**18
testDict['uuids'] = [str(uuid.uuid4()) for I in range( testDict['uuCount'] )]
def execTest( testDict, pickler, useBlosc=False,
compressor='zstd', clevel=1, shuffle=0, **pickler_kwargs ):
if useBlosc:
picklerName = 'blosc_{}{}_'.format(compressor,clevel) + pickler.__name__
filename = "testfile." + picklerName
with open( filename, 'wb' ) as stream:
t0 = time()
bloscpickle.dump(testDict, stream, pickler= pickler,
compressor=compressor, clevel=clevel, shuffle=shuffle, **pickler_kwargs )
write[picklerName] = time() - t0
with open( filename, 'rb' ) as stream:
t1 = time()
outDict = bloscpickle.load( stream, pickler=pickler )
read[picklerName] = time() - t1
if pickler is msgpack:
print( "WARNING: {} failed in/out assert test".format(picklerName) )
else:
assert( testDict == outDict )
else:
picklerName = pickler.__name__
filename = "testfile." + picklerName
if pickler in (pickle,marshal,msgpack):
with open( filename, 'wb' ) as stream:
t0 = time()
pickler.dump( testDict, stream, **pickler_kwargs )
write[picklerName] = time() - t0
with open( filename, 'rb' ) as stream:
t1 = time()
outDict = pickler.load( stream )
read[picklerName] = time() - t1
try:
assert( testDict == outDict )
except:
print( "WARNING: {} failed in/out assert test".format(picklerName) )
else:
with open( filename, 'w' ) as stream:
t0 = time()
pickler.dump( testDict, stream, **pickler_kwargs )
write[picklerName] = time() - t0
with open( filename, 'r' ) as stream:
t1 = time()
outDict = pickler.load( stream )
read[picklerName] = time() - t1
try:
assert( testDict == outDict )
except:
print( "WARNING: {} failed in/out assert test".format(picklerName) )
sizes[picklerName] = os.path.getsize( filename ) / MB
os.remove( filename )
print( "{}:: write {:.2e} s, read {:.2e} s, size: {:.3f} MB"\
.format( picklerName, write[picklerName], read[picklerName], sizes[picklerName] ) )
return write[picklerName], sizes[picklerName]
execTest( testDict, pickle )
execTest( testDict, pickle, useBlosc=True, compressor='zstd', clevel=1 )
execTest( testDict, pickle, useBlosc=True, compressor='lz4', clevel=9 )
execTest( testDict, marshal )
execTest( testDict, marshal, useBlosc=True, compressor='zstd', clevel=1 )
execTest( testDict, marshal, useBlosc=True, compressor='lz4', clevel=9 )
execTest( testDict, json, ensure_ascii=False )
execTest( testDict, json, useBlosc=True, compressor='zstd', clevel=1, ensure_ascii=False )
execTest( testDict, json, useBlosc=True, compressor='lz4', clevel=9, ensure_ascii=False )
execTest( testDict, rapidjson )
execTest( testDict, rapidjson, useBlosc=True, compressor='zstd', clevel=1 )
execTest( testDict, rapidjson, useBlosc=True, compressor='lz4', clevel=9 )
execTest( testDict, ujson, ensure_ascii=False )
execTest( testDict, ujson, useBlosc=True, compressor='zstd', clevel=1, ensure_ascii=False )
execTest( testDict, ujson, useBlosc=True, compressor='lz4', clevel=9, ensure_ascii=False )
execTest( testDict, msgpack, use_bin_type=False )
execTest( testDict, msgpack, useBlosc=True, compressor='zstd', clevel=1, use_bin_type=False )
execTest( testDict, msgpack, useBlosc=True, compressor='lz4', clevel=9, use_bin_type=False )
uncompressed_writes = [write['pickle'], write['marshal'], write['json'],
write['rapidjson'], write['ujson'], write['msgpack'] ]
zstd_writes = [write['blosc_zstd1_pickle'],write['blosc_zstd1_marshal'], write['blosc_zstd1_json'],
write['blosc_zstd1_rapidjson'], write['blosc_zstd1_ujson'], write['blosc_zstd1_msgpack'] ]
lz4_writes = [write['blosc_lz49_pickle'],write['blosc_lz49_marshal'], write['blosc_lz49_json'],
write['blosc_zstd1_rapidjson'], write['blosc_lz49_ujson'], write['blosc_lz49_msgpack'] ]
indices = np.arange(6)
bwidth = 0.25
fig, ax = plt.subplots( figsize=(10,8) )
bars_uncomp = ax.bar( indices, uncompressed_writes, bwidth, color='steelblue' )
bars_zstd = ax.bar( indices+bwidth, zstd_writes, bwidth, color='orange' )
bars_lz4 = ax.bar( indices+2*bwidth, lz4_writes, bwidth, color='purple' )
ax.set_ylabel( "Serialization write to disk time (s)" )
ax.set_xticks( indices + 0.33 )
ax.set_xticklabels( ('pickle','marshal','json','rapidjson','ujson','msgpack') )
ax.legend( (bars_uncomp,bars_zstd,bars_lz4), ('uncompressed', 'zstd','lz4'), loc='best' )
plt.savefig( "bloscpickle_uuid_writerate.png" )
uncompressed_reads = [read['pickle'], read['marshal'], read['json'],
read['rapidjson'], read['ujson'], read['msgpack'] ]
zstd_reads = [read['blosc_zstd1_pickle'],read['blosc_zstd1_marshal'], read['blosc_zstd1_json'],
read['blosc_zstd1_rapidjson'], read['blosc_zstd1_ujson'], read['blosc_zstd1_msgpack'] ]
lz4_reads = [read['blosc_lz49_pickle'],read['blosc_lz49_marshal'], read['blosc_lz49_json'],
read['blosc_lz49_rapidjson'], read['blosc_lz49_ujson'], read['blosc_lz49_msgpack'] ]
fig, ax = plt.subplots( figsize=(10,8) )
bars_uncomp = ax.bar( indices, uncompressed_reads, bwidth, color='steelblue' )
bars_zstd = ax.bar( indices+bwidth, zstd_reads, bwidth, color='orange' )
bars_lz4 = ax.bar( indices+2*bwidth, lz4_reads, bwidth, color='purple' )
ax.set_ylabel( "Serialization read from disk time (s)" )
#ax.set_title( "German dictionary with 326980 words" )
ax.set_xticks( indices + 0.33 )
ax.set_xticklabels( ('pickle','marshal','json', 'rapidjson', 'ujson','msgpack') )
ax.legend( (bars_uncomp,bars_zstd,bars_lz4), ('uncompressed', 'zstd','lz4'), loc='best' )
plt.savefig( "bloscpickle_uuid_readrate.png" )
uncompressed_sizes = [sizes['pickle'], sizes['marshal'], sizes['json'],
sizes['rapidjson'], sizes['ujson'], sizes['msgpack'] ]
zstd_sizes = [sizes['blosc_zstd1_pickle'],sizes['blosc_zstd1_marshal'], sizes['blosc_zstd1_json'],
sizes['blosc_zstd1_rapidjson'], sizes['blosc_zstd1_ujson'], sizes['blosc_zstd1_msgpack'] ]
lz4_sizes = [sizes['blosc_lz49_pickle'],sizes['blosc_lz49_marshal'], sizes['blosc_lz49_json'],
sizes['blosc_lz49_rapidjson'], sizes['blosc_lz49_ujson'], sizes['blosc_lz49_msgpack'] ]
fig2, ax2 = plt.subplots( figsize=(10,8) )
bars_uncomp2 = ax2.bar( indices, uncompressed_sizes, bwidth, color='steelblue' )
bars_zstd2 = ax2.bar( indices+bwidth, zstd_sizes, bwidth, color='orange' )
bars_lz42 = ax2.bar( indices+2*bwidth, lz4_sizes, bwidth, color='purple' )
ax2.set_ylabel( "Disk usage (MB)" )
ax2.set_xticks( indices + 0.33 )
ax2.set_xticklabels( ('pickle','marshal','json','rapidjson','ujson','msgpack') )
ax2.legend( (bars_uncomp2,bars_zstd2,bars_lz42), ('uncompressed', 'zstd','lz4'), loc='best' )
plt.savefig( "bloscpickle_uuid_disksize.png" )
def testJSON():
"""
Compressing structured text dictionaries is a test case where we expect
compression to have a big impact.
This requires a 'sample.json' file which is not included in the distribution.
I recommend the following tool for generating sample JSON data:
http://www.json-generator.com/
It can be trivally modified to generate 10'000 entries.
"""
write = {}
read = {}
sizes = {}
with open( "sample.json", 'r' ) as jh:
testDict = ujson.load( jh )
def execTest( testDict, pickler, useBlosc=False,
compressor='zstd', clevel=1, shuffle=0, **pickler_kwargs ):
if useBlosc:
picklerName = 'blosc_{}{}_'.format(compressor,clevel) + pickler.__name__
filename = "testfile." + picklerName
with open( filename, 'wb' ) as stream:
t0 = time()
bloscpickle.dump(testDict, stream, pickler= pickler,
compressor=compressor, clevel=clevel, shuffle=shuffle, **pickler_kwargs )
write[picklerName] = time() - t0
with open( filename, 'rb' ) as stream:
t1 = time()
outDict = bloscpickle.load( stream, pickler=pickler )
read[picklerName] = time() - t1
try:
assert( testDict == outDict )
except AssertionError:
print( "WARNING: {} failed in/out assert test".format(picklerName) )
else:
picklerName = pickler.__name__
filename = "testfile." + picklerName
if pickler in (pickle,marshal,msgpack):
with open( filename, 'wb' ) as stream:
t0 = time()
pickler.dump( testDict, stream, **pickler_kwargs )
write[picklerName] = time() - t0
with open( filename, 'rb' ) as stream:
t1 = time()
outDict = pickler.load( stream )
read[picklerName] = time() - t1
try:
assert( testDict == outDict )
except AssertionError:
print( "WARNING: {} failed in/out assert test".format(picklerName) )
else:
with open( filename, 'w' ) as stream:
t0 = time()
pickler.dump( testDict, stream, **pickler_kwargs )
write[picklerName] = time() - t0
with open( filename, 'r' ) as stream:
t1 = time()
outDict = pickler.load( stream )
read[picklerName] = time() - t1
try:
assert( testDict == outDict )
except AssertionError:
print( "WARNING: {} failed in/out assert test".format(picklerName) )
sizes[picklerName] = os.path.getsize( filename ) / MB
os.remove( filename )
print( "{}:: write {:.2e} s, read {:.2e} s, size: {:.3f} MB"\
.format( picklerName, write[picklerName], read[picklerName], sizes[picklerName] ) )
return outDict
execTest( testDict, pickle )
execTest( testDict, pickle, useBlosc=True, compressor='zstd', clevel=1 )
execTest( testDict, pickle, useBlosc=True, compressor='lz4', clevel=9 )
execTest( testDict, marshal )
execTest( testDict, marshal, useBlosc=True, compressor='zstd', clevel=1 )
execTest( testDict, marshal, useBlosc=True, compressor='lz4', clevel=9 )
execTest( testDict, json, ensure_ascii=False )
execTest( testDict, json, useBlosc=True, compressor='zstd', clevel=1, ensure_ascii=False )
execTest( testDict, json, useBlosc=True, compressor='lz4', clevel=9, ensure_ascii=False )
execTest( testDict, rapidjson )
execTest( testDict, rapidjson, useBlosc=True, compressor='zstd', clevel=1 )
execTest( testDict, rapidjson, useBlosc=True, compressor='lz4', clevel=9 )
# Testing here to try and find what broke on read/write for UltraJSON.
# Probably floating point precision
outDict = execTest( testDict, ujson, encode_html_chars=True )
execTest( testDict, ujson, useBlosc=True, compressor='zstd', clevel=1, encode_html_chars=True )
execTest( testDict, ujson, useBlosc=True, compressor='lz4', clevel=9, encode_html_chars=True )
execTest( testDict, msgpack, use_bin_type=False )
execTest( testDict, msgpack, useBlosc=True, compressor='zstd', clevel=1, use_bin_type=False )
execTest( testDict, msgpack, useBlosc=True, compressor='lz4', clevel=9, use_bin_type=False )
uncompressed_writes = [write['pickle'], write['marshal'], write['json'],
write['rapidjson'], write['ujson'], write['msgpack'] ]
zstd_writes = [write['blosc_zstd1_pickle'],write['blosc_zstd1_marshal'], write['blosc_zstd1_json'],
write['blosc_zstd1_rapidjson'], write['blosc_zstd1_ujson'], write['blosc_zstd1_msgpack'] ]
lz4_writes = [write['blosc_lz49_pickle'],write['blosc_lz49_marshal'], write['blosc_lz49_json'],
write['blosc_zstd1_rapidjson'], write['blosc_lz49_ujson'], write['blosc_lz49_msgpack'] ]
indices = np.arange(6)
bwidth = 0.25
fig, ax = plt.subplots( figsize=(10,8) )
bars_uncomp = ax.bar( indices, uncompressed_writes, bwidth, color='steelblue' )
bars_zstd = ax.bar( indices+bwidth, zstd_writes, bwidth, color='orange' )
bars_lz4 = ax.bar( indices+2*bwidth, lz4_writes, bwidth, color='purple' )
ax.set_ylabel( "Serialization write to disk time (s)" )
ax.set_xticks( indices + 0.33 )
ax.set_xticklabels( ('pickle','marshal','json', 'rapidjson', 'ujson','msgpack') )
ax.legend( (bars_uncomp,bars_zstd,bars_lz4), ('uncompressed', 'zstd','lz4'), loc='best' )
plt.savefig( "bloscpickle_jsongen_writerate.png" )
uncompressed_reads = [read['pickle'], read['marshal'], read['json'],
read['rapidjson'], read['ujson'], read['msgpack'] ]
zstd_reads = [read['blosc_zstd1_pickle'],read['blosc_zstd1_marshal'], read['blosc_zstd1_json'],
read['blosc_zstd1_rapidjson'], read['blosc_zstd1_ujson'], read['blosc_zstd1_msgpack'] ]
lz4_reads = [read['blosc_lz49_pickle'],read['blosc_lz49_marshal'], read['blosc_lz49_json'],
read['blosc_lz49_rapidjson'], read['blosc_lz49_ujson'], read['blosc_lz49_msgpack'] ]
fig, ax = plt.subplots( figsize=(10,8) )
bars_uncomp = ax.bar( indices, uncompressed_reads, bwidth, color='steelblue' )
bars_zstd = ax.bar( indices+bwidth, zstd_reads, bwidth, color='orange' )
bars_lz4 = ax.bar( indices+2*bwidth, lz4_reads, bwidth, color='purple' )
ax.set_ylabel( "Serialization read from disk time (s)" )
#ax.set_title( "German dictionary with 326980 words" )
ax.set_xticks( indices + 0.33 )
ax.set_xticklabels( ('pickle','marshal','json', 'rapidjson', 'ujson','msgpack') )
ax.legend( (bars_uncomp,bars_zstd,bars_lz4), ('uncompressed', 'zstd','lz4'), loc='best' )
plt.savefig( "bloscpickle_jsongen_readrate.png" )
uncompressed_sizes = [sizes['pickle'], sizes['marshal'], sizes['json'],
sizes['rapidjson'], sizes['ujson'], sizes['msgpack'] ]
zstd_sizes = [sizes['blosc_zstd1_pickle'],sizes['blosc_zstd1_marshal'], sizes['blosc_zstd1_json'],
sizes['blosc_zstd1_rapidjson'], sizes['blosc_zstd1_ujson'], sizes['blosc_zstd1_msgpack'] ]
lz4_sizes = [sizes['blosc_lz49_pickle'],sizes['blosc_lz49_marshal'], sizes['blosc_lz49_json'],
sizes['blosc_lz49_rapidjson'], sizes['blosc_lz49_ujson'], sizes['blosc_lz49_msgpack'] ]
fig2, ax2 = plt.subplots( figsize=(10,8) )
bars_uncomp2 = ax2.bar( indices, uncompressed_sizes, bwidth, color='steelblue' )
bars_zstd2 = ax2.bar( indices+bwidth, zstd_sizes, bwidth, color='orange' )
bars_lz42 = ax2.bar( indices+2*bwidth, lz4_sizes, bwidth, color='purple' )
ax2.set_ylabel( "Disk usage (MB)" )
ax2.set_xticks( indices + 0.33 )
ax2.set_xticklabels( ('pickle','marshal','json','rapidjson','ujson','msgpack') )
ax2.legend( (bars_uncomp2,bars_zstd2,bars_lz42), ('uncompressed', 'zstd','lz4'), loc='best' )
plt.savefig( "bloscpickle_jsongen_disksize.png" )
pass
if __name__ == "__main__":
testUUID()
testJSON()
| 49.726496 | 111 | 0.594133 | 1,896 | 17,454 | 5.304852 | 0.125 | 0.060449 | 0.052496 | 0.02923 | 0.88785 | 0.88785 | 0.885961 | 0.885961 | 0.884371 | 0.877013 | 0 | 0.025513 | 0.274665 | 17,454 | 350 | 112 | 49.868571 | 0.768957 | 0.045606 | 0 | 0.842697 | 0 | 0 | 0.179413 | 0.021771 | 0 | 0 | 0 | 0 | 0.05618 | 1 | 0.014981 | false | 0.003745 | 0.048689 | 0 | 0.071161 | 0.029963 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
38638e3e88a2434d1aef63d8a623b63d27b64afb | 162 | py | Python | saleor/graphql/payment/utils.py | fairhopeweb/saleor | 9ac6c22652d46ba65a5b894da5f1ba5bec48c019 | [
"CC-BY-4.0"
] | 15,337 | 2015-01-12T02:11:52.000Z | 2021-10-05T19:19:29.000Z | saleor/graphql/payment/utils.py | fairhopeweb/saleor | 9ac6c22652d46ba65a5b894da5f1ba5bec48c019 | [
"CC-BY-4.0"
] | 7,486 | 2015-02-11T10:52:13.000Z | 2021-10-06T09:37:15.000Z | saleor/graphql/payment/utils.py | fairhopeweb/saleor | 9ac6c22652d46ba65a5b894da5f1ba5bec48c019 | [
"CC-BY-4.0"
] | 5,864 | 2015-01-16T14:52:54.000Z | 2021-10-05T23:01:15.000Z | from typing import List
def metadata_contains_empty_key(metadata_list: List[dict]) -> bool:
return not all([data["key"].strip() for data in metadata_list])
| 27 | 67 | 0.746914 | 25 | 162 | 4.64 | 0.72 | 0.206897 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.135802 | 162 | 5 | 68 | 32.4 | 0.828571 | 0 | 0 | 0 | 0 | 0 | 0.018519 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | false | 0 | 0.333333 | 0.333333 | 1 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 7 |
38a39313338477f46367bc7b16653313029d8a99 | 11,617 | py | Python | @muuTera$u.py | Tripl0Color/AmuteraSu-Pattern | c78e73481b54ef20cba6a5657cb5f05c74682cbf | [
"Unlicense"
] | null | null | null | @muuTera$u.py | Tripl0Color/AmuteraSu-Pattern | c78e73481b54ef20cba6a5657cb5f05c74682cbf | [
"Unlicense"
] | null | null | null | @muuTera$u.py | Tripl0Color/AmuteraSu-Pattern | c78e73481b54ef20cba6a5657cb5f05c74682cbf | [
"Unlicense"
] | null | null | null | #Use on py flask
print ("""$$$$$$$$\ $$\ $$\ $$$$$$\ $$\
\__$$ __| \__| $$ | $$ __$$\ $$ |
$$ | $$$$$$\ $$\ $$$$$$\ $$ | $$ / \__| $$$$$$\ $$ | $$$$$$\ $$$$$$\
$$ |$$ __$$\ $$ |$$ __$$\ $$ | $$ | $$ __$$\ $$ |$$ __$$\ $$ __$$\
$$ |$$ | \__|$$ |$$ / $$ |$$ | $$ | $$ / $$ |$$ |$$ / $$ |$$ | \__|
$$ |$$ | $$ |$$ | $$ |$$ | $$ | $$\ $$ | $$ |$$ |$$ | $$ |$$ |
$$ |$$ | $$ |$$$$$$$ |$$ | \$$$$$$ |\$$$$$$ |$$ |\$$$$$$ |$$ |
\__|\__| \__|$$ ____/ \__|$$$$$$\\______/ \______/ \__| \______/ \__|
$$ | \______|
$$ |
\__| """)
from flask import Flask, request, json
import time
import vk_api
import random
vk = vk_api.VkApi(token="paste your token vk group here") #vk group token here
msg = "msg here" #Your ded message
app = Flask(__name__)
@app.route('/', methods = ["POST"])
def main():
data = json.loads(request.data)
if data["type"] == "confirmation":
return "paste code vk here" #code vk here
elif data["type"] == "message_new":
object = data["object"]
id = object["peer_id"]
body = object["text"]
if body.lower() == "hello":
vk.method("messages.send", {"peer_id": id, "message": "hi", "random_id": random.randint(1, 2147483647)})
else:
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
vk.method("messages.send", {"peer_id": id, "message": msg, "random_id": random.randint(1, 2147483647)})
return "ok"
| 94.447154 | 121 | 0.56512 | 1,362 | 11,617 | 4.640969 | 0.039648 | 0.081633 | 0.215156 | 0.268945 | 0.940832 | 0.940832 | 0.93577 | 0.93577 | 0.930233 | 0.930233 | 0 | 0.103797 | 0.224585 | 11,617 | 122 | 122 | 95.221311 | 0.597913 | 0.005337 | 0 | 0.730435 | 0 | 0.034783 | 0.355849 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.008696 | false | 0 | 0.034783 | 0 | 0.06087 | 0.008696 | 0 | 0 | 0 | null | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 9 |
38e934436fdf9c4e8e317eea5f7d04ff624ca858 | 93,243 | py | Python | msgraph-cli-extensions/beta/bookings_beta/azext_bookings_beta/vendored_sdks/bookings/operations/_booking_businesses_operations.py | thewahome/msgraph-cli | 33127d9efa23a0e5f5303c93242fbdbb73348671 | [
"MIT"
] | null | null | null | msgraph-cli-extensions/beta/bookings_beta/azext_bookings_beta/vendored_sdks/bookings/operations/_booking_businesses_operations.py | thewahome/msgraph-cli | 33127d9efa23a0e5f5303c93242fbdbb73348671 | [
"MIT"
] | null | null | null | msgraph-cli-extensions/beta/bookings_beta/azext_bookings_beta/vendored_sdks/bookings/operations/_booking_businesses_operations.py | thewahome/msgraph-cli | 33127d9efa23a0e5f5303c93242fbdbb73348671 | [
"MIT"
] | null | null | null | # coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.paging import ItemPaged
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpRequest, HttpResponse
from azure.mgmt.core.exceptions import ARMErrorFormat
from .. import models
if TYPE_CHECKING:
# pylint: disable=unused-import,ungrouped-imports
from typing import Any, Callable, Dict, Generic, Iterable, List, Optional, TypeVar, Union
T = TypeVar('T')
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
class BookingBusinessesOperations(object):
"""BookingBusinessesOperations operations.
You should not instantiate this class directly. Instead, you should create a Client instance that
instantiates it for you and attaches it as an attribute.
:ivar models: Alias to model classes used in this operation group.
:type models: ~bookings.models
:param client: Client for service requests.
:param config: Configuration of service client.
:param serializer: An object model serializer.
:param deserializer: An object model deserializer.
"""
models = models
def __init__(self, client, config, serializer, deserializer):
self._client = client
self._serialize = serializer
self._deserialize = deserializer
self._config = config
def list_appointments(
self,
booking_business_id, # type: str
orderby=None, # type: Optional[List[Union[str, "models.Enum13"]]]
select=None, # type: Optional[List[Union[str, "models.Enum14"]]]
expand=None, # type: Optional[List[str]]
**kwargs # type: Any
):
# type: (...) -> Iterable["models.CollectionOfBookingAppointment"]
"""Get appointments from bookingBusinesses.
Get appointments from bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param orderby: Order items by property values.
:type orderby: list[str or ~bookings.models.Enum13]
:param select: Select properties to be returned.
:type select: list[str or ~bookings.models.Enum14]
:param expand: Expand related entities.
:type expand: list[str]
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either CollectionOfBookingAppointment or the result of cls(response)
:rtype: ~azure.core.paging.ItemPaged[~bookings.models.CollectionOfBookingAppointment]
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType["models.CollectionOfBookingAppointment"]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
accept = "application/json"
def prepare_request(next_link=None):
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
if not next_link:
# Construct URL
url = self.list_appointments.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
if self._config.top is not None:
query_parameters['$top'] = self._serialize.query("self._config.top", self._config.top, 'int', minimum=0)
if self._config.skip is not None:
query_parameters['$skip'] = self._serialize.query("self._config.skip", self._config.skip, 'int', minimum=0)
if self._config.search is not None:
query_parameters['$search'] = self._serialize.query("self._config.search", self._config.search, 'str')
if self._config.filter is not None:
query_parameters['$filter'] = self._serialize.query("self._config.filter", self._config.filter, 'str')
if self._config.count is not None:
query_parameters['$count'] = self._serialize.query("self._config.count", self._config.count, 'bool')
if orderby is not None:
query_parameters['$orderby'] = self._serialize.query("orderby", orderby, '[str]', div=',')
if select is not None:
query_parameters['$select'] = self._serialize.query("select", select, '[str]', div=',')
if expand is not None:
query_parameters['$expand'] = self._serialize.query("expand", expand, '[str]', div=',')
request = self._client.get(url, query_parameters, header_parameters)
else:
url = next_link
query_parameters = {} # type: Dict[str, Any]
request = self._client.get(url, query_parameters, header_parameters)
return request
def extract_data(pipeline_response):
deserialized = self._deserialize('CollectionOfBookingAppointment', pipeline_response)
list_of_elem = deserialized.value
if cls:
list_of_elem = cls(list_of_elem)
return deserialized.odata_next_link or None, iter(list_of_elem)
def get_next(next_link=None):
request = prepare_request(next_link)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [200]:
error = self._deserialize(models.OdataError, response)
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
return pipeline_response
return ItemPaged(
get_next, extract_data
)
list_appointments.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/appointments'} # type: ignore
def create_appointments(
self,
booking_business_id, # type: str
body, # type: "models.MicrosoftGraphBookingAppointment"
**kwargs # type: Any
):
# type: (...) -> "models.MicrosoftGraphBookingAppointment"
"""Create new navigation property to appointments for bookingBusinesses.
Create new navigation property to appointments for bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param body: New navigation property.
:type body: ~bookings.models.MicrosoftGraphBookingAppointment
:keyword callable cls: A custom type or function that will be passed the direct response
:return: MicrosoftGraphBookingAppointment, or the result of cls(response)
:rtype: ~bookings.models.MicrosoftGraphBookingAppointment
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType["models.MicrosoftGraphBookingAppointment"]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
content_type = kwargs.pop("content_type", "application/json")
accept = "application/json"
# Construct URL
url = self.create_appointments.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str')
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
body_content_kwargs = {} # type: Dict[str, Any]
body_content = self._serialize.body(body, 'MicrosoftGraphBookingAppointment')
body_content_kwargs['content'] = body_content
request = self._client.post(url, query_parameters, header_parameters, **body_content_kwargs)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [201]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.OdataError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize('MicrosoftGraphBookingAppointment', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
create_appointments.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/appointments'} # type: ignore
def get_appointments(
self,
booking_business_id, # type: str
booking_appointment_id, # type: str
select=None, # type: Optional[List[Union[str, "models.Enum15"]]]
expand=None, # type: Optional[List[str]]
**kwargs # type: Any
):
# type: (...) -> "models.MicrosoftGraphBookingAppointment"
"""Get appointments from bookingBusinesses.
Get appointments from bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param booking_appointment_id: key: id of bookingAppointment.
:type booking_appointment_id: str
:param select: Select properties to be returned.
:type select: list[str or ~bookings.models.Enum15]
:param expand: Expand related entities.
:type expand: list[str]
:keyword callable cls: A custom type or function that will be passed the direct response
:return: MicrosoftGraphBookingAppointment, or the result of cls(response)
:rtype: ~bookings.models.MicrosoftGraphBookingAppointment
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType["models.MicrosoftGraphBookingAppointment"]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
accept = "application/json"
# Construct URL
url = self.get_appointments.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
'bookingAppointment-id': self._serialize.url("booking_appointment_id", booking_appointment_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
if select is not None:
query_parameters['$select'] = self._serialize.query("select", select, '[str]', div=',')
if expand is not None:
query_parameters['$expand'] = self._serialize.query("expand", expand, '[str]', div=',')
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
request = self._client.get(url, query_parameters, header_parameters)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.OdataError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize('MicrosoftGraphBookingAppointment', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
get_appointments.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/appointments/{bookingAppointment-id}'} # type: ignore
def update_appointments(
self,
booking_business_id, # type: str
booking_appointment_id, # type: str
body, # type: "models.MicrosoftGraphBookingAppointment"
**kwargs # type: Any
):
# type: (...) -> None
"""Update the navigation property appointments in bookingBusinesses.
Update the navigation property appointments in bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param booking_appointment_id: key: id of bookingAppointment.
:type booking_appointment_id: str
:param body: New navigation property values.
:type body: ~bookings.models.MicrosoftGraphBookingAppointment
:keyword callable cls: A custom type or function that will be passed the direct response
:return: None, or the result of cls(response)
:rtype: None
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType[None]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
content_type = kwargs.pop("content_type", "application/json")
accept = "application/json"
# Construct URL
url = self.update_appointments.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
'bookingAppointment-id': self._serialize.url("booking_appointment_id", booking_appointment_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str')
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
body_content_kwargs = {} # type: Dict[str, Any]
body_content = self._serialize.body(body, 'MicrosoftGraphBookingAppointment')
body_content_kwargs['content'] = body_content
request = self._client.patch(url, query_parameters, header_parameters, **body_content_kwargs)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [204]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.OdataError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
if cls:
return cls(pipeline_response, None, {})
update_appointments.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/appointments/{bookingAppointment-id}'} # type: ignore
def delete_appointments(
self,
booking_business_id, # type: str
booking_appointment_id, # type: str
if_match=None, # type: Optional[str]
**kwargs # type: Any
):
# type: (...) -> None
"""Delete navigation property appointments for bookingBusinesses.
Delete navigation property appointments for bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param booking_appointment_id: key: id of bookingAppointment.
:type booking_appointment_id: str
:param if_match: ETag.
:type if_match: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: None, or the result of cls(response)
:rtype: None
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType[None]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
accept = "application/json"
# Construct URL
url = self.delete_appointments.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
'bookingAppointment-id': self._serialize.url("booking_appointment_id", booking_appointment_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
# Construct headers
header_parameters = {} # type: Dict[str, Any]
if if_match is not None:
header_parameters['If-Match'] = self._serialize.header("if_match", if_match, 'str')
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
request = self._client.delete(url, query_parameters, header_parameters)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [204]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.OdataError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
if cls:
return cls(pipeline_response, None, {})
delete_appointments.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/appointments/{bookingAppointment-id}'} # type: ignore
def list_calendar_view(
self,
booking_business_id, # type: str
start, # type: str
end, # type: str
orderby=None, # type: Optional[List[Union[str, "models.Enum16"]]]
select=None, # type: Optional[List[Union[str, "models.Get9ItemsItem"]]]
expand=None, # type: Optional[List[str]]
**kwargs # type: Any
):
# type: (...) -> Iterable["models.CollectionOfBookingAppointment0"]
"""Get calendarView from bookingBusinesses.
Get calendarView from bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param start: The start date and time of the time range, represented in ISO 8601 format. For
example, 2019-11-08T19:00:00-08:00.
:type start: str
:param end: The end date and time of the time range, represented in ISO 8601 format. For
example, 2019-11-08T20:00:00-08:00.
:type end: str
:param orderby: Order items by property values.
:type orderby: list[str or ~bookings.models.Enum16]
:param select: Select properties to be returned.
:type select: list[str or ~bookings.models.Get9ItemsItem]
:param expand: Expand related entities.
:type expand: list[str]
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either CollectionOfBookingAppointment0 or the result of cls(response)
:rtype: ~azure.core.paging.ItemPaged[~bookings.models.CollectionOfBookingAppointment0]
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType["models.CollectionOfBookingAppointment0"]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
accept = "application/json"
def prepare_request(next_link=None):
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
if not next_link:
# Construct URL
url = self.list_calendar_view.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
query_parameters['start'] = self._serialize.query("start", start, 'str')
query_parameters['end'] = self._serialize.query("end", end, 'str')
if self._config.top is not None:
query_parameters['$top'] = self._serialize.query("self._config.top", self._config.top, 'int', minimum=0)
if self._config.skip is not None:
query_parameters['$skip'] = self._serialize.query("self._config.skip", self._config.skip, 'int', minimum=0)
if self._config.search is not None:
query_parameters['$search'] = self._serialize.query("self._config.search", self._config.search, 'str')
if self._config.filter is not None:
query_parameters['$filter'] = self._serialize.query("self._config.filter", self._config.filter, 'str')
if self._config.count is not None:
query_parameters['$count'] = self._serialize.query("self._config.count", self._config.count, 'bool')
if orderby is not None:
query_parameters['$orderby'] = self._serialize.query("orderby", orderby, '[str]', div=',')
if select is not None:
query_parameters['$select'] = self._serialize.query("select", select, '[str]', div=',')
if expand is not None:
query_parameters['$expand'] = self._serialize.query("expand", expand, '[str]', div=',')
request = self._client.get(url, query_parameters, header_parameters)
else:
url = next_link
query_parameters = {} # type: Dict[str, Any]
request = self._client.get(url, query_parameters, header_parameters)
return request
def extract_data(pipeline_response):
deserialized = self._deserialize('CollectionOfBookingAppointment0', pipeline_response)
list_of_elem = deserialized.value
if cls:
list_of_elem = cls(list_of_elem)
return deserialized.odata_next_link or None, iter(list_of_elem)
def get_next(next_link=None):
request = prepare_request(next_link)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [200]:
error = self._deserialize(models.OdataError, response)
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
return pipeline_response
return ItemPaged(
get_next, extract_data
)
list_calendar_view.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/calendarView'} # type: ignore
def create_calendar_view(
self,
booking_business_id, # type: str
body, # type: "models.MicrosoftGraphBookingAppointment"
**kwargs # type: Any
):
# type: (...) -> "models.MicrosoftGraphBookingAppointment"
"""Create new navigation property to calendarView for bookingBusinesses.
Create new navigation property to calendarView for bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param body: New navigation property.
:type body: ~bookings.models.MicrosoftGraphBookingAppointment
:keyword callable cls: A custom type or function that will be passed the direct response
:return: MicrosoftGraphBookingAppointment, or the result of cls(response)
:rtype: ~bookings.models.MicrosoftGraphBookingAppointment
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType["models.MicrosoftGraphBookingAppointment"]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
content_type = kwargs.pop("content_type", "application/json")
accept = "application/json"
# Construct URL
url = self.create_calendar_view.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str')
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
body_content_kwargs = {} # type: Dict[str, Any]
body_content = self._serialize.body(body, 'MicrosoftGraphBookingAppointment')
body_content_kwargs['content'] = body_content
request = self._client.post(url, query_parameters, header_parameters, **body_content_kwargs)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [201]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.OdataError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize('MicrosoftGraphBookingAppointment', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
create_calendar_view.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/calendarView'} # type: ignore
def get_calendar_view(
self,
booking_business_id, # type: str
booking_appointment_id, # type: str
start, # type: str
end, # type: str
select=None, # type: Optional[List[Union[str, "models.Get4ItemsItem"]]]
expand=None, # type: Optional[List[str]]
**kwargs # type: Any
):
# type: (...) -> "models.MicrosoftGraphBookingAppointment"
"""Get calendarView from bookingBusinesses.
Get calendarView from bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param booking_appointment_id: key: id of bookingAppointment.
:type booking_appointment_id: str
:param start: The start date and time of the time range, represented in ISO 8601 format. For
example, 2019-11-08T19:00:00-08:00.
:type start: str
:param end: The end date and time of the time range, represented in ISO 8601 format. For
example, 2019-11-08T20:00:00-08:00.
:type end: str
:param select: Select properties to be returned.
:type select: list[str or ~bookings.models.Get4ItemsItem]
:param expand: Expand related entities.
:type expand: list[str]
:keyword callable cls: A custom type or function that will be passed the direct response
:return: MicrosoftGraphBookingAppointment, or the result of cls(response)
:rtype: ~bookings.models.MicrosoftGraphBookingAppointment
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType["models.MicrosoftGraphBookingAppointment"]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
accept = "application/json"
# Construct URL
url = self.get_calendar_view.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
'bookingAppointment-id': self._serialize.url("booking_appointment_id", booking_appointment_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
query_parameters['start'] = self._serialize.query("start", start, 'str')
query_parameters['end'] = self._serialize.query("end", end, 'str')
if select is not None:
query_parameters['$select'] = self._serialize.query("select", select, '[str]', div=',')
if expand is not None:
query_parameters['$expand'] = self._serialize.query("expand", expand, '[str]', div=',')
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
request = self._client.get(url, query_parameters, header_parameters)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.OdataError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize('MicrosoftGraphBookingAppointment', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
get_calendar_view.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/calendarView/{bookingAppointment-id}'} # type: ignore
def update_calendar_view(
self,
booking_business_id, # type: str
booking_appointment_id, # type: str
body, # type: "models.MicrosoftGraphBookingAppointment"
**kwargs # type: Any
):
# type: (...) -> None
"""Update the navigation property calendarView in bookingBusinesses.
Update the navigation property calendarView in bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param booking_appointment_id: key: id of bookingAppointment.
:type booking_appointment_id: str
:param body: New navigation property values.
:type body: ~bookings.models.MicrosoftGraphBookingAppointment
:keyword callable cls: A custom type or function that will be passed the direct response
:return: None, or the result of cls(response)
:rtype: None
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType[None]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
content_type = kwargs.pop("content_type", "application/json")
accept = "application/json"
# Construct URL
url = self.update_calendar_view.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
'bookingAppointment-id': self._serialize.url("booking_appointment_id", booking_appointment_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str')
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
body_content_kwargs = {} # type: Dict[str, Any]
body_content = self._serialize.body(body, 'MicrosoftGraphBookingAppointment')
body_content_kwargs['content'] = body_content
request = self._client.patch(url, query_parameters, header_parameters, **body_content_kwargs)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [204]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.OdataError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
if cls:
return cls(pipeline_response, None, {})
update_calendar_view.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/calendarView/{bookingAppointment-id}'} # type: ignore
def delete_calendar_view(
self,
booking_business_id, # type: str
booking_appointment_id, # type: str
if_match=None, # type: Optional[str]
**kwargs # type: Any
):
# type: (...) -> None
"""Delete navigation property calendarView for bookingBusinesses.
Delete navigation property calendarView for bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param booking_appointment_id: key: id of bookingAppointment.
:type booking_appointment_id: str
:param if_match: ETag.
:type if_match: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: None, or the result of cls(response)
:rtype: None
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType[None]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
accept = "application/json"
# Construct URL
url = self.delete_calendar_view.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
'bookingAppointment-id': self._serialize.url("booking_appointment_id", booking_appointment_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
# Construct headers
header_parameters = {} # type: Dict[str, Any]
if if_match is not None:
header_parameters['If-Match'] = self._serialize.header("if_match", if_match, 'str')
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
request = self._client.delete(url, query_parameters, header_parameters)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [204]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.OdataError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
if cls:
return cls(pipeline_response, None, {})
delete_calendar_view.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/calendarView/{bookingAppointment-id}'} # type: ignore
def list_customers(
self,
booking_business_id, # type: str
orderby=None, # type: Optional[List[Union[str, "models.Enum19"]]]
select=None, # type: Optional[List[Union[str, "models.Enum20"]]]
expand=None, # type: Optional[List[str]]
**kwargs # type: Any
):
# type: (...) -> Iterable["models.CollectionOfBookingCustomer"]
"""Get customers from bookingBusinesses.
Get customers from bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param orderby: Order items by property values.
:type orderby: list[str or ~bookings.models.Enum19]
:param select: Select properties to be returned.
:type select: list[str or ~bookings.models.Enum20]
:param expand: Expand related entities.
:type expand: list[str]
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either CollectionOfBookingCustomer or the result of cls(response)
:rtype: ~azure.core.paging.ItemPaged[~bookings.models.CollectionOfBookingCustomer]
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType["models.CollectionOfBookingCustomer"]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
accept = "application/json"
def prepare_request(next_link=None):
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
if not next_link:
# Construct URL
url = self.list_customers.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
if self._config.top is not None:
query_parameters['$top'] = self._serialize.query("self._config.top", self._config.top, 'int', minimum=0)
if self._config.skip is not None:
query_parameters['$skip'] = self._serialize.query("self._config.skip", self._config.skip, 'int', minimum=0)
if self._config.search is not None:
query_parameters['$search'] = self._serialize.query("self._config.search", self._config.search, 'str')
if self._config.filter is not None:
query_parameters['$filter'] = self._serialize.query("self._config.filter", self._config.filter, 'str')
if self._config.count is not None:
query_parameters['$count'] = self._serialize.query("self._config.count", self._config.count, 'bool')
if orderby is not None:
query_parameters['$orderby'] = self._serialize.query("orderby", orderby, '[str]', div=',')
if select is not None:
query_parameters['$select'] = self._serialize.query("select", select, '[str]', div=',')
if expand is not None:
query_parameters['$expand'] = self._serialize.query("expand", expand, '[str]', div=',')
request = self._client.get(url, query_parameters, header_parameters)
else:
url = next_link
query_parameters = {} # type: Dict[str, Any]
request = self._client.get(url, query_parameters, header_parameters)
return request
def extract_data(pipeline_response):
deserialized = self._deserialize('CollectionOfBookingCustomer', pipeline_response)
list_of_elem = deserialized.value
if cls:
list_of_elem = cls(list_of_elem)
return deserialized.odata_next_link or None, iter(list_of_elem)
def get_next(next_link=None):
request = prepare_request(next_link)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [200]:
error = self._deserialize(models.OdataError, response)
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
return pipeline_response
return ItemPaged(
get_next, extract_data
)
list_customers.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/customers'} # type: ignore
def create_customers(
self,
booking_business_id, # type: str
body, # type: "models.MicrosoftGraphBookingCustomer"
**kwargs # type: Any
):
# type: (...) -> "models.MicrosoftGraphBookingCustomer"
"""Create new navigation property to customers for bookingBusinesses.
Create new navigation property to customers for bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param body: New navigation property.
:type body: ~bookings.models.MicrosoftGraphBookingCustomer
:keyword callable cls: A custom type or function that will be passed the direct response
:return: MicrosoftGraphBookingCustomer, or the result of cls(response)
:rtype: ~bookings.models.MicrosoftGraphBookingCustomer
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType["models.MicrosoftGraphBookingCustomer"]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
content_type = kwargs.pop("content_type", "application/json")
accept = "application/json"
# Construct URL
url = self.create_customers.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str')
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
body_content_kwargs = {} # type: Dict[str, Any]
body_content = self._serialize.body(body, 'MicrosoftGraphBookingCustomer')
body_content_kwargs['content'] = body_content
request = self._client.post(url, query_parameters, header_parameters, **body_content_kwargs)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [201]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.OdataError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize('MicrosoftGraphBookingCustomer', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
create_customers.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/customers'} # type: ignore
def get_customers(
self,
booking_business_id, # type: str
booking_customer_id, # type: str
select=None, # type: Optional[List[Union[str, "models.Enum21"]]]
expand=None, # type: Optional[List[str]]
**kwargs # type: Any
):
# type: (...) -> "models.MicrosoftGraphBookingCustomer"
"""Get customers from bookingBusinesses.
Get customers from bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param booking_customer_id: key: id of bookingCustomer.
:type booking_customer_id: str
:param select: Select properties to be returned.
:type select: list[str or ~bookings.models.Enum21]
:param expand: Expand related entities.
:type expand: list[str]
:keyword callable cls: A custom type or function that will be passed the direct response
:return: MicrosoftGraphBookingCustomer, or the result of cls(response)
:rtype: ~bookings.models.MicrosoftGraphBookingCustomer
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType["models.MicrosoftGraphBookingCustomer"]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
accept = "application/json"
# Construct URL
url = self.get_customers.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
'bookingCustomer-id': self._serialize.url("booking_customer_id", booking_customer_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
if select is not None:
query_parameters['$select'] = self._serialize.query("select", select, '[str]', div=',')
if expand is not None:
query_parameters['$expand'] = self._serialize.query("expand", expand, '[str]', div=',')
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
request = self._client.get(url, query_parameters, header_parameters)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.OdataError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize('MicrosoftGraphBookingCustomer', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
get_customers.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/customers/{bookingCustomer-id}'} # type: ignore
def update_customers(
self,
booking_business_id, # type: str
booking_customer_id, # type: str
body, # type: "models.MicrosoftGraphBookingCustomer"
**kwargs # type: Any
):
# type: (...) -> None
"""Update the navigation property customers in bookingBusinesses.
Update the navigation property customers in bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param booking_customer_id: key: id of bookingCustomer.
:type booking_customer_id: str
:param body: New navigation property values.
:type body: ~bookings.models.MicrosoftGraphBookingCustomer
:keyword callable cls: A custom type or function that will be passed the direct response
:return: None, or the result of cls(response)
:rtype: None
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType[None]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
content_type = kwargs.pop("content_type", "application/json")
accept = "application/json"
# Construct URL
url = self.update_customers.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
'bookingCustomer-id': self._serialize.url("booking_customer_id", booking_customer_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str')
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
body_content_kwargs = {} # type: Dict[str, Any]
body_content = self._serialize.body(body, 'MicrosoftGraphBookingCustomer')
body_content_kwargs['content'] = body_content
request = self._client.patch(url, query_parameters, header_parameters, **body_content_kwargs)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [204]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.OdataError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
if cls:
return cls(pipeline_response, None, {})
update_customers.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/customers/{bookingCustomer-id}'} # type: ignore
def delete_customers(
self,
booking_business_id, # type: str
booking_customer_id, # type: str
if_match=None, # type: Optional[str]
**kwargs # type: Any
):
# type: (...) -> None
"""Delete navigation property customers for bookingBusinesses.
Delete navigation property customers for bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param booking_customer_id: key: id of bookingCustomer.
:type booking_customer_id: str
:param if_match: ETag.
:type if_match: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: None, or the result of cls(response)
:rtype: None
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType[None]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
accept = "application/json"
# Construct URL
url = self.delete_customers.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
'bookingCustomer-id': self._serialize.url("booking_customer_id", booking_customer_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
# Construct headers
header_parameters = {} # type: Dict[str, Any]
if if_match is not None:
header_parameters['If-Match'] = self._serialize.header("if_match", if_match, 'str')
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
request = self._client.delete(url, query_parameters, header_parameters)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [204]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.OdataError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
if cls:
return cls(pipeline_response, None, {})
delete_customers.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/customers/{bookingCustomer-id}'} # type: ignore
def publish(
self,
booking_business_id, # type: str
**kwargs # type: Any
):
# type: (...) -> None
"""Invoke action publish.
Invoke action publish.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: None, or the result of cls(response)
:rtype: None
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType[None]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
accept = "application/json"
# Construct URL
url = self.publish.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
request = self._client.post(url, query_parameters, header_parameters)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [204]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.OdataError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
if cls:
return cls(pipeline_response, None, {})
publish.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/microsoft.graph.publish'} # type: ignore
def unpublish(
self,
booking_business_id, # type: str
**kwargs # type: Any
):
# type: (...) -> None
"""Invoke action unpublish.
Invoke action unpublish.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: None, or the result of cls(response)
:rtype: None
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType[None]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
accept = "application/json"
# Construct URL
url = self.unpublish.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
request = self._client.post(url, query_parameters, header_parameters)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [204]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.OdataError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
if cls:
return cls(pipeline_response, None, {})
unpublish.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/microsoft.graph.unpublish'} # type: ignore
def list_services(
self,
booking_business_id, # type: str
orderby=None, # type: Optional[List[Union[str, "models.Enum22"]]]
select=None, # type: Optional[List[Union[str, "models.Enum23"]]]
expand=None, # type: Optional[List[str]]
**kwargs # type: Any
):
# type: (...) -> Iterable["models.CollectionOfBookingService"]
"""Get services from bookingBusinesses.
Get services from bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param orderby: Order items by property values.
:type orderby: list[str or ~bookings.models.Enum22]
:param select: Select properties to be returned.
:type select: list[str or ~bookings.models.Enum23]
:param expand: Expand related entities.
:type expand: list[str]
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either CollectionOfBookingService or the result of cls(response)
:rtype: ~azure.core.paging.ItemPaged[~bookings.models.CollectionOfBookingService]
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType["models.CollectionOfBookingService"]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
accept = "application/json"
def prepare_request(next_link=None):
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
if not next_link:
# Construct URL
url = self.list_services.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
if self._config.top is not None:
query_parameters['$top'] = self._serialize.query("self._config.top", self._config.top, 'int', minimum=0)
if self._config.skip is not None:
query_parameters['$skip'] = self._serialize.query("self._config.skip", self._config.skip, 'int', minimum=0)
if self._config.search is not None:
query_parameters['$search'] = self._serialize.query("self._config.search", self._config.search, 'str')
if self._config.filter is not None:
query_parameters['$filter'] = self._serialize.query("self._config.filter", self._config.filter, 'str')
if self._config.count is not None:
query_parameters['$count'] = self._serialize.query("self._config.count", self._config.count, 'bool')
if orderby is not None:
query_parameters['$orderby'] = self._serialize.query("orderby", orderby, '[str]', div=',')
if select is not None:
query_parameters['$select'] = self._serialize.query("select", select, '[str]', div=',')
if expand is not None:
query_parameters['$expand'] = self._serialize.query("expand", expand, '[str]', div=',')
request = self._client.get(url, query_parameters, header_parameters)
else:
url = next_link
query_parameters = {} # type: Dict[str, Any]
request = self._client.get(url, query_parameters, header_parameters)
return request
def extract_data(pipeline_response):
deserialized = self._deserialize('CollectionOfBookingService', pipeline_response)
list_of_elem = deserialized.value
if cls:
list_of_elem = cls(list_of_elem)
return deserialized.odata_next_link or None, iter(list_of_elem)
def get_next(next_link=None):
request = prepare_request(next_link)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [200]:
error = self._deserialize(models.OdataError, response)
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
return pipeline_response
return ItemPaged(
get_next, extract_data
)
list_services.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/services'} # type: ignore
def create_services(
self,
booking_business_id, # type: str
body, # type: "models.MicrosoftGraphBookingService"
**kwargs # type: Any
):
# type: (...) -> "models.MicrosoftGraphBookingService"
"""Create new navigation property to services for bookingBusinesses.
Create new navigation property to services for bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param body: New navigation property.
:type body: ~bookings.models.MicrosoftGraphBookingService
:keyword callable cls: A custom type or function that will be passed the direct response
:return: MicrosoftGraphBookingService, or the result of cls(response)
:rtype: ~bookings.models.MicrosoftGraphBookingService
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType["models.MicrosoftGraphBookingService"]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
content_type = kwargs.pop("content_type", "application/json")
accept = "application/json"
# Construct URL
url = self.create_services.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str')
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
body_content_kwargs = {} # type: Dict[str, Any]
body_content = self._serialize.body(body, 'MicrosoftGraphBookingService')
body_content_kwargs['content'] = body_content
request = self._client.post(url, query_parameters, header_parameters, **body_content_kwargs)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [201]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.OdataError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize('MicrosoftGraphBookingService', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
create_services.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/services'} # type: ignore
def get_services(
self,
booking_business_id, # type: str
booking_service_id, # type: str
select=None, # type: Optional[List[Union[str, "models.Enum24"]]]
expand=None, # type: Optional[List[str]]
**kwargs # type: Any
):
# type: (...) -> "models.MicrosoftGraphBookingService"
"""Get services from bookingBusinesses.
Get services from bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param booking_service_id: key: id of bookingService.
:type booking_service_id: str
:param select: Select properties to be returned.
:type select: list[str or ~bookings.models.Enum24]
:param expand: Expand related entities.
:type expand: list[str]
:keyword callable cls: A custom type or function that will be passed the direct response
:return: MicrosoftGraphBookingService, or the result of cls(response)
:rtype: ~bookings.models.MicrosoftGraphBookingService
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType["models.MicrosoftGraphBookingService"]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
accept = "application/json"
# Construct URL
url = self.get_services.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
'bookingService-id': self._serialize.url("booking_service_id", booking_service_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
if select is not None:
query_parameters['$select'] = self._serialize.query("select", select, '[str]', div=',')
if expand is not None:
query_parameters['$expand'] = self._serialize.query("expand", expand, '[str]', div=',')
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
request = self._client.get(url, query_parameters, header_parameters)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.OdataError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize('MicrosoftGraphBookingService', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
get_services.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/services/{bookingService-id}'} # type: ignore
def update_services(
self,
booking_business_id, # type: str
booking_service_id, # type: str
body, # type: "models.MicrosoftGraphBookingService"
**kwargs # type: Any
):
# type: (...) -> None
"""Update the navigation property services in bookingBusinesses.
Update the navigation property services in bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param booking_service_id: key: id of bookingService.
:type booking_service_id: str
:param body: New navigation property values.
:type body: ~bookings.models.MicrosoftGraphBookingService
:keyword callable cls: A custom type or function that will be passed the direct response
:return: None, or the result of cls(response)
:rtype: None
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType[None]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
content_type = kwargs.pop("content_type", "application/json")
accept = "application/json"
# Construct URL
url = self.update_services.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
'bookingService-id': self._serialize.url("booking_service_id", booking_service_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str')
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
body_content_kwargs = {} # type: Dict[str, Any]
body_content = self._serialize.body(body, 'MicrosoftGraphBookingService')
body_content_kwargs['content'] = body_content
request = self._client.patch(url, query_parameters, header_parameters, **body_content_kwargs)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [204]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.OdataError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
if cls:
return cls(pipeline_response, None, {})
update_services.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/services/{bookingService-id}'} # type: ignore
def delete_services(
self,
booking_business_id, # type: str
booking_service_id, # type: str
if_match=None, # type: Optional[str]
**kwargs # type: Any
):
# type: (...) -> None
"""Delete navigation property services for bookingBusinesses.
Delete navigation property services for bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param booking_service_id: key: id of bookingService.
:type booking_service_id: str
:param if_match: ETag.
:type if_match: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: None, or the result of cls(response)
:rtype: None
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType[None]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
accept = "application/json"
# Construct URL
url = self.delete_services.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
'bookingService-id': self._serialize.url("booking_service_id", booking_service_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
# Construct headers
header_parameters = {} # type: Dict[str, Any]
if if_match is not None:
header_parameters['If-Match'] = self._serialize.header("if_match", if_match, 'str')
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
request = self._client.delete(url, query_parameters, header_parameters)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [204]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.OdataError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
if cls:
return cls(pipeline_response, None, {})
delete_services.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/services/{bookingService-id}'} # type: ignore
def list_staff_members(
self,
booking_business_id, # type: str
orderby=None, # type: Optional[List[Union[str, "models.Enum25"]]]
select=None, # type: Optional[List[Union[str, "models.Enum26"]]]
expand=None, # type: Optional[List[str]]
**kwargs # type: Any
):
# type: (...) -> Iterable["models.CollectionOfBookingStaffMember"]
"""Get staffMembers from bookingBusinesses.
Get staffMembers from bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param orderby: Order items by property values.
:type orderby: list[str or ~bookings.models.Enum25]
:param select: Select properties to be returned.
:type select: list[str or ~bookings.models.Enum26]
:param expand: Expand related entities.
:type expand: list[str]
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either CollectionOfBookingStaffMember or the result of cls(response)
:rtype: ~azure.core.paging.ItemPaged[~bookings.models.CollectionOfBookingStaffMember]
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType["models.CollectionOfBookingStaffMember"]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
accept = "application/json"
def prepare_request(next_link=None):
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
if not next_link:
# Construct URL
url = self.list_staff_members.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
if self._config.top is not None:
query_parameters['$top'] = self._serialize.query("self._config.top", self._config.top, 'int', minimum=0)
if self._config.skip is not None:
query_parameters['$skip'] = self._serialize.query("self._config.skip", self._config.skip, 'int', minimum=0)
if self._config.search is not None:
query_parameters['$search'] = self._serialize.query("self._config.search", self._config.search, 'str')
if self._config.filter is not None:
query_parameters['$filter'] = self._serialize.query("self._config.filter", self._config.filter, 'str')
if self._config.count is not None:
query_parameters['$count'] = self._serialize.query("self._config.count", self._config.count, 'bool')
if orderby is not None:
query_parameters['$orderby'] = self._serialize.query("orderby", orderby, '[str]', div=',')
if select is not None:
query_parameters['$select'] = self._serialize.query("select", select, '[str]', div=',')
if expand is not None:
query_parameters['$expand'] = self._serialize.query("expand", expand, '[str]', div=',')
request = self._client.get(url, query_parameters, header_parameters)
else:
url = next_link
query_parameters = {} # type: Dict[str, Any]
request = self._client.get(url, query_parameters, header_parameters)
return request
def extract_data(pipeline_response):
deserialized = self._deserialize('CollectionOfBookingStaffMember', pipeline_response)
list_of_elem = deserialized.value
if cls:
list_of_elem = cls(list_of_elem)
return deserialized.odata_next_link or None, iter(list_of_elem)
def get_next(next_link=None):
request = prepare_request(next_link)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [200]:
error = self._deserialize(models.OdataError, response)
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
return pipeline_response
return ItemPaged(
get_next, extract_data
)
list_staff_members.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/staffMembers'} # type: ignore
def create_staff_members(
self,
booking_business_id, # type: str
body, # type: "models.MicrosoftGraphBookingStaffMember"
**kwargs # type: Any
):
# type: (...) -> "models.MicrosoftGraphBookingStaffMember"
"""Create new navigation property to staffMembers for bookingBusinesses.
Create new navigation property to staffMembers for bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param body: New navigation property.
:type body: ~bookings.models.MicrosoftGraphBookingStaffMember
:keyword callable cls: A custom type or function that will be passed the direct response
:return: MicrosoftGraphBookingStaffMember, or the result of cls(response)
:rtype: ~bookings.models.MicrosoftGraphBookingStaffMember
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType["models.MicrosoftGraphBookingStaffMember"]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
content_type = kwargs.pop("content_type", "application/json")
accept = "application/json"
# Construct URL
url = self.create_staff_members.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str')
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
body_content_kwargs = {} # type: Dict[str, Any]
body_content = self._serialize.body(body, 'MicrosoftGraphBookingStaffMember')
body_content_kwargs['content'] = body_content
request = self._client.post(url, query_parameters, header_parameters, **body_content_kwargs)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [201]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.OdataError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize('MicrosoftGraphBookingStaffMember', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
create_staff_members.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/staffMembers'} # type: ignore
def get_staff_members(
self,
booking_business_id, # type: str
booking_staff_member_id, # type: str
select=None, # type: Optional[List[Union[str, "models.Enum27"]]]
expand=None, # type: Optional[List[str]]
**kwargs # type: Any
):
# type: (...) -> "models.MicrosoftGraphBookingStaffMember"
"""Get staffMembers from bookingBusinesses.
Get staffMembers from bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param booking_staff_member_id: key: id of bookingStaffMember.
:type booking_staff_member_id: str
:param select: Select properties to be returned.
:type select: list[str or ~bookings.models.Enum27]
:param expand: Expand related entities.
:type expand: list[str]
:keyword callable cls: A custom type or function that will be passed the direct response
:return: MicrosoftGraphBookingStaffMember, or the result of cls(response)
:rtype: ~bookings.models.MicrosoftGraphBookingStaffMember
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType["models.MicrosoftGraphBookingStaffMember"]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
accept = "application/json"
# Construct URL
url = self.get_staff_members.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
'bookingStaffMember-id': self._serialize.url("booking_staff_member_id", booking_staff_member_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
if select is not None:
query_parameters['$select'] = self._serialize.query("select", select, '[str]', div=',')
if expand is not None:
query_parameters['$expand'] = self._serialize.query("expand", expand, '[str]', div=',')
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
request = self._client.get(url, query_parameters, header_parameters)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.OdataError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
deserialized = self._deserialize('MicrosoftGraphBookingStaffMember', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
get_staff_members.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/staffMembers/{bookingStaffMember-id}'} # type: ignore
def update_staff_members(
self,
booking_business_id, # type: str
booking_staff_member_id, # type: str
body, # type: "models.MicrosoftGraphBookingStaffMember"
**kwargs # type: Any
):
# type: (...) -> None
"""Update the navigation property staffMembers in bookingBusinesses.
Update the navigation property staffMembers in bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param booking_staff_member_id: key: id of bookingStaffMember.
:type booking_staff_member_id: str
:param body: New navigation property values.
:type body: ~bookings.models.MicrosoftGraphBookingStaffMember
:keyword callable cls: A custom type or function that will be passed the direct response
:return: None, or the result of cls(response)
:rtype: None
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType[None]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
content_type = kwargs.pop("content_type", "application/json")
accept = "application/json"
# Construct URL
url = self.update_staff_members.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
'bookingStaffMember-id': self._serialize.url("booking_staff_member_id", booking_staff_member_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str')
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
body_content_kwargs = {} # type: Dict[str, Any]
body_content = self._serialize.body(body, 'MicrosoftGraphBookingStaffMember')
body_content_kwargs['content'] = body_content
request = self._client.patch(url, query_parameters, header_parameters, **body_content_kwargs)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [204]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.OdataError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
if cls:
return cls(pipeline_response, None, {})
update_staff_members.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/staffMembers/{bookingStaffMember-id}'} # type: ignore
def delete_staff_members(
self,
booking_business_id, # type: str
booking_staff_member_id, # type: str
if_match=None, # type: Optional[str]
**kwargs # type: Any
):
# type: (...) -> None
"""Delete navigation property staffMembers for bookingBusinesses.
Delete navigation property staffMembers for bookingBusinesses.
:param booking_business_id: key: id of bookingBusiness.
:type booking_business_id: str
:param booking_staff_member_id: key: id of bookingStaffMember.
:type booking_staff_member_id: str
:param if_match: ETag.
:type if_match: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: None, or the result of cls(response)
:rtype: None
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType[None]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
accept = "application/json"
# Construct URL
url = self.delete_staff_members.metadata['url'] # type: ignore
path_format_arguments = {
'bookingBusiness-id': self._serialize.url("booking_business_id", booking_business_id, 'str'),
'bookingStaffMember-id': self._serialize.url("booking_staff_member_id", booking_staff_member_id, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
# Construct headers
header_parameters = {} # type: Dict[str, Any]
if if_match is not None:
header_parameters['If-Match'] = self._serialize.header("if_match", if_match, 'str')
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
request = self._client.delete(url, query_parameters, header_parameters)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [204]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.OdataError, response)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
if cls:
return cls(pipeline_response, None, {})
delete_staff_members.metadata = {'url': '/bookingBusinesses/{bookingBusiness-id}/staffMembers/{bookingStaffMember-id}'} # type: ignore
| 48.162707 | 139 | 0.653314 | 9,826 | 93,243 | 6.002544 | 0.028598 | 0.032841 | 0.038911 | 0.016378 | 0.957308 | 0.95663 | 0.948136 | 0.939455 | 0.928401 | 0.925196 | 0 | 0.00685 | 0.242227 | 93,243 | 1,935 | 140 | 48.187597 | 0.827901 | 0.282724 | 0 | 0.856769 | 0 | 0 | 0.117259 | 0.045256 | 0 | 0 | 0 | 0 | 0 | 1 | 0.037555 | false | 0 | 0.00786 | 0 | 0.092576 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
c7f745307ede1bf1503e1cd0489477de3f39885f | 277 | py | Python | poly/common.py | jdanford/poly | 4f3a242dbb54fb68375a310af943be759588f459 | [
"0BSD"
] | null | null | null | poly/common.py | jdanford/poly | 4f3a242dbb54fb68375a310af943be759588f459 | [
"0BSD"
] | null | null | null | poly/common.py | jdanford/poly | 4f3a242dbb54fb68375a310af943be759588f459 | [
"0BSD"
] | null | null | null | class PolyError(Exception):
pass
SAFE_IDENT = r"[a-zA-Z!@\$%\^&\*=\|<>\?\/][a-zA-Z0-9_!@\$%\^&\*\-\+=\|<>\?\/]*|[\-\+]([a-zA-Z!@\$%\^&\*\-\+=\|<>\?\/][a-zA-Z0-9_!@\$%\^&\*\-\+=\|<>\?\/]*)?"
SAFE_SYMBOL = r"#[a-zA-Z!@\$%\^&\*=\|<>\?\/][a-zA-Z0-9_!@\$%\^&\*\-\+=\|<>\?\/]*"
| 46.166667 | 156 | 0.299639 | 31 | 277 | 2.516129 | 0.419355 | 0.230769 | 0.153846 | 0.192308 | 0.410256 | 0.410256 | 0.410256 | 0.282051 | 0 | 0 | 0 | 0.022814 | 0.050542 | 277 | 5 | 157 | 55.4 | 0.273764 | 0 | 0 | 0 | 0 | 0.25 | 0.736462 | 0.736462 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.25 | 0 | 0 | 0.25 | 0 | 0 | 0 | 0 | null | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 8 |
2a0aa9c94f65d473518398a5c70f792007bc7e48 | 4,440 | py | Python | tests/test_string_buffer_right.py | robertblackwell/simple_curses | 47f2bb81bcbc2087101839372f71a9117f5dc643 | [
"MIT"
] | null | null | null | tests/test_string_buffer_right.py | robertblackwell/simple_curses | 47f2bb81bcbc2087101839372f71a9117f5dc643 | [
"MIT"
] | null | null | null | tests/test_string_buffer_right.py | robertblackwell/simple_curses | 47f2bb81bcbc2087101839372f71a9117f5dc643 | [
"MIT"
] | null | null | null | import sys
import unittest
import string_buffer
class TestStringBufferRight(unittest.TestCase):
def test_right_arrow_01(self):
sb = string_buffer.StringBuffer("abc", 5)
self.assertEqual(sb.content, "abc")
self.assertEqual(sb.display_string, "abc" + sb.EOSPAD)
self.assertEqual(sb.cpos_buffer, 3)
sb.handle_left()
sb.handle_left()
sb.handle_left()
self.assertEqual(sb.content, "abc")
self.assertEqual(sb.display_string, "abc")
self.assertEqual(sb.cpos_buffer, 0)
self.assertEqual(sb.state, sb.STATE_EDITING)
sb.handle_right()
self.assertEqual(sb.content, "abc")
self.assertEqual(sb.display_string, "abc")
self.assertEqual(sb.cpos_buffer, 1)
self.assertEqual(sb.state, sb.STATE_EDITING)
sb.handle_right()
self.assertEqual(sb.content, "abc")
self.assertEqual(sb.display_string, "abc")
self.assertEqual(sb.cpos_buffer, 2)
self.assertEqual(sb.state, sb.STATE_EDITING)
sb.handle_right()
self.assertEqual(sb.content, "abc")
self.assertEqual(sb.display_string, "abc" + sb.EOSPAD)
self.assertEqual(sb.cpos_buffer, 3)
self.assertEqual(sb.state, sb.STATE_APPENDING)
sb.handle_right()
self.assertEqual(sb.content, "abc")
self.assertEqual(sb.display_string, "abc" + sb.EOSPAD)
self.assertEqual(sb.cpos_buffer, 3)
self.assertEqual(sb.state, sb.STATE_APPENDING)
def test_right_arrow_02(self):
sb = string_buffer.StringBuffer("abcdefg", 5)
self.assertEqual(sb.content, "abcdefg")
self.assertEqual(sb.cpos_buffer, 4)
sb.handle_left()
sb.handle_left()
sb.handle_left()
sb.handle_left()
sb.handle_left()
sb.handle_left()
sb.handle_left()
sb.handle_left()
self.assertEqual(sb.content, "abcdefg")
self.assertEqual(sb.display_string, "abcde")
self.assertEqual(sb.cpos_buffer, 0)
self.assertEqual(sb.state, sb.STATE_EDITING)
sb.handle_right()
self.assertEqual(sb.content, "abcdefg")
self.assertEqual(sb.display_string, "abcde")
self.assertEqual(sb.cpos_buffer, 1)
self.assertEqual(sb.state, sb.STATE_EDITING)
sb.handle_right()
self.assertEqual(sb.content, "abcdefg")
self.assertEqual(sb.display_string, "abcde")
self.assertEqual(sb.cpos_buffer, 2)
self.assertEqual(sb.state, sb.STATE_EDITING)
sb.handle_right()
self.assertEqual(sb.content, "abcdefg")
self.assertEqual(sb.display_string, "abcde")
self.assertEqual(sb.cpos_buffer, 3)
self.assertEqual(sb.state, sb.STATE_EDITING)
sb.handle_right()
self.assertEqual(sb.content, "abcdefg")
self.assertEqual(sb.display_string, "abcde")
self.assertEqual(sb.cpos_buffer, 4)
self.assertEqual(sb.state, sb.STATE_EDITING)
sb.handle_right()
self.assertEqual(sb.content, "abcdefg")
self.assertEqual(sb.display_string, "bcdef")
self.assertEqual(sb.cpos_buffer, 4)
self.assertEqual(sb.state, sb.STATE_EDITING)
sb.handle_right()
self.assertEqual(sb.content, "abcdefg")
self.assertEqual(sb.display_string, "cdefg")
self.assertEqual(sb.cpos_buffer, 4)
self.assertEqual(sb.state, sb.STATE_EDITING)
sb.handle_right()
self.assertEqual(sb.content, "abcdefg")
self.assertEqual(sb.display_string, "defg" + sb.EOSPAD)
self.assertEqual(sb.cpos_buffer, 4)
self.assertEqual(sb.state, sb.STATE_APPENDING)
sb.handle_right()
self.assertEqual(sb.content, "abcdefg")
self.assertEqual(sb.display_string, "defg" + sb.EOSPAD)
self.assertEqual(sb.cpos_buffer, 4)
self.assertEqual(sb.state, sb.STATE_APPENDING)
sb.handle_right()
self.assertEqual(sb.content, "abcdefg")
self.assertEqual(sb.display_string, "defg" + sb.EOSPAD)
self.assertEqual(sb.cpos_buffer, 4)
self.assertEqual(sb.state, sb.STATE_APPENDING)
sb.handle_right()
self.assertEqual(sb.content, "abcdefg")
self.assertEqual(sb.display_string, "defg" + sb.EOSPAD)
self.assertEqual(sb.cpos_buffer, 4)
self.assertEqual(sb.state, sb.STATE_APPENDING)
if __name__ == '__main__':
unittest.main()
| 34.6875 | 63 | 0.649324 | 541 | 4,440 | 5.157116 | 0.077634 | 0.370968 | 0.42043 | 0.154839 | 0.941577 | 0.919355 | 0.915412 | 0.915412 | 0.898208 | 0.898208 | 0 | 0.006987 | 0.226351 | 4,440 | 127 | 64 | 34.96063 | 0.80524 | 0 | 0 | 0.884615 | 0 | 0 | 0.042568 | 0 | 0 | 0 | 0 | 0 | 0.663462 | 1 | 0.019231 | false | 0 | 0.028846 | 0 | 0.057692 | 0 | 0 | 0 | 0 | null | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 10 |
2a469749b52b2b413e42b92363ee2989065349f9 | 106 | py | Python | Codewars/8kyu/is-it-a-number/Python/test.py | RevansChen/online-judge | ad1b07fee7bd3c49418becccda904e17505f3018 | [
"MIT"
] | 7 | 2017-09-20T16:40:39.000Z | 2021-08-31T18:15:08.000Z | Codewars/8kyu/is-it-a-number/Python/test.py | RevansChen/online-judge | ad1b07fee7bd3c49418becccda904e17505f3018 | [
"MIT"
] | null | null | null | Codewars/8kyu/is-it-a-number/Python/test.py | RevansChen/online-judge | ad1b07fee7bd3c49418becccda904e17505f3018 | [
"MIT"
] | null | null | null | # Python - 3.6.0
test.assert_equals(isDigit('s2324'), False)
test.assert_equals(isDigit('-234.4'), True)
| 21.2 | 43 | 0.707547 | 17 | 106 | 4.294118 | 0.764706 | 0.273973 | 0.438356 | 0.630137 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.113402 | 0.084906 | 106 | 4 | 44 | 26.5 | 0.639175 | 0.132075 | 0 | 0 | 0 | 0 | 0.122222 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | true | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
2a609a64bb8d2da5534f203dd9bec0b73c7725f1 | 20,582 | py | Python | test/unit/testPayment.py | Ghost93/python-sdk | 24fffc1d7cfb53e5f8548c6afa05f6706411a8ba | [
"MIT"
] | 2 | 2021-05-07T16:07:55.000Z | 2021-12-07T01:52:33.000Z | test/unit/testPayment.py | Ghost93/python-sdk | 24fffc1d7cfb53e5f8548c6afa05f6706411a8ba | [
"MIT"
] | 5 | 2018-02-13T16:11:51.000Z | 2021-06-25T10:45:36.000Z | test/unit/testPayment.py | Ghost93/python-sdk | 24fffc1d7cfb53e5f8548c6afa05f6706411a8ba | [
"MIT"
] | 8 | 2018-06-05T19:20:10.000Z | 2021-12-07T02:35:34.000Z | import sys
import os
import unittest
sys.path.append(os.path.abspath('.'))
import paymentrails.configuration
import paymentrails.payment
from mock import MagicMock, Mock, patch
import paymentrails.exceptions.notFoundException
import paymentrails.exceptions.invalidFieldException
def fake_find(paymentId,batchId,term=""):
if paymentId == None:
raise paymentrails.exceptions.invalidFieldException.InvalidFieldException("Payment id cannot be None")
if paymentId[0:1] != "P":
raise paymentrails.exceptions.notFoundException.NotFoundException("Payment id is invalid")
if batchId == None:
raise paymentrails.exceptions.invalidFieldException.InvalidFieldException("Batch id cannot be None")
if batchId[0:1] != "B":
raise paymentrails.exceptions.notFoundException.NotFoundException("Batch id is invalid")
return {"ok":"true","payment":{"id":"P-91XQ40VT54GQM","recipient":{"id":"R-91XQ0PJH39U54","referenceId":"U345678912","email":"Johnny@test.com","name":"mark Test","lastName":"Test","firstName":"mark","type":"individual","status":"active","language":"en","complianceStatus":"pending","dob":"null","payoutMethod":"paypal","updatedAt":"2017-05-08T14:49:12.512Z","createdAt":"2017-05-04T16:17:04.378Z","gravatarUrl":"https://s3.amazonaws.com/static.api.paymentrails.com/icon_user.svg","compliance":{"status":"pending","checkedAt":"null"},"payout":{"autoswitch":{"limit":1000,"active":"false"},"holdup":{"limit":1000,"active":"false"},"primary":{"method":"paypal","currency":{"currency":{}}},"method":"paypal","accounts":{"paypal":{"address":"testpaypal@example.com"}},"methodDisplay":"PayPal"},"address":{"street1":"null","street2":"null","city":"null","postalCode":"null","country":"null","region":"null","phone":"null"}},"status":"pending","sourceAmount":"900.90","exchangeRate":"1.000000","fees":"0.00","recipientFees":"0.00","targetAmount":"65.00","fxRate":"2.000000","memo":"","processedAt":"null","createdAt":"2017-05-08T18:30:45.012Z","updatedAt":"2017-05-12T18:39:06.061Z","merchantFees":"0.00","compliance":{"status":"pending","checkedAt":"null"},"sourceCurrency":"USD","sourceCurrencyName":"US Dollar","targetCurrency":"USD","targetCurrencyName":"US Dollar","batch":{"id":"B-91XQ40VT5HF18","createdAt":"2017-05-08T18:30:44.905Z","updatedAt":"2017-05-12T18:39:06.125Z","sentAt":"null","completedAt":"null"}}}
def fake_update(paymentId,batchId, body):
if paymentId == None:
raise paymentrails.exceptions.invalidFieldException.InvalidFieldException("Payment id cannot be None")
if batchId == None:
raise paymentrails.exceptions.invalidFieldException.InvalidFieldException("Batch id cannot be None")
if batchId[0:1] != "B":
raise paymentrails.exceptions.notFoundException.NotFoundException("Batch id is invalid")
if paymentId[0:1] != "P":
raise paymentrails.exceptions.notFoundException.NotFoundException("Payment id is invalid")
if body == None:
raise paymentrails.exceptions.invalidFieldException.InvalidFieldException("Body cannot be None")
return {"ok": "true", "object": "updated"}
def fake_create(body,batchId):
if batchId == None:
raise paymentrails.exceptions.invalidFieldException.InvalidFieldException("Batch id cannot be None")
if body == None:
raise paymentrails.exceptions.invalidFieldException.InvalidFieldException("Body is invalid")
if batchId[0:1] != "B":
raise paymentrails.exceptions.notFoundException.NotFoundException("Batch Id is invalid")
return {"ok": "true"}
def fake_delete(paymentId,batchId):
if paymentId == None:
raise paymentrails.exceptions.invalidFieldException.InvalidFieldException("Payment id cannot be None")
if batchId == None:
raise paymentrails.exceptions.invalidFieldException.InvalidFieldException("Batch id cannot be None")
if batchId[0:1] != "B":
raise paymentrails.exceptions.notFoundException.NotFoundException("Batch id is invalid")
if paymentId[0:1] != "P":
raise paymentrails.exceptions.notFoundException.NotFoundException("Payment id is invalid")
return {"ok": "true", "object": "deleted"}
def fake_search(page,pageSize,term):
if term == None:
raise paymentrails.exceptions.invalidFieldException.InvalidFieldException("Term cannot be None")
return {"ok":"true","payments":[{"id":"P-912Q8JUA75HNC","recipient":{"id":"R-91XQ0PJH39U54","referenceId":"U345678912","email":"Johnny@test.com","name":"mark Test","lastName":"Test","firstName":"mark","type":"individual","status":"active","language":"en","complianceStatus":"pending","dob":"null","payoutMethod":"paypal","updatedAt":"2017-05-08T14:49:12.512Z","createdAt":"2017-05-04T16:17:04.378Z","gravatarUrl":"https://s3.amazonaws.com/static.api.paymentrails.com/icon_user.svg","compliance":{"status":"pending","checkedAt":"null"},"payout":{"autoswitch":{"limit":1000,"active":"false"},"holdup":{"limit":1000,"active":"false"},"primary":{"method":"paypal","currency":{"currency":{}}},"method":"paypal","accounts":{"paypal":{"address":"testpaypal@example.com"}},"methodDisplay":"PayPal"},"address":{"street1":"null","street2":"null","city":"null","postalCode":"null","country":"null","region":"null","phone":"null"}},"status":"pending","sourceAmount":"15.00","exchangeRate":"1.000000","fees":"0.00","recipientFees":"0.00","targetAmount":"65.00","fxRate":"2.000000","memo":"","processedAt":"null","createdAt":"2017-05-08T17:18:16.948Z","updatedAt":"2017-05-11T19:05:53.172Z","merchantFees":"0.00","compliance":{"status":"pending","checkedAt":"null"},"sourceCurrency":"USD","sourceCurrencyName":"US Dollar","targetCurrency":"USD","targetCurrencyName":"US Dollar","batch":{"id":"B-91XQ2ZHXARPJE","createdAt":"2017-05-08T17:18:16.893Z","updatedAt":"2017-05-11T19:05:53.265Z","sentAt":"null","completedAt":"null"}}],"meta":{"page":1,"pages":1,"records":1}}
class TestPayment(unittest.TestCase):
public_key = ("public_key")
private_key = ("private_key")
@patch('paymentrails.payment.Payment.find', fake_find)
def test_retrieve_payment(self):
paymentrails.configuration.Configuration.set_public_key(TestPayment.public_key)
paymentrails.configuration.Configuration.set_private_key(TestPayment.private_key)
batchId = "B-912Q61G0BRVGC"
response = paymentrails.payment.Payment.find('P-91XQ0U0B1RW5M',batchId)
status = {"ok":"true","payment":{"id":"P-91XQ40VT54GQM","recipient":{"id":"R-91XQ0PJH39U54","referenceId":"U345678912","email":"Johnny@test.com","name":"mark Test","lastName":"Test","firstName":"mark","type":"individual","status":"active","language":"en","complianceStatus":"pending","dob":"null","payoutMethod":"paypal","updatedAt":"2017-05-08T14:49:12.512Z","createdAt":"2017-05-04T16:17:04.378Z","gravatarUrl":"https://s3.amazonaws.com/static.api.paymentrails.com/icon_user.svg","compliance":{"status":"pending","checkedAt":"null"},"payout":{"autoswitch":{"limit":1000,"active":"false"},"holdup":{"limit":1000,"active":"false"},"primary":{"method":"paypal","currency":{"currency":{}}},"method":"paypal","accounts":{"paypal":{"address":"testpaypal@example.com"}},"methodDisplay":"PayPal"},"address":{"street1":"null","street2":"null","city":"null","postalCode":"null","country":"null","region":"null","phone":"null"}},"status":"pending","sourceAmount":"900.90","exchangeRate":"1.000000","fees":"0.00","recipientFees":"0.00","targetAmount":"65.00","fxRate":"2.000000","memo":"","processedAt":"null","createdAt":"2017-05-08T18:30:45.012Z","updatedAt":"2017-05-12T18:39:06.061Z","merchantFees":"0.00","compliance":{"status":"pending","checkedAt":"null"},"sourceCurrency":"USD","sourceCurrencyName":"US Dollar","targetCurrency":"USD","targetCurrencyName":"US Dollar","batch":{"id":"B-91XQ40VT5HF18","createdAt":"2017-05-08T18:30:44.905Z","updatedAt":"2017-05-12T18:39:06.125Z","sentAt":"null","completedAt":"null"}}}
self.assertEqual(response, status)
@patch('paymentrails.payment.Payment.find', fake_find)
def test_retrieve_payment_InvalidPaymentId(self):
with self.assertRaises(paymentrails.exceptions.notFoundException.NotFoundException):
paymentrails.configuration.Configuration.set_public_key(TestPayment.public_key)
paymentrails.configuration.Configuration.set_private_key(TestPayment.private_key)
batchId = "B-912Q61G0BRVGC"
response = paymentrails.payment.Payment.find('wdwdwd',batchId)
@patch('paymentrails.payment.Payment.find', fake_find)
def test_retrieve_payment_InvalidBatchId(self):
with self.assertRaises(paymentrails.exceptions.notFoundException.NotFoundException):
paymentrails.configuration.Configuration.set_public_key(TestPayment.public_key)
paymentrails.configuration.Configuration.set_private_key(TestPayment.private_key)
batchId = "wwdwdwd"
response = paymentrails.payment.Payment.find('P-91XQ0U0B1RW5M',batchId)
@patch('paymentrails.payment.Payment.find', fake_find)
def test_retrieve_payment_None_Batch(self):
with self.assertRaises( paymentrails.exceptions.invalidFieldException.InvalidFieldException):
paymentrails.configuration.Configuration.set_public_key(TestPayment.public_key)
paymentrails.configuration.Configuration.set_private_key(TestPayment.private_key)
response = paymentrails.payment.Payment.find('P-91XQ0U0B1RW5M',None)
@patch('paymentrails.payment.Payment.find', fake_find)
def test_retrieve_payment_None_Payment(self):
with self.assertRaises( paymentrails.exceptions.invalidFieldException.InvalidFieldException):
paymentrails.configuration.Configuration.set_public_key(TestPayment.public_key)
paymentrails.configuration.Configuration.set_private_key(TestPayment.private_key)
response = paymentrails.payment.Payment.find(None,"B-hghgh")
@patch('paymentrails.payment.Payment.create', fake_create)
def test_create_payment(self):
paymentrails.configuration.Configuration.set_public_key(TestPayment.public_key)
paymentrails.configuration.Configuration.set_private_key(TestPayment.private_key)
body = {"payments": [{"recipient": {"id": "R-91XPYX3V2MM1G"},
"sourceAmount": "65", "memo": "", "sourceCurrency": "CAD"}]}
batchId = "B-912Q61G0BRVGC"
response = paymentrails.payment.Payment.create(body,batchId)
status = {"ok": "true"}
self.assertEqual(response, status)
@patch('paymentrails.payment.Payment.create', fake_create)
def test_create_payment_InvalidBatchId(self):
with self.assertRaises(paymentrails.exceptions.notFoundException.NotFoundException):
paymentrails.configuration.Configuration.set_public_key(TestPayment.public_key)
paymentrails.configuration.Configuration.set_private_key(TestPayment.private_key)
body = {"payments": [{"recipient": {"id": "R-91XPYX3V2MM1G"},
"sourceAmount": "65", "memo": "", "sourceCurrency": "CAD"}]}
batchId = "dddd"
response = paymentrails.payment.Payment.create(body,batchId)
@patch('paymentrails.payment.Payment.create', fake_create)
def test_create_payment_None_body(self):
with self.assertRaises( paymentrails.exceptions.invalidFieldException.InvalidFieldException):
paymentrails.configuration.Configuration.set_public_key(TestPayment.public_key)
paymentrails.configuration.Configuration.set_private_key(TestPayment.private_key)
batchId = "B-dddd"
response = paymentrails.payment.Payment.create(None,batchId)
@patch('paymentrails.payment.Payment.create', fake_create)
def test_create_payment_None_batch(self):
with self.assertRaises( paymentrails.exceptions.invalidFieldException.InvalidFieldException):
paymentrails.configuration.Configuration.set_public_key(TestPayment.public_key)
paymentrails.configuration.Configuration.set_private_key(TestPayment.private_key)
body = {"payments": [{"recipient": {"id": "R-91XPYX3V2MM1G"},
"sourceAmount": "65", "memo": "", "sourceCurrency": "CAD"}]}
response = paymentrails.payment.Payment.create(body,None)
@patch('paymentrails.payment.Payment.update', fake_update)
def test_update_payment(self):
paymentrails.configuration.Configuration.set_public_key(TestPayment.public_key)
paymentrails.configuration.Configuration.set_private_key(TestPayment.private_key)
body = {"sourceAmount": "900.90"}
batchId = "B-912Q61G0BRVGC"
response = paymentrails.payment.Payment.update("P-91XQ0U0B1RW5M",batchId, body)
status = {"ok": "true", "object": "updated"}
self.assertEqual(response, status)
@patch('paymentrails.payment.Payment.update', fake_update)
def test_update_payment_InvalidBatchId(self):
with self.assertRaises(paymentrails.exceptions.notFoundException.NotFoundException):
paymentrails.configuration.Configuration.set_public_key(TestPayment.public_key)
paymentrails.configuration.Configuration.set_private_key(TestPayment.private_key)
body = {"sourceAmount": "900.90"}
batchId = "dddd"
response = paymentrails.payment.Payment.update("P-91XQ0U0B1RW5M",batchId, body)
@patch('paymentrails.payment.Payment.update', fake_update)
def test_update_payment_InvalidPaymentId(self):
with self.assertRaises(paymentrails.exceptions.notFoundException.NotFoundException):
paymentrails.configuration.Configuration.set_public_key(TestPayment.public_key)
paymentrails.configuration.Configuration.set_private_key(TestPayment.private_key)
body = {"sourceAmount": "900.90"}
batchId = "B-912Q61G0BRVGC"
response = paymentrails.payment.Payment.update("ddd",batchId, body)
@patch('paymentrails.payment.Payment.update', fake_update)
def test_update_payment_None_body(self):
with self.assertRaises( paymentrails.exceptions.invalidFieldException.InvalidFieldException):
paymentrails.configuration.Configuration.set_public_key(TestPayment.public_key)
paymentrails.configuration.Configuration.set_private_key(TestPayment.private_key)
batchId = "B-dddd"
response = paymentrails.payment.Payment.update("P-91XQ0U0B1RW5M",batchId, None)
@patch('paymentrails.payment.Payment.update', fake_update)
def test_update_payment_None_payment(self):
with self.assertRaises( paymentrails.exceptions.invalidFieldException.InvalidFieldException):
paymentrails.configuration.Configuration.set_public_key(TestPayment.public_key)
paymentrails.configuration.Configuration.set_private_key(TestPayment.private_key)
body = {"sourceAmount": "900.90"}
batchId = "dddd"
response = paymentrails.payment.Payment.update(None,batchId, body)
@patch('paymentrails.payment.Payment.update', fake_update)
def test_update_payment_None_batch(self):
with self.assertRaises( paymentrails.exceptions.invalidFieldException.InvalidFieldException):
paymentrails.configuration.Configuration.set_public_key(TestPayment.public_key)
paymentrails.configuration.Configuration.set_private_key(TestPayment.private_key)
body = {"sourceAmount": "900.90"}
response = paymentrails.payment.Payment.update("P-91XQ0U0B1RW5M",None, body)
@patch('paymentrails.payment.Payment.delete', fake_delete)
def test_delete_payment(self):
paymentrails.configuration.Configuration.set_public_key(TestPayment.public_key)
paymentrails.configuration.Configuration.set_private_key(TestPayment.private_key)
batchId = "B-912Q61G0BRVGC"
response = paymentrails.payment.Payment.delete('P-912Q61G06TT6A',batchId)
status = {"ok": "true", "object": "deleted"}
self.assertEqual(response, status)
@patch('paymentrails.payment.Payment.delete', fake_delete)
def test_delete_payment_InvalidBatchId(self):
with self.assertRaises(paymentrails.exceptions.notFoundException.NotFoundException):
paymentrails.configuration.Configuration.set_public_key(TestPayment.public_key)
paymentrails.configuration.Configuration.set_private_key(TestPayment.private_key)
batchId = "ffff"
response = paymentrails.payment.Payment.delete('P-912Q61G06TT6A',batchId)
@patch('paymentrails.payment.Payment.delete', fake_delete)
def test_delete_payment_None_payment(self):
with self.assertRaises( paymentrails.exceptions.invalidFieldException.InvalidFieldException):
paymentrails.configuration.Configuration.set_public_key(TestPayment.public_key)
paymentrails.configuration.Configuration.set_private_key(TestPayment.private_key)
batchId = "B-ffff"
response = paymentrails.payment.Payment.delete(None,batchId)
@patch('paymentrails.payment.Payment.delete', fake_delete)
def test_delete_payment_None_batch(self):
with self.assertRaises( paymentrails.exceptions.invalidFieldException.InvalidFieldException):
paymentrails.configuration.Configuration.set_public_key(TestPayment.public_key)
paymentrails.configuration.Configuration.set_private_key(TestPayment.private_key)
response = paymentrails.payment.Payment.delete("P-fhfh",None)
@patch('paymentrails.payment.Payment.delete', fake_delete)
def test_delete_payment_InvalidPaymentId(self):
with self.assertRaises(paymentrails.exceptions.notFoundException.NotFoundException):
paymentrails.configuration.Configuration.set_public_key(TestPayment.public_key)
paymentrails.configuration.Configuration.set_private_key(TestPayment.private_key)
batchId = "B-912Q61G0BRVGC"
response = paymentrails.payment.Payment.delete('fffff',batchId)
@patch('paymentrails.payment.Payment.search',fake_search)
def test_list_allPaymentsWithQueries(self):
paymentrails.configuration.Configuration.set_public_key(TestPayment.public_key)
paymentrails.configuration.Configuration.set_private_key(TestPayment.private_key)
response = paymentrails.payment.Payment.search(1, 10, "hnc")
status = {"ok":"true","payments":[{"id":"P-912Q8JUA75HNC","recipient":{"id":"R-91XQ0PJH39U54","referenceId":"U345678912","email":"Johnny@test.com","name":"mark Test","lastName":"Test","firstName":"mark","type":"individual","status":"active","language":"en","complianceStatus":"pending","dob":"null","payoutMethod":"paypal","updatedAt":"2017-05-08T14:49:12.512Z","createdAt":"2017-05-04T16:17:04.378Z","gravatarUrl":"https://s3.amazonaws.com/static.api.paymentrails.com/icon_user.svg","compliance":{"status":"pending","checkedAt":"null"},"payout":{"autoswitch":{"limit":1000,"active":"false"},"holdup":{"limit":1000,"active":"false"},"primary":{"method":"paypal","currency":{"currency":{}}},"method":"paypal","accounts":{"paypal":{"address":"testpaypal@example.com"}},"methodDisplay":"PayPal"},"address":{"street1":"null","street2":"null","city":"null","postalCode":"null","country":"null","region":"null","phone":"null"}},"status":"pending","sourceAmount":"15.00","exchangeRate":"1.000000","fees":"0.00","recipientFees":"0.00","targetAmount":"65.00","fxRate":"2.000000","memo":"","processedAt":"null","createdAt":"2017-05-08T17:18:16.948Z","updatedAt":"2017-05-11T19:05:53.172Z","merchantFees":"0.00","compliance":{"status":"pending","checkedAt":"null"},"sourceCurrency":"USD","sourceCurrencyName":"US Dollar","targetCurrency":"USD","targetCurrencyName":"US Dollar","batch":{"id":"B-91XQ2ZHXARPJE","createdAt":"2017-05-08T17:18:16.893Z","updatedAt":"2017-05-11T19:05:53.265Z","sentAt":"null","completedAt":"null"}}],"meta":{"page":1,"pages":1,"records":1}}
self.assertEqual(response, status)
@patch('paymentrails.payment.Payment.search',fake_search)
def test_list_allPayments_None_body(self):
with self.assertRaises( paymentrails.exceptions.invalidFieldException.InvalidFieldException):
paymentrails.configuration.Configuration.set_public_key(TestPayment.public_key)
paymentrails.configuration.Configuration.set_private_key(TestPayment.private_key)
response = paymentrails.payment.Payment.search(1, 10, None)
if __name__ == '__main__':
unittest.main()
| 81.351779 | 1,564 | 0.722525 | 2,173 | 20,582 | 6.730327 | 0.09434 | 0.028308 | 0.078222 | 0.12335 | 0.953573 | 0.952274 | 0.93559 | 0.923487 | 0.903453 | 0.887863 | 0 | 0.047145 | 0.115781 | 20,582 | 252 | 1,565 | 81.674603 | 0.75647 | 0 | 0 | 0.669683 | 0 | 0 | 0.303178 | 0.069187 | 0 | 0 | 0 | 0 | 0.099548 | 1 | 0.122172 | false | 0 | 0.036199 | 0 | 0.19457 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
aa7d856091377820ac55301c149cd841d385f82a | 89 | py | Python | testm.py | sintrb/sinutils | ab74180ed06e19006ce23d45bb9c6056d8231a14 | [
"MIT"
] | null | null | null | testm.py | sintrb/sinutils | ab74180ed06e19006ce23d45bb9c6056d8231a14 | [
"MIT"
] | null | null | null | testm.py | sintrb/sinutils | ab74180ed06e19006ce23d45bb9c6056d8231a14 | [
"MIT"
] | null | null | null | # -*- coding: UTF-8 -*
'''
Created on 2021-04-16
'''
def test():
print('hi 43311')
| 9.888889 | 22 | 0.516854 | 13 | 89 | 3.538462 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.202899 | 0.224719 | 89 | 8 | 23 | 11.125 | 0.463768 | 0.483146 | 0 | 0 | 0 | 0 | 0.210526 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.5 | true | 0 | 0 | 0 | 0.5 | 0.5 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 7 |
aac35425ddc8430c989cd348e418763f50e707fd | 9,861 | py | Python | egybestAPI.py | unl1kely/egybestAPI | 97560aac848ff52416f8805039babfb375d86e3a | [
"MIT"
] | 2 | 2021-02-15T16:50:12.000Z | 2022-01-29T00:12:55.000Z | egybestAPI.py | unl1kely/egybestAPI | 97560aac848ff52416f8805039babfb375d86e3a | [
"MIT"
] | 1 | 2021-02-13T17:45:37.000Z | 2021-02-27T11:49:25.000Z | egybestAPI.py | unl1kely/egybestAPI | 97560aac848ff52416f8805039babfb375d86e3a | [
"MIT"
] | 1 | 2021-05-20T22:46:22.000Z | 2021-05-20T22:46:22.000Z | from bs4 import BeautifulSoup as bs
from JskPy import encodeUrl, best_match
from requests import get
domainEgyBest = "https://egybest.online"
dataUrlScript = "https://cdn-static.egybest.net/packed/G78uOQIvP42dDsB.js"
egyResponse = str(get(domainEgyBest))
if "200" not in egyResponse:
print(f"[!] - Couldn't reach {domainEgyBest}")
input("Press Enter to exit...")
exit()
class Serie:
def __init__(self, title):
self.title = title
self.search_url = f"{domainEgyBest}/explore/?q={encodeUrl(self.title)}"
self.search_page = get(self.search_url).text
self.search_soup = bs(self.search_page, "html.parser")
self.result_div = self.search_soup.find(id="movies")
if self.result_div==None:
self.found = 0
self.message = f"Incorrect input : {self.title}"
else:
self.result_list = self.result_div.find_all("a")
if len(self.result_list)==0:
self.found = 0
self.message = f"{self.title} - Serie not found."
else:
self.title_link = False
self.series = [ ]
for a_tag in self.result_list:
if "/series/" in a_tag.get("href"):
# is serie
self.series.append(a_tag)
######################################
if not self.series:
self.found = 0
self.message = f'Nothing found by "{self.title}".'
else:
self.titles = [a_tag.find(class_="title").text for a_tag in self.series]
self.result_index = best_match(self.title, self.titles)
if not self.result_index in range(len(self.titles)):
self.found = 0
self.message = f"{self.title} - Serie not found."
else:
self.name = self.titles[self.result_index]
self.title_link = self.series[self.result_index].get("href")
self.title_page = get(self.title_link).text
self.title_soup = bs(self.title_page, "html.parser")
self.lastEpLink = self.title_soup.find_all(class_="movies_small")[1].find("a").get("href") ##############
self.end_index = self.lastEpLink.index("-season-")
self.start_index = self.lastEpLink.index("episode/") + 8 # len("episode/") = 8
self.show_id = self.lastEpLink[self.start_index:self.end_index]
self.found = 1
self.message = "Found serie : "+self.name
###################################
'''
for a_tag in self.series:
if self.title.casefold().replace(" ", "") in a_tag.find(class_="title").text.casefold().replace(" ", ""):
# desired serie
self.title_link = a_tag.get("href")
self.name = a_tag.find(class_="title").text
break
if not self.title_link:
self.found = 0
self.message = f"{self.title} - Serie not found.")
else:
self.title_page = get(self.title_link).text
self.title_soup = bs(self.title_page, "html.parser")
#<serie>
self.lastEpLink = self.title_soup.find_all(class_="movies_small")[1].find("a").get("href") ##############
self.end_index = self.lastEpLink.index("-season-")
self.start_index = self.lastEpLink.index("episode/") + 8 # len("episode/") = 8
self.show_id = self.lastEpLink[self.start_index:self.end_index]
#</serie>
self.found = 1
self.message = "Found serie : "+self.name)'''
@staticmethod
def define(title):
global current_
current_ = Serie(title)
def watch(self, season, episode, quality="Auto"):
self.season = season
self.episode = episode
self.page_link = "{0}/episode/{1}-season-{2}-ep-{3}".format(domainEgyBest, self.show_id, self.season, self.episode)
self.page_soup = bs(get(self.page_link).text, "html.parser")
self.watch_quality = quality
if self.watch_quality=="Auto": #iframe
self.watch_link = domainEgyBest + self.page_soup.find("iframe").get("src")
else:
self.tbody = self.page_soup.find(class_="dls_table")
self.watch_links = self.tbody.find_all(class_="nop btn b dl _open_window")
if len(self.watch_links)==4:
if self.watch_quality=="240p":
print("[!] - 240p not available for this episode. Using 360p instead...")
self.watch_quality = "360p"
self.vidstream_link = domainEgyBest + self.watch_links[qualities_dict[self.watch_quality]].get("data-url")
print(self.vidstream_link,3*"\n")
self.vidstream_page = bs(get(self.vidstream_link).text, "html.parser")
self.vidstream_source = self.vidstream_page.find("source")
self.watch_link = self.vidstream_source.get("src")
print("self vidstream source",self.vidstream_source)
if __name__ != '__main__':
self.message = f"{self.name} S{self.season}E{self.episode} link copied to clipboard"
else:
self.message = self.watch_link
return self.message
def download(self, season, episode, quality="720p"):
return 0
self.season = season
self.episode = episode
self.page_link = "{0}/episode/{1}-season-{2}-ep-{3}".format(domainEgyBest, self.show_id, self.season, self.episode)
self.page_soup = bs(get(self.page_link).text, "html.parser")
self.download_quality = quality
if self.download_quality=="Auto":
self.download_quality = "720p"
self.tbody = self.page_soup.find(class_="dls_table")
self.download_links = self.tbody.find_all(class_="nop btn g dl _open_window")
if len(self.download_links)==4:
if self.download_quality=="240p":
print("[!] - 240p not available for this episode. Using 360p instead...")
self.download_quality = "360p"
self.vidstream_link = domainEgyBest + self.download_links[qualities_dict[self.download_quality]].get("data-url")
#print(self.vidstream_link,3*"\n")
self.vidstream_page = bs(get(self.vidstream_link).text, "html.parser")
self.vidstream_bigbuttons = self.vidstream_page.find("p").find_all(class_="bigbutton")
#print(self.vidstream_bigbuttons)
self.download_link = self.vidstream_bigbuttons[0].get("href")
#print(self.vidstream_link)
if __name__ != '__main__':
self.message = f"{self.name} S{self.season}E{self.episode} download link copied to clipboard"
else:
self.message = self.download_link
return self.message
# download:g0;watch:b1
class Film:
def __init__(self, title):
# ==============================
self.title = title
self.search_url = f"{domainEgyBest}/explore/?q={self.title.replace(' ', '%20')}"
self.search_page = get(self.search_url).text
self.search_soup = bs(self.search_page, "html.parser")
self.result_div = self.search_soup.find(id="movies")
if self.result_div==None:
self.found = 0
self.message = f"Incorrect input : {self.title}"
else:
self.result_list = self.result_div.find_all("a")
if len(self.result_list)==0:
self.found = 0
self.message = f"{self.title} - Film not found."
else:
self.title_link = False
self.films = [ ]
for a_tag in self.result_list:
if "/movie/" in a_tag.get("href"): # is film
self.films.append(a_tag)
if not self.films:
self.found = 0
self.message = f'Nothing found by "{self.title}".'
else:
self.titles = [a_tag.find(class_="title").text for a_tag in self.films]
self.result_index = best_match(self.title, self.titles)
if not self.result_index in range(len(self.titles)):
self.found = 0
self.message = f"{self.title} - Film not found."
else:
self.name = self.titles[self.result_index]
self.title_link = self.films[self.result_index].get("href")
self.title_page = get(self.title_link).text
self.title_soup = bs(self.title_page, "html.parser")
self.found = 1
self.message = "Found film : "+self.name
@staticmethod
def define(title):
global current_
current_ = Film(title)
def watch(self, quality="Auto"):
self.watch_quality = quality
if self.watch_quality=="Auto": #iframe
self.watch_link = domainEgyBest + self.title_soup.find("iframe").get("src")
else:
self.tbody = self.title_soup.find(class_="dls_table")
self.watch_links = self.tbody.find_all(class_="nop btn b dl _open_window")
if len(self.watch_links)==4:
if self.watch_quality=="240p":
print("[!] - 240p not available for this episode. Using 360p instead...")
self.watch_quality = "360p"
self.vidstream_link = domainEgyBest + self.watch_links[qualities_dict[self.watch_quality]].get("data-url")
#print(self.vidstream_link,3*"\n")
self.vidstream_page = bs(get(self.vidstream_link).text, "html.parser")
self.vidstream_source = self.vidstream_page.find("source")
self.watch_link = self.vidstream_source.get("src")
#print("self vidstream source",self.vidstream_source)
if __name__ != '__main__':
self.message = f"{self.name} video link copied to clipboard"
else:
self.message = self.watch_link
return self.message
def download(self, quality="720p"):
return 0
# currently working on this
self.download_quality = quality
if self.download_quality=="Auto":
self.download_quality = "720p"
self.tbody = self.title_soup.find(class_="dls_table")
self.download_links = self.tbody.find_all(class_="nop btn g dl _open_window")
if len(self.download_links)==4:
if self.download_quality=="240p":
print("[!] - 240p not available for this episode. Using 360p instead...")
self.download_quality = "360p"
self.vidstream_link = domainEgyBest + self.download_links[qualities_dict[self.download_quality]].get("data-url")
#print(self.vidstream_link,3*"\n")
self.vidstream_page = bs(get(self.vidstream_link).text, "html.parser")
self.vidstream_bigbuttons = self.vidstream_page.find("p").find_all(class_="bigbutton")
#print(self.vidstream_bigbuttons)
self.download_link = self.vidstream_bigbuttons[0].get("href")
#print(self.vidstream_link)
if __name__ != '__main__':
self.message = f"{self.name} ({self.download_quality}) download link copied to clipboard"
else:
self.message = self.download_link
return self.message | 44.219731 | 118 | 0.671433 | 1,382 | 9,861 | 4.60275 | 0.111433 | 0.05801 | 0.037416 | 0.019808 | 0.886653 | 0.884138 | 0.859142 | 0.859142 | 0.846408 | 0.810879 | 0 | 0.013724 | 0.172396 | 9,861 | 223 | 119 | 44.219731 | 0.765715 | 0.039854 | 0 | 0.752688 | 0 | 0.010753 | 0.200923 | 0.030005 | 0 | 0 | 0 | 0 | 0 | 1 | 0.043011 | false | 0 | 0.016129 | 0 | 0.102151 | 0.037634 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
2aee82d0752affb83ba587e5bdd11e28cd06c90e | 2,297 | py | Python | icarus/scenarios/test/test_workload.py | oascigil/icarus_edge_comp | b7bb9f9b8d0f27b4b01469dcba9cfc0c4949d64b | [
"MIT"
] | 5 | 2021-03-20T09:22:55.000Z | 2021-12-20T17:01:33.000Z | icarus/scenarios/test/test_workload.py | oascigil/icarus_edge_comp | b7bb9f9b8d0f27b4b01469dcba9cfc0c4949d64b | [
"MIT"
] | 1 | 2021-12-13T07:40:46.000Z | 2021-12-20T16:59:08.000Z | icarus/scenarios/test/test_workload.py | oascigil/icarus_edge_comp | b7bb9f9b8d0f27b4b01469dcba9cfc0c4949d64b | [
"MIT"
] | 1 | 2021-11-25T05:42:20.000Z | 2021-11-25T05:42:20.000Z | # -*- coding: utf-8 -*-
import unittest
import icarus.scenarios as workload
class TestYCBS(unittest.TestCase):
@classmethod
def setUpClass(cls):
pass
@classmethod
def tearDownClass(cls):
pass
def setUp(self):
pass
def tearDown(self):
pass
def test_a(self):
n_items = 5
event = list(workload.YCSBWorkload("A", n_items, 1, 2))
self.assertEqual(len(event), 3)
ev_1 = event[0]
self.assertFalse(event[0]['log'])
self.assertIn(ev_1['item'], range(1, n_items + 1))
self.assertIn(ev_1['op'], ["READ", "UPDATE"])
ev_2 = event[1]
self.assertTrue(ev_2['log'])
self.assertIn(ev_2['item'], range(1, n_items + 1))
self.assertIn(ev_2['op'], ["READ", "UPDATE"])
ev_3 = event[2]
self.assertTrue(ev_3['log'])
self.assertIn(ev_3['item'], range(1, n_items + 1))
self.assertIn(ev_3['op'], ["READ", "UPDATE"])
def test_b(self):
n_items = 5
event = list(workload.YCSBWorkload("B", n_items, 1, 2))
self.assertEqual(len(event), 3)
ev_1 = event[0]
self.assertFalse(event[0]['log'])
self.assertIn(ev_1['item'], range(1, n_items + 1))
self.assertIn(ev_1['op'], ["READ", "UPDATE"])
ev_2 = event[1]
self.assertTrue(ev_2['log'])
self.assertIn(ev_2['item'], range(1, n_items + 1))
self.assertIn(ev_2['op'], ["READ", "UPDATE"])
ev_3 = event[2]
self.assertTrue(ev_3['log'])
self.assertIn(ev_3['item'], range(1, n_items + 1))
self.assertIn(ev_3['op'], ["READ", "UPDATE"])
def test_c(self):
n_items = 5
event = list(workload.YCSBWorkload("C", n_items, 1, 2))
self.assertEqual(len(event), 3)
ev_1 = event[0]
self.assertFalse(event[0]['log'])
self.assertIn(ev_1['item'], range(1, n_items + 1))
self.assertEqual(ev_1['op'], "READ")
ev_2 = event[1]
self.assertTrue(ev_2['log'])
self.assertIn(ev_2['item'], range(1, n_items + 1))
self.assertEqual(ev_2['op'], "READ")
ev_3 = event[2]
self.assertTrue(ev_3['log'])
self.assertIn(ev_3['item'], range(1, n_items + 1))
self.assertEqual(ev_3['op'], "READ")
| 31.465753 | 63 | 0.554201 | 326 | 2,297 | 3.748466 | 0.144172 | 0.07365 | 0.171849 | 0.125205 | 0.821604 | 0.821604 | 0.821604 | 0.821604 | 0.723404 | 0.691489 | 0 | 0.045024 | 0.265128 | 2,297 | 72 | 64 | 31.902778 | 0.67891 | 0.009142 | 0 | 0.737705 | 0 | 0 | 0.068602 | 0 | 0 | 0 | 0 | 0 | 0.491803 | 1 | 0.114754 | false | 0.065574 | 0.032787 | 0 | 0.163934 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 9 |
631e410fda7af47e590c1b29d5d5fc0b94793246 | 7,651 | py | Python | olc_webportalv2/geneseekr/tests/test_views.py | OLC-Bioinformatics/olc_genomics_portal | d70ec669a3a49106f8290fff5dee089726259a23 | [
"MIT"
] | 3 | 2019-01-03T21:22:21.000Z | 2019-04-23T15:47:29.000Z | olc_webportalv2/geneseekr/tests/test_views.py | OLC-Bioinformatics/olc_genomics_portal | d70ec669a3a49106f8290fff5dee089726259a23 | [
"MIT"
] | 49 | 2019-01-03T18:15:12.000Z | 2022-03-11T23:37:20.000Z | olc_webportalv2/geneseekr/tests/test_views.py | OLC-Bioinformatics/olc_webportalv2 | d70ec669a3a49106f8290fff5dee089726259a23 | [
"MIT"
] | 58 | 2019-01-03T21:21:59.000Z | 2021-11-02T18:00:20.000Z | from django.test import TestCase, Client
from django.urls import reverse
from olc_webportalv2.users.models import User
from olc_webportalv2.geneseekr.models import GeneSeekrRequest, Tree, AMRSummary, ProkkaRequest
class SampleTestCase(TestCase):
@classmethod
def setUpTestData(cls):
user = User.objects.create(username='TestUser')
user.set_password('password')
user.save()
user1 = User.objects.create(username='Test')
user1.set_password('password')
user1.save()
request_one = GeneSeekrRequest.objects.create(name='123',query_sequence='>seqAAAAAAAA', user=user)
request_two = GeneSeekrRequest.objects.create(name='456',query_sequence='>seqAAATTTTA', user=user)
tree_one = Tree.objects.create(name='123',user=user)
tree_two = Tree.objects.create(name='456',user=user)
amr_one = AMRSummary.objects.create(name='123',user=user)
amr_two = AMRSummary.objects.create(name='456',user=user)
prokka_one = ProkkaRequest.objects.create(name='123',user=user)
prokka_two = ProkkaRequest.objects.create(name='456',user=user)
# Geneseekr View Tests ----------------------------------------------------------------------------------------------------------------->
def test_geneseekr_home_login_required(self):
resp = self.client.get(reverse('geneseekr:geneseekr_home'))
self.assertEqual(resp.status_code, 302) # Should get 302 redirected if user is not logged in.
def test_geneseekr_home(self):
self.client.login(username='TestUser', password='password')
resp = self.client.get(reverse('geneseekr:geneseekr_home'))
self.assertEqual(resp.status_code, 200)
geneseekr_requests = GeneSeekrRequest.objects.filter()
for request in geneseekr_requests:
self.assertIn(request.name, resp.content.decode('utf-8'))
def test_user_geneseekr_home(self):
self.client.login(username='Test', password='password')
resp = self.client.get(reverse('geneseekr:geneseekr_home'))
self.assertEqual(resp.status_code, 200)
geneseekr_requests = GeneSeekrRequest.objects.filter()
for request in geneseekr_requests:
self.assertNotIn(request.name, resp.content.decode('utf-8'))
def test_geneseekr_processing_login_required(self):
resp = self.client.get(reverse('geneseekr:geneseekr_processing', kwargs={'geneseekr_request_pk': 1}))
self.assertEqual(resp.status_code, 302) # Should get 302 redirected if user is not logged in.
def test_geneseekr_processing_404_no_run(self):
self.client.login(username='TestUser', password='password')
resp = self.client.get(reverse('geneseekr:geneseekr_processing', kwargs={'geneseekr_request_pk': 123}))
self.assertEqual(resp.status_code, 404)
# Tree View Tests ----------------------------------------------------------------------------------------------------------------->
def test_tree_home_login_required(self):
resp = self.client.get(reverse('geneseekr:tree_home'))
self.assertEqual(resp.status_code, 302) # Should get 302 redirected if user is not logged in.
def test_tree_home(self):
self.client.login(username='TestUser', password='password')
resp = self.client.get(reverse('geneseekr:tree_home'))
self.assertEqual(resp.status_code, 200)
tree_requests = Tree.objects.filter()
for request in tree_requests:
self.assertIn(request.name, resp.content.decode('utf-8'))
def test_user_tree_home(self):
self.client.login(username='Test', password='password')
resp = self.client.get(reverse('geneseekr:tree_home'))
self.assertEqual(resp.status_code, 200)
tree_requests = Tree.objects.filter()
for request in tree_requests:
self.assertNotIn(request.name, resp.content.decode('utf-8'))
def test_tree_result_login_required(self):
resp = self.client.get(reverse('geneseekr:tree_result', kwargs={'tree_request_pk': 1}))
self.assertEqual(resp.status_code, 302) # Should get 302 redirected if user is not logged in.
def test_tree_result_404_no_run(self):
self.client.login(username='TestUser', password='password')
resp = self.client.get(reverse('geneseekr:tree_result', kwargs={'tree_request_pk': 123}))
self.assertEqual(resp.status_code, 404)
# AMR View Tests ----------------------------------------------------------------------------------------------------------------->
def test_amr_home_login_required(self):
resp = self.client.get(reverse('geneseekr:amr_home'))
self.assertEqual(resp.status_code, 302) # Should get 302 redirected if user is not logged in.
def test_amr_home(self):
self.client.login(username='TestUser', password='password')
resp = self.client.get(reverse('geneseekr:amr_home'))
self.assertEqual(resp.status_code, 200)
amr_requests = AMRSummary.objects.filter()
for request in amr_requests:
self.assertIn(request.name, resp.content.decode('utf-8'))
def test_user_amr_home(self):
self.client.login(username='Test', password='password')
resp = self.client.get(reverse('geneseekr:amr_home'))
self.assertEqual(resp.status_code, 200)
amr_requests = AMRSummary.objects.filter()
for request in amr_requests:
self.assertNotIn(request.name, resp.content.decode('utf-8'))
def test_amr_result_login_required(self):
resp = self.client.get(reverse('geneseekr:amr_result', kwargs={'amr_request_pk': 1}))
self.assertEqual(resp.status_code, 302) # Should get 302 redirected if user is not logged in.
def test_amr_result_404_no_run(self):
self.client.login(username='TestUser', password='password')
resp = self.client.get(reverse('geneseekr:amr_result', kwargs={'amr_request_pk': 123}))
self.assertEqual(resp.status_code, 404)
# Prokka View Tests ----------------------------------------------------------------------------------------------------------------->
def test_prokka_home_login_required(self):
resp = self.client.get(reverse('geneseekr:prokka_home'))
self.assertEqual(resp.status_code, 302) # Should get 302 redirected if user is not logged in.
def test_prokka_home(self):
self.client.login(username='TestUser', password='password')
resp = self.client.get(reverse('geneseekr:prokka_home'))
self.assertEqual(resp.status_code, 200)
prokka_requests = ProkkaRequest.objects.filter()
for request in prokka_requests:
self.assertIn(request.name, resp.content.decode('utf-8'))
def test_user_prokka_home(self):
self.client.login(username='Test', password='password')
resp = self.client.get(reverse('geneseekr:prokka_home'))
self.assertEqual(resp.status_code, 200)
prokka_requests = ProkkaRequest.objects.filter()
for request in prokka_requests:
self.assertNotIn(request.name, resp.content.decode('utf-8'))
def test_prokka_result_login_required(self):
resp = self.client.get(reverse('geneseekr:prokka_result', kwargs={'prokka_request_pk': 1}))
self.assertEqual(resp.status_code, 302) # Should get 302 redirected if user is not logged in.
def test_prokka_result_404_no_run(self):
self.client.login(username='TestUser', password='password')
resp = self.client.get(reverse('geneseekr:prokka_result', kwargs={'prokka_request_pk': 123}))
self.assertEqual(resp.status_code, 404)
| 52.047619 | 137 | 0.657953 | 917 | 7,651 | 5.317339 | 0.088332 | 0.065628 | 0.057424 | 0.069729 | 0.840443 | 0.840443 | 0.805989 | 0.801477 | 0.801477 | 0.772765 | 0 | 0.023498 | 0.171219 | 7,651 | 146 | 138 | 52.40411 | 0.745466 | 0.123513 | 0 | 0.581197 | 0 | 0 | 0.128194 | 0.042283 | 0 | 0 | 0 | 0 | 0.239316 | 1 | 0.179487 | false | 0.119658 | 0.034188 | 0 | 0.222222 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 7 |
2d6ad08342201fcf5805dcd46c000a9261b8e36d | 422 | py | Python | dog_cat/settings.py | xiaoyu2018/pytorch_demos | f92d2e10df4a68dac299ee6029d4c38bcdb26b23 | [
"Apache-2.0"
] | 2 | 2022-02-15T02:32:15.000Z | 2022-03-01T09:36:08.000Z | dog_cat/settings.py | xiaoyu2018/pytorch_demos | f92d2e10df4a68dac299ee6029d4c38bcdb26b23 | [
"Apache-2.0"
] | null | null | null | dog_cat/settings.py | xiaoyu2018/pytorch_demos | f92d2e10df4a68dac299ee6029d4c38bcdb26b23 | [
"Apache-2.0"
] | null | null | null | <<<<<<< HEAD
DATA_DIR="D:/2021UCAS/机器学习/大作业/pytorch_learning/dog_cat/DOGvsCAT"
SAVE_DIR="D:/2021UCAS/机器学习/大作业/pytorch_learning/dog_cat"
EPOCH=50
BATCH_SIZE=256
IMG_SIZE=32
DEVICE="cuda:0"
=======
DATA_DIR="D:/2021UCAS/机器学习/大作业/pytorch_learning/dog_cat/DOGvsCAT"
SAVE_DIR="D:/2021UCAS/机器学习/大作业/pytorch_learning/dog_cat"
EPOCH=50
BATCH_SIZE=256
IMG_SIZE=32
DEVICE="cuda:0"
>>>>>>> 26700f85104969189a826e0cb75e794a9b87d2d2
| 23.444444 | 65 | 0.781991 | 66 | 422 | 4.757576 | 0.363636 | 0.050955 | 0.152866 | 0.203822 | 0.859873 | 0.859873 | 0.859873 | 0.859873 | 0.859873 | 0.859873 | 0 | 0.153846 | 0.045024 | 422 | 17 | 66 | 24.823529 | 0.62531 | 0 | 0 | 0.8 | 0 | 0 | 0.49763 | 0.469194 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0 | null | null | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 10 |
9340d828b660693775c48c80319b51393c472cf7 | 34 | py | Python | external/models/basic_BERT/__init__.py | swapUniba/Elliot_refactor-tesi-Ventrella | 3ddffc041696c90a6f6d3e8906c212fc4f55f842 | [
"Apache-2.0"
] | null | null | null | external/models/basic_BERT/__init__.py | swapUniba/Elliot_refactor-tesi-Ventrella | 3ddffc041696c90a6f6d3e8906c212fc4f55f842 | [
"Apache-2.0"
] | null | null | null | external/models/basic_BERT/__init__.py | swapUniba/Elliot_refactor-tesi-Ventrella | 3ddffc041696c90a6f6d3e8906c212fc4f55f842 | [
"Apache-2.0"
] | null | null | null | from .basic_BERT import basic_BERT | 34 | 34 | 0.882353 | 6 | 34 | 4.666667 | 0.666667 | 0.642857 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.088235 | 34 | 1 | 34 | 34 | 0.903226 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
93847827b921250ad6ded6e72261c6eb98bbdb10 | 1,748 | py | Python | tests/surrortg/inputs/test_joystick.py | cedricsellin/surrogate | 03f13d297fdd74d7e5d164821039acc38d0b2103 | [
"MIT"
] | 2 | 2020-11-25T00:29:07.000Z | 2020-12-01T20:24:47.000Z | tests/surrortg/inputs/test_joystick.py | cedricsellin/surrogate | 03f13d297fdd74d7e5d164821039acc38d0b2103 | [
"MIT"
] | 1 | 2021-04-10T11:59:23.000Z | 2021-04-10T11:59:23.000Z | tests/surrortg/inputs/test_joystick.py | cedricsellin/surrogate | 03f13d297fdd74d7e5d164821039acc38d0b2103 | [
"MIT"
] | 2 | 2021-01-28T17:43:13.000Z | 2021-03-29T13:19:38.000Z | import unittest
from surrortg.inputs import Joystick, Directions
class TestJoystick(Joystick):
async def reset(self, seat):
pass
class JoystickTest(unittest.TestCase):
def test_get_direction_4(self):
"""Test that the directions are correct in 4 case
"""
joystick = TestJoystick()
self.assertEqual(joystick.get_direction_4(0, 1), Directions.TOP)
self.assertEqual(joystick.get_direction_4(0, -1), Directions.BOTTOM)
self.assertEqual(joystick.get_direction_4(1, 0), Directions.RIGHT)
self.assertEqual(joystick.get_direction_4(-1, 0), Directions.LEFT)
self.assertEqual(joystick.get_direction_4(0, 0), Directions.MIDDLE)
self.assertEqual(joystick.get_direction_4(0, 0.09), Directions.MIDDLE)
def test_get_direction_8(self):
"""Test that the directions are correct in 8 case
"""
joystick = TestJoystick()
self.assertEqual(joystick.get_direction_8(0, 1), Directions.TOP)
self.assertEqual(joystick.get_direction_8(0, -1), Directions.BOTTOM)
self.assertEqual(joystick.get_direction_8(1, 0), Directions.RIGHT)
self.assertEqual(joystick.get_direction_8(-1, 0), Directions.LEFT)
self.assertEqual(joystick.get_direction_8(0, 0), Directions.MIDDLE)
self.assertEqual(joystick.get_direction_8(0, 0.09), Directions.MIDDLE)
self.assertEqual(joystick.get_direction_8(-1, 1), Directions.TOP_LEFT)
self.assertEqual(joystick.get_direction_8(1, 1), Directions.TOP_RIGHT)
self.assertEqual(
joystick.get_direction_8(-1, -1), Directions.BOTTOM_LEFT
)
self.assertEqual(
joystick.get_direction_8(1, -1), Directions.BOTTOM_RIGHT
)
| 38.844444 | 78 | 0.693936 | 221 | 1,748 | 5.298643 | 0.167421 | 0.184458 | 0.314261 | 0.355252 | 0.841161 | 0.824082 | 0.824082 | 0.824082 | 0.695132 | 0.186166 | 0 | 0.039886 | 0.196796 | 1,748 | 44 | 79 | 39.727273 | 0.79416 | 0.058352 | 0 | 0.133333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.533333 | 1 | 0.066667 | false | 0.033333 | 0.066667 | 0 | 0.2 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
8786b8a72ba6a32b59ec7b85b1823a87f67f1886 | 25,653 | py | Python | metadatautilspkg/premis.py | CLACI/DarkArchiveWorkflow | 385bb3fb58dd177573bd9a02412070dae5cc1b91 | [
"BSD-3-Clause"
] | 2 | 2017-10-22T20:56:15.000Z | 2017-11-16T03:13:55.000Z | metadatautilspkg/premis.py | CLACI/DarkArchiveWorkflow | 385bb3fb58dd177573bd9a02412070dae5cc1b91 | [
"BSD-3-Clause"
] | 6 | 2017-05-19T15:47:26.000Z | 2018-02-15T20:34:10.000Z | metadatautilspkg/premis.py | CLACI/DarkArchiveWorkflow | 385bb3fb58dd177573bd9a02412070dae5cc1b91 | [
"BSD-3-Clause"
] | 1 | 2017-10-05T20:49:34.000Z | 2017-10-05T20:49:34.000Z | # -*- coding: utf-8 -*-
# BSD 3-Clause License
#
# Copyright (c) 2017, ColoredInsaneAsylums
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright notice, this
# list of conditions and the following disclaimer.
#
# * Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
#
# * Neither the name of the copyright holder nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
# CREDITS
# Creator: Nitin Verma (nitin dot verma at utexas dot edu)
#
import metadatautilspkg.globalvars as globalvars
from metadatautilspkg.metadatautils import *
from metadatautilspkg.adminmetadatautils import *
# FUNCTION DEFINITIONS
def getEventDetails():
return "" # TODO: temporary, needs more work!!
def getEventOutcome():
return "" # TODO: temporary, needs more work!!
def getEventOutcomeDetail():
return "" # TODO: temporary, needs more work!!
def getLinkingAgentId():
return "" # TODO: temporary, needs more work!!
def getLinkingAgentRole():
return "" # TODO: temporary, needs more work!!
def initMetadataRecord(initParams):
"""initMetadataRecord
Arguments:
initParams: initial parameters needed to populate the various fields
of the new metadata record. Passed as a dictionary object.
This function creates a 'skeletal' metadata record, with as many fields
populated as possible at this initialization stage.
"""
metadataRecord = {}
uniqueId = getUniqueID()
metadataRecord["_id"] = uniqueId
# Create the ADMIN entity here:
arrangementInfo = initParams[globalvars.ARRANGEMENT_INFO_LABEL]
adminEntity = initAdminMetadataEntity(arrangementInfo)
metadataRecord[globalvars.labels.admn_entity.name] = adminEntity
# Create the PREMIS (or preservation) entity here:
metadataRecord[globalvars.labels.pres_entity.name] = {}
metadataRecord[globalvars.labels.pres_entity.name][globalvars.labels.obj_entity.name] = {}
metadataRecord[globalvars.labels.pres_entity.name][globalvars.labels.obj_entity.name][globalvars.labels.obj_id.name] = {}
metadataRecord[globalvars.labels.pres_entity.name][globalvars.labels.obj_entity.name][globalvars.labels.obj_id.name][globalvars.labels.obj_id_typ.name] = globalvars.OBJ_ID_TYPE
metadataRecord[globalvars.labels.pres_entity.name][globalvars.labels.obj_entity.name][globalvars.labels.obj_id.name][globalvars.labels.obj_id_val.name] = uniqueId
metadataRecord[globalvars.labels.pres_entity.name][globalvars.labels.obj_entity.name][globalvars.labels.obj_cat.name] = globalvars.vocab.objCat
metadataRecord[globalvars.labels.pres_entity.name][globalvars.labels.obj_entity.name][globalvars.labels.obj_chars.name] = {}
metadataRecord[globalvars.labels.pres_entity.name][globalvars.labels.obj_entity.name][globalvars.labels.obj_chars.name][globalvars.labels.obj_fixity.name] = {}
metadataRecord[globalvars.labels.pres_entity.name][globalvars.labels.obj_entity.name][globalvars.labels.obj_chars.name][globalvars.labels.obj_fixity.name][globalvars.labels.obj_msgdgst_algo.name] = globalvars.MD_INIT_STRING
metadataRecord[globalvars.labels.pres_entity.name][globalvars.labels.obj_entity.name][globalvars.labels.obj_chars.name][globalvars.labels.obj_fixity.name][globalvars.labels.obj_msgdgst.name] = globalvars.MD_INIT_STRING
metadataRecord[globalvars.labels.pres_entity.name][globalvars.labels.obj_entity.name][globalvars.labels.obj_chars.name][globalvars.labels.obj_size.name] = initParams["fileSize"]
metadataRecord[globalvars.labels.pres_entity.name][globalvars.labels.obj_entity.name][globalvars.labels.obj_chars.name][globalvars.labels.obj_fmt.name] = {}
metadataRecord[globalvars.labels.pres_entity.name][globalvars.labels.obj_entity.name][globalvars.labels.obj_chars.name][globalvars.labels.obj_fmt.name][globalvars.labels.obj_fmt_dsgn.name] = {}
metadataRecord[globalvars.labels.pres_entity.name][globalvars.labels.obj_entity.name][globalvars.labels.obj_chars.name][globalvars.labels.obj_fmt.name][globalvars.labels.obj_fmt_dsgn.name][globalvars.labels.obj_fmt_name.name] = initParams["fmtName"]
#metadataRecord[globalvars.labels.pres_entity.name][globalvars.labels.obj_entity.name][globalvars.labels.obj_chars.name][globalvars.labels.obj_fmt.name][globalvars.labels.obj_fmt_dsgn.name][globalvars.labels.obj_fmt_ver.name] = initParams["fmtVer"]
metadataRecord[globalvars.labels.pres_entity.name][globalvars.labels.obj_entity.name][globalvars.labels.obj_orig_name.name] = initParams["fileName"]
# Create a parent entity (list) of all PREMIS 'event' entities.
metadataRecord[globalvars.labels.pres_entity.name][globalvars.labels.evt_parent_entity.name] = []
print_info("The following record has been initialized: {}".format(metadataRecord))
return metadataRecord
def createIDAssignmentEvent(uniqueId):
eventRecord = {}
eventRecord[globalvars.labels.evt_entity.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name][globalvars.labels.evt_id_typ.name] = globalvars.EVT_ID_TYP
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name][globalvars.labels.evt_id_val.name] = getUniqueID()
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_typ.name] = globalvars.vocab.evtTyp.idAssgn
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_dttime.name] = getCurrentEDTFTimestamp()
# Create a parent entity (list) for all PREMIS 'eventDetailInformation' entities
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_detail_parent.name] = []
eventDetailRecord = {} # Create a single record for event detail information
eventDetailRecord[globalvars.labels.evt_detail_info.name] = {}
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name] = {}
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name][globalvars.labels.evt_detail_algo.name] = globalvars.UNIQUE_ID_ALGO
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name][globalvars.labels.evt_detail_proglang.name] = globalvars.PYTHON_VER_STR
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name][globalvars.labels.evt_detail_mthd.name] = globalvars.UNIQUE_ID_METHOD
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name][globalvars.labels.evt_detail_idAssgn.name] = uniqueId
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_detail_parent.name].append(eventDetailRecord)
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_outcm_info.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_outcm_info.name][globalvars.labels.evt_outcm.name] = globalvars.vocab.evtOutcm.success
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name][globalvars.labels.evt_lnk_agnt_id_typ.name] = globalvars.LNK_AGNT_ID_TYPE
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name][globalvars.labels.evt_lnk_agnt_id_val.name] = globalvars.LNK_AGNT_ID_VAL
return eventRecord
def createMsgDigestCalcEvent(chksm, chksmAlgo):
eventRecord = {}
eventRecord[globalvars.labels.evt_entity.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name][globalvars.labels.evt_id_typ.name] = globalvars.EVT_ID_TYP
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name][globalvars.labels.evt_id_val.name] = getUniqueID()
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_typ.name] = globalvars.vocab.evtTyp.msgDgstCalc
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_dttime.name] = getCurrentEDTFTimestamp()
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_detail_parent.name] = []
eventDetailRecord = {} # Create a single record for event detail information
eventDetailRecord[globalvars.labels.evt_detail_info.name] = {}
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name] = {}
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name][globalvars.labels.evt_detail_algo.name] = globalvars.CHECKSUM_ALGO
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name][globalvars.labels.evt_detail_proglang.name] = globalvars.PYTHON_VER_STR
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name][globalvars.labels.evt_detail_mthd.name] = globalvars.CHECKSUM_METHOD
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name][globalvars.labels.evt_detail_msgDgst.name] = chksm
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_detail_parent.name].append(eventDetailRecord)
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_outcm_info.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_outcm_info.name][globalvars.labels.evt_outcm.name] = globalvars.vocab.evtOutcm.success
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name][globalvars.labels.evt_lnk_agnt_id_typ.name] = globalvars.LNK_AGNT_ID_TYPE
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name][globalvars.labels.evt_lnk_agnt_id_val.name] = globalvars.LNK_AGNT_ID_VAL
return eventRecord
def createFileCopyEvent(evtTyp, srcFilePath, dstFilePath):
eventRecord = {}
eventRecord[globalvars.labels.evt_entity.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name][globalvars.labels.evt_id_typ.name] = globalvars.EVT_ID_TYP
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name][globalvars.labels.evt_id_val.name] = getUniqueID()
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_typ.name] = globalvars.vocab.evtTyp.replication
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_dttime.name] = getCurrentEDTFTimestamp()
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_detail_parent.name] = []
eventDetailRecord = {} # Create a single record for event detail information
eventDetailRecord[globalvars.labels.evt_detail_info.name] = {}
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name] = {}
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name][globalvars.labels.evt_detail_src.name] = srcFilePath
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name][globalvars.labels.evt_detail_dst.name] = dstFilePath
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_detail_parent.name].append(eventDetailRecord)
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_outcm_info.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_outcm_info.name][globalvars.labels.evt_outcm.name] = globalvars.vocab.evtOutcm.success
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name][globalvars.labels.evt_lnk_agnt_id_typ.name] = globalvars.LNK_AGNT_ID_TYPE
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name][globalvars.labels.evt_lnk_agnt_id_val.name] = globalvars.LNK_AGNT_ID_VAL
return eventRecord
def createFilenameChangeEvent(dstFilePrelimPath, dstFileUniquePath):
eventRecord = {}
eventRecord[globalvars.labels.evt_entity.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name][globalvars.labels.evt_id_typ.name] = globalvars.EVT_ID_TYP
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name][globalvars.labels.evt_id_val.name] = getUniqueID()
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_typ.name] = globalvars.vocab.evtTyp.filenameChg
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_dttime.name] = getCurrentEDTFTimestamp()
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_detail_parent.name] = []
eventDetailRecord = {} # Create a single record for event detail information
eventDetailRecord[globalvars.labels.evt_detail_info.name] = {}
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name] = {}
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name][globalvars.labels.evt_detail_src.name] = dstFilePrelimPath
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name][globalvars.labels.evt_detail_dst.name] = dstFileUniquePath
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_detail_parent.name].append(eventDetailRecord)
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_outcm_info.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_outcm_info.name][globalvars.labels.evt_outcm.name] = globalvars.vocab.evtOutcm.success
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name][globalvars.labels.evt_lnk_agnt_id_typ.name] = globalvars.LNK_AGNT_ID_TYPE
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name][globalvars.labels.evt_lnk_agnt_id_val.name] = globalvars.LNK_AGNT_ID_VAL
return eventRecord
def createFixityCheckEvent(status, calcChecksum):
eventRecord = {}
eventRecord[globalvars.labels.evt_entity.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name][globalvars.labels.evt_id_typ.name] = globalvars.EVT_ID_TYP
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name][globalvars.labels.evt_id_val.name] = getUniqueID()
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_typ.name] = globalvars.vocab.evtTyp.fixityChk
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_dttime.name] = getCurrentEDTFTimestamp()
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_outcm_info.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_outcm_info.name][globalvars.labels.evt_outcm.name] = globalvars.vocab.evtOutcm.success
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name][globalvars.labels.evt_lnk_agnt_id_typ.name] = globalvars.LNK_AGNT_ID_TYPE
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name][globalvars.labels.evt_lnk_agnt_id_val.name] = globalvars.LNK_AGNT_ID_VAL
return eventRecord
def createAccessionEvent():
eventRecord = {}
eventRecord[globalvars.labels.evt_entity.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name][globalvars.labels.evt_id_typ.name] = globalvars.EVT_ID_TYP
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name][globalvars.labels.evt_id_val.name] = getUniqueID()
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_typ.name] = globalvars.vocab.evtTyp.accession
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_dttime.name] = getCurrentEDTFTimestamp()
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_outcm_info.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_outcm_info.name][globalvars.labels.evt_outcm.name] = globalvars.vocab.evtOutcm.success
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name][globalvars.labels.evt_lnk_agnt_id_typ.name] = globalvars.LNK_AGNT_ID_TYPE
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name][globalvars.labels.evt_lnk_agnt_id_val.name] = globalvars.LNK_AGNT_ID_VAL
return eventRecord
def createMetadataExtractionEvent(extdMethd, extdmeta):
eventRecord = {}
eventRecord[globalvars.labels.evt_entity.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name][globalvars.labels.evt_id_typ.name] = globalvars.EVT_ID_TYP
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name][globalvars.labels.evt_id_val.name] = getUniqueID()
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_typ.name] = globalvars.vocab.evtTyp.metadataExt
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_dttime.name] = getCurrentEDTFTimestamp()
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_detail_parent.name] = []
eventDetailRecord = {} # Create a single record for event detail information
eventDetailRecord[globalvars.labels.evt_detail_info.name] = {}
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name] = {}
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name][globalvars.labels.evt_detail_mthd.name] = extdMethd
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name][globalvars.labels.evt_detail_metadataExtraction.name] = extdmeta
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_detail_parent.name].append(eventDetailRecord)
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_outcm_info.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_outcm_info.name][globalvars.labels.evt_outcm.name] = globalvars.vocab.evtOutcm.success
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name][globalvars.labels.evt_lnk_agnt_id_typ.name] = globalvars.LNK_AGNT_ID_TYPE
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name][globalvars.labels.evt_lnk_agnt_id_val.name] = globalvars.LNK_AGNT_ID_VAL
return eventRecord
def createMetadataModificationEvent(before, after):
eventRecord = {}
eventRecord[globalvars.labels.evt_entity.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name][globalvars.labels.evt_id_typ.name] = globalvars.EVT_ID_TYP
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name][globalvars.labels.evt_id_val.name] = getUniqueID()
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_typ.name] = globalvars.vocab.evtTyp.metadataMod
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_dttime.name] = getCurrentEDTFTimestamp()
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_detail_parent.name] = []
eventDetailRecord = {} # Create a single record for event detail information
eventDetailRecord[globalvars.labels.evt_detail_info.name] = {}
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name] = {}
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name][globalvars.labels.evt_detail_before.name] = before
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name][globalvars.labels.evt_detail_after.name] = after
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_detail_parent.name].append(eventDetailRecord)
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_outcm_info.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_outcm_info.name][globalvars.labels.evt_outcm.name] = globalvars.vocab.evtOutcm.success
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name][globalvars.labels.evt_lnk_agnt_id_typ.name] = globalvars.LNK_AGNT_ID_TYPE
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name][globalvars.labels.evt_lnk_agnt_id_val.name] = globalvars.LNK_AGNT_ID_VAL
return eventRecord
def createMigrationEvent(fileType, fileSize, imgWidth, imgHeight, fileName):
eventRecord = {}
eventRecord[globalvars.labels.evt_entity.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name][globalvars.labels.evt_id_typ.name] = globalvars.EVT_ID_TYP
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_id.name][globalvars.labels.evt_id_val.name] = getUniqueID()
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_typ.name] = globalvars.vocab.evtTyp.migration
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_dttime.name] = getCurrentEDTFTimestamp()
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_detail_parent.name] = []
eventDetailRecord = {} # Create a single record for event detail information
eventDetailRecord[globalvars.labels.evt_detail_info.name] = {}
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name] = {}
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name][globalvars.labels.evt_detail_fileType.name] = fileType
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name][globalvars.labels.evt_detail_fileSize.name] = fileSize
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name][globalvars.labels.evt_detail_imgWidth.name] = imgWidth
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name][globalvars.labels.evt_detail_imgHeight.name] = imgHeight
eventDetailRecord[globalvars.labels.evt_detail_info.name][globalvars.labels.evt_detail_ext.name][globalvars.labels.evt_detail_fileName.name] = fileName
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_detail_parent.name].append(eventDetailRecord)
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_outcm_info.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_outcm_info.name][globalvars.labels.evt_outcm.name] = globalvars.vocab.evtOutcm.success
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name] = {}
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name][globalvars.labels.evt_lnk_agnt_id_typ.name] = globalvars.LNK_AGNT_ID_TYPE
eventRecord[globalvars.labels.evt_entity.name][globalvars.labels.evt_lnk_agnt_id.name][globalvars.labels.evt_lnk_agnt_id_val.name] = globalvars.LNK_AGNT_ID_VAL
return eventRecord
| 75.228739 | 253 | 0.810432 | 3,287 | 25,653 | 6.095224 | 0.087314 | 0.328226 | 0.329074 | 0.22845 | 0.850262 | 0.845421 | 0.843524 | 0.834789 | 0.831794 | 0.831794 | 0 | 0.000254 | 0.080108 | 25,653 | 340 | 254 | 75.45 | 0.848758 | 0.114295 | 0 | 0.681818 | 0 | 0 | 0.003136 | 0 | 0 | 0 | 0 | 0.002941 | 0 | 1 | 0.068182 | false | 0 | 0.013636 | 0.022727 | 0.15 | 0.004545 | 0 | 0 | 0 | null | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 9 |
87d3a2c5afdbcac9eefbb452cf51217b3b73eecb | 188 | py | Python | wynncraft/utils/__init__.py | martinkovacs/wynncraft-python | 0c35e3eb4d080aa32b997543d21998933ffa7819 | [
"0BSD"
] | null | null | null | wynncraft/utils/__init__.py | martinkovacs/wynncraft-python | 0c35e3eb4d080aa32b997543d21998933ffa7819 | [
"0BSD"
] | null | null | null | wynncraft/utils/__init__.py | martinkovacs/wynncraft-python | 0c35e3eb4d080aa32b997543d21998933ffa7819 | [
"0BSD"
] | null | null | null | from wynncraft.utils.constants import API_KEY
from wynncraft.utils.constants import CACHE_TIME
from wynncraft.utils.constants import TIMEOUT
from wynncraft.utils.constants import RL_ENABLE | 47 | 48 | 0.87766 | 27 | 188 | 6 | 0.444444 | 0.320988 | 0.444444 | 0.666667 | 0.814815 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.079787 | 188 | 4 | 49 | 47 | 0.936416 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 9 |
87dcb1d5748c549a84f7fa561107ed18c6cfa436 | 2,252 | py | Python | tests/test_behavior.py | jamoralp/pyecore | df1f230e6e99dfe0a6ccfa34776b626e2bb13d63 | [
"BSD-3-Clause"
] | 99 | 2017-06-02T14:03:51.000Z | 2022-03-11T06:34:11.000Z | tests/test_behavior.py | jamoralp/pyecore | df1f230e6e99dfe0a6ccfa34776b626e2bb13d63 | [
"BSD-3-Clause"
] | 108 | 2017-05-19T05:53:45.000Z | 2022-03-30T04:49:47.000Z | tests/test_behavior.py | jamoralp/pyecore | df1f230e6e99dfe0a6ccfa34776b626e2bb13d63 | [
"BSD-3-Clause"
] | 41 | 2017-06-02T14:07:35.000Z | 2021-12-02T06:21:01.000Z | import pytest
from pyecore.ecore import *
from pyecore.behavior import behavior, main, run
def test_static_metamodel_behavior_injection():
@EMetaclass
class A(object):
pass
@A.behavior
def my_fun(self):
return True
@A.behavior
def __init__(self, i=15):
self.i = i
a = A()
assert a.my_fun() is True
assert a.i == 15
a = A(i=0)
assert a.i == 0
def test_static_metamodel_entry_point():
@EMetaclass
class A(object):
pass
@A.behavior
def my_fun(self, i):
return i + 1
a = A()
x = 1
with pytest.raises(NotImplementedError):
run(a)
# We add the behavior *after* the instance creation
@main
@A.behavior
def entry_point(self, i=0):
return self.my_fun(i)
y = run(a, x)
assert y == x + 1
def test_dynamic_metamodel_behavior_injection():
A = EClass('A')
@A.behavior
def my_fun(self):
return True
@A.behavior
def __init__(self, i=15):
self.i = i
a = A()
assert a.my_fun() is True
assert a.i == 15
a = A(i=0)
assert a.i == 0
def test_dynamic_metamodel_entry_point():
A = EClass('A')
@A.behavior
def my_fun(self, i):
return i + 1
a = A()
x = 1
with pytest.raises(NotImplementedError):
run(a)
# We add the behavior *after* the instance creation
@main
@A.behavior
def entry_point(self, i=0):
return self.my_fun(i)
y = run(a, x)
assert y == x + 1
def test_dynamic_metamodel_behavior_injection_newdecorator():
A = EClass('A')
@behavior(A)
def my_fun(self):
return True
@behavior(A)
def __init__(self, i=15):
self.i = i
a = A()
assert a.my_fun() is True
assert a.i == 15
a = A(i=0)
assert a.i == 0
def test_static_metamodel_behavior_injection_newdecorator():
@EMetaclass
class A(object):
...
@behavior(A)
def my_fun(self, stuff):
"""mydoc"""
return stuff + 5
@behavior(A)
def __init__(self, i=15):
self.i = i
a = A()
assert a.my_fun(0) == 5
assert a.i == 15
a = A(i=0)
assert a.i == 0
assert A.my_fun.__doc__ == "mydoc"
| 17.060606 | 61 | 0.564831 | 335 | 2,252 | 3.614925 | 0.149254 | 0.053675 | 0.079273 | 0.059455 | 0.834021 | 0.828241 | 0.739059 | 0.739059 | 0.739059 | 0.725846 | 0 | 0.022713 | 0.315719 | 2,252 | 131 | 62 | 17.19084 | 0.763141 | 0.047069 | 0 | 0.847826 | 0 | 0 | 0.00374 | 0 | 0 | 0 | 0 | 0 | 0.163043 | 1 | 0.195652 | false | 0.021739 | 0.032609 | 0.076087 | 0.347826 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
3568c9af4e11e5ca5da46f8f3f5757f7d8ab0c9c | 1,740 | py | Python | osf/migrations/0192_add_registation_responses_fields.py | gaybro8777/osf.io | 30408511510a40bc393565817b343ef5fd76ab14 | [
"Apache-2.0"
] | 628 | 2015-01-15T04:33:22.000Z | 2022-03-30T06:40:10.000Z | osf/migrations/0192_add_registation_responses_fields.py | gaybro8777/osf.io | 30408511510a40bc393565817b343ef5fd76ab14 | [
"Apache-2.0"
] | 4,712 | 2015-01-02T01:41:53.000Z | 2022-03-30T14:18:40.000Z | osf/migrations/0192_add_registation_responses_fields.py | Johnetordoff/osf.io | de10bf249c46cede04c78f7e6f7e352c69e6e6b5 | [
"Apache-2.0"
] | 371 | 2015-01-12T16:14:08.000Z | 2022-03-31T18:58:29.000Z | # -*- coding: utf-8 -*-
# Generated by Django 1.11.15 on 2019-09-01 23:15
from __future__ import unicode_literals
from django.db import migrations, models
import osf.utils.datetime_aware_jsonfield
class Migration(migrations.Migration):
dependencies = [
('osf', '0191_migrate_schemas_to_schemablocks'),
]
operations = [
migrations.AddField(
model_name='abstractnode',
name='registration_responses',
field=osf.utils.datetime_aware_jsonfield.DateTimeAwareJSONField(blank=True, default=dict, encoder=osf.utils.datetime_aware_jsonfield.DateTimeAwareJSONEncoder)
),
migrations.AddField(
model_name='abstractnode',
name='registration_responses_migrated',
field=models.NullBooleanField(db_index=True),
),
migrations.AddField(
model_name='draftregistration',
name='registration_responses',
field=osf.utils.datetime_aware_jsonfield.DateTimeAwareJSONField(blank=True, default=dict, encoder=osf.utils.datetime_aware_jsonfield.DateTimeAwareJSONEncoder),
),
migrations.AddField(
model_name='draftregistration',
name='registration_responses_migrated',
field=models.NullBooleanField(db_index=True),
),
migrations.AlterField(
model_name='abstractnode',
name='registration_responses_migrated',
field=models.NullBooleanField(db_index=True, default=True),
),
migrations.AlterField(
model_name='draftregistration',
name='registration_responses_migrated',
field=models.NullBooleanField(db_index=True, default=True),
),
]
| 37.021277 | 171 | 0.667241 | 160 | 1,740 | 7.0125 | 0.34375 | 0.048128 | 0.13369 | 0.093583 | 0.815508 | 0.762032 | 0.762032 | 0.762032 | 0.69697 | 0.69697 | 0 | 0.016579 | 0.237356 | 1,740 | 46 | 172 | 37.826087 | 0.828937 | 0.039655 | 0 | 0.717949 | 1 | 0 | 0.176259 | 0.122302 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.076923 | 0 | 0.153846 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
357cb879d8a7229d36e789aa6fa85bd7ee5d5ace | 9,041 | py | Python | tests/integration/test_lock.py | akudelka/sherlock | 9e85f36c01e0cb1d495283f024423bc60c3f7a4e | [
"MIT"
] | 165 | 2015-01-12T09:09:19.000Z | 2022-03-14T11:26:23.000Z | tests/integration/test_lock.py | akudelka/sherlock | 9e85f36c01e0cb1d495283f024423bc60c3f7a4e | [
"MIT"
] | 35 | 2015-01-07T14:57:24.000Z | 2022-03-24T17:43:28.000Z | tests/integration/test_lock.py | akudelka/sherlock | 9e85f36c01e0cb1d495283f024423bc60c3f7a4e | [
"MIT"
] | 38 | 2015-03-11T09:10:05.000Z | 2022-01-17T11:29:38.000Z | '''
Integration tests for backend locks.
'''
import etcd
import pylibmc
import redis
import sherlock
import time
import unittest
class TestRedisLock(unittest.TestCase):
def setUp(self):
try:
self.client = redis.StrictRedis(host='redis')
except Exception as err:
print(str(err))
raise Exception('You must have Redis server running on localhost '
'to be able to run integration tests.')
self.lock_name = 'test_lock'
def test_acquire(self):
lock = sherlock.RedisLock(self.lock_name, client=self.client)
self.assertTrue(lock._acquire())
self.assertEqual(self.client.get(self.lock_name).decode('UTF-8'),
str(lock._owner))
def test_acquire_with_namespace(self):
lock = sherlock.RedisLock(self.lock_name, client=self.client,
namespace='ns')
self.assertTrue(lock._acquire())
self.assertEqual(
self.client.get('ns_%s' % self.lock_name).decode('UTF-8'),
str(lock._owner))
def test_acquire_once_only(self):
lock1 = sherlock.RedisLock(self.lock_name, client=self.client)
lock2 = sherlock.RedisLock(self.lock_name, client=self.client)
self.assertTrue(lock1._acquire())
self.assertFalse(lock2._acquire())
def test_acquire_check_expiry(self):
lock = sherlock.RedisLock(self.lock_name, client=self.client, expire=1)
lock.acquire()
time.sleep(2)
self.assertFalse(lock.locked())
def test_acquire_check_expire_is_not_set(self):
lock = sherlock.RedisLock(self.lock_name, client=self.client,
expire=None)
lock.acquire()
time.sleep(2)
self.assertTrue(self.client.ttl(self.lock_name) < 0)
def test_release(self):
lock = sherlock.RedisLock(self.lock_name, client=self.client)
lock._acquire()
lock._release()
self.assertEqual(self.client.get(self.lock_name), None)
def test_release_with_namespace(self):
lock = sherlock.RedisLock(self.lock_name, client=self.client,
namespace='ns')
lock._acquire()
lock._release()
self.assertEqual(self.client.get('ns_%s' % self.lock_name), None)
def test_release_own_only(self):
lock1 = sherlock.RedisLock(self.lock_name, client=self.client)
lock2 = sherlock.RedisLock(self.lock_name, client=self.client)
lock1._acquire()
self.assertRaises(sherlock.LockException, lock2._release)
lock1._release()
def test_locked(self):
lock = sherlock.RedisLock(self.lock_name, client=self.client)
lock._acquire()
self.assertTrue(lock._locked)
lock._release()
self.assertFalse(lock._locked)
def test_deleting_lock_object_releases_the_lock(self):
lock = sherlock.lock.RedisLock(self.lock_name, client=self.client)
lock.acquire()
self.assertEqual(self.client.get(self.lock_name).decode('UTF-8'),
str(lock._owner))
del lock
self.assertEqual(self.client.get(self.lock_name), None)
def tearDown(self):
self.client.delete(self.lock_name)
self.client.delete('ns_%s' % self.lock_name)
class TestEtcdLock(unittest.TestCase):
def setUp(self):
self.client = etcd.Client(host='etcd')
self.lock_name = 'test_lock'
def test_acquire(self):
lock = sherlock.EtcdLock(self.lock_name, client=self.client)
self.assertTrue(lock._acquire())
self.assertEqual(self.client.get(self.lock_name).value,
str(lock._owner))
def test_acquire_with_namespace(self):
lock = sherlock.EtcdLock(self.lock_name, client=self.client,
namespace='ns')
self.assertTrue(lock._acquire())
self.assertEqual(self.client.get('/ns/%s' % self.lock_name).value,
str(lock._owner))
def test_acquire_once_only(self):
lock1 = sherlock.EtcdLock(self.lock_name, client=self.client)
lock2 = sherlock.EtcdLock(self.lock_name, client=self.client)
self.assertTrue(lock1._acquire())
self.assertFalse(lock2._acquire())
def test_acquire_check_expiry(self):
lock = sherlock.EtcdLock(self.lock_name, client=self.client, expire=1)
lock.acquire()
time.sleep(2)
self.assertFalse(lock.locked())
def test_acquire_check_expire_is_not_set(self):
lock = sherlock.EtcdLock(self.lock_name, client=self.client,
expire=None)
lock.acquire()
time.sleep(2)
self.assertEquals(self.client.get(self.lock_name).ttl, None)
def test_release(self):
lock = sherlock.EtcdLock(self.lock_name, client=self.client)
lock._acquire()
lock._release()
self.assertRaises(etcd.EtcdKeyNotFound, self.client.get, self.lock_name)
def test_release_with_namespace(self):
lock = sherlock.EtcdLock(self.lock_name, client=self.client,
namespace='ns')
lock._acquire()
lock._release()
self.assertRaises(etcd.EtcdKeyNotFound, self.client.get, '/ns/%s' % self.lock_name)
def test_release_own_only(self):
lock1 = sherlock.EtcdLock(self.lock_name, client=self.client)
lock2 = sherlock.EtcdLock(self.lock_name, client=self.client)
lock1._acquire()
self.assertRaises(sherlock.LockException, lock2._release)
lock1._release()
def test_locked(self):
lock = sherlock.EtcdLock(self.lock_name, client=self.client)
lock._acquire()
self.assertTrue(lock._locked)
lock._release()
self.assertFalse(lock._locked)
def test_deleting_lock_object_releases_the_lock(self):
lock = sherlock.lock.EtcdLock(self.lock_name, client=self.client)
lock.acquire()
self.assertEqual(self.client.get(self.lock_name).value, str(lock._owner))
del lock
self.assertRaises(etcd.EtcdKeyNotFound, self.client.get, self.lock_name)
def tearDown(self):
try:
self.client.delete(self.lock_name)
except etcd.EtcdKeyNotFound:
pass
try:
self.client.delete('/ns/%s' % self.lock_name)
except etcd.EtcdKeyNotFound:
pass
class TestMCLock(unittest.TestCase):
def setUp(self):
self.client = pylibmc.Client(['memcached'], binary=True)
self.lock_name = 'test_lock'
def test_acquire(self):
lock = sherlock.MCLock(self.lock_name, client=self.client)
self.assertTrue(lock._acquire())
self.assertEqual(self.client.get(self.lock_name), str(lock._owner))
def test_acquire_with_namespace(self):
lock = sherlock.MCLock(self.lock_name, client=self.client,
namespace='ns')
self.assertTrue(lock._acquire())
self.assertEqual(self.client.get('ns_%s' % self.lock_name),
str(lock._owner))
def test_acquire_once_only(self):
lock1 = sherlock.MCLock(self.lock_name, client=self.client)
lock2 = sherlock.MCLock(self.lock_name, client=self.client)
self.assertTrue(lock1._acquire())
self.assertFalse(lock2._acquire())
def test_acquire_check_expiry(self):
lock = sherlock.MCLock(self.lock_name, client=self.client, expire=1)
lock.acquire()
time.sleep(2)
self.assertFalse(lock.locked())
def test_release(self):
lock = sherlock.MCLock(self.lock_name, client=self.client)
lock._acquire()
lock._release()
self.assertEqual(self.client.get(self.lock_name), None)
def test_release_with_namespace(self):
lock = sherlock.MCLock(self.lock_name, client=self.client,
namespace='ns')
lock._acquire()
lock._release()
self.assertEqual(self.client.get('ns_%s' % self.lock_name), None)
def test_release_own_only(self):
lock1 = sherlock.MCLock(self.lock_name, client=self.client)
lock2 = sherlock.MCLock(self.lock_name, client=self.client)
lock1._acquire()
self.assertRaises(sherlock.LockException, lock2._release)
lock1._release()
def test_locked(self):
lock = sherlock.MCLock(self.lock_name, client=self.client)
lock._acquire()
self.assertTrue(lock._locked)
lock._release()
self.assertFalse(lock._locked)
def test_deleting_lock_object_releases_the_lock(self):
lock = sherlock.lock.MCLock(self.lock_name, client=self.client)
lock.acquire()
self.assertEqual(self.client.get(self.lock_name), str(lock._owner))
del lock
self.assertEqual(self.client.get(self.lock_name), None)
def tearDown(self):
self.client.delete(self.lock_name)
self.client.delete('ns_%s' % self.lock_name)
| 36.309237 | 91 | 0.639089 | 1,082 | 9,041 | 5.145102 | 0.088725 | 0.125022 | 0.137956 | 0.113167 | 0.923118 | 0.918089 | 0.903179 | 0.876953 | 0.863661 | 0.863661 | 0 | 0.005718 | 0.245548 | 9,041 | 248 | 92 | 36.455645 | 0.810438 | 0.003982 | 0 | 0.840796 | 0 | 0 | 0.022684 | 0 | 0 | 0 | 0 | 0 | 0.218905 | 1 | 0.174129 | false | 0.00995 | 0.029851 | 0 | 0.218905 | 0.004975 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
35be819222bbfcfab0e03a321f77a0e23fb57e40 | 21,125 | py | Python | Binary_Search_Tree_Unbalanced/BST_Test.py | rockgard3n/Data-Structures | 93b6b5aaf74cb0f39be233d0f80fd881e27969af | [
"MIT"
] | null | null | null | Binary_Search_Tree_Unbalanced/BST_Test.py | rockgard3n/Data-Structures | 93b6b5aaf74cb0f39be233d0f80fd881e27969af | [
"MIT"
] | null | null | null | Binary_Search_Tree_Unbalanced/BST_Test.py | rockgard3n/Data-Structures | 93b6b5aaf74cb0f39be233d0f80fd881e27969af | [
"MIT"
] | null | null | null | import unittest
from Binary_Search_Tree import Binary_Search_Tree
class BinarySearchTree_Tester(unittest.TestCase):
def setUp(self):
self.__tree = Binary_Search_Tree()
##Tests on empty
def test_empty_tree_string_IO(self):
self.assertEqual("[ ]", self.__tree.in_order())
def test_empty_tree_string_PRO(self):
self.assertEqual("[ ]", self.__tree.pre_order())
def test_empty_tree_string_PSTO(self):
self.assertEqual("[ ]", self.__tree.post_order())
def test_empty_tree(self):
self.assertEqual(0, self.__tree.get_height())
##Insertion Tests
#Height 1
def test_insert_on_empty_IO(self):
self.__tree.insert_element(25)
self.assertEqual("[ 25 ]", self.__tree.in_order())
def test_insert_on_empty_PRO(self):
self.__tree.insert_element(25)
self.assertEqual("[ 25 ]", self.__tree.pre_order())
def test_insert_on_empty_POST(self):
self.__tree.insert_element(25)
self.assertEqual("[ 25 ]", self.__tree.post_order())
def test_insert_on_empty_height(self):
self.__tree.insert_element(25)
self.assertEqual(1, self.__tree.get_height())
#Height 2
def test_insert_on_h1_lessthan_IO(self):
self.__tree.insert_element(25)
self.__tree.insert_element(15)
self.assertEqual("[ 15, 25 ]", self.__tree.in_order())
def test_insert_on_h1_lessthan_PRO(self):
self.__tree.insert_element(25)
self.__tree.insert_element(15)
self.assertEqual("[ 25, 15 ]", self.__tree.pre_order())
def test_insert_on_h1_lessthan_IO(self):
self.__tree.insert_element(25)
self.__tree.insert_element(15)
self.assertEqual("[ 15, 25 ]", self.__tree.post_order())
def test_insert_on_h1_lessthan_height(self):
self.__tree.insert_element(25)
self.__tree.insert_element(15)
self.assertEqual(2, self.__tree.get_height())
def test_insert_on_h1_gthan_IO(self):
self.__tree.insert_element(25)
self.__tree.insert_element(35)
self.assertEqual("[ 25, 35 ]", self.__tree.in_order())
def test_insert_on_h1_gthan_PRO(self):
self.__tree.insert_element(25)
self.__tree.insert_element(35)
self.assertEqual("[ 25, 35 ]", self.__tree.pre_order())
def test_insert_on_h1_gthan_PSTO(self):
self.__tree.insert_element(25)
self.__tree.insert_element(35)
self.assertEqual("[ 35, 25 ]", self.__tree.post_order())
def test_insert_on_h1_gthan_height(self):
self.__tree.insert_element(25)
self.__tree.insert_element(35)
self.assertEqual(2, self.__tree.get_height())
#perfect tree tests
def test_insert_h2_perfect_tree_IO(self):
self.__tree.insert_element(20)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.assertEqual("[ 15, 20, 25 ]", self.__tree.in_order())
def test_insert_h2_perfect_tree_PRO(self):
self.__tree.insert_element(20)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.assertEqual("[ 20, 15, 25 ]", self.__tree.pre_order())
def test_insert_h2_perfect_tree_PSTO(self):
self.__tree.insert_element(20)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.assertEqual("[ 15, 25, 20 ]", self.__tree.post_order())
#Height 3 less than
def test_insert_on_h2_lessthan_IO(self):
self.__tree.insert_element(25)
self.__tree.insert_element(15)
self.__tree.insert_element(10)
self.assertEqual("[ 10, 15, 25 ]", self.__tree.in_order())
def test_insert_on_h2_lessthan_PRO(self):
self.__tree.insert_element(25)
self.__tree.insert_element(15)
self.__tree.insert_element(10)
self.assertEqual("[ 25, 15, 10 ]", self.__tree.pre_order())
def test_insert_on_h2_lessthan_IO(self):
self.__tree.insert_element(25)
self.__tree.insert_element(15)
self.__tree.insert_element(10)
self.assertEqual("[ 10, 15, 25 ]", self.__tree.post_order())
def test_insert_on_h2_lessthan_height(self):
self.__tree.insert_element(25)
self.__tree.insert_element(15)
self.__tree.insert_element(10)
self.assertEqual(3, self.__tree.get_height())
#Height 3 greather than
def test_insert_on_h2_gthan_IO(self):
self.__tree.insert_element(10)
self.__tree.insert_element(25)
self.__tree.insert_element(35)
self.assertEqual("[ 10, 25, 35 ]", self.__tree.in_order())
def test_insert_on_h2_gthan_PRO(self):
self.__tree.insert_element(10)
self.__tree.insert_element(25)
self.__tree.insert_element(35)
self.assertEqual("[ 10, 25, 35 ]", self.__tree.pre_order())
def test_insert_on_h2_gthan_PSTO(self):
self.__tree.insert_element(10)
self.__tree.insert_element(25)
self.__tree.insert_element(35)
self.assertEqual("[ 35, 25, 10 ]", self.__tree.post_order())
def test_insert_on_h2_gthan_height(self):
self.__tree.insert_element(10)
self.__tree.insert_element(25)
self.__tree.insert_element(15)
self.assertEqual(3, self.__tree.get_height())
#Insert height 3 with elbow
def test_insert_h3_elbow_IO(self):
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.insert_element(20)
self.assertEqual("[ 15, 20, 25 ]", self.__tree.in_order())
def test_insert_h3_elbow_PRO(self):
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.insert_element(20)
self.assertEqual("[ 15, 25, 20 ]", self.__tree.pre_order())
def test_insert_h3_elbow_PSTO(self):
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.insert_element(20)
self.assertEqual("[ 20, 25, 15 ]", self.__tree.post_order())
def test_insert_h3_elbow_height(self):
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.insert_element(20)
self.assertEqual(3, self.__tree.get_height())
###Large tree insertion test
def test_insert_h3_perfect_IO(self):
self.__tree.insert_element(30)
self.__tree.insert_element(20)
self.__tree.insert_element(40)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.insert_element(35)
self.__tree.insert_element(45)
self.assertEqual("[ 15, 20, 25, 30, 35, 40, 45 ]", self.__tree.in_order())
def test_insert_h3_perfect_PRO(self):
self.__tree.insert_element(30)
self.__tree.insert_element(20)
self.__tree.insert_element(40)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.insert_element(35)
self.__tree.insert_element(45)
self.assertEqual("[ 30, 20, 15, 25, 40, 35, 45 ]", self.__tree.pre_order())
def test_insert_h3_perfect_POST(self):
self.__tree.insert_element(30)
self.__tree.insert_element(20)
self.__tree.insert_element(40)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.insert_element(35)
self.__tree.insert_element(45)
self.assertEqual("[ 15, 25, 20, 35, 45, 40, 30 ]", self.__tree.post_order())
##Removal Tests
#empty
def test_remove_empty_IO(self):
self.__tree.remove_element(25)
self.assertEqual("[ ]", self.__tree.in_order())
def test_remove_empty_PRO(self):
self.__tree.remove_element(25)
self.assertEqual("[ ]", self.__tree.pre_order())
def test_remove_empty_PSTO(self):
self.__tree.remove_element(25)
self.assertEqual("[ ]", self.__tree.post_order())
#Height 1
def test_remove_h1_IO(self):
self.__tree.insert_element(25)
self.__tree.remove_element(25)
self.assertEqual("[ ]", self.__tree.in_order())
def test_remove_h1_PRO(self):
self.__tree.insert_element(25)
self.__tree.remove_element(25)
self.assertEqual("[ ]", self.__tree.pre_order())
def test_remove_h1_POST(self):
self.__tree.insert_element(25)
self.__tree.remove_element(25)
self.assertEqual("[ ]", self.__tree.post_order())
def test_remove_h1_height(self):
self.__tree.insert_element(25)
self.__tree.remove_element(25)
self.assertEqual(0, self.__tree.get_height())
#Height 2 Removals, tests check removal on both leaf and root
def test_remove_h2_leaf_IO(self):
self.__tree.insert_element(15)
self.__tree.insert_element(20)
self.__tree.remove_element(20)
self.assertEqual("[ 15 ]", self.__tree.in_order())
def test_remove_h2_leaf_PRO(self):
self.__tree.insert_element(15)
self.__tree.insert_element(20)
self.__tree.remove_element(20)
self.assertEqual("[ 15 ]", self.__tree.pre_order())
def test_remove_h2_leaf_POST(self):
self.__tree.insert_element(15)
self.__tree.insert_element(20)
self.__tree.remove_element(20)
self.assertEqual("[ 15 ]", self.__tree.post_order())
def test_remove_h2_leaf_height(self):
self.__tree.insert_element(15)
self.__tree.insert_element(20)
self.__tree.remove_element(20)
self.assertEqual(1, self.__tree.get_height())
def test_remove_h2_root_IO(self):
self.__tree.insert_element(15)
self.__tree.insert_element(20)
self.__tree.remove_element(15)
self.assertEqual("[ 20 ]", self.__tree.in_order())
def test_remove_h2_root_PRO(self):
self.__tree.insert_element(15)
self.__tree.insert_element(20)
self.__tree.remove_element(15)
self.assertEqual("[ 20 ]", self.__tree.pre_order())
def test_remove_h2_root_POST(self):
self.__tree.insert_element(15)
self.__tree.insert_element(20)
self.__tree.remove_element(15)
self.assertEqual("[ 20 ]", self.__tree.post_order())
def test_remove_h2_root_height(self):
self.__tree.insert_element(15)
self.__tree.insert_element(20)
self.__tree.remove_element(15)
self.assertEqual(1, self.__tree.get_height())
#3 nodes removal tests
###Remove both leaves test
def test_remove_both_leaves_IO(self):
self.__tree.insert_element(20)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.remove_element(15)
self.__tree.remove_element(25)
self.assertEqual("[ 20 ]", self.__tree.in_order())
def test_remove_both_leaves_PRO(self):
self.__tree.insert_element(20)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.remove_element(15)
self.__tree.remove_element(25)
self.assertEqual("[ 20 ]", self.__tree.pre_order())
def test_remove_both_leaves_POST(self):
self.__tree.insert_element(20)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.remove_element(15)
self.__tree.remove_element(25)
self.assertEqual("[ 20 ]", self.__tree.post_order())
def test_remove_both_leaves_height(self):
self.__tree.insert_element(20)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.remove_element(15)
self.__tree.remove_element(25)
self.assertEqual(1, self.__tree.get_height())
def test_remove_both_leaves_IO_reverse(self):
self.__tree.insert_element(20)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.remove_element(25)
self.__tree.remove_element(15)
self.assertEqual("[ 20 ]", self.__tree.in_order())
def test_remove_both_leaves_PRO_reverse(self):
self.__tree.insert_element(20)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.remove_element(25)
self.__tree.remove_element(15)
self.assertEqual("[ 20 ]", self.__tree.pre_order())
def test_remove_both_leaves_POST_reverse(self):
self.__tree.insert_element(20)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.remove_element(25)
self.__tree.remove_element(15)
self.assertEqual("[ 20 ]", self.__tree.post_order())
def test_remove_both_leaves_height_reverse(self):
self.__tree.insert_element(20)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.remove_element(25)
self.__tree.remove_element(15)
self.assertEqual(1, self.__tree.get_height())
###Remove right leaf
def test_remove_right_leaf_IO(self):
self.__tree.insert_element(20)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.remove_element(25)
self.assertEqual("[ 15, 20 ]", self.__tree.in_order())
def test_remove_right_leaf_PRO(self):
self.__tree.insert_element(20)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.remove_element(25)
self.assertEqual("[ 20, 15 ]", self.__tree.pre_order())
def test_remove_right_leaf_POST(self):
self.__tree.insert_element(20)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.remove_element(25)
self.assertEqual("[ 15, 20 ]", self.__tree.post_order())
###Removal of left leaf
def test_remove_left_leaf_IO(self):
self.__tree.insert_element(20)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.remove_element(15)
self.assertEqual("[ 20, 25 ]", self.__tree.in_order())
def test_remove_left_leaf_PRO(self):
self.__tree.insert_element(20)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.remove_element(15)
self.assertEqual("[ 20, 25 ]", self.__tree.pre_order())
def test_remove_left_leaf_POST(self):
self.__tree.insert_element(20)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.remove_element(15)
self.assertEqual("[ 25, 20 ]", self.__tree.post_order())
def test_remove_left_leaf_height(self):
self.__tree.insert_element(20)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.remove_element(15)
self.assertEqual(2, self.__tree.get_height())
###3 nodes 2 height, perfect, removal of root
def test_remove_root_perfect_IO(self):
self.__tree.insert_element(20)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.remove_element(20)
self.assertEqual("[ 15, 25 ]", self.__tree.in_order())
def test_remove_root_perfect_PRO(self):
self.__tree.insert_element(20)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.remove_element(20)
self.assertEqual("[ 25, 15 ]", self.__tree.pre_order())
def test_remove_root_perfect_POST(self):
self.__tree.insert_element(20)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.remove_element(20)
self.assertEqual("[ 15, 25 ]", self.__tree.post_order())
def test_remove_root_perfect_height(self):
self.__tree.insert_element(20)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.remove_element(20)
self.assertEqual(2, self.__tree.get_height())
###Removal of joint of elbow
def test_remove_joint_elbowtree_IO(self):
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.insert_element(20)
self.__tree.remove_element(25)
self.assertEqual("[ 15, 20 ]", self.__tree.in_order())
def test_remove_joint_elbowtree_PRO(self):
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.insert_element(20)
self.__tree.remove_element(25)
self.assertEqual("[ 15, 20 ]", self.__tree.pre_order())
def test_remove_joint_elbowtree_POST(self):
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.insert_element(20)
self.__tree.remove_element(25)
self.assertEqual("[ 20, 15 ]", self.__tree.post_order())
def test_remove_joint_elbowtree_IO(self):
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.insert_element(20)
self.__tree.remove_element(25)
self.assertEqual(2, self.__tree.get_height())
###Removal tests on perfect tree of height 3 (testing removal of node at h2 which has 2 children)
def test_remove_left_child_h2_IO(self):
self.__tree.insert_element(30)
self.__tree.insert_element(20)
self.__tree.insert_element(40)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.insert_element(35)
self.__tree.insert_element(45)
self.__tree.remove_element(20)
self.assertEqual("[ 15, 25, 30, 35, 40, 45 ]", self.__tree.in_order())
def test_remove_left_child_h2_PRO(self):
self.__tree.insert_element(30)
self.__tree.insert_element(20)
self.__tree.insert_element(40)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.insert_element(35)
self.__tree.insert_element(45)
self.__tree.remove_element(20)
self.assertEqual("[ 30, 25, 15, 40, 35, 45 ]", self.__tree.pre_order())
def test_remove_left_child_h2_POST(self):
self.__tree.insert_element(30)
self.__tree.insert_element(20)
self.__tree.insert_element(40)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.insert_element(35)
self.__tree.insert_element(45)
self.__tree.remove_element(20)
self.assertEqual("[ 15, 25, 35, 45, 40, 30 ]", self.__tree.post_order())
def test_remove_left_child_h2_height(self):
self.__tree.insert_element(30)
self.__tree.insert_element(20)
self.__tree.insert_element(40)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.insert_element(35)
self.__tree.insert_element(45)
self.__tree.remove_element(20)
self.assertEqual(3, self.__tree.get_height())
###Removal tests on perfect tree of height 3 (removing root)
def test_remove_root_from_perfecth3_IO(self):
self.__tree.insert_element(30)
self.__tree.insert_element(20)
self.__tree.insert_element(40)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.insert_element(35)
self.__tree.insert_element(45)
self.__tree.remove_element(30)
self.assertEqual("[ 15, 20, 25, 35, 40, 45 ]", self.__tree.in_order())
def test_remove_root_from_perfecth3_PRO(self):
self.__tree.insert_element(30)
self.__tree.insert_element(20)
self.__tree.insert_element(40)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.insert_element(35)
self.__tree.insert_element(45)
self.__tree.remove_element(30)
self.assertEqual("[ 35, 20, 15, 25, 40, 45 ]", self.__tree.pre_order())
def test_remove_root_from_perfecth3_POST(self):
self.__tree.insert_element(30)
self.__tree.insert_element(20)
self.__tree.insert_element(40)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.insert_element(35)
self.__tree.insert_element(45)
self.__tree.remove_element(30)
self.assertEqual("[ 15, 25, 20, 45, 40, 35 ]", self.__tree.post_order())
def test_remove_root_from_perfecth3_height(self):
self.__tree.insert_element(30)
self.__tree.insert_element(20)
self.__tree.insert_element(40)
self.__tree.insert_element(15)
self.__tree.insert_element(25)
self.__tree.insert_element(35)
self.__tree.insert_element(45)
self.__tree.remove_element(30)
self.assertEqual(3, self.__tree.get_height())
if __name__ == "__main__":
unittest.main() | 38.131769 | 101 | 0.654533 | 2,777 | 21,125 | 4.455528 | 0.029888 | 0.236644 | 0.261376 | 0.392063 | 0.955791 | 0.934777 | 0.90851 | 0.877475 | 0.822355 | 0.800048 | 0 | 0.057521 | 0.230533 | 21,125 | 554 | 102 | 38.131769 | 0.70366 | 0.025657 | 0 | 0.743363 | 0 | 0 | 0.034998 | 0 | 0 | 0 | 0 | 0 | 0.176991 | 1 | 0.179204 | false | 0 | 0.004425 | 0 | 0.185841 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 10 |
ea581eaeb48210f577dcb0981e3af66092b982a8 | 10,896 | py | Python | tests.py | dmtlvn/dotdict | 018288ecc0b1aa12b69ca1b6460133b7f54c50f0 | [
"MIT"
] | 2 | 2021-09-11T12:50:04.000Z | 2021-09-13T08:20:33.000Z | tests.py | dmtlvn/dotdict | 018288ecc0b1aa12b69ca1b6460133b7f54c50f0 | [
"MIT"
] | null | null | null | tests.py | dmtlvn/dotdict | 018288ecc0b1aa12b69ca1b6460133b7f54c50f0 | [
"MIT"
] | null | null | null | import unittest
import pickle
import json
from dotdict.dotdict import dotdict
class DotDictTestCase(unittest.TestCase):
def setUp(self):
self.dict_ex = dict(
a = 1,
b = 2,
c = dict(
d = 3,
e = 4,
f = dict(
g = 5,
h = 6
)
)
)
self.attrdict_ex = dotdict(self.dict_ex)
self.keywords = {
"clear", "copy", "fromkeys", "get", "items", "keys",
"pop", "popitem", "setdefault", "update", "values", "to_dict"
}
def test_from_dict(self):
d = dict(a = 1, b = dict(c = 2))
a = dotdict(d)
self.assertEqual(a.a, d['a'])
self.assertEqual(a.b, d['b'])
self.assertEqual(a.b.c, d['b']['c'])
def test_nested_list(self):
d = dict(a = 1, b = [2, dict(c = 3)])
a = dotdict(d)
self.assertEqual(a.b[1].c, 3)
def test_nested_tuple(self):
d = dict(a = 1, b = (2, dict(c = 3)))
a = dotdict(d)
self.assertEqual(a.b[1].c, 3)
def test_subclasses_dict(self):
class A(dict):
pass
d = dict(a = 1, b = A(c = 2))
a = dotdict(d)
self.assertRaises(AttributeError, lambda m: m.c, a.b)
def test_subclasses_tuple(self):
class A(tuple):
pass
d = dict(a = 1, b = A((2, {'c': 3})))
a = dotdict(d)
self.assertRaises(AttributeError, lambda m: m.c, a.b[1])
def test_subclasses_list(self):
class A(list):
pass
d = dict(a = 1, b = A((2, {'c': 3})))
a = dotdict(d)
self.assertRaises(AttributeError, lambda m: m.c, a.b[1])
def test_to_dict_dict(self):
d = dotdict(a = 1, b = dict(c = 2)).to_dict()
self.assertRaises(AttributeError, lambda m: m.c, d['b'])
def test_to_dict_list(self):
d = dotdict(a = 1, b = [1, dict(c = 2)]).to_dict()
self.assertRaises(AttributeError, lambda m: m.c, d['b'][1])
def test_to_dict_tuple(self):
d = dotdict(a = 1, b = (1, dict(c = 2))).to_dict()
self.assertRaises(AttributeError, lambda m: m.c, d['b'][1])
def test_isinstance(self):
self.assertTrue(isinstance(self.attrdict_ex, dict))
def test_hasattr(self):
self.assertTrue(hasattr(self.attrdict_ex, 'a'))
def test_hasattr_methods(self):
for k in self.keywords:
self.assertTrue(hasattr(self.attrdict_ex, k))
def test_dict_comparison(self):
self.assertEqual(self.attrdict_ex, self.dict_ex)
def test_str(self):
d = dotdict(a = 42, b = dict(c = 69))
self.assertEqual(str(d), "attrdict({'a': 42, 'b': attrdict({'c': 69})})")
def test_pickle(self):
ref = dotdict(a = 42, b = dict(c = 69))
pkl = pickle.dumps(ref)
rec = pickle.loads(pkl)
self.assertEqual(rec, ref)
def test_json(self):
ref = dotdict(a = 42, b = dict(c = 69))
jsn = json.dumps(ref)
rec = json.loads(jsn)
self.assertEqual(rec, ref)
def test_pyyaml(self):
d = dotdict(a = 42, b = dict(c = 69))
try:
import yaml
s = yaml.dump(d)
self.assertEqual(s, 'a: 42\nb:\n c: 69\n')
except ImportError:
pass
# get-tests
def test_getattr(self):
self.assertEqual(self.attrdict_ex.a, 1)
def test_getitem(self):
self.assertEqual(self.attrdict_ex['a'], 1)
def test_getattr_recursive(self):
self.assertEqual(self.attrdict_ex.c.d, 3)
def test_getitem_recursive(self):
self.assertEqual(self.attrdict_ex['c']['d'], 3)
def test_getattr_mixed(self):
self.assertEqual(self.attrdict_ex.c['d'], 3)
def test_getitem_mixed(self):
self.assertEqual(self.attrdict_ex['c'].d, 3)
def test_getattr_error(self):
self.assertRaises(KeyError, lambda d: d.non_existent, self.attrdict_ex)
def test_getitem_error(self):
self.assertRaises(KeyError, lambda d: d['non_existent'], self.attrdict_ex)
def test_getitem_protected(self):
d = dotdict(a = 42, keys = 69)
self.assertEqual(d['keys'], 69)
def test_getattr_protected(self):
d = dotdict(a = 42, keys = 69)
self.assertTrue(callable(d.keys))
# set-tests
def test_setattr_existing(self):
self.attrdict_ex.a = 42
self.assertEqual(self.attrdict_ex.a, 42)
def test_setattr_new(self):
self.attrdict_ex.q = 69
self.assertEqual(self.attrdict_ex.q, 69)
def test_setattr_nested_dict(self):
self.attrdict_ex.q = {'a': 1, 'b': {'c': 69}}
self.assertEqual(self.attrdict_ex.q.b.c, 69)
def test_setattr_nested_dict_subclass(self):
class A(dict):
pass
self.attrdict_ex.q = A(a = 1)
self.assertTrue(isinstance(self.attrdict_ex.q, A))
self.assertRaises(AttributeError, lambda m: m.a, self.attrdict_ex.q)
def test_setattr_nested_tuple_subclass(self):
class A(tuple):
pass
self.attrdict_ex.q = A(({'a': 1},))
self.assertTrue(isinstance(self.attrdict_ex.q, A))
self.assertTrue(type(self.attrdict_ex.q[0]) is dict)
self.assertRaises(AttributeError, lambda m: m.a, self.attrdict_ex.q[0])
def test_setattr_nested_list_subclass(self):
class A(tuple):
pass
self.attrdict_ex.q = A([{'a': 1}])
self.assertTrue(isinstance(self.attrdict_ex.q, A))
self.assertTrue(type(self.attrdict_ex.q[0]) is dict)
self.assertRaises(AttributeError, lambda m: m.a, self.attrdict_ex.q[0])
def test_setattr_nested_tuple(self):
self.attrdict_ex.q = {'a': 1, 'b': ({'c': 69},)}
self.assertEqual(self.attrdict_ex.q.b[0].c, 69)
def test_setattr_nested_list(self):
self.attrdict_ex.q = {'a': 1, 'b': [{'c': 69}]}
self.assertEqual(self.attrdict_ex.q.b[0].c, 69)
def test_setitem_existing(self):
self.attrdict_ex['a'] = 42
self.assertEqual(self.attrdict_ex['a'], 42)
def test_setitem_new(self):
self.attrdict_ex['q'] = 69
self.assertEqual(self.attrdict_ex['q'], 69)
def test_setattr_recursive_existing(self):
self.attrdict_ex.c.f.g = 42
self.assertEqual(self.attrdict_ex.c.f.g, 42)
def test_setattr_recursive_new(self):
self.attrdict_ex.c.f.q = 69
self.assertEqual(self.attrdict_ex.c.f.q, 69)
def test_setitem_recursive_existing(self):
self.attrdict_ex['c']['f']['g'] = 42
self.assertEqual(self.attrdict_ex['c']['f']['g'], 42)
def test_setitem_recursive_new(self):
self.attrdict_ex['c']['f']['q'] = 69
self.assertEqual(self.attrdict_ex['c']['f']['q'], 69)
def test_setattr_mixed_existing(self):
self.attrdict_ex.c['f'].g = 42
self.assertEqual(self.attrdict_ex.c['f'].g, 42)
def test_setattr_mixed_new(self):
self.attrdict_ex.c['f'].q = 69
self.assertEqual(self.attrdict_ex.c['f'].q, 69)
def test_setattr_unresolved(self):
def test():
self.attrdict_ex.c.non_existent.foo = 69
self.assertRaises(KeyError, test)
def test_setattr_protected(self):
def test(key):
self.attrdict_ex.__setattr__(key, 69)
for k in self.keywords:
self.assertRaises(AttributeError, test, k)
# del-tests
def test_delattr(self):
del self.attrdict_ex.a
self.assertFalse('a' in self.attrdict_ex)
def test_delitem(self):
del self.attrdict_ex['a']
self.assertFalse('a' in self.attrdict_ex)
def test_delattr_error(self):
def test():
del self.attrdict_ex.non_existent
self.assertRaises(KeyError, test)
def test_delitem_error(self):
def test():
del self.attrdict_ex['non_existent']
self.assertRaises(KeyError, test)
def test_delattr_protected(self):
def test(d, key):
d.__delattr__(key)
d = dotdict(a = 42, keys = 69)
for k in self.keywords:
self.assertRaises(AttributeError, test, d, k)
# update tests
def test_update_dict(self):
upd = dict(a = 42, c = dict(d = 69))
ref = dict(a = 42, b = 2, c = dict(d = 69))
self.attrdict_ex.update(upd)
self.assertEqual(self.attrdict_ex, ref)
def test_update_iterable(self):
upd = [('a', 42), ('c', dict(d = 69))]
ref = dict(a = 42, b = 2, c = dict(d = 69))
self.attrdict_ex.update(upd)
self.assertEqual(self.attrdict_ex, ref)
def test_update_kwargs(self):
upd = dict(a = 42, c = dict(d = 69))
ref = dict(a = 42, b = 2, c = 69)
self.attrdict_ex.update(upd, c = 69)
self.assertEqual(self.attrdict_ex, ref)
def test_update_error(self):
self.assertRaises(TypeError, self.attrdict_ex.update, 42)
self.assertRaises(TypeError, self.attrdict_ex.update, 42, 69)
def test_update_iterable_error(self):
self.assertRaises(TypeError, self.attrdict_ex.update, [42, 69])
def test_update_dict_recursive(self):
upd = dict(a = 42, c = dict(d = 69))
ref = self.dict_ex
ref['a'], ref['c']['d'] = 42, 69
self.attrdict_ex.update(upd, recursive = True)
self.assertEqual(self.attrdict_ex, ref)
def test_update_iterable_recursive(self):
upd = [('a', 42), ('c', dict(d = 69))]
ref = self.dict_ex
ref['a'], ref['c']['d'] = 42, 69
self.attrdict_ex.update(upd, recursive = True)
self.assertEqual(self.attrdict_ex, ref)
def test_update_nested_iterable_recursive(self):
upd = [('a', 42), ('c', [('d', 69)])]
ref = dict(a = 42, b = 2, c = [('d', 69)])
self.attrdict_ex.update(upd, recursive = True)
self.assertEqual(self.attrdict_ex, ref)
def test_update_kwargs_recursive(self):
upd = dict(a = 42, c = dict(d = 69))
ref = self.dict_ex
ref['a'], ref['c'] = 42, 69
self.attrdict_ex.update(upd, c = 69, recursive = True)
self.assertEqual(self.attrdict_ex, ref)
def test_update_kwargs_nested_recursive(self):
upd = dict(a = 42, c = dict(d = 69))
self.attrdict_ex.update(upd, c = dict(d = 420), recursive = True)
ref = self.dict_ex
ref['a'], ref['c']['d'] = 42, 420
self.assertEqual(self.attrdict_ex, ref)
def test_update_error_recursive(self):
self.assertRaises(TypeError, self.attrdict_ex.update, 42, recursive = True)
self.assertRaises(TypeError, self.attrdict_ex.update, 42, 69, recursive = True)
def test_update_iterable_error_recursive(self):
self.assertRaises(TypeError, self.attrdict_ex.update, [42, 69], recursive = True)
if __name__ == "__main__":
unittest.main()
| 32.428571 | 89 | 0.58627 | 1,540 | 10,896 | 3.982468 | 0.075325 | 0.15653 | 0.182619 | 0.123268 | 0.806131 | 0.785912 | 0.722811 | 0.714006 | 0.704875 | 0.669493 | 0 | 0.030873 | 0.268722 | 10,896 | 335 | 90 | 32.525373 | 0.73883 | 0.003855 | 0 | 0.319231 | 0 | 0 | 0.021845 | 0 | 0 | 0 | 0 | 0 | 0.273077 | 1 | 0.261538 | false | 0.026923 | 0.023077 | 0 | 0.311538 | 0 | 0 | 0 | 0 | null | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
5776a121cc136747bc5980a5421ad56ebd83e72c | 232,192 | py | Python | openeo/processes.py | jonathom/openeo-python-client | 43140b8371b01f67806deff39508b02572944280 | [
"Apache-2.0"
] | 75 | 2017-11-17T11:49:15.000Z | 2022-02-15T14:21:42.000Z | openeo/processes.py | jonathom/openeo-python-client | 43140b8371b01f67806deff39508b02572944280 | [
"Apache-2.0"
] | 238 | 2017-12-05T14:48:30.000Z | 2022-03-31T15:42:38.000Z | openeo/processes.py | jonathom/openeo-python-client | 43140b8371b01f67806deff39508b02572944280 | [
"Apache-2.0"
] | 28 | 2018-01-24T08:42:54.000Z | 2022-01-27T09:16:26.000Z |
# Do not edit this file directly.
# It is automatically generated.
# Used command line arguments:
# openeo/internal/processes/generator.py ../openeo-processes/ ../openeo-processes/proposals/ --output openeo/processes.py
import builtins
from openeo.internal.processes.builder import ProcessBuilderBase, UNSET
class ProcessBuilder(ProcessBuilderBase):
def __add__(self, other) -> 'ProcessBuilder':
return self.add(other)
def __radd__(self, other) -> 'ProcessBuilder':
return add(other, self)
def __sub__(self, other) -> 'ProcessBuilder':
return self.subtract(other)
def __rsub__(self, other) -> 'ProcessBuilder':
return subtract(other, self)
def __mul__(self, other) -> 'ProcessBuilder':
return self.multiply(other)
def __rmul__(self, other) -> 'ProcessBuilder':
return multiply(other, self)
def __truediv__(self, other) -> 'ProcessBuilder':
return self.divide(other)
def __rtruediv__(self, other) -> 'ProcessBuilder':
return divide(other, self)
def __neg__(self) -> 'ProcessBuilder':
return self.multiply(-1)
def __pow__(self, other) -> 'ProcessBuilder':
return self.power(other)
def __getitem__(self, key) -> 'ProcessBuilder':
if isinstance(key, builtins.int):
return self.array_element(index=key)
else:
return self.array_element(label=key)
def __eq__(self, other) -> 'ProcessBuilder':
return eq(self, other)
def __ne__(self, other) -> 'ProcessBuilder':
return neq(self, other)
def absolute(self) -> 'ProcessBuilder':
"""
Absolute value
:param self: A number.
:return: The computed absolute value.
"""
return absolute(x=self)
def add(self, y) -> 'ProcessBuilder':
"""
Addition of two numbers
:param self: The first summand.
:param y: The second summand.
:return: The computed sum of the two numbers.
"""
return add(x=self, y=y)
def add_dimension(self, name, label, type=UNSET) -> 'ProcessBuilder':
"""
Add a new dimension
:param self: A data cube to add the dimension to.
:param name: Name for the dimension.
:param label: A dimension label.
:param type: The type of dimension, defaults to `other`.
:return: The data cube with a newly added dimension. The new dimension has exactly one dimension label.
All other dimensions remain unchanged.
"""
return add_dimension(data=self, name=name, label=label, type=type)
def aggregate_spatial(self, geometries, reducer, target_dimension=UNSET, context=UNSET) -> 'ProcessBuilder':
"""
Zonal statistics for geometries
:param self: A raster data cube. The data cube must have been reduced to only contain two spatial
dimensions and a third dimension the values are aggregated for, for example the temporal dimension to
get a time series. Otherwise, this process fails with the `TooManyDimensions` exception. The data cube
implicitly gets restricted to the bounds of the geometries as if ``filter_spatial()`` would have been
used with the same values for the corresponding parameters immediately before this process.
:param geometries: Geometries as GeoJSON on which the aggregation will be based. One value will be
computed per GeoJSON `Feature`, `Geometry` or `GeometryCollection`. For a `FeatureCollection` multiple
values will be computed, one value per contained `Feature`. For example, a single value will be
computed for a `MultiPolygon`, but two values will be computed for a `FeatureCollection` containing two
polygons. - For **polygons**, the process considers all pixels for which the point at the pixel center
intersects with the corresponding polygon (as defined in the Simple Features standard by the OGC). -
For **points**, the process considers the closest pixel center. - For **lines** (line strings), the
process considers all the pixels whose centers are closest to at least one point on the line. Thus,
pixels may be part of multiple geometries and be part of multiple aggregations. To maximize
interoperability, a nested `GeometryCollection` should be avoided. Furthermore, a `GeometryCollection`
composed of a single type of geometries should be avoided in favour of the corresponding multi-part
type (e.g. `MultiPolygon`).
:param reducer: A reducer to be applied on all values of each geometry. A reducer is a single process
such as ``mean()`` or a set of processes, which computes a single value for a list of values, see the
category 'reducer' for such processes.
:param target_dimension: The new dimension name to be used for storing the results. Defaults to
`result`.
:param context: Additional data to be passed to the reducer.
:return: A vector data cube with the computed results and restricted to the bounds of the geometries.
The computed value is used for the dimension with the name that was specified in the parameter
`target_dimension`. The computation also stores information about the total count of pixels (valid +
invalid pixels) and the number of valid pixels (see ``is_valid()``) for each geometry. These values are
added as a new dimension with a dimension name derived from `target_dimension` by adding the suffix
`_meta`. The new dimension has the dimension labels `total_count` and `valid_count`.
"""
return aggregate_spatial(data=self, geometries=geometries, reducer=reducer, target_dimension=target_dimension, context=context)
def aggregate_spatial_binary(self, geometries, reducer, target_dimension=UNSET, context=UNSET) -> 'ProcessBuilder':
"""
Zonal statistics for geometries by binary aggregation
:param self: A raster data cube. The data cube implicitly gets restricted to the bounds of the
geometries as if ``filter_spatial()`` would have been used with the same values for the corresponding
parameters immediately before this process.
:param geometries: Geometries as GeoJSON on which the aggregation will be based.
:param reducer: A reduction operator to be applied consecutively on tuples of values. It must be both
associative and commutative as the execution may be executed in parallel and therefore the order of
execution is arbitrary. The reduction operator may be a single process such as ``multiply()`` or
consist of multiple sub-processes.
:param target_dimension: The new dimension name to be used for storing the results. Defaults to
`result`.
:param context: Additional data to be passed to the reducer.
:return: A vector data cube with the computed results and restricted to the bounds of the geometries.
The computed value is stored in dimension with the name that was specified in the parameter
`target_dimension`. The computation also stores information about the total count of pixels (valid +
invalid pixels) and the number of valid pixels (see ``is_valid()``) for each geometry. These values are
stored as new dimension with a dimension name derived from `target_dimension` by adding the suffix
`_meta`. The new dimension has the dimension labels `total_count` and `valid_count`.
"""
return aggregate_spatial_binary(data=self, geometries=geometries, reducer=reducer, target_dimension=target_dimension, context=context)
def aggregate_spatial_window(self, reducer, size, boundary=UNSET, align=UNSET, context=UNSET) -> 'ProcessBuilder':
"""
Zonal statistics for rectangular windows
:param self: A raster data cube with exactly two horizontal spatial dimensions and an arbitrary number
of additional dimensions. The process is applied to all additional dimensions individually.
:param reducer: A reducer to be applied on the list of values, which contain all pixels covered by the
window. A reducer is a single process such as ``mean()`` or a set of processes, which computes a single
value for a list of values, see the category 'reducer' for such processes.
:param size: Window size in pixels along the horizontal spatial dimensions. The first value
corresponds to the `x` axis, the second value corresponds to the `y` axis.
:param boundary: Behavior to apply if the number of values for the axes `x` and `y` is not a multiple
of the corresponding value in the `size` parameter. Options are: - `pad` (default): pad the data cube
with the no-data value `null` to fit the required window size. - `trim`: trim the data cube to fit the
required window size. Set the parameter `align` to specifies to which corner the data is aligned to.
:param align: If the data requires padding or trimming (see parameter `boundary`), specifies to which
corner of the spatial extent the data is aligned to. For example, if the data is aligned to the upper
left, the process pads/trims at the lower-right.
:param context: Additional data to be passed to the reducer.
:return: A data cube with the newly computed values and the same dimensions. The resolution will
change depending on the chosen values for the `size` and `boundary` parameter. It usually decreases for
the dimensions which have the corresponding parameter `size` set to values greater than 1. The
dimension labels will be set to the coordinate at the center of the window. The other dimension
properties (name, type and reference system) remain unchanged.
"""
return aggregate_spatial_window(data=self, reducer=reducer, size=size, boundary=boundary, align=align, context=context)
def aggregate_temporal(self, intervals, reducer, labels=UNSET, dimension=UNSET, context=UNSET) -> 'ProcessBuilder':
"""
Temporal aggregations
:param self: A data cube.
:param intervals: Left-closed temporal intervals, which are allowed to overlap. Each temporal interval
in the array has exactly two elements: 1. The first element is the start of the temporal interval. The
specified instance in time is **included** in the interval. 2. The second element is the end of the
temporal interval. The specified instance in time is **excluded** from the interval. The specified
temporal strings follow [RFC 3339](https://www.rfc-editor.org/rfc/rfc3339.html). Although [RFC 3339
prohibits the hour to be '24'](https://www.rfc-editor.org/rfc/rfc3339.html#section-5.7), **this process
allows the value '24' for the hour** of an end time in order to make it possible that left-closed time
intervals can fully cover the day.
:param reducer: A reducer to be applied for the values contained in each interval. A reducer is a
single process such as ``mean()`` or a set of processes, which computes a single value for a list of
values, see the category 'reducer' for such processes. Intervals may not contain any values, which for
most reducers leads to no-data (`null`) values by default.
:param labels: Distinct labels for the intervals, which can contain dates and/or times. Is only
required to be specified if the values for the start of the temporal intervals are not distinct and
thus the default labels would not be unique. The number of labels and the number of groups need to be
equal.
:param dimension: The name of the temporal dimension for aggregation. All data along the dimension is
passed through the specified reducer. If the dimension is not set or set to `null`, the data cube is
expected to only have one temporal dimension. Fails with a `TooManyDimensions` exception if it has more
dimensions. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist.
:param context: Additional data to be passed to the reducer.
:return: A new data cube with the same dimensions. The dimension properties (name, type, labels,
reference system and resolution) remain unchanged, except for the resolution and dimension labels of
the given temporal dimension.
"""
return aggregate_temporal(data=self, intervals=intervals, reducer=reducer, labels=labels, dimension=dimension, context=context)
def aggregate_temporal_period(self, period, reducer, dimension=UNSET, context=UNSET) -> 'ProcessBuilder':
"""
Temporal aggregations based on calendar hierarchies
:param self: A data cube.
:param period: The time intervals to aggregate. The following pre-defined values are available: *
`hour`: Hour of the day * `day`: Day of the year * `week`: Week of the year * `dekad`: Ten day periods,
counted per year with three periods per month (day 1 - 10, 11 - 20 and 21 - end of month). The third
dekad of the month can range from 8 to 11 days. For example, the fourth dekad is Feb, 1 - Feb, 10 each
year. * `month`: Month of the year * `season`: Three month periods of the calendar seasons (December -
February, March - May, June - August, September - November). * `tropical-season`: Six month periods of
the tropical seasons (November - April, May - October). * `year`: Proleptic years * `decade`: Ten year
periods ([0-to-9 decade](https://en.wikipedia.org/wiki/Decade#0-to-9_decade)), from a year ending in a
0 to the next year ending in a 9. * `decade-ad`: Ten year periods ([1-to-0
decade](https://en.wikipedia.org/wiki/Decade#1-to-0_decade)) better aligned with the anno Domini (AD)
calendar era, from a year ending in a 1 to the next year ending in a 0.
:param reducer: A reducer to be applied for the values contained in each period. A reducer is a single
process such as ``mean()`` or a set of processes, which computes a single value for a list of values,
see the category 'reducer' for such processes. Periods may not contain any values, which for most
reducers leads to no-data (`null`) values by default.
:param dimension: The name of the temporal dimension for aggregation. All data along the dimension is
passed through the specified reducer. If the dimension is not set or set to `null`, the data cube is
expected to only have one temporal dimension. Fails with a `TooManyDimensions` exception if it has more
dimensions. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist.
:param context: Additional data to be passed to the reducer.
:return: A new data cube with the same dimensions. The dimension properties (name, type, labels,
reference system and resolution) remain unchanged, except for the resolution and dimension labels of
the given temporal dimension. The specified temporal dimension has the following dimension labels
(`YYYY` = four-digit year, `MM` = two-digit month, `DD` two-digit day of month): * `hour`: `YYYY-MM-
DD-00` - `YYYY-MM-DD-23` * `day`: `YYYY-001` - `YYYY-365` * `week`: `YYYY-01` - `YYYY-52` * `dekad`:
`YYYY-00` - `YYYY-36` * `month`: `YYYY-01` - `YYYY-12` * `season`: `YYYY-djf` (December - February),
`YYYY-mam` (March - May), `YYYY-jja` (June - August), `YYYY-son` (September - November). * `tropical-
season`: `YYYY-ndjfma` (November - April), `YYYY-mjjaso` (May - October). * `year`: `YYYY` * `decade`:
`YYY0` * `decade-ad`: `YYY1`
"""
return aggregate_temporal_period(data=self, period=period, reducer=reducer, dimension=dimension, context=context)
def all(self, ignore_nodata=UNSET) -> 'ProcessBuilder':
"""
Are all of the values true?
:param self: A set of boolean values.
:param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default.
:return: Boolean result of the logical operation.
"""
return all(data=self, ignore_nodata=ignore_nodata)
def and_(self, y) -> 'ProcessBuilder':
"""
Logical AND
:param self: A boolean value.
:param y: A boolean value.
:return: Boolean result of the logical AND.
"""
return and_(x=self, y=y)
def anomaly(self, normals, period) -> 'ProcessBuilder':
"""
Compute anomalies
:param self: A data cube with exactly one temporal dimension and the following dimension labels for the
given period (`YYYY` = four-digit year, `MM` = two-digit month, `DD` two-digit day of month): *
`hour`: `YYYY-MM-DD-00` - `YYYY-MM-DD-23` * `day`: `YYYY-001` - `YYYY-365` * `week`: `YYYY-01` -
`YYYY-52` * `dekad`: `YYYY-00` - `YYYY-36` * `month`: `YYYY-01` - `YYYY-12` * `season`: `YYYY-djf`
(December - February), `YYYY-mam` (March - May), `YYYY-jja` (June - August), `YYYY-son` (September -
November). * `tropical-season`: `YYYY-ndjfma` (November - April), `YYYY-mjjaso` (May - October). *
`year`: `YYYY` * `decade`: `YYY0` * `decade-ad`: `YYY1` * `single-period` / `climatology-period`: Any
``aggregate_temporal_period()`` can compute such a data cube.
:param normals: A data cube with normals, e.g. daily, monthly or yearly values computed from a process
such as ``climatological_normal()``. Must contain exactly one temporal dimension with the following
dimension labels for the given period: * `hour`: `00` - `23` * `day`: `001` - `365` * `week`: `01` -
`52` * `dekad`: `00` - `36` * `month`: `01` - `12` * `season`: `djf` (December - February), `mam`
(March - May), `jja` (June - August), `son` (September - November) * `tropical-season`: `ndjfma`
(November - April), `mjjaso` (May - October) * `year`: Four-digit year numbers * `decade`: Four-digit
year numbers, the last digit being a `0` * `decade-ad`: Four-digit year numbers, the last digit being a
`1` * `single-period` / `climatology-period`: A single dimension label with any name is expected.
:param period: Specifies the time intervals available in the normals data cube. The following options
are available: * `hour`: Hour of the day * `day`: Day of the year * `week`: Week of the year *
`dekad`: Ten day periods, counted per year with three periods per month (day 1 - 10, 11 - 20 and 21 -
end of month). The third dekad of the month can range from 8 to 11 days. For example, the fourth dekad
is Feb, 1 - Feb, 10 each year. * `month`: Month of the year * `season`: Three month periods of the
calendar seasons (December - February, March - May, June - August, September - November). * `tropical-
season`: Six month periods of the tropical seasons (November - April, May - October). * `year`:
Proleptic years * `decade`: Ten year periods ([0-to-9
decade](https://en.wikipedia.org/wiki/Decade#0-to-9_decade)), from a year ending in a 0 to the next
year ending in a 9. * `decade-ad`: Ten year periods ([1-to-0
decade](https://en.wikipedia.org/wiki/Decade#1-to-0_decade)) better aligned with the anno Domini (AD)
calendar era, from a year ending in a 1 to the next year ending in a 0. * `single-period` /
`climatology-period`: A single period of arbitrary length
:return: A data cube with the same dimensions. The dimension properties (name, type, labels, reference
system and resolution) remain unchanged.
"""
return anomaly(data=self, normals=normals, period=period)
def any(self, ignore_nodata=UNSET) -> 'ProcessBuilder':
"""
Is at least one value true?
:param self: A set of boolean values.
:param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default.
:return: Boolean result of the logical operation.
"""
return any(data=self, ignore_nodata=ignore_nodata)
def apply(self, process, context=UNSET) -> 'ProcessBuilder':
"""
Apply a process to each pixel
:param self: A data cube.
:param process: A process that accepts and returns a single value and is applied on each individual
value in the data cube. The process may consist of multiple sub-processes and could, for example,
consist of processes such as ``abs()`` or ``linear_scale_range()``.
:param context: Additional data to be passed to the process.
:return: A data cube with the newly computed values and the same dimensions. The dimension properties
(name, type, labels, reference system and resolution) remain unchanged.
"""
return apply(data=self, process=process, context=context)
def apply_dimension(self, process, dimension, target_dimension=UNSET, context=UNSET) -> 'ProcessBuilder':
"""
Apply a process to pixels along a dimension
:param self: A data cube.
:param process: Process to be applied on all pixel values. The specified process needs to accept an
array and must return an array with at least one element. A process may consist of multiple sub-
processes.
:param dimension: The name of the source dimension to apply the process on. Fails with a
`DimensionNotAvailable` exception if the specified dimension does not exist.
:param target_dimension: The name of the target dimension or `null` (the default) to use the source
dimension specified in the parameter `dimension`. By specifying a target dimension, the source
dimension is removed. The target dimension with the specified name and the type `other` (see
``add_dimension()``) is created, if it doesn't exist yet.
:param context: Additional data to be passed to the process.
:return: A data cube with the newly computed values. All dimensions stay the same, except for the
dimensions specified in corresponding parameters. There are three cases how the dimensions can change:
1. The source dimension is the target dimension: - The (number of) dimensions remain unchanged as
the source dimension is the target dimension. - The source dimension properties name and type remain
unchanged. - The dimension labels, the reference system and the resolution are preserved only if the
number of pixel values in the source dimension is equal to the number of values computed by the
process. Otherwise, all other dimension properties change as defined in the list below. 2. The source
dimension is not the target dimension and the latter exists: - The number of dimensions decreases by
one as the source dimension is dropped. - The target dimension properties name and type remain
unchanged. All other dimension properties change as defined in the list below. 3. The source dimension
is not the target dimension and the latter does not exist: - The number of dimensions remain
unchanged, but the source dimension is replaced with the target dimension. - The target dimension
has the specified name and the type other. All other dimension properties are set as defined in the
list below. Unless otherwise stated above, for the given (target) dimension the following applies: -
the number of dimension labels is equal to the number of values computed by the process, - the
dimension labels are incrementing integers starting from zero, - the resolution changes, and - the
reference system is undefined.
"""
return apply_dimension(data=self, process=process, dimension=dimension, target_dimension=target_dimension, context=context)
def apply_kernel(self, kernel, factor=UNSET, border=UNSET, replace_invalid=UNSET) -> 'ProcessBuilder':
"""
Apply a spatial convolution with a kernel
:param self: A data cube.
:param kernel: Kernel as a two-dimensional array of weights. The inner level of the nested array aligns
with the `x` axis and the outer level aligns with the `y` axis. Each level of the kernel must have an
uneven number of elements, otherwise the process throws a `KernelDimensionsUneven` exception.
:param factor: A factor that is multiplied to each value after the kernel has been applied. This is
basically a shortcut for explicitly multiplying each value by a factor afterwards, which is often
required for some kernel-based algorithms such as the Gaussian blur.
:param border: Determines how the data is extended when the kernel overlaps with the borders. Defaults
to fill the border with zeroes. The following options are available: * *numeric value* - fill with a
user-defined constant number `n`: `nnnnnn|abcdefgh|nnnnnn` (default, with `n` = 0) * `replicate` -
repeat the value from the pixel at the border: `aaaaaa|abcdefgh|hhhhhh` * `reflect` - mirror/reflect
from the border: `fedcba|abcdefgh|hgfedc` * `reflect_pixel` - mirror/reflect from the center of the
pixel at the border: `gfedcb|abcdefgh|gfedcb` * `wrap` - repeat/wrap the image:
`cdefgh|abcdefgh|abcdef`
:param replace_invalid: This parameter specifies the value to replace non-numerical or infinite
numerical values with. By default, those values are replaced with zeroes.
:return: A data cube with the newly computed values and the same dimensions. The dimension properties
(name, type, labels, reference system and resolution) remain unchanged.
"""
return apply_kernel(data=self, kernel=kernel, factor=factor, border=border, replace_invalid=replace_invalid)
def apply_neighborhood(self, process, size, overlap=UNSET, context=UNSET) -> 'ProcessBuilder':
"""
Apply a process to pixels in a n-dimensional neighborhood
:param self: A data cube.
:param process: Process to be applied on all neighborhoods.
:param size: Neighborhood sizes along each dimension. This object maps dimension names to either a
physical measure (e.g. 100 m, 10 days) or pixels (e.g. 32 pixels). For dimensions not specified, the
default is to provide all values. Be aware that including all values from overly large dimensions may
not be processed at once.
:param overlap: Overlap of neighborhoods along each dimension to avoid border effects. For instance a
temporal dimension can add 1 month before and after a neighborhood. In the spatial dimensions, this is
often a number of pixels. The overlap specified is added before and after, so an overlap of 8 pixels
will add 8 pixels on both sides of the window, so 16 in total. Be aware that large overlaps increase
the need for computational resources and modifying overlapping data in subsequent operations have no
effect.
:param context: Additional data to be passed to the process.
:return: A data cube with the newly computed values and the same dimensions. The dimension properties
(name, type, labels, reference system and resolution) remain unchanged.
"""
return apply_neighborhood(data=self, process=process, size=size, overlap=overlap, context=context)
def arccos(self) -> 'ProcessBuilder':
"""
Inverse cosine
:param self: A number.
:return: The computed angle in radians.
"""
return arccos(x=self)
def arcosh(self) -> 'ProcessBuilder':
"""
Inverse hyperbolic cosine
:param self: A number.
:return: The computed angle in radians.
"""
return arcosh(x=self)
def arcsin(self) -> 'ProcessBuilder':
"""
Inverse sine
:param self: A number.
:return: The computed angle in radians.
"""
return arcsin(x=self)
def arctan(self) -> 'ProcessBuilder':
"""
Inverse tangent
:param self: A number.
:return: The computed angle in radians.
"""
return arctan(x=self)
def arctan2(self, x) -> 'ProcessBuilder':
"""
Inverse tangent of two numbers
:param self: A number to be used as the dividend.
:param x: A number to be used as the divisor.
:return: The computed angle in radians.
"""
return arctan2(y=self, x=x)
def ard_normalized_radar_backscatter(self, elevation_model=UNSET, contributing_area=UNSET, ellipsoid_incidence_angle=UNSET, noise_removal=UNSET) -> 'ProcessBuilder':
"""
CARD4L compliant SAR NRB generation
:param self: The source data cube containing SAR input.
:param elevation_model: The digital elevation model to use. Set to `null` (the default) to allow the
back-end to choose, which will improve portability, but reduce reproducibility.
:param contributing_area: If set to `true`, a DEM-based local contributing area band named
`contributing_area` is added. The values are given in square meters.
:param ellipsoid_incidence_angle: If set to `true`, an ellipsoidal incidence angle band named
`ellipsoid_incidence_angle` is added. The values are given in degrees.
:param noise_removal: If set to `false`, no noise removal is applied. Defaults to `true`, which removes
noise.
:return: Backscatter values expressed as gamma0 in linear scale. In addition to the bands
`contributing_area` and `ellipsoid_incidence_angle` that can optionally be added with corresponding
parameters, the following bands are always added to the data cube: - `mask`: A data mask that
indicates which values are valid (1), invalid (0) or contain no-data (null). - `local_incidence_angle`:
A band with DEM-based local incidence angles in degrees. The data returned is CARD4L compliant with
corresponding metadata.
"""
return ard_normalized_radar_backscatter(data=self, elevation_model=elevation_model, contributing_area=contributing_area, ellipsoid_incidence_angle=ellipsoid_incidence_angle, noise_removal=noise_removal)
def ard_surface_reflectance(self, atmospheric_correction_method, cloud_detection_method, elevation_model=UNSET, atmospheric_correction_options=UNSET, cloud_detection_options=UNSET) -> 'ProcessBuilder':
"""
CARD4L compliant Surface Reflectance generation
:param self: The source data cube containing multi-spectral optical top of the atmosphere (TOA)
reflectances. There must be a single dimension of type `bands` available.
:param atmospheric_correction_method: The atmospheric correction method to use.
:param cloud_detection_method: The cloud detection method to use. Each method supports detecting
different atmospheric disturbances such as clouds, cloud shadows, aerosols, haze, ozone and/or water
vapour in optical imagery.
:param elevation_model: The digital elevation model to use. Set to `null` (the default) to allow the
back-end to choose, which will improve portability, but reduce reproducibility.
:param atmospheric_correction_options: Proprietary options for the atmospheric correction method.
Specifying proprietary options will reduce portability.
:param cloud_detection_options: Proprietary options for the cloud detection method. Specifying
proprietary options will reduce portability.
:return: Data cube containing bottom of atmosphere reflectances for each spectral band in the source
data cube, with atmospheric disturbances like clouds and cloud shadows removed. No-data values (null)
are directly set in the bands. Depending on the methods used, several additional bands will be added to
the data cube: Data cube containing bottom of atmosphere reflectances for each spectral band in the
source data cube, with atmospheric disturbances like clouds and cloud shadows removed. Depending on the
methods used, several additional bands will be added to the data cube: - `date` (optional): Specifies
per-pixel acquisition timestamps. - `incomplete-testing` (required): Identifies pixels with a value of
1 for which the per-pixel tests (at least saturation, cloud and cloud shadows, see CARD4L specification
for details) have not all been successfully completed. Otherwise, the value is 0. - `saturation`
(required) / `saturation_{band}` (optional): Indicates where pixels in the input spectral bands are
saturated (1) or not (0). If the saturation is given per band, the band names are `saturation_{band}`
with `{band}` being the band name from the source data cube. - `cloud`, `shadow` (both
required),`aerosol`, `haze`, `ozone`, `water_vapor` (all optional): Indicates the probability of pixels
being an atmospheric disturbance such as clouds. All bands have values between 0 (clear) and 1, which
describes the probability that it is an atmospheric disturbance. - `snow-ice` (optional): Points to a
file that indicates whether a pixel is assessed as being snow/ice (1) or not (0). All values describe
the probability and must be between 0 and 1. - `land-water` (optional): Indicates whether a pixel is
assessed as being land (1) or water (0). All values describe the probability and must be between 0 and
1. - `incidence-angle` (optional): Specifies per-pixel incidence angles in degrees. - `azimuth`
(optional): Specifies per-pixel azimuth angles in degrees. - `sun-azimuth:` (optional): Specifies per-
pixel sun azimuth angles in degrees. - `sun-elevation` (optional): Specifies per-pixel sun elevation
angles in degrees. - `terrain-shadow` (optional): Indicates with a value of 1 whether a pixel is not
directly illuminated due to terrain shadowing. Otherwise, the value is 0. - `terrain-occlusion`
(optional): Indicates with a value of 1 whether a pixel is not visible to the sensor due to terrain
occlusion during off-nadir viewing. Otherwise, the value is 0. - `terrain-illumination` (optional):
Contains coefficients used for terrain illumination correction are provided for each pixel. The data
returned is CARD4L compliant with corresponding metadata.
"""
return ard_surface_reflectance(data=self, atmospheric_correction_method=atmospheric_correction_method, cloud_detection_method=cloud_detection_method, elevation_model=elevation_model, atmospheric_correction_options=atmospheric_correction_options, cloud_detection_options=cloud_detection_options)
def array_append(self, value) -> 'ProcessBuilder':
"""
Append a value to an array
:param self: An array.
:param value: Value to append to the array.
:return: The new array with the value being appended.
"""
return array_append(data=self, value=value)
def array_apply(self, process, context=UNSET) -> 'ProcessBuilder':
"""
Apply a process to each array element
:param self: An array.
:param process: A process that accepts and returns a single value and is applied on each individual
value in the array. The process may consist of multiple sub-processes and could, for example, consist
of processes such as ``abs()`` or ``linear_scale_range()``.
:param context: Additional data to be passed to the process.
:return: An array with the newly computed values. The number of elements are the same as for the
original array.
"""
return array_apply(data=self, process=process, context=context)
def array_concat(self, array2) -> 'ProcessBuilder':
"""
Merge two arrays
:param self: The first array.
:param array2: The second array.
:return: The merged array.
"""
return array_concat(array1=self, array2=array2)
def array_contains(self, value) -> 'ProcessBuilder':
"""
Check whether the array contains a given value
:param self: List to find the value in.
:param value: Value to find in `data`.
:return: `true` if the list contains the value, false` otherwise.
"""
return array_contains(data=self, value=value)
def array_create(self=UNSET, repeat=UNSET) -> 'ProcessBuilder':
"""
Create an array
:param self: A (native) array to fill the newly created array with. Defaults to an empty array.
:param repeat: The number of times the (native) array specified in `data` is repeatedly added after
each other to the new array being created. Defaults to `1`.
:return: The newly created array.
"""
return array_create(data=self, repeat=repeat)
def array_create_labeled(self, labels) -> 'ProcessBuilder':
"""
Create a labeled array
:param self: An array of values to be used.
:param labels: An array of labels to be used.
:return: The newly created labeled array.
"""
return array_create_labeled(data=self, labels=labels)
def array_element(self, index=UNSET, label=UNSET, return_nodata=UNSET) -> 'ProcessBuilder':
"""
Get an element from an array
:param self: An array.
:param index: The zero-based index of the element to retrieve.
:param label: The label of the element to retrieve. Throws an `ArrayNotLabeled` exception, if the given
array is not a labeled array and this parameter is set.
:param return_nodata: By default this process throws an `ArrayElementNotAvailable` exception if the
index or label is invalid. If you want to return `null` instead, set this flag to `true`.
:return: The value of the requested element.
"""
return array_element(data=self, index=index, label=label, return_nodata=return_nodata)
def array_filter(self, condition, context=UNSET) -> 'ProcessBuilder':
"""
Filter an array based on a condition
:param self: An array.
:param condition: A condition that is evaluated against each value, index and/or label in the array.
Only the array elements for which the condition returns `true` are preserved.
:param context: Additional data to be passed to the condition.
:return: An array filtered by the specified condition. The number of elements are less than or equal
compared to the original array.
"""
return array_filter(data=self, condition=condition, context=context)
def array_find(self, value) -> 'ProcessBuilder':
"""
Get the index for a value in an array
:param self: List to find the value in.
:param value: Value to find in `data`.
:return: The index of the first element with the specified value. If no element was found, `null` is
returned.
"""
return array_find(data=self, value=value)
def array_find_label(self, label) -> 'ProcessBuilder':
"""
Get the index for a label in a labeled array
:param self: List to find the label in.
:param label: Label to find in `data`.
:return: The index of the element with the specified label assigned. If no such label was found, `null`
is returned.
"""
return array_find_label(data=self, label=label)
def array_interpolate_linear(self) -> 'ProcessBuilder':
"""
One-dimensional linear interpolation for arrays
:param self: An array of numbers and no-data values. If the given array is a labeled array, the labels
must have a natural/inherent label order and the process expects the labels to be sorted accordingly.
This is the default behavior in openEO for spatial and temporal dimensions.
:return: An array with no-data values being replaced with interpolated values. If not at least 2
numerical values are available in the array, the array stays the same.
"""
return array_interpolate_linear(data=self)
def array_labels(self) -> 'ProcessBuilder':
"""
Get the labels for an array
:param self: An array with labels.
:return: The labels as an array.
"""
return array_labels(data=self)
def array_modify(self, values, index, length=UNSET) -> 'ProcessBuilder':
"""
Change the content of an array (insert, remove, update)
:param self: An array.
:param values: The values to fill the array with.
:param index: The index of the element to insert the value(s) before. If the index is greater than the
number of elements, the process throws an `ArrayElementNotAvailable` exception. To insert after the
last element, there are two options: 1. Use the simpler processes ``array_append()`` to append a
single value or ``array_concat`` to append multiple values. 2. Specify the number of elements in the
array. You can retrieve the number of elements with the process ``count()``, having the parameter
`condition` set to `true`.
:param length: The number of elements to replace. This parameter has no effect in case the given
`index` does not exist in the array given.
:return: An array with values added, updated or removed.
"""
return array_modify(data=self, values=values, index=index, length=length)
def arsinh(self) -> 'ProcessBuilder':
"""
Inverse hyperbolic sine
:param self: A number.
:return: The computed angle in radians.
"""
return arsinh(x=self)
def artanh(self) -> 'ProcessBuilder':
"""
Inverse hyperbolic tangent
:param self: A number.
:return: The computed angle in radians.
"""
return artanh(x=self)
def atmospheric_correction(self, method, elevation_model=UNSET, options=UNSET) -> 'ProcessBuilder':
"""
Apply atmospheric correction
:param self: Data cube containing multi-spectral optical top of atmosphere reflectances to be
corrected.
:param method: The atmospheric correction method to use. To get reproducible results, you have to set a
specific method. Set to `null` to allow the back-end to choose, which will improve portability, but
reduce reproducibility as you *may* get different results if you run the processes multiple times.
:param elevation_model: The digital elevation model to use. Set to `null` (the default) to allow the
back-end to choose, which will improve portability, but reduce reproducibility.
:param options: Proprietary options for the atmospheric correction method. Specifying proprietary
options will reduce portability.
:return: Data cube containing bottom of atmosphere reflectances.
"""
return atmospheric_correction(data=self, method=method, elevation_model=elevation_model, options=options)
def between(self, min, max, exclude_max=UNSET) -> 'ProcessBuilder':
"""
Between comparison
:param self: The value to check.
:param min: Lower boundary (inclusive) to check against.
:param max: Upper boundary (inclusive) to check against.
:param exclude_max: Exclude the upper boundary `max` if set to `true`. Defaults to `false`.
:return: `true` if `x` is between the specified bounds, otherwise `false`.
"""
return between(x=self, min=min, max=max, exclude_max=exclude_max)
def ceil(self) -> 'ProcessBuilder':
"""
Round fractions up
:param self: A number to round up.
:return: The number rounded up.
"""
return ceil(x=self)
def climatological_normal(self, period, climatology_period=UNSET) -> 'ProcessBuilder':
"""
Compute climatology normals
:param self: A data cube with exactly one temporal dimension. The data cube must span at least the
temporal interval specified in the parameter `climatology-period`. Seasonal periods may span two
consecutive years, e.g. temporal winter that includes months December, January and February. If the
required months before the actual climate period are available, the season is taken into account. If
not available, the first season is not taken into account and the seasonal mean is based on one year
less than the other seasonal normals. The incomplete season at the end of the last year is never taken
into account.
:param period: The time intervals to aggregate the average value for. The following pre-defined
frequencies are supported: * `day`: Day of the year * `month`: Month of the year * `climatology-
period`: The period specified in the `climatology-period`. * `season`: Three month periods of the
calendar seasons (December - February, March - May, June - August, September - November). * `tropical-
season`: Six month periods of the tropical seasons (November - April, May - October).
:param climatology_period: The climatology period as a closed temporal interval. The first element of
the array is the first year to be fully included in the temporal interval. The second element is the
last year to be fully included in the temporal interval. The default period is from 1981 until 2010
(both inclusive).
:return: A data cube with the same dimensions. The dimension properties (name, type, labels, reference
system and resolution) remain unchanged, except for the resolution and dimension labels of the temporal
dimension. The temporal dimension has the following dimension labels: * `day`: `001` - `365` *
`month`: `01` - `12` * `climatology-period`: `climatology-period` * `season`: `djf` (December -
February), `mam` (March - May), `jja` (June - August), `son` (September - November) * `tropical-
season`: `ndjfma` (November - April), `mjjaso` (May - October)
"""
return climatological_normal(data=self, period=period, climatology_period=climatology_period)
def clip(self, min, max) -> 'ProcessBuilder':
"""
Clip a value between a minimum and a maximum
:param self: A number.
:param min: Minimum value. If the value is lower than this value, the process will return the value of
this parameter.
:param max: Maximum value. If the value is greater than this value, the process will return the value
of this parameter.
:return: The value clipped to the specified range.
"""
return clip(x=self, min=min, max=max)
def cloud_detection(self, method, options=UNSET) -> 'ProcessBuilder':
"""
Create cloud masks
:param self: The source data cube containing multi-spectral optical top of the atmosphere (TOA)
reflectances on which to perform cloud detection.
:param method: The cloud detection method to use. To get reproducible results, you have to set a
specific method. Set to `null` to allow the back-end to choose, which will improve portability, but
reduce reproducibility as you *may* get different results if you run the processes multiple times.
:param options: Proprietary options for the cloud detection method. Specifying proprietary options will
reduce portability.
:return: A data cube with bands for the atmospheric disturbances. Each of the masks contains values
between 0 and 1. The data cube has the same spatial and temporal dimensions as the source data cube and
a dimension that contains a dimension label for each of the supported/considered atmospheric
disturbance.
"""
return cloud_detection(data=self, method=method, options=options)
def constant(self) -> 'ProcessBuilder':
"""
Define a constant value
:param self: The value of the constant.
:return: The value of the constant.
"""
return constant(x=self)
def cos(self) -> 'ProcessBuilder':
"""
Cosine
:param self: An angle in radians.
:return: The computed cosine of `x`.
"""
return cos(x=self)
def cosh(self) -> 'ProcessBuilder':
"""
Hyperbolic cosine
:param self: An angle in radians.
:return: The computed hyperbolic cosine of `x`.
"""
return cosh(x=self)
def count(self, condition=UNSET, context=UNSET) -> 'ProcessBuilder':
"""
Count the number of elements
:param self: An array with elements of any data type.
:param condition: A condition consists of one or more processes, which in the end return a boolean
value. It is evaluated against each element in the array. An element is counted only if the condition
returns `true`. Defaults to count valid elements in a list (see ``is_valid()``). Setting this parameter
to boolean `true` counts all elements in the list.
:param context: Additional data to be passed to the condition.
:return: The counted number of elements.
"""
return count(data=self, condition=condition, context=context)
def create_raster_cube(self) -> 'ProcessBuilder':
"""
Create an empty raster data cube
:return: An empty raster data cube with zero dimensions.
"""
return create_raster_cube()
def cummax(self, ignore_nodata=UNSET) -> 'ProcessBuilder':
"""
Cumulative maxima
:param self: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default.
Setting this flag to `false` considers no-data values so that `null` is set for all the following
elements.
:return: An array with the computed cumulative maxima.
"""
return cummax(data=self, ignore_nodata=ignore_nodata)
def cummax(self, ignore_nodata=UNSET) -> 'ProcessBuilder':
"""
Cumulative maxima
:param self: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default.
Setting this flag to `false` considers no-data values so that `null` is set for all the following
elements.
:return: An array with the computed cumulative maxima.
"""
return cummax(data=self, ignore_nodata=ignore_nodata)
def cummin(self, ignore_nodata=UNSET) -> 'ProcessBuilder':
"""
Cumulative minima
:param self: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default.
Setting this flag to `false` considers no-data values so that `null` is set for all the following
elements.
:return: An array with the computed cumulative minima.
"""
return cummin(data=self, ignore_nodata=ignore_nodata)
def cummin(self, ignore_nodata=UNSET) -> 'ProcessBuilder':
"""
Cumulative minima
:param self: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default.
Setting this flag to `false` considers no-data values so that `null` is set for all the following
elements.
:return: An array with the computed cumulative minima.
"""
return cummin(data=self, ignore_nodata=ignore_nodata)
def cumproduct(self, ignore_nodata=UNSET) -> 'ProcessBuilder':
"""
Cumulative products
:param self: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default.
Setting this flag to `false` considers no-data values so that `null` is set for all the following
elements.
:return: An array with the computed cumulative products.
"""
return cumproduct(data=self, ignore_nodata=ignore_nodata)
def cumproduct(self, ignore_nodata=UNSET) -> 'ProcessBuilder':
"""
Cumulative products
:param self: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default.
Setting this flag to `false` considers no-data values so that `null` is set for all the following
elements.
:return: An array with the computed cumulative products.
"""
return cumproduct(data=self, ignore_nodata=ignore_nodata)
def cumsum(self, ignore_nodata=UNSET) -> 'ProcessBuilder':
"""
Cumulative sums
:param self: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default.
Setting this flag to `false` considers no-data values so that `null` is set for all the following
elements.
:return: An array with the computed cumulative sums.
"""
return cumsum(data=self, ignore_nodata=ignore_nodata)
def cumsum(self, ignore_nodata=UNSET) -> 'ProcessBuilder':
"""
Cumulative sums
:param self: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default.
Setting this flag to `false` considers no-data values so that `null` is set for all the following
elements.
:return: An array with the computed cumulative sums.
"""
return cumsum(data=self, ignore_nodata=ignore_nodata)
def date_shift(self, value, unit) -> 'ProcessBuilder':
"""
Manipulates dates and times by addition or subtraction
:param self: The date (and optionally time) to manipulate. If the given date doesn't include the time,
the process assumes that the time component is `00:00:00Z` (i.e. midnight, in UTC). The millisecond
part of the time is optional and defaults to `0` if not given.
:param value: The period of time in the unit given that is added (positive numbers) or subtracted
(negative numbers). The value `0` doesn't have any effect.
:param unit: The unit for the value given. The following pre-defined units are available: -
millisecond: Milliseconds - second: Seconds - leap seconds are ignored in computations. - minute:
Minutes - hour: Hours - day: Days - changes only the the day part of a date - week: Weeks (equivalent
to 7 days) - month: Months - year: Years Manipulations with the unit `year`, `month`, `week` or `day`
do never change the time. If any of the manipulations result in an invalid date or time, the
corresponding part is rounded down to the next valid date or time respectively. For example, adding a
month to `2020-01-31` would result in `2020-02-29`.
:return: The manipulated date. If a time component was given in the parameter `date`, the time
component is returned with the date.
"""
return date_shift(date=self, value=value, unit=unit)
def debug(self, code=UNSET, level=UNSET, message=UNSET) -> 'ProcessBuilder':
"""
Publish debugging information
:param self: Data to publish.
:param code: An identifier to help identify the log entry in a bunch of other log entries.
:param level: The severity level of this message, defaults to `info`. Note that the level `error`
forces the computation to be stopped!
:param message: A message to send in addition to the data.
:return: Returns the data as passed to the `data` parameter.
"""
return debug(data=self, code=code, level=level, message=message)
def debug(self, code=UNSET, level=UNSET, message=UNSET) -> 'ProcessBuilder':
"""
Publish debugging information
:param self: Data to publish.
:param code: An identifier to help identify the log entry in a bunch of other log entries.
:param level: The severity level of this message, defaults to `info`. Note that the level `error`
forces the computation to be stopped!
:param message: A message to send in addition to the data.
:return: The data as passed to the `data` parameter without any modification.
"""
return debug(data=self, code=code, level=level, message=message)
def dimension_labels(self, dimension) -> 'ProcessBuilder':
"""
Get the dimension labels
:param self: The data cube.
:param dimension: The name of the dimension to get the labels for.
:return: The labels as an array.
"""
return dimension_labels(data=self, dimension=dimension)
def divide(self, y) -> 'ProcessBuilder':
"""
Division of two numbers
:param self: The dividend.
:param y: The divisor.
:return: The computed result.
"""
return divide(x=self, y=y)
def drop_dimension(self, name) -> 'ProcessBuilder':
"""
Remove a dimension
:param self: The data cube to drop a dimension from.
:param name: Name of the dimension to drop.
:return: A data cube without the specified dimension. The number of dimensions decreases by one, but
the dimension properties (name, type, labels, reference system and resolution) for all other dimensions
remain unchanged.
"""
return drop_dimension(data=self, name=name)
def e(self) -> 'ProcessBuilder':
"""
Euler's number (e)
:return: The numerical value of Euler's number.
"""
return e()
def eq(self, y, delta=UNSET, case_sensitive=UNSET) -> 'ProcessBuilder':
"""
Equal to comparison
:param self: First operand.
:param y: Second operand.
:param delta: Only applicable for comparing two numbers. If this optional parameter is set to a
positive non-zero number the equality of two numbers is checked against a delta value. This is
especially useful to circumvent problems with floating-point inaccuracy in machine-based computation.
This option is basically an alias for the following computation: `lte(abs(minus([x, y]), delta)`
:param case_sensitive: Only applicable for comparing two strings. Case sensitive comparison can be
disabled by setting this parameter to `false`.
:return: `true` if `x` is equal to `y`, `null` if any operand is `null`, otherwise `false`.
"""
return eq(x=self, y=y, delta=delta, case_sensitive=case_sensitive)
def exp(self) -> 'ProcessBuilder':
"""
Exponentiation to the base e
:param self: The numerical exponent.
:return: The computed value for *e* raised to the power of `p`.
"""
return exp(p=self)
def extrema(self, ignore_nodata=UNSET) -> 'ProcessBuilder':
"""
Minimum and maximum values
:param self: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default.
Setting this flag to `false` considers no-data values so that an array with two `null` values is
returned if any value is such a value.
:return: An array containing the minimum and maximum values for the specified numbers. The first
element is the minimum, the second element is the maximum. If the input array is empty both elements
are set to `null`.
"""
return extrema(data=self, ignore_nodata=ignore_nodata)
def filter_bands(self, bands=UNSET, wavelengths=UNSET) -> 'ProcessBuilder':
"""
Filter the bands by names
:param self: A data cube with bands.
:param bands: A list of band names. Either the unique band name (metadata field `name` in bands) or one
of the common band names (metadata field `common_name` in bands). If the unique band name and the
common name conflict, the unique band name has a higher priority. The order of the specified array
defines the order of the bands in the data cube. If multiple bands match a common name, all matched
bands are included in the original order.
:param wavelengths: A list of sub-lists with each sub-list consisting of two elements. The first
element is the minimum wavelength and the second element is the maximum wavelength. Wavelengths are
specified in micrometers (μm). The order of the specified array defines the order of the bands in the
data cube. If multiple bands match the wavelengths, all matched bands are included in the original
order.
:return: A data cube limited to a subset of its original bands. The dimensions and dimension properties
(name, type, labels, reference system and resolution) remain unchanged, except that the dimension of
type `bands` has less (or the same) dimension labels.
"""
return filter_bands(data=self, bands=bands, wavelengths=wavelengths)
def filter_bbox(self, extent) -> 'ProcessBuilder':
"""
Spatial filter using a bounding box
:param self: A data cube.
:param extent: A bounding box, which may include a vertical axis (see `base` and `height`).
:return: A data cube restricted to the bounding box. The dimensions and dimension properties (name,
type, labels, reference system and resolution) remain unchanged, except that the spatial dimensions
have less (or the same) dimension labels.
"""
return filter_bbox(data=self, extent=extent)
def filter_labels(self, condition, dimension, context=UNSET) -> 'ProcessBuilder':
"""
Filter dimension labels based on a condition
:param self: A data cube.
:param condition: A condition that is evaluated against each dimension label in the specified
dimension. A dimension label and the corresponding data is preserved for the given dimension, if the
condition returns `true`.
:param dimension: The name of the dimension to filter on. Fails with a `DimensionNotAvailable` error if
the specified dimension does not exist.
:param context: Additional data to be passed to the condition.
:return: A data cube with the same dimensions. The dimension properties (name, type, labels, reference
system and resolution) remain unchanged, except that the given dimension has less (or the same)
dimension labels.
"""
return filter_labels(data=self, condition=condition, dimension=dimension, context=context)
def filter_labels(self, condition, dimension, context=UNSET) -> 'ProcessBuilder':
"""
Filter dimension labels based on a condition
:param self: A data cube.
:param condition: A condition that is evaluated against each dimension label in the specified
dimension. A dimension label and the corresponding data is preserved for the given dimension, if the
condition returns `true`.
:param dimension: The name of the dimension to filter on. Fails with a `DimensionNotAvailable`
exception if the specified dimension does not exist.
:param context: Additional data to be passed to the condition.
:return: A data cube with the same dimensions. The dimension properties (name, type, labels, reference
system and resolution) remain unchanged, except that the given dimension has less (or the same)
dimension labels.
"""
return filter_labels(data=self, condition=condition, dimension=dimension, context=context)
def filter_spatial(self, geometries) -> 'ProcessBuilder':
"""
Spatial filter using geometries
:param self: A data cube.
:param geometries: One or more geometries used for filtering, specified as GeoJSON.
:return: A data cube restricted to the specified geometries. The dimensions and dimension properties
(name, type, labels, reference system and resolution) remain unchanged, except that the spatial
dimensions have less (or the same) dimension labels.
"""
return filter_spatial(data=self, geometries=geometries)
def filter_temporal(self, extent, dimension=UNSET) -> 'ProcessBuilder':
"""
Temporal filter for a temporal intervals
:param self: A data cube.
:param extent: Left-closed temporal interval, i.e. an array with exactly two elements: 1. The first
element is the start of the temporal interval. The specified instance in time is **included** in the
interval. 2. The second element is the end of the temporal interval. The specified instance in time is
**excluded** from the interval. The specified temporal strings follow [RFC 3339](https://www.rfc-
editor.org/rfc/rfc3339.html). Also supports open intervals by setting one of the boundaries to `null`,
but never both.
:param dimension: The name of the temporal dimension to filter on. If no specific dimension is
specified or it is set to `null`, the filter applies to all temporal dimensions. Fails with a
`DimensionNotAvailable` exception if the specified dimension does not exist.
:return: A data cube restricted to the specified temporal extent. The dimensions and dimension
properties (name, type, labels, reference system and resolution) remain unchanged, except that the
temporal dimensions (determined by `dimensions` parameter) may have less dimension labels.
"""
return filter_temporal(data=self, extent=extent, dimension=dimension)
def first(self, ignore_nodata=UNSET) -> 'ProcessBuilder':
"""
First element
:param self: An array with elements of any data type.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default.
Setting this flag to `false` considers no-data values so that `null` is returned if the first value is
such a value.
:return: The first element of the input array.
"""
return first(data=self, ignore_nodata=ignore_nodata)
def floor(self) -> 'ProcessBuilder':
"""
Round fractions down
:param self: A number to round down.
:return: The number rounded down.
"""
return floor(x=self)
def gt(self, y) -> 'ProcessBuilder':
"""
Greater than comparison
:param self: First operand.
:param y: Second operand.
:return: `true` if `x` is strictly greater than `y` or `null` if any operand is `null`, otherwise
`false`.
"""
return gt(x=self, y=y)
def gte(self, y) -> 'ProcessBuilder':
"""
Greater than or equal to comparison
:param self: First operand.
:param y: Second operand.
:return: `true` if `x` is greater than or equal to `y`, `null` if any operand is `null`, otherwise
`false`.
"""
return gte(x=self, y=y)
def if_(self, accept, reject=UNSET) -> 'ProcessBuilder':
"""
If-Then-Else conditional
:param self: A boolean value.
:param accept: A value that is returned if the boolean value is `true`.
:param reject: A value that is returned if the boolean value is **not** `true`. Defaults to `null`.
:return: Either the `accept` or `reject` argument depending on the given boolean value.
"""
return if_(value=self, accept=accept, reject=reject)
def int(self) -> 'ProcessBuilder':
"""
Integer part of a number
:param self: A number.
:return: Integer part of the number.
"""
return int(x=self)
def is_infinite(self) -> 'ProcessBuilder':
"""
Value is an infinite number
:param self: The data to check.
:return: `true` if the data is an infinite number, otherwise `false`.
"""
return is_infinite(x=self)
def is_nan(self) -> 'ProcessBuilder':
"""
Value is not a number
:param self: The data to check.
:return: `true` if the data is not a number, otherwise `false`.
"""
return is_nan(x=self)
def is_nodata(self) -> 'ProcessBuilder':
"""
Value is not a no-data value
:param self: The data to check.
:return: `true` if the data is a no-data value, otherwise `false`.
"""
return is_nodata(x=self)
def is_valid(self) -> 'ProcessBuilder':
"""
Value is valid data
:param self: The data to check.
:return: `true` if the data is valid, otherwise `false`.
"""
return is_valid(x=self)
def last(self, ignore_nodata=UNSET) -> 'ProcessBuilder':
"""
Last element
:param self: An array with elements of any data type.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default.
Setting this flag to `false` considers no-data values so that `null` is returned if the last value is
such a value.
:return: The last element of the input array.
"""
return last(data=self, ignore_nodata=ignore_nodata)
def linear_scale_range(self, inputMin, inputMax, outputMin=UNSET, outputMax=UNSET) -> 'ProcessBuilder':
"""
Linear transformation between two ranges
:param self: A number to transform. The number gets clipped to the bounds specified in `inputMin` and
`inputMax`.
:param inputMin: Minimum value the input can obtain.
:param inputMax: Maximum value the input can obtain.
:param outputMin: Minimum value of the desired output range.
:param outputMax: Maximum value of the desired output range.
:return: The transformed number.
"""
return linear_scale_range(x=self, inputMin=inputMin, inputMax=inputMax, outputMin=outputMin, outputMax=outputMax)
def ln(self) -> 'ProcessBuilder':
"""
Natural logarithm
:param self: A number to compute the natural logarithm for.
:return: The computed natural logarithm.
"""
return ln(x=self)
def load_collection(self, spatial_extent, temporal_extent, bands=UNSET, properties=UNSET) -> 'ProcessBuilder':
"""
Load a collection
:param self: The collection id.
:param spatial_extent: Limits the data to load from the collection to the specified bounding box or
polygons. The process puts a pixel into the data cube if the point at the pixel center intersects with
the bounding box or any of the polygons (as defined in the Simple Features standard by the OGC). The
GeoJSON can be one of the following feature types: * A `Polygon` or `MultiPolygon` geometry, * a
`Feature` with a `Polygon` or `MultiPolygon` geometry, * a `FeatureCollection` containing at least one
`Feature` with `Polygon` or `MultiPolygon` geometries, or * a `GeometryCollection` containing `Polygon`
or `MultiPolygon` geometries. To maximize interoperability, `GeometryCollection` should be avoided in
favour of one of the alternatives above. Set this parameter to `null` to set no limit for the spatial
extent. Be careful with this when loading large datasets! It is recommended to use this parameter
instead of using ``filter_bbox()`` or ``filter_spatial()`` directly after loading unbounded data.
:param temporal_extent: Limits the data to load from the collection to the specified left-closed
temporal interval. Applies to all temporal dimensions. The interval has to be specified as an array
with exactly two elements: 1. The first element is the start of the temporal interval. The specified
instance in time is **included** in the interval. 2. The second element is the end of the temporal
interval. The specified instance in time is **excluded** from the interval. The specified temporal
strings follow [RFC 3339](https://www.rfc-editor.org/rfc/rfc3339.html). Also supports open intervals by
setting one of the boundaries to `null`, but never both. Set this parameter to `null` to set no limit
for the temporal extent. Be careful with this when loading large datasets! It is recommended to use
this parameter instead of using ``filter_temporal()`` directly after loading unbounded data.
:param bands: Only adds the specified bands into the data cube so that bands that don't match the list
of band names are not available. Applies to all dimensions of type `bands`. Either the unique band
name (metadata field `name` in bands) or one of the common band names (metadata field `common_name` in
bands) can be specified. If the unique band name and the common name conflict, the unique band name has
a higher priority. The order of the specified array defines the order of the bands in the data cube.
If multiple bands match a common name, all matched bands are included in the original order. It is
recommended to use this parameter instead of using ``filter_bands()`` directly after loading unbounded
data.
:param properties: Limits the data by metadata properties to include only data in the data cube which
all given conditions return `true` for (AND operation). Specify key-value-pairs with the key being the
name of the metadata property, which can be retrieved with the openEO Data Discovery for Collections.
The value must a condition (user-defined process) to be evaluated against the collection metadata, see
the example.
:return: A data cube for further processing. The dimensions and dimension properties (name, type,
labels, reference system and resolution) correspond to the collection's metadata, but the dimension
labels are restricted as specified in the parameters.
"""
return load_collection(id=self, spatial_extent=spatial_extent, temporal_extent=temporal_extent, bands=bands, properties=properties)
def load_result(self) -> 'ProcessBuilder':
"""
Load batch job results
:param self: The id of a batch job with results.
:return: A data cube for further processing.
"""
return load_result(id=self)
def load_result(self) -> 'ProcessBuilder':
"""
Load batch job results
:param self: The id of a batch job with results.
:return: A data cube for further processing.
"""
return load_result(id=self)
def load_uploaded_files(self, format, options=UNSET) -> 'ProcessBuilder':
"""
Load files from the user workspace
:param self: The files to read. Folders can't be specified, instead specify all files. An error is
thrown if a file can't be read.
:param format: The file format to read from. It must be one of the values that the server reports as
supported input file formats, which usually correspond to the short GDAL/OGR codes. If the format is
not suitable for loading the data, a `FormatUnsuitable` exception will be thrown. This parameter is
*case insensitive*.
:param options: The file format parameters to be used to read the files. Must correspond to the
parameters that the server reports as supported parameters for the chosen `format`. The parameter names
and valid values usually correspond to the GDAL/OGR format options.
:return: A data cube for further processing.
"""
return load_uploaded_files(paths=self, format=format, options=options)
def load_uploaded_files(self, format, options=UNSET) -> 'ProcessBuilder':
"""
Load files from the user workspace
:param self: The files to read. Folders can't be specified, specify all files instead. An exception is
thrown if a file can't be read.
:param format: The file format to read from. It must be one of the values that the server reports as
supported input file formats, which usually correspond to the short GDAL/OGR codes. If the format is
not suitable for loading the data, a `FormatUnsuitable` exception will be thrown. This parameter is
*case insensitive*.
:param options: The file format parameters to be used to read the files. Must correspond to the
parameters that the server reports as supported parameters for the chosen `format`. The parameter names
and valid values usually correspond to the GDAL/OGR format options.
:return: A data cube for further processing.
"""
return load_uploaded_files(paths=self, format=format, options=options)
def log(self, base) -> 'ProcessBuilder':
"""
Logarithm to a base
:param self: A number to compute the logarithm for.
:param base: The numerical base.
:return: The computed logarithm.
"""
return log(x=self, base=base)
def lt(self, y) -> 'ProcessBuilder':
"""
Less than comparison
:param self: First operand.
:param y: Second operand.
:return: `true` if `x` is strictly less than `y`, `null` if any operand is `null`, otherwise `false`.
"""
return lt(x=self, y=y)
def lte(self, y) -> 'ProcessBuilder':
"""
Less than or equal to comparison
:param self: First operand.
:param y: Second operand.
:return: `true` if `x` is less than or equal to `y`, `null` if any operand is `null`, otherwise
`false`.
"""
return lte(x=self, y=y)
def mask(self, mask, replacement=UNSET) -> 'ProcessBuilder':
"""
Apply a raster mask
:param self: A raster data cube.
:param mask: A mask as a raster data cube. Every pixel in `data` must have a corresponding element in
`mask`.
:param replacement: The value used to replace masked values with.
:return: A masked raster data cube with the same dimensions. The dimension properties (name, type,
labels, reference system and resolution) remain unchanged.
"""
return mask(data=self, mask=mask, replacement=replacement)
def mask_polygon(self, mask, replacement=UNSET, inside=UNSET) -> 'ProcessBuilder':
"""
Apply a polygon mask
:param self: A raster data cube.
:param mask: A GeoJSON object containing at least one polygon. The provided feature types can be one of
the following: * A `Polygon` or `MultiPolygon` geometry, * a `Feature` with a `Polygon` or
`MultiPolygon` geometry, * a `FeatureCollection` containing at least one `Feature` with `Polygon` or
`MultiPolygon` geometries, or * a `GeometryCollection` containing `Polygon` or `MultiPolygon`
geometries. To maximize interoperability, `GeometryCollection` should be avoided in favour of one of
the alternatives above.
:param replacement: The value used to replace masked values with.
:param inside: If set to `true` all pixels for which the point at the pixel center **does** intersect
with any polygon are replaced.
:return: A masked raster data cube with the same dimensions. The dimension properties (name, type,
labels, reference system and resolution) remain unchanged.
"""
return mask_polygon(data=self, mask=mask, replacement=replacement, inside=inside)
def max(self, ignore_nodata=UNSET) -> 'ProcessBuilder':
"""
Maximum value
:param self: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default.
Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a
value.
:return: The maximum value.
"""
return max(data=self, ignore_nodata=ignore_nodata)
def mean(self, ignore_nodata=UNSET) -> 'ProcessBuilder':
"""
Arithmetic mean (average)
:param self: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default.
Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a
value.
:return: The computed arithmetic mean.
"""
return mean(data=self, ignore_nodata=ignore_nodata)
def median(self, ignore_nodata=UNSET) -> 'ProcessBuilder':
"""
Statistical median
:param self: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default.
Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a
value.
:return: The computed statistical median.
"""
return median(data=self, ignore_nodata=ignore_nodata)
def merge_cubes(self, cube2, overlap_resolver=UNSET, context=UNSET) -> 'ProcessBuilder':
"""
Merge two data cubes
:param self: The first data cube.
:param cube2: The second data cube.
:param overlap_resolver: A reduction operator that resolves the conflict if the data overlaps. The
reducer must return a value of the same data type as the input values are. The reduction operator may
be a single process such as ``multiply()`` or consist of multiple sub-processes. `null` (the default)
can be specified if no overlap resolver is required.
:param context: Additional data to be passed to the overlap resolver.
:return: The merged data cube. See the process description for details regarding the dimensions and
dimension properties (name, type, labels, reference system and resolution).
"""
return merge_cubes(cube1=self, cube2=cube2, overlap_resolver=overlap_resolver, context=context)
def min(self, ignore_nodata=UNSET) -> 'ProcessBuilder':
"""
Minimum value
:param self: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default.
Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a
value.
:return: The minimum value.
"""
return min(data=self, ignore_nodata=ignore_nodata)
def mod(self, y) -> 'ProcessBuilder':
"""
Modulo
:param self: A number to be used as the dividend.
:param y: A number to be used as the divisor.
:return: The remainder after division.
"""
return mod(x=self, y=y)
def multiply(self, y) -> 'ProcessBuilder':
"""
Multiplication of two numbers
:param self: The multiplier.
:param y: The multiplicand.
:return: The computed product of the two numbers.
"""
return multiply(x=self, y=y)
def nan(self) -> 'ProcessBuilder':
"""
Not a Number (NaN)
:return: Returns `NaN`.
"""
return nan()
def ndvi(self, nir=UNSET, red=UNSET, target_band=UNSET) -> 'ProcessBuilder':
"""
Normalized Difference Vegetation Index
:param self: A raster data cube with two bands that have the common names `red` and `nir` assigned.
:param nir: The name of the NIR band. Defaults to the band that has the common name `nir` assigned.
Either the unique band name (metadata field `name` in bands) or one of the common band names (metadata
field `common_name` in bands) can be specified. If the unique band name and the common name conflict,
the unique band name has a higher priority.
:param red: The name of the red band. Defaults to the band that has the common name `red` assigned.
Either the unique band name (metadata field `name` in bands) or one of the common band names (metadata
field `common_name` in bands) can be specified. If the unique band name and the common name conflict,
the unique band name has a higher priority.
:param target_band: By default, the dimension of type `bands` is dropped. To keep the dimension specify
a new band name in this parameter so that a new dimension label with the specified name will be added
for the computed values.
:return: A raster data cube containing the computed NDVI values. The structure of the data cube differs
depending on the value passed to `target_band`: * `target_band` is `null`: The data cube does not
contain the dimension of type `bands`, the number of dimensions decreases by one. The dimension
properties (name, type, labels, reference system and resolution) for all other dimensions remain
unchanged. * `target_band` is a string: The data cube keeps the same dimensions. The dimension
properties remain unchanged, but the number of dimension labels for the dimension of type `bands`
increases by one. The additional label is named as specified in `target_band`.
"""
return ndvi(data=self, nir=nir, red=red, target_band=target_band)
def neq(self, y, delta=UNSET, case_sensitive=UNSET) -> 'ProcessBuilder':
"""
Not equal to comparison
:param self: First operand.
:param y: Second operand.
:param delta: Only applicable for comparing two numbers. If this optional parameter is set to a
positive non-zero number the non-equality of two numbers is checked against a delta value. This is
especially useful to circumvent problems with floating-point inaccuracy in machine-based computation.
This option is basically an alias for the following computation: `gt(abs(minus([x, y]), delta)`
:param case_sensitive: Only applicable for comparing two strings. Case sensitive comparison can be
disabled by setting this parameter to `false`.
:return: `true` if `x` is *not* equal to `y`, `null` if any operand is `null`, otherwise `false`.
"""
return neq(x=self, y=y, delta=delta, case_sensitive=case_sensitive)
def normalized_difference(self, y) -> 'ProcessBuilder':
"""
Normalized difference
:param self: The value for the first band.
:param y: The value for the second band.
:return: The computed normalized difference.
"""
return normalized_difference(x=self, y=y)
def not_(self) -> 'ProcessBuilder':
"""
Inverting a boolean
:param self: Boolean value to invert.
:return: Inverted boolean value.
"""
return not_(x=self)
def or_(self, y) -> 'ProcessBuilder':
"""
Logical OR
:param self: A boolean value.
:param y: A boolean value.
:return: Boolean result of the logical OR.
"""
return or_(x=self, y=y)
def order(self, asc=UNSET, nodata=UNSET) -> 'ProcessBuilder':
"""
Create a permutation
:param self: An array to compute the order for.
:param asc: The default sort order is ascending, with smallest values first. To sort in reverse
(descending) order, set this parameter to `false`.
:param nodata: Controls the handling of no-data values (`null`). By default, they are removed. If set
to `true`, missing values in the data are put last; if set to `false`, they are put first.
:return: The computed permutation.
"""
return order(data=self, asc=asc, nodata=nodata)
def pi(self) -> 'ProcessBuilder':
"""
Pi (π)
:return: The numerical value of Pi.
"""
return pi()
def power(self, p) -> 'ProcessBuilder':
"""
Exponentiation
:param self: The numerical base.
:param p: The numerical exponent.
:return: The computed value for `base` raised to the power of `p`.
"""
return power(base=self, p=p)
def product(self, ignore_nodata=UNSET) -> 'ProcessBuilder':
"""
Compute the product by multiplying numbers
:param self: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default.
Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a
value.
:return: The computed product of the sequence of numbers.
"""
return product(data=self, ignore_nodata=ignore_nodata)
def quantiles(self, probabilities=UNSET, q=UNSET, ignore_nodata=UNSET) -> 'ProcessBuilder':
"""
Quantiles
:param self: An array of numbers.
:param probabilities: A list of probabilities to calculate quantiles for. The probabilities must be
between 0 and 1.
:param q: Intervals to calculate quantiles for. Calculates q-quantiles with (nearly) equal-sized
intervals.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default.
Setting this flag to `false` considers no-data values so that an array with `null` values is returned
if any element is such a value.
:return: An array with the computed quantiles. The list has either * as many elements as the given
list of `probabilities` had or * *`q`-1* elements. If the input array is empty the resulting array is
filled with as many `null` values as required according to the list above. See the 'Empty array'
example for an example.
"""
return quantiles(data=self, probabilities=probabilities, q=q, ignore_nodata=ignore_nodata)
def rearrange(self, order) -> 'ProcessBuilder':
"""
Rearrange an array based on a permutation
:param self: The array to rearrange.
:param order: The permutation used for rearranging.
:return: The rearranged array.
"""
return rearrange(data=self, order=order)
def reduce_dimension(self, reducer, dimension, context=UNSET) -> 'ProcessBuilder':
"""
Reduce dimensions
:param self: A data cube.
:param reducer: A reducer to apply on the specified dimension. A reducer is a single process such as
``mean()`` or a set of processes, which computes a single value for a list of values, see the category
'reducer' for such processes.
:param dimension: The name of the dimension over which to reduce. Fails with a `DimensionNotAvailable`
exception if the specified dimension does not exist.
:param context: Additional data to be passed to the reducer.
:return: A data cube with the newly computed values. It is missing the given dimension, the number of
dimensions decreases by one. The dimension properties (name, type, labels, reference system and
resolution) for all other dimensions remain unchanged.
"""
return reduce_dimension(data=self, reducer=reducer, dimension=dimension, context=context)
def reduce_dimension_binary(self, reducer, dimension, context=UNSET) -> 'ProcessBuilder':
"""
Reduce dimensions using binary reduction
:param self: A data cube.
:param reducer: A reduction operator to be applied consecutively on pairs of values. It must be both
associative and commutative as the execution may be executed in parallel and therefore the order of
execution is arbitrary. The reduction operator may be a single process such as ``multiply()`` or
consist of multiple sub-processes.
:param dimension: The name of the dimension over which to reduce. Fails with a `DimensionNotAvailable`
error if the specified dimension does not exist.
:param context: Additional data to be passed to the reducer.
:return: A data cube with the newly computed values. It is missing the given dimension, the number of
dimensions decreases by one. The dimension properties (name, type, labels, reference system and
resolution) for all other dimensions remain unchanged.
"""
return reduce_dimension_binary(data=self, reducer=reducer, dimension=dimension, context=context)
def reduce_spatial(self, reducer, context=UNSET) -> 'ProcessBuilder':
"""
Reduce spatial dimensions 'x' and 'y'
:param self: A data cube.
:param reducer: A reducer to apply on the horizontal spatial dimensions. A reducer is a single process
such as ``mean()`` or a set of processes, which computes a single value for a list of values, see the
category 'reducer' for such processes.
:param context: Additional data to be passed to the reducer.
:return: A data cube with the newly computed values. It is missing the horizontal spatial dimensions,
the number of dimensions decreases by two. The dimension properties (name, type, labels, reference
system and resolution) for all other dimensions remain unchanged.
"""
return reduce_spatial(data=self, reducer=reducer, context=context)
def rename_dimension(self, source, target) -> 'ProcessBuilder':
"""
Rename a dimension
:param self: The data cube.
:param source: The current name of the dimension. Fails with a `DimensionNotAvailable` exception if the
specified dimension does not exist.
:param target: A new Name for the dimension. Fails with a `DimensionExists` exception if a dimension
with the specified name exists.
:return: A data cube with the same dimensions, but the name of one of the dimensions changes. The old
name can not be referred to any longer. The dimension properties (name, type, labels, reference system
and resolution) remain unchanged.
"""
return rename_dimension(data=self, source=source, target=target)
def rename_labels(self, dimension, target, source=UNSET) -> 'ProcessBuilder':
"""
Rename dimension labels
:param self: The data cube.
:param dimension: The name of the dimension to rename the labels for.
:param target: The new names for the labels. The dimension labels in the data cube are expected to be
enumerated if the parameter `target` is not specified. If a target dimension label already exists in
the data cube, a `LabelExists` exception is thrown.
:param source: The names of the labels as they are currently in the data cube. The array defines an
unsorted and potentially incomplete list of labels that should be renamed to the names available in the
corresponding array elements in the parameter `target`. If one of the source dimension labels doesn't
exist, the `LabelNotAvailable` exception is thrown. By default, the array is empty so that the
dimension labels in the data cube are expected to be enumerated.
:return: The data cube with the same dimensions. The dimension properties (name, type, labels,
reference system and resolution) remain unchanged, except that for the given dimension the labels
change. The old labels can not be referred to any longer. The number of labels remains the same.
"""
return rename_labels(data=self, dimension=dimension, target=target, source=source)
def resample_cube_spatial(self, target, method=UNSET) -> 'ProcessBuilder':
"""
Resample the spatial dimensions to match a target data cube
:param self: A data cube.
:param target: A data cube that describes the spatial target resolution.
:param method: Resampling method to use. The following options are available and are meant to align
with [`gdalwarp`](https://gdal.org/programs/gdalwarp.html#cmdoption-gdalwarp-r): * `average`: average
(mean) resampling, computes the weighted average of all valid pixels * `bilinear`: bilinear resampling
* `cubic`: cubic resampling * `cubicspline`: cubic spline resampling * `lanczos`: Lanczos windowed sinc
resampling * `max`: maximum resampling, selects the maximum value from all valid pixels * `med`: median
resampling, selects the median value of all valid pixels * `min`: minimum resampling, selects the
minimum value from all valid pixels * `mode`: mode resampling, selects the value which appears most
often of all the sampled points * `near`: nearest neighbour resampling (default) * `q1`: first quartile
resampling, selects the first quartile value of all valid pixels * `q3`: third quartile resampling,
selects the third quartile value of all valid pixels * `rms` root mean square (quadratic mean) of all
valid pixels * `sum`: compute the weighted sum of all valid pixels Valid pixels are determined based
on the function ``is_valid()``.
:return: A data cube with the same dimensions. The dimension properties (name, type, labels, reference
system and resolution) remain unchanged, except for the resolution and dimension labels of the spatial
dimensions.
"""
return resample_cube_spatial(data=self, target=target, method=method)
def resample_cube_temporal(self, target, method, dimension=UNSET, context=UNSET) -> 'ProcessBuilder':
"""
Resample a temporal dimension to match a target data cube
:param self: A data cube.
:param target: A data cube that describes the temporal target resolution.
:param method: A resampling method to be applied, could be a reducer for downsampling or other methods
for upsampling. A reducer is a single process such as ``mean()`` or a set of processes, which computes
a single value for a list of values, see the category 'reducer' for such processes.
:param dimension: The name of the temporal dimension to resample, which must exist with this name in
both data cubes. If the dimension is not set or is set to `null`, the data cube is expected to only
have one temporal dimension. Fails with a `TooManyDimensions` error if it has more dimensions. Fails
with a `DimensionNotAvailable` error if the specified dimension does not exist.
:param context: Additional data to be passed to the process specified for the parameter `method`.
:return: A raster data cube with the same dimensions and the same dimension properties (name, type,
labels, reference system and resolution) for all non-temporal dimensions. For the temporal dimension
the name and type remain unchanged, but the reference system changes and the labels and resolution may
change.
"""
return resample_cube_temporal(data=self, target=target, method=method, dimension=dimension, context=context)
def resample_cube_temporal(self, target, dimension=UNSET, valid_within=UNSET) -> 'ProcessBuilder':
"""
Resample temporal dimensions to match a target data cube
:param self: A data cube with one or more temporal dimensions.
:param target: A data cube that describes the temporal target resolution.
:param dimension: The name of the temporal dimension to resample, which must exist with this name in
both data cubes. If the dimension is not set or is set to `null`, the process resamples all temporal
dimensions that exist with the same names in both data cubes. The following exceptions may occur: * A
dimension is given, but it does not exist in any of the data cubes: `DimensionNotAvailable` * A
dimension is given, but one of them is not temporal: `DimensionMismatch` * No specific dimension name
is given and there are no temporal dimensions with the same name in the data: `DimensionMismatch`
:param valid_within: Setting this parameter to a numerical value enables that the process searches for
valid values within the given period of days before and after the target timestamps. Valid values are
determined based on the function ``is_valid()``. For example, the limit of `7` for the target
timestamps `2020-01-15 12:00:00` looks for a nearest neighbor after `2020-01-08 12:00:00` and before
`2020-01-22 12:00:00`. If no valid value is found within the given period, the value will be set to no-
data (`null`).
:return: A raster data cube with the same dimensions and the same dimension properties (name, type,
labels, reference system and resolution) for all non-temporal dimensions. For the temporal dimension,
the name and type remain unchanged, but the dimension labels, resolution and reference system may
change.
"""
return resample_cube_temporal(data=self, target=target, dimension=dimension, valid_within=valid_within)
def resample_spatial(self, resolution=UNSET, projection=UNSET, method=UNSET, align=UNSET) -> 'ProcessBuilder':
"""
Resample and warp the spatial dimensions
:param self: A raster data cube.
:param resolution: Resamples the data cube to the target resolution, which can be specified either as
separate values for x and y or as a single value for both axes. Specified in the units of the target
projection. Doesn't change the resolution by default (`0`).
:param projection: Warps the data cube to the target projection, specified as as [EPSG
code](http://www.epsg-registry.org/), [WKT2 (ISO 19162)
string](http://docs.opengeospatial.org/is/18-010r7/18-010r7.html), [PROJ definition
(deprecated)](https://proj.org/usage/quickstart.html). By default (`null`), the projection is not
changed.
:param method: Resampling method to use. The following options are available and are meant to align
with [`gdalwarp`](https://gdal.org/programs/gdalwarp.html#cmdoption-gdalwarp-r): * `average`: average
(mean) resampling, computes the weighted average of all valid pixels * `bilinear`: bilinear resampling
* `cubic`: cubic resampling * `cubicspline`: cubic spline resampling * `lanczos`: Lanczos windowed sinc
resampling * `max`: maximum resampling, selects the maximum value from all valid pixels * `med`: median
resampling, selects the median value of all valid pixels * `min`: minimum resampling, selects the
minimum value from all valid pixels * `mode`: mode resampling, selects the value which appears most
often of all the sampled points * `near`: nearest neighbour resampling (default) * `q1`: first quartile
resampling, selects the first quartile value of all valid pixels * `q3`: third quartile resampling,
selects the third quartile value of all valid pixels * `rms` root mean square (quadratic mean) of all
valid pixels * `sum`: compute the weighted sum of all valid pixels Valid pixels are determined based
on the function ``is_valid()``.
:param align: Specifies to which corner of the spatial extent the new resampled data is aligned to.
:return: A raster data cube with values warped onto the new projection. It has the same dimensions and
the same dimension properties (name, type, labels, reference system and resolution) for all non-spatial
or vertical spatial dimensions. For the horizontal spatial dimensions the name and type remain
unchanged, but reference system, labels and resolution may change depending on the given parameters.
"""
return resample_spatial(data=self, resolution=resolution, projection=projection, method=method, align=align)
def round(self, p=UNSET) -> 'ProcessBuilder':
"""
Round to a specified precision
:param self: A number to round.
:param p: A positive number specifies the number of digits after the decimal point to round to. A
negative number means rounding to a power of ten, so for example *-2* rounds to the nearest hundred.
Defaults to *0*.
:return: The rounded number.
"""
return round(x=self, p=p)
def run_udf(self, udf, runtime, version=UNSET, context=UNSET) -> 'ProcessBuilder':
"""
Run a UDF
:param self: The data to be passed to the UDF as an array or raster data cube.
:param udf: Either source code, an absolute URL or a path to a UDF script.
:param runtime: A UDF runtime identifier available at the back-end.
:param version: An UDF runtime version. If set to `null`, the default runtime version specified for
each runtime is used.
:param context: Additional data such as configuration options to be passed to the UDF.
:return: The data processed by the UDF. * Returns a raster data cube, if a raster data cube is passed
for `data`. Details on the dimensions and dimension properties (name, type, labels, reference system
and resolution) depend on the UDF. * If an array is passed for `data`, the returned value can be of any
data type, but is exactly what the UDF returns.
"""
return run_udf(data=self, udf=udf, runtime=runtime, version=version, context=context)
def run_udf_externally(self, url, context=UNSET) -> 'ProcessBuilder':
"""
Run an externally hosted UDF container
:param self: The data to be passed to the UDF as array or raster data cube.
:param url: URL to a remote UDF service.
:param context: Additional data such as configuration options that should be passed to the UDF.
:return: The data processed by the UDF service. * Returns a raster data cube, if a raster data cube is
passed for `data`. Details on the dimensions and dimension properties (name, type, labels, reference
system and resolution) depend on the UDF. * If an array is passed for `data`, the returned value can be
of any data type, but is exactly what the UDF returns.
"""
return run_udf_externally(data=self, url=url, context=context)
def run_udf_externally(self, url, context=UNSET) -> 'ProcessBuilder':
"""
Run an externally hosted UDF container
:param self: The data to be passed to the UDF as an array or raster data cube.
:param url: Absolute URL to a remote UDF service.
:param context: Additional data such as configuration options to be passed to the UDF.
:return: The data processed by the UDF service. * Returns a raster data cube if a raster data cube is
passed for `data`. Details on the dimensions and dimension properties (name, type, labels, reference
system and resolution) depend on the UDF. * If an array is passed for `data`, the returned value can be
of any data type, but is exactly what the UDF returns.
"""
return run_udf_externally(data=self, url=url, context=context)
def sar_backscatter(self, coefficient=UNSET, elevation_model=UNSET, mask=UNSET, contributing_area=UNSET, local_incidence_angle=UNSET, ellipsoid_incidence_angle=UNSET, noise_removal=UNSET) -> 'ProcessBuilder':
"""
Computes backscatter from SAR input
:param self: The source data cube containing SAR input.
:param coefficient: Select the radiometric correction coefficient. The following options are available:
* `beta0`: radar brightness * `sigma0-ellipsoid`: ground area computed with ellipsoid earth model *
`sigma0-terrain`: ground area computed with terrain earth model * `gamma0-ellipsoid`: ground area
computed with ellipsoid earth model in sensor line of sight * `gamma0-terrain`: ground area computed
with terrain earth model in sensor line of sight (default) * `null`: non-normalized backscatter
:param elevation_model: The digital elevation model to use. Set to `null` (the default) to allow the
back-end to choose, which will improve portability, but reduce reproducibility.
:param mask: If set to `true`, a data mask is added to the bands with the name `mask`. It indicates
which values are valid (1), invalid (0) or contain no-data (null).
:param contributing_area: If set to `true`, a DEM-based local contributing area band named
`contributing_area` is added. The values are given in square meters.
:param local_incidence_angle: If set to `true`, a DEM-based local incidence angle band named
`local_incidence_angle` is added. The values are given in degrees.
:param ellipsoid_incidence_angle: If set to `true`, an ellipsoidal incidence angle band named
`ellipsoid_incidence_angle` is added. The values are given in degrees.
:param noise_removal: If set to `false`, no noise removal is applied. Defaults to `true`, which removes
noise.
:return: Backscatter values corresponding to the chosen parametrization. The values are given in linear
scale.
"""
return sar_backscatter(data=self, coefficient=coefficient, elevation_model=elevation_model, mask=mask, contributing_area=contributing_area, local_incidence_angle=local_incidence_angle, ellipsoid_incidence_angle=ellipsoid_incidence_angle, noise_removal=noise_removal)
def save_result(self, format, options=UNSET) -> 'ProcessBuilder':
"""
Save processed data to storage
:param self: The data to save.
:param format: The file format to save to. It must be one of the values that the server reports as
supported output file formats, which usually correspond to the short GDAL/OGR codes. If the format is
not suitable for storing the underlying data structure, a `FormatUnsuitable` exception will be thrown.
This parameter is *case insensitive*.
:param options: The file format parameters to be used to create the file(s). Must correspond to the
parameters that the server reports as supported parameters for the chosen `format`. The parameter names
and valid values usually correspond to the GDAL/OGR format options.
:return: `false` if saving failed, `true` otherwise.
"""
return save_result(data=self, format=format, options=options)
def sd(self, ignore_nodata=UNSET) -> 'ProcessBuilder':
"""
Standard deviation
:param self: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default.
Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a
value.
:return: The computed sample standard deviation.
"""
return sd(data=self, ignore_nodata=ignore_nodata)
def sgn(self) -> 'ProcessBuilder':
"""
Signum
:param self: A number.
:return: The computed signum value of `x`.
"""
return sgn(x=self)
def sin(self) -> 'ProcessBuilder':
"""
Sine
:param self: An angle in radians.
:return: The computed sine of `x`.
"""
return sin(x=self)
def sinh(self) -> 'ProcessBuilder':
"""
Hyperbolic sine
:param self: An angle in radians.
:return: The computed hyperbolic sine of `x`.
"""
return sinh(x=self)
def sort(self, asc=UNSET, nodata=UNSET) -> 'ProcessBuilder':
"""
Sort data
:param self: An array with data to sort.
:param asc: The default sort order is ascending, with smallest values first. To sort in reverse
(descending) order, set this parameter to `false`.
:param nodata: Controls the handling of no-data values (`null`). By default, they are removed. If set
to `true`, missing values in the data are put last; if set to `false`, they are put first.
:return: The sorted array.
"""
return sort(data=self, asc=asc, nodata=nodata)
def sqrt(self) -> 'ProcessBuilder':
"""
Square root
:param self: A number.
:return: The computed square root.
"""
return sqrt(x=self)
def subtract(self, y) -> 'ProcessBuilder':
"""
Subtraction of two numbers
:param self: The minuend.
:param y: The subtrahend.
:return: The computed result.
"""
return subtract(x=self, y=y)
def sum(self, ignore_nodata=UNSET) -> 'ProcessBuilder':
"""
Compute the sum by adding up numbers
:param self: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default.
Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a
value.
:return: The computed sum of the sequence of numbers.
"""
return sum(data=self, ignore_nodata=ignore_nodata)
def tan(self) -> 'ProcessBuilder':
"""
Tangent
:param self: An angle in radians.
:return: The computed tangent of `x`.
"""
return tan(x=self)
def tanh(self) -> 'ProcessBuilder':
"""
Hyperbolic tangent
:param self: An angle in radians.
:return: The computed hyperbolic tangent of `x`.
"""
return tanh(x=self)
def text_begins(self, pattern, case_sensitive=UNSET) -> 'ProcessBuilder':
"""
Text begins with another text
:param self: Text in which to find something at the beginning.
:param pattern: Text to find at the beginning of `data`. Regular expressions are not supported.
:param case_sensitive: Case sensitive comparison can be disabled by setting this parameter to `false`.
:return: `true` if `data` begins with `pattern`, false` otherwise.
"""
return text_begins(data=self, pattern=pattern, case_sensitive=case_sensitive)
def text_contains(self, pattern, case_sensitive=UNSET) -> 'ProcessBuilder':
"""
Text contains another text
:param self: Text in which to find something in.
:param pattern: Text to find in `data`. Regular expressions are not supported.
:param case_sensitive: Case sensitive comparison can be disabled by setting this parameter to `false`.
:return: `true` if `data` contains the `pattern`, false` otherwise.
"""
return text_contains(data=self, pattern=pattern, case_sensitive=case_sensitive)
def text_ends(self, pattern, case_sensitive=UNSET) -> 'ProcessBuilder':
"""
Text ends with another text
:param self: Text in which to find something at the end.
:param pattern: Text to find at the end of `data`. Regular expressions are not supported.
:param case_sensitive: Case sensitive comparison can be disabled by setting this parameter to `false`.
:return: `true` if `data` ends with `pattern`, false` otherwise.
"""
return text_ends(data=self, pattern=pattern, case_sensitive=case_sensitive)
def text_merge(self, separator=UNSET) -> 'ProcessBuilder':
"""
Concatenate elements to a single text
:param self: A set of elements. Numbers, boolean values and null values get converted to their (lower
case) string representation. For example: `1` (integer), `-1.5` (number), `true` / `false` (boolean
values)
:param separator: A separator to put between each of the individual texts. Defaults to an empty string.
:return: A string containing a string representation of all the array elements in the same order, with
the separator between each element.
"""
return text_merge(data=self, separator=separator)
def trim_cube(self) -> 'ProcessBuilder':
"""
Remove dimension labels with no-data values
:param self: A raster data cube to trim.
:return: A trimmed raster data cube with the same dimensions. The dimension properties name, type,
reference system and resolution remain unchanged. The number of dimension labels may decrease.
"""
return trim_cube(data=self)
def variance(self, ignore_nodata=UNSET) -> 'ProcessBuilder':
"""
Variance
:param self: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default.
Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a
value.
:return: The computed sample variance.
"""
return variance(data=self, ignore_nodata=ignore_nodata)
def xor(self, y) -> 'ProcessBuilder':
"""
Logical XOR (exclusive or)
:param self: A boolean value.
:param y: A boolean value.
:return: Boolean result of the logical XOR.
"""
return xor(x=self, y=y)
# Public shortcut
process = ProcessBuilder.process
# Private shortcut that has lower chance to collide with a process argument named `process`
_process = ProcessBuilder.process
def absolute(x) -> ProcessBuilder:
"""
Absolute value
:param x: A number.
:return: The computed absolute value.
"""
return _process('absolute', x=x)
def add(x, y) -> ProcessBuilder:
"""
Addition of two numbers
:param x: The first summand.
:param y: The second summand.
:return: The computed sum of the two numbers.
"""
return _process('add', x=x, y=y)
def add_dimension(data, name, label, type=UNSET) -> ProcessBuilder:
"""
Add a new dimension
:param data: A data cube to add the dimension to.
:param name: Name for the dimension.
:param label: A dimension label.
:param type: The type of dimension, defaults to `other`.
:return: The data cube with a newly added dimension. The new dimension has exactly one dimension label. All
other dimensions remain unchanged.
"""
return _process('add_dimension', data=data, name=name, label=label, type=type)
def aggregate_spatial(data, geometries, reducer, target_dimension=UNSET, context=UNSET) -> ProcessBuilder:
"""
Zonal statistics for geometries
:param data: A raster data cube. The data cube must have been reduced to only contain two spatial
dimensions and a third dimension the values are aggregated for, for example the temporal dimension to get a
time series. Otherwise, this process fails with the `TooManyDimensions` exception. The data cube
implicitly gets restricted to the bounds of the geometries as if ``filter_spatial()`` would have been used
with the same values for the corresponding parameters immediately before this process.
:param geometries: Geometries as GeoJSON on which the aggregation will be based. One value will be
computed per GeoJSON `Feature`, `Geometry` or `GeometryCollection`. For a `FeatureCollection` multiple
values will be computed, one value per contained `Feature`. For example, a single value will be computed
for a `MultiPolygon`, but two values will be computed for a `FeatureCollection` containing two polygons. -
For **polygons**, the process considers all pixels for which the point at the pixel center intersects with
the corresponding polygon (as defined in the Simple Features standard by the OGC). - For **points**, the
process considers the closest pixel center. - For **lines** (line strings), the process considers all the
pixels whose centers are closest to at least one point on the line. Thus, pixels may be part of multiple
geometries and be part of multiple aggregations. To maximize interoperability, a nested
`GeometryCollection` should be avoided. Furthermore, a `GeometryCollection` composed of a single type of
geometries should be avoided in favour of the corresponding multi-part type (e.g. `MultiPolygon`).
:param reducer: A reducer to be applied on all values of each geometry. A reducer is a single process such
as ``mean()`` or a set of processes, which computes a single value for a list of values, see the category
'reducer' for such processes.
:param target_dimension: The new dimension name to be used for storing the results. Defaults to `result`.
:param context: Additional data to be passed to the reducer.
:return: A vector data cube with the computed results and restricted to the bounds of the geometries. The
computed value is used for the dimension with the name that was specified in the parameter
`target_dimension`. The computation also stores information about the total count of pixels (valid +
invalid pixels) and the number of valid pixels (see ``is_valid()``) for each geometry. These values are
added as a new dimension with a dimension name derived from `target_dimension` by adding the suffix
`_meta`. The new dimension has the dimension labels `total_count` and `valid_count`.
"""
return _process('aggregate_spatial', data=data, geometries=geometries, reducer=reducer, target_dimension=target_dimension, context=context)
def aggregate_spatial_binary(data, geometries, reducer, target_dimension=UNSET, context=UNSET) -> ProcessBuilder:
"""
Zonal statistics for geometries by binary aggregation
:param data: A raster data cube. The data cube implicitly gets restricted to the bounds of the geometries
as if ``filter_spatial()`` would have been used with the same values for the corresponding parameters
immediately before this process.
:param geometries: Geometries as GeoJSON on which the aggregation will be based.
:param reducer: A reduction operator to be applied consecutively on tuples of values. It must be both
associative and commutative as the execution may be executed in parallel and therefore the order of
execution is arbitrary. The reduction operator may be a single process such as ``multiply()`` or consist of
multiple sub-processes.
:param target_dimension: The new dimension name to be used for storing the results. Defaults to `result`.
:param context: Additional data to be passed to the reducer.
:return: A vector data cube with the computed results and restricted to the bounds of the geometries. The
computed value is stored in dimension with the name that was specified in the parameter `target_dimension`.
The computation also stores information about the total count of pixels (valid + invalid pixels) and the
number of valid pixels (see ``is_valid()``) for each geometry. These values are stored as new dimension
with a dimension name derived from `target_dimension` by adding the suffix `_meta`. The new dimension has
the dimension labels `total_count` and `valid_count`.
"""
return _process('aggregate_spatial_binary', data=data, geometries=geometries, reducer=reducer, target_dimension=target_dimension, context=context)
def aggregate_spatial_window(data, reducer, size, boundary=UNSET, align=UNSET, context=UNSET) -> ProcessBuilder:
"""
Zonal statistics for rectangular windows
:param data: A raster data cube with exactly two horizontal spatial dimensions and an arbitrary number of
additional dimensions. The process is applied to all additional dimensions individually.
:param reducer: A reducer to be applied on the list of values, which contain all pixels covered by the
window. A reducer is a single process such as ``mean()`` or a set of processes, which computes a single
value for a list of values, see the category 'reducer' for such processes.
:param size: Window size in pixels along the horizontal spatial dimensions. The first value corresponds to
the `x` axis, the second value corresponds to the `y` axis.
:param boundary: Behavior to apply if the number of values for the axes `x` and `y` is not a multiple of
the corresponding value in the `size` parameter. Options are: - `pad` (default): pad the data cube with
the no-data value `null` to fit the required window size. - `trim`: trim the data cube to fit the required
window size. Set the parameter `align` to specifies to which corner the data is aligned to.
:param align: If the data requires padding or trimming (see parameter `boundary`), specifies to which
corner of the spatial extent the data is aligned to. For example, if the data is aligned to the upper left,
the process pads/trims at the lower-right.
:param context: Additional data to be passed to the reducer.
:return: A data cube with the newly computed values and the same dimensions. The resolution will change
depending on the chosen values for the `size` and `boundary` parameter. It usually decreases for the
dimensions which have the corresponding parameter `size` set to values greater than 1. The dimension
labels will be set to the coordinate at the center of the window. The other dimension properties (name,
type and reference system) remain unchanged.
"""
return _process('aggregate_spatial_window', data=data, reducer=reducer, size=size, boundary=boundary, align=align, context=context)
def aggregate_temporal(data, intervals, reducer, labels=UNSET, dimension=UNSET, context=UNSET) -> ProcessBuilder:
"""
Temporal aggregations
:param data: A data cube.
:param intervals: Left-closed temporal intervals, which are allowed to overlap. Each temporal interval in
the array has exactly two elements: 1. The first element is the start of the temporal interval. The
specified instance in time is **included** in the interval. 2. The second element is the end of the
temporal interval. The specified instance in time is **excluded** from the interval. The specified
temporal strings follow [RFC 3339](https://www.rfc-editor.org/rfc/rfc3339.html). Although [RFC 3339
prohibits the hour to be '24'](https://www.rfc-editor.org/rfc/rfc3339.html#section-5.7), **this process
allows the value '24' for the hour** of an end time in order to make it possible that left-closed time
intervals can fully cover the day.
:param reducer: A reducer to be applied for the values contained in each interval. A reducer is a single
process such as ``mean()`` or a set of processes, which computes a single value for a list of values, see
the category 'reducer' for such processes. Intervals may not contain any values, which for most reducers
leads to no-data (`null`) values by default.
:param labels: Distinct labels for the intervals, which can contain dates and/or times. Is only required to
be specified if the values for the start of the temporal intervals are not distinct and thus the default
labels would not be unique. The number of labels and the number of groups need to be equal.
:param dimension: The name of the temporal dimension for aggregation. All data along the dimension is
passed through the specified reducer. If the dimension is not set or set to `null`, the data cube is
expected to only have one temporal dimension. Fails with a `TooManyDimensions` exception if it has more
dimensions. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist.
:param context: Additional data to be passed to the reducer.
:return: A new data cube with the same dimensions. The dimension properties (name, type, labels, reference
system and resolution) remain unchanged, except for the resolution and dimension labels of the given
temporal dimension.
"""
return _process('aggregate_temporal', data=data, intervals=intervals, reducer=reducer, labels=labels, dimension=dimension, context=context)
def aggregate_temporal_period(data, period, reducer, dimension=UNSET, context=UNSET) -> ProcessBuilder:
"""
Temporal aggregations based on calendar hierarchies
:param data: A data cube.
:param period: The time intervals to aggregate. The following pre-defined values are available: * `hour`:
Hour of the day * `day`: Day of the year * `week`: Week of the year * `dekad`: Ten day periods, counted per
year with three periods per month (day 1 - 10, 11 - 20 and 21 - end of month). The third dekad of the month
can range from 8 to 11 days. For example, the fourth dekad is Feb, 1 - Feb, 10 each year. * `month`: Month
of the year * `season`: Three month periods of the calendar seasons (December - February, March - May, June
- August, September - November). * `tropical-season`: Six month periods of the tropical seasons (November -
April, May - October). * `year`: Proleptic years * `decade`: Ten year periods ([0-to-9
decade](https://en.wikipedia.org/wiki/Decade#0-to-9_decade)), from a year ending in a 0 to the next year
ending in a 9. * `decade-ad`: Ten year periods ([1-to-0
decade](https://en.wikipedia.org/wiki/Decade#1-to-0_decade)) better aligned with the anno Domini (AD)
calendar era, from a year ending in a 1 to the next year ending in a 0.
:param reducer: A reducer to be applied for the values contained in each period. A reducer is a single
process such as ``mean()`` or a set of processes, which computes a single value for a list of values, see
the category 'reducer' for such processes. Periods may not contain any values, which for most reducers
leads to no-data (`null`) values by default.
:param dimension: The name of the temporal dimension for aggregation. All data along the dimension is
passed through the specified reducer. If the dimension is not set or set to `null`, the data cube is
expected to only have one temporal dimension. Fails with a `TooManyDimensions` exception if it has more
dimensions. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist.
:param context: Additional data to be passed to the reducer.
:return: A new data cube with the same dimensions. The dimension properties (name, type, labels, reference
system and resolution) remain unchanged, except for the resolution and dimension labels of the given
temporal dimension. The specified temporal dimension has the following dimension labels (`YYYY` = four-
digit year, `MM` = two-digit month, `DD` two-digit day of month): * `hour`: `YYYY-MM-DD-00` - `YYYY-MM-
DD-23` * `day`: `YYYY-001` - `YYYY-365` * `week`: `YYYY-01` - `YYYY-52` * `dekad`: `YYYY-00` - `YYYY-36` *
`month`: `YYYY-01` - `YYYY-12` * `season`: `YYYY-djf` (December - February), `YYYY-mam` (March - May),
`YYYY-jja` (June - August), `YYYY-son` (September - November). * `tropical-season`: `YYYY-ndjfma` (November
- April), `YYYY-mjjaso` (May - October). * `year`: `YYYY` * `decade`: `YYY0` * `decade-ad`: `YYY1`
"""
return _process('aggregate_temporal_period', data=data, period=period, reducer=reducer, dimension=dimension, context=context)
def all(data, ignore_nodata=UNSET) -> ProcessBuilder:
"""
Are all of the values true?
:param data: A set of boolean values.
:param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default.
:return: Boolean result of the logical operation.
"""
return _process('all', data=data, ignore_nodata=ignore_nodata)
def and_(x, y) -> ProcessBuilder:
"""
Logical AND
:param x: A boolean value.
:param y: A boolean value.
:return: Boolean result of the logical AND.
"""
return _process('and', x=x, y=y)
def anomaly(data, normals, period) -> ProcessBuilder:
"""
Compute anomalies
:param data: A data cube with exactly one temporal dimension and the following dimension labels for the
given period (`YYYY` = four-digit year, `MM` = two-digit month, `DD` two-digit day of month): * `hour`:
`YYYY-MM-DD-00` - `YYYY-MM-DD-23` * `day`: `YYYY-001` - `YYYY-365` * `week`: `YYYY-01` - `YYYY-52` *
`dekad`: `YYYY-00` - `YYYY-36` * `month`: `YYYY-01` - `YYYY-12` * `season`: `YYYY-djf` (December -
February), `YYYY-mam` (March - May), `YYYY-jja` (June - August), `YYYY-son` (September - November). *
`tropical-season`: `YYYY-ndjfma` (November - April), `YYYY-mjjaso` (May - October). * `year`: `YYYY` *
`decade`: `YYY0` * `decade-ad`: `YYY1` * `single-period` / `climatology-period`: Any
``aggregate_temporal_period()`` can compute such a data cube.
:param normals: A data cube with normals, e.g. daily, monthly or yearly values computed from a process such
as ``climatological_normal()``. Must contain exactly one temporal dimension with the following dimension
labels for the given period: * `hour`: `00` - `23` * `day`: `001` - `365` * `week`: `01` - `52` * `dekad`:
`00` - `36` * `month`: `01` - `12` * `season`: `djf` (December - February), `mam` (March - May), `jja`
(June - August), `son` (September - November) * `tropical-season`: `ndjfma` (November - April), `mjjaso`
(May - October) * `year`: Four-digit year numbers * `decade`: Four-digit year numbers, the last digit being
a `0` * `decade-ad`: Four-digit year numbers, the last digit being a `1` * `single-period` / `climatology-
period`: A single dimension label with any name is expected.
:param period: Specifies the time intervals available in the normals data cube. The following options are
available: * `hour`: Hour of the day * `day`: Day of the year * `week`: Week of the year * `dekad`: Ten
day periods, counted per year with three periods per month (day 1 - 10, 11 - 20 and 21 - end of month). The
third dekad of the month can range from 8 to 11 days. For example, the fourth dekad is Feb, 1 - Feb, 10
each year. * `month`: Month of the year * `season`: Three month periods of the calendar seasons (December -
February, March - May, June - August, September - November). * `tropical-season`: Six month periods of the
tropical seasons (November - April, May - October). * `year`: Proleptic years * `decade`: Ten year periods
([0-to-9 decade](https://en.wikipedia.org/wiki/Decade#0-to-9_decade)), from a year ending in a 0 to the
next year ending in a 9. * `decade-ad`: Ten year periods ([1-to-0
decade](https://en.wikipedia.org/wiki/Decade#1-to-0_decade)) better aligned with the anno Domini (AD)
calendar era, from a year ending in a 1 to the next year ending in a 0. * `single-period` / `climatology-
period`: A single period of arbitrary length
:return: A data cube with the same dimensions. The dimension properties (name, type, labels, reference
system and resolution) remain unchanged.
"""
return _process('anomaly', data=data, normals=normals, period=period)
def any(data, ignore_nodata=UNSET) -> ProcessBuilder:
"""
Is at least one value true?
:param data: A set of boolean values.
:param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default.
:return: Boolean result of the logical operation.
"""
return _process('any', data=data, ignore_nodata=ignore_nodata)
def apply(data, process, context=UNSET) -> ProcessBuilder:
"""
Apply a process to each pixel
:param data: A data cube.
:param process: A process that accepts and returns a single value and is applied on each individual value
in the data cube. The process may consist of multiple sub-processes and could, for example, consist of
processes such as ``abs()`` or ``linear_scale_range()``.
:param context: Additional data to be passed to the process.
:return: A data cube with the newly computed values and the same dimensions. The dimension properties
(name, type, labels, reference system and resolution) remain unchanged.
"""
return _process('apply', data=data, process=process, context=context)
def apply_dimension(data, process, dimension, target_dimension=UNSET, context=UNSET) -> ProcessBuilder:
"""
Apply a process to pixels along a dimension
:param data: A data cube.
:param process: Process to be applied on all pixel values. The specified process needs to accept an array
and must return an array with at least one element. A process may consist of multiple sub-processes.
:param dimension: The name of the source dimension to apply the process on. Fails with a
`DimensionNotAvailable` exception if the specified dimension does not exist.
:param target_dimension: The name of the target dimension or `null` (the default) to use the source
dimension specified in the parameter `dimension`. By specifying a target dimension, the source dimension
is removed. The target dimension with the specified name and the type `other` (see ``add_dimension()``) is
created, if it doesn't exist yet.
:param context: Additional data to be passed to the process.
:return: A data cube with the newly computed values. All dimensions stay the same, except for the
dimensions specified in corresponding parameters. There are three cases how the dimensions can change: 1.
The source dimension is the target dimension: - The (number of) dimensions remain unchanged as the
source dimension is the target dimension. - The source dimension properties name and type remain
unchanged. - The dimension labels, the reference system and the resolution are preserved only if the
number of pixel values in the source dimension is equal to the number of values computed by the process.
Otherwise, all other dimension properties change as defined in the list below. 2. The source dimension is
not the target dimension and the latter exists: - The number of dimensions decreases by one as the
source dimension is dropped. - The target dimension properties name and type remain unchanged. All other
dimension properties change as defined in the list below. 3. The source dimension is not the target
dimension and the latter does not exist: - The number of dimensions remain unchanged, but the source
dimension is replaced with the target dimension. - The target dimension has the specified name and the
type other. All other dimension properties are set as defined in the list below. Unless otherwise stated
above, for the given (target) dimension the following applies: - the number of dimension labels is equal
to the number of values computed by the process, - the dimension labels are incrementing integers starting
from zero, - the resolution changes, and - the reference system is undefined.
"""
return _process('apply_dimension', data=data, process=process, dimension=dimension, target_dimension=target_dimension, context=context)
def apply_kernel(data, kernel, factor=UNSET, border=UNSET, replace_invalid=UNSET) -> ProcessBuilder:
"""
Apply a spatial convolution with a kernel
:param data: A data cube.
:param kernel: Kernel as a two-dimensional array of weights. The inner level of the nested array aligns
with the `x` axis and the outer level aligns with the `y` axis. Each level of the kernel must have an
uneven number of elements, otherwise the process throws a `KernelDimensionsUneven` exception.
:param factor: A factor that is multiplied to each value after the kernel has been applied. This is
basically a shortcut for explicitly multiplying each value by a factor afterwards, which is often required
for some kernel-based algorithms such as the Gaussian blur.
:param border: Determines how the data is extended when the kernel overlaps with the borders. Defaults to
fill the border with zeroes. The following options are available: * *numeric value* - fill with a user-
defined constant number `n`: `nnnnnn|abcdefgh|nnnnnn` (default, with `n` = 0) * `replicate` - repeat the
value from the pixel at the border: `aaaaaa|abcdefgh|hhhhhh` * `reflect` - mirror/reflect from the border:
`fedcba|abcdefgh|hgfedc` * `reflect_pixel` - mirror/reflect from the center of the pixel at the border:
`gfedcb|abcdefgh|gfedcb` * `wrap` - repeat/wrap the image: `cdefgh|abcdefgh|abcdef`
:param replace_invalid: This parameter specifies the value to replace non-numerical or infinite numerical
values with. By default, those values are replaced with zeroes.
:return: A data cube with the newly computed values and the same dimensions. The dimension properties
(name, type, labels, reference system and resolution) remain unchanged.
"""
return _process('apply_kernel', data=data, kernel=kernel, factor=factor, border=border, replace_invalid=replace_invalid)
def apply_neighborhood(data, process, size, overlap=UNSET, context=UNSET) -> ProcessBuilder:
"""
Apply a process to pixels in a n-dimensional neighborhood
:param data: A data cube.
:param process: Process to be applied on all neighborhoods.
:param size: Neighborhood sizes along each dimension. This object maps dimension names to either a
physical measure (e.g. 100 m, 10 days) or pixels (e.g. 32 pixels). For dimensions not specified, the
default is to provide all values. Be aware that including all values from overly large dimensions may not
be processed at once.
:param overlap: Overlap of neighborhoods along each dimension to avoid border effects. For instance a
temporal dimension can add 1 month before and after a neighborhood. In the spatial dimensions, this is
often a number of pixels. The overlap specified is added before and after, so an overlap of 8 pixels will
add 8 pixels on both sides of the window, so 16 in total. Be aware that large overlaps increase the need
for computational resources and modifying overlapping data in subsequent operations have no effect.
:param context: Additional data to be passed to the process.
:return: A data cube with the newly computed values and the same dimensions. The dimension properties
(name, type, labels, reference system and resolution) remain unchanged.
"""
return _process('apply_neighborhood', data=data, process=process, size=size, overlap=overlap, context=context)
def arccos(x) -> ProcessBuilder:
"""
Inverse cosine
:param x: A number.
:return: The computed angle in radians.
"""
return _process('arccos', x=x)
def arcosh(x) -> ProcessBuilder:
"""
Inverse hyperbolic cosine
:param x: A number.
:return: The computed angle in radians.
"""
return _process('arcosh', x=x)
def arcsin(x) -> ProcessBuilder:
"""
Inverse sine
:param x: A number.
:return: The computed angle in radians.
"""
return _process('arcsin', x=x)
def arctan(x) -> ProcessBuilder:
"""
Inverse tangent
:param x: A number.
:return: The computed angle in radians.
"""
return _process('arctan', x=x)
def arctan2(y, x) -> ProcessBuilder:
"""
Inverse tangent of two numbers
:param y: A number to be used as the dividend.
:param x: A number to be used as the divisor.
:return: The computed angle in radians.
"""
return _process('arctan2', y=y, x=x)
def ard_normalized_radar_backscatter(data, elevation_model=UNSET, contributing_area=UNSET, ellipsoid_incidence_angle=UNSET, noise_removal=UNSET) -> ProcessBuilder:
"""
CARD4L compliant SAR NRB generation
:param data: The source data cube containing SAR input.
:param elevation_model: The digital elevation model to use. Set to `null` (the default) to allow the back-
end to choose, which will improve portability, but reduce reproducibility.
:param contributing_area: If set to `true`, a DEM-based local contributing area band named
`contributing_area` is added. The values are given in square meters.
:param ellipsoid_incidence_angle: If set to `true`, an ellipsoidal incidence angle band named
`ellipsoid_incidence_angle` is added. The values are given in degrees.
:param noise_removal: If set to `false`, no noise removal is applied. Defaults to `true`, which removes
noise.
:return: Backscatter values expressed as gamma0 in linear scale. In addition to the bands
`contributing_area` and `ellipsoid_incidence_angle` that can optionally be added with corresponding
parameters, the following bands are always added to the data cube: - `mask`: A data mask that indicates
which values are valid (1), invalid (0) or contain no-data (null). - `local_incidence_angle`: A band with
DEM-based local incidence angles in degrees. The data returned is CARD4L compliant with corresponding
metadata.
"""
return _process('ard_normalized_radar_backscatter', data=data, elevation_model=elevation_model, contributing_area=contributing_area, ellipsoid_incidence_angle=ellipsoid_incidence_angle, noise_removal=noise_removal)
def ard_surface_reflectance(data, atmospheric_correction_method, cloud_detection_method, elevation_model=UNSET, atmospheric_correction_options=UNSET, cloud_detection_options=UNSET) -> ProcessBuilder:
"""
CARD4L compliant Surface Reflectance generation
:param data: The source data cube containing multi-spectral optical top of the atmosphere (TOA)
reflectances. There must be a single dimension of type `bands` available.
:param atmospheric_correction_method: The atmospheric correction method to use.
:param cloud_detection_method: The cloud detection method to use. Each method supports detecting different
atmospheric disturbances such as clouds, cloud shadows, aerosols, haze, ozone and/or water vapour in
optical imagery.
:param elevation_model: The digital elevation model to use. Set to `null` (the default) to allow the back-
end to choose, which will improve portability, but reduce reproducibility.
:param atmospheric_correction_options: Proprietary options for the atmospheric correction method.
Specifying proprietary options will reduce portability.
:param cloud_detection_options: Proprietary options for the cloud detection method. Specifying proprietary
options will reduce portability.
:return: Data cube containing bottom of atmosphere reflectances for each spectral band in the source data
cube, with atmospheric disturbances like clouds and cloud shadows removed. No-data values (null) are
directly set in the bands. Depending on the methods used, several additional bands will be added to the
data cube: Data cube containing bottom of atmosphere reflectances for each spectral band in the source
data cube, with atmospheric disturbances like clouds and cloud shadows removed. Depending on the methods
used, several additional bands will be added to the data cube: - `date` (optional): Specifies per-pixel
acquisition timestamps. - `incomplete-testing` (required): Identifies pixels with a value of 1 for which
the per-pixel tests (at least saturation, cloud and cloud shadows, see CARD4L specification for details)
have not all been successfully completed. Otherwise, the value is 0. - `saturation` (required) /
`saturation_{band}` (optional): Indicates where pixels in the input spectral bands are saturated (1) or not
(0). If the saturation is given per band, the band names are `saturation_{band}` with `{band}` being the
band name from the source data cube. - `cloud`, `shadow` (both required),`aerosol`, `haze`, `ozone`,
`water_vapor` (all optional): Indicates the probability of pixels being an atmospheric disturbance such as
clouds. All bands have values between 0 (clear) and 1, which describes the probability that it is an
atmospheric disturbance. - `snow-ice` (optional): Points to a file that indicates whether a pixel is
assessed as being snow/ice (1) or not (0). All values describe the probability and must be between 0 and 1.
- `land-water` (optional): Indicates whether a pixel is assessed as being land (1) or water (0). All values
describe the probability and must be between 0 and 1. - `incidence-angle` (optional): Specifies per-pixel
incidence angles in degrees. - `azimuth` (optional): Specifies per-pixel azimuth angles in degrees. - `sun-
azimuth:` (optional): Specifies per-pixel sun azimuth angles in degrees. - `sun-elevation` (optional):
Specifies per-pixel sun elevation angles in degrees. - `terrain-shadow` (optional): Indicates with a value
of 1 whether a pixel is not directly illuminated due to terrain shadowing. Otherwise, the value is 0. -
`terrain-occlusion` (optional): Indicates with a value of 1 whether a pixel is not visible to the sensor
due to terrain occlusion during off-nadir viewing. Otherwise, the value is 0. - `terrain-illumination`
(optional): Contains coefficients used for terrain illumination correction are provided for each pixel.
The data returned is CARD4L compliant with corresponding metadata.
"""
return _process('ard_surface_reflectance', data=data, atmospheric_correction_method=atmospheric_correction_method, cloud_detection_method=cloud_detection_method, elevation_model=elevation_model, atmospheric_correction_options=atmospheric_correction_options, cloud_detection_options=cloud_detection_options)
def array_append(data, value) -> ProcessBuilder:
"""
Append a value to an array
:param data: An array.
:param value: Value to append to the array.
:return: The new array with the value being appended.
"""
return _process('array_append', data=data, value=value)
def array_apply(data, process, context=UNSET) -> ProcessBuilder:
"""
Apply a process to each array element
:param data: An array.
:param process: A process that accepts and returns a single value and is applied on each individual value
in the array. The process may consist of multiple sub-processes and could, for example, consist of
processes such as ``abs()`` or ``linear_scale_range()``.
:param context: Additional data to be passed to the process.
:return: An array with the newly computed values. The number of elements are the same as for the original
array.
"""
return _process('array_apply', data=data, process=process, context=context)
def array_concat(array1, array2) -> ProcessBuilder:
"""
Merge two arrays
:param array1: The first array.
:param array2: The second array.
:return: The merged array.
"""
return _process('array_concat', array1=array1, array2=array2)
def array_contains(data, value) -> ProcessBuilder:
"""
Check whether the array contains a given value
:param data: List to find the value in.
:param value: Value to find in `data`.
:return: `true` if the list contains the value, false` otherwise.
"""
return _process('array_contains', data=data, value=value)
def array_create(data=UNSET, repeat=UNSET) -> ProcessBuilder:
"""
Create an array
:param data: A (native) array to fill the newly created array with. Defaults to an empty array.
:param repeat: The number of times the (native) array specified in `data` is repeatedly added after each
other to the new array being created. Defaults to `1`.
:return: The newly created array.
"""
return _process('array_create', data=data, repeat=repeat)
def array_create_labeled(data, labels) -> ProcessBuilder:
"""
Create a labeled array
:param data: An array of values to be used.
:param labels: An array of labels to be used.
:return: The newly created labeled array.
"""
return _process('array_create_labeled', data=data, labels=labels)
def array_element(data, index=UNSET, label=UNSET, return_nodata=UNSET) -> ProcessBuilder:
"""
Get an element from an array
:param data: An array.
:param index: The zero-based index of the element to retrieve.
:param label: The label of the element to retrieve. Throws an `ArrayNotLabeled` exception, if the given
array is not a labeled array and this parameter is set.
:param return_nodata: By default this process throws an `ArrayElementNotAvailable` exception if the index
or label is invalid. If you want to return `null` instead, set this flag to `true`.
:return: The value of the requested element.
"""
return _process('array_element', data=data, index=index, label=label, return_nodata=return_nodata)
def array_filter(data, condition, context=UNSET) -> ProcessBuilder:
"""
Filter an array based on a condition
:param data: An array.
:param condition: A condition that is evaluated against each value, index and/or label in the array. Only
the array elements for which the condition returns `true` are preserved.
:param context: Additional data to be passed to the condition.
:return: An array filtered by the specified condition. The number of elements are less than or equal
compared to the original array.
"""
return _process('array_filter', data=data, condition=condition, context=context)
def array_find(data, value) -> ProcessBuilder:
"""
Get the index for a value in an array
:param data: List to find the value in.
:param value: Value to find in `data`.
:return: The index of the first element with the specified value. If no element was found, `null` is
returned.
"""
return _process('array_find', data=data, value=value)
def array_find_label(data, label) -> ProcessBuilder:
"""
Get the index for a label in a labeled array
:param data: List to find the label in.
:param label: Label to find in `data`.
:return: The index of the element with the specified label assigned. If no such label was found, `null` is
returned.
"""
return _process('array_find_label', data=data, label=label)
def array_interpolate_linear(data) -> ProcessBuilder:
"""
One-dimensional linear interpolation for arrays
:param data: An array of numbers and no-data values. If the given array is a labeled array, the labels
must have a natural/inherent label order and the process expects the labels to be sorted accordingly. This
is the default behavior in openEO for spatial and temporal dimensions.
:return: An array with no-data values being replaced with interpolated values. If not at least 2 numerical
values are available in the array, the array stays the same.
"""
return _process('array_interpolate_linear', data=data)
def array_labels(data) -> ProcessBuilder:
"""
Get the labels for an array
:param data: An array with labels.
:return: The labels as an array.
"""
return _process('array_labels', data=data)
def array_modify(data, values, index, length=UNSET) -> ProcessBuilder:
"""
Change the content of an array (insert, remove, update)
:param data: An array.
:param values: The values to fill the array with.
:param index: The index of the element to insert the value(s) before. If the index is greater than the
number of elements, the process throws an `ArrayElementNotAvailable` exception. To insert after the last
element, there are two options: 1. Use the simpler processes ``array_append()`` to append a single value
or ``array_concat`` to append multiple values. 2. Specify the number of elements in the array. You can
retrieve the number of elements with the process ``count()``, having the parameter `condition` set to
`true`.
:param length: The number of elements to replace. This parameter has no effect in case the given `index`
does not exist in the array given.
:return: An array with values added, updated or removed.
"""
return _process('array_modify', data=data, values=values, index=index, length=length)
def arsinh(x) -> ProcessBuilder:
"""
Inverse hyperbolic sine
:param x: A number.
:return: The computed angle in radians.
"""
return _process('arsinh', x=x)
def artanh(x) -> ProcessBuilder:
"""
Inverse hyperbolic tangent
:param x: A number.
:return: The computed angle in radians.
"""
return _process('artanh', x=x)
def atmospheric_correction(data, method, elevation_model=UNSET, options=UNSET) -> ProcessBuilder:
"""
Apply atmospheric correction
:param data: Data cube containing multi-spectral optical top of atmosphere reflectances to be corrected.
:param method: The atmospheric correction method to use. To get reproducible results, you have to set a
specific method. Set to `null` to allow the back-end to choose, which will improve portability, but reduce
reproducibility as you *may* get different results if you run the processes multiple times.
:param elevation_model: The digital elevation model to use. Set to `null` (the default) to allow the back-
end to choose, which will improve portability, but reduce reproducibility.
:param options: Proprietary options for the atmospheric correction method. Specifying proprietary options
will reduce portability.
:return: Data cube containing bottom of atmosphere reflectances.
"""
return _process('atmospheric_correction', data=data, method=method, elevation_model=elevation_model, options=options)
def between(x, min, max, exclude_max=UNSET) -> ProcessBuilder:
"""
Between comparison
:param x: The value to check.
:param min: Lower boundary (inclusive) to check against.
:param max: Upper boundary (inclusive) to check against.
:param exclude_max: Exclude the upper boundary `max` if set to `true`. Defaults to `false`.
:return: `true` if `x` is between the specified bounds, otherwise `false`.
"""
return _process('between', x=x, min=min, max=max, exclude_max=exclude_max)
def ceil(x) -> ProcessBuilder:
"""
Round fractions up
:param x: A number to round up.
:return: The number rounded up.
"""
return _process('ceil', x=x)
def climatological_normal(data, period, climatology_period=UNSET) -> ProcessBuilder:
"""
Compute climatology normals
:param data: A data cube with exactly one temporal dimension. The data cube must span at least the temporal
interval specified in the parameter `climatology-period`. Seasonal periods may span two consecutive years,
e.g. temporal winter that includes months December, January and February. If the required months before the
actual climate period are available, the season is taken into account. If not available, the first season
is not taken into account and the seasonal mean is based on one year less than the other seasonal normals.
The incomplete season at the end of the last year is never taken into account.
:param period: The time intervals to aggregate the average value for. The following pre-defined frequencies
are supported: * `day`: Day of the year * `month`: Month of the year * `climatology-period`: The period
specified in the `climatology-period`. * `season`: Three month periods of the calendar seasons (December -
February, March - May, June - August, September - November). * `tropical-season`: Six month periods of the
tropical seasons (November - April, May - October).
:param climatology_period: The climatology period as a closed temporal interval. The first element of the
array is the first year to be fully included in the temporal interval. The second element is the last year
to be fully included in the temporal interval. The default period is from 1981 until 2010 (both inclusive).
:return: A data cube with the same dimensions. The dimension properties (name, type, labels, reference
system and resolution) remain unchanged, except for the resolution and dimension labels of the temporal
dimension. The temporal dimension has the following dimension labels: * `day`: `001` - `365` * `month`:
`01` - `12` * `climatology-period`: `climatology-period` * `season`: `djf` (December - February), `mam`
(March - May), `jja` (June - August), `son` (September - November) * `tropical-season`: `ndjfma` (November
- April), `mjjaso` (May - October)
"""
return _process('climatological_normal', data=data, period=period, climatology_period=climatology_period)
def clip(x, min, max) -> ProcessBuilder:
"""
Clip a value between a minimum and a maximum
:param x: A number.
:param min: Minimum value. If the value is lower than this value, the process will return the value of this
parameter.
:param max: Maximum value. If the value is greater than this value, the process will return the value of
this parameter.
:return: The value clipped to the specified range.
"""
return _process('clip', x=x, min=min, max=max)
def cloud_detection(data, method, options=UNSET) -> ProcessBuilder:
"""
Create cloud masks
:param data: The source data cube containing multi-spectral optical top of the atmosphere (TOA)
reflectances on which to perform cloud detection.
:param method: The cloud detection method to use. To get reproducible results, you have to set a specific
method. Set to `null` to allow the back-end to choose, which will improve portability, but reduce
reproducibility as you *may* get different results if you run the processes multiple times.
:param options: Proprietary options for the cloud detection method. Specifying proprietary options will
reduce portability.
:return: A data cube with bands for the atmospheric disturbances. Each of the masks contains values between
0 and 1. The data cube has the same spatial and temporal dimensions as the source data cube and a dimension
that contains a dimension label for each of the supported/considered atmospheric disturbance.
"""
return _process('cloud_detection', data=data, method=method, options=options)
def constant(x) -> ProcessBuilder:
"""
Define a constant value
:param x: The value of the constant.
:return: The value of the constant.
"""
return _process('constant', x=x)
def cos(x) -> ProcessBuilder:
"""
Cosine
:param x: An angle in radians.
:return: The computed cosine of `x`.
"""
return _process('cos', x=x)
def cosh(x) -> ProcessBuilder:
"""
Hyperbolic cosine
:param x: An angle in radians.
:return: The computed hyperbolic cosine of `x`.
"""
return _process('cosh', x=x)
def count(data, condition=UNSET, context=UNSET) -> ProcessBuilder:
"""
Count the number of elements
:param data: An array with elements of any data type.
:param condition: A condition consists of one or more processes, which in the end return a boolean value.
It is evaluated against each element in the array. An element is counted only if the condition returns
`true`. Defaults to count valid elements in a list (see ``is_valid()``). Setting this parameter to boolean
`true` counts all elements in the list.
:param context: Additional data to be passed to the condition.
:return: The counted number of elements.
"""
return _process('count', data=data, condition=condition, context=context)
def create_raster_cube() -> ProcessBuilder:
"""
Create an empty raster data cube
:return: An empty raster data cube with zero dimensions.
"""
return _process('create_raster_cube', )
def cummax(data, ignore_nodata=UNSET) -> ProcessBuilder:
"""
Cumulative maxima
:param data: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting
this flag to `false` considers no-data values so that `null` is set for all the following elements.
:return: An array with the computed cumulative maxima.
"""
return _process('cummax', data=data, ignore_nodata=ignore_nodata)
def cummax(data, ignore_nodata=UNSET) -> ProcessBuilder:
"""
Cumulative maxima
:param data: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default.
Setting this flag to `false` considers no-data values so that `null` is set for all the following elements.
:return: An array with the computed cumulative maxima.
"""
return _process('cummax', data=data, ignore_nodata=ignore_nodata)
def cummin(data, ignore_nodata=UNSET) -> ProcessBuilder:
"""
Cumulative minima
:param data: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting
this flag to `false` considers no-data values so that `null` is set for all the following elements.
:return: An array with the computed cumulative minima.
"""
return _process('cummin', data=data, ignore_nodata=ignore_nodata)
def cummin(data, ignore_nodata=UNSET) -> ProcessBuilder:
"""
Cumulative minima
:param data: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default.
Setting this flag to `false` considers no-data values so that `null` is set for all the following elements.
:return: An array with the computed cumulative minima.
"""
return _process('cummin', data=data, ignore_nodata=ignore_nodata)
def cumproduct(data, ignore_nodata=UNSET) -> ProcessBuilder:
"""
Cumulative products
:param data: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting
this flag to `false` considers no-data values so that `null` is set for all the following elements.
:return: An array with the computed cumulative products.
"""
return _process('cumproduct', data=data, ignore_nodata=ignore_nodata)
def cumproduct(data, ignore_nodata=UNSET) -> ProcessBuilder:
"""
Cumulative products
:param data: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default.
Setting this flag to `false` considers no-data values so that `null` is set for all the following elements.
:return: An array with the computed cumulative products.
"""
return _process('cumproduct', data=data, ignore_nodata=ignore_nodata)
def cumsum(data, ignore_nodata=UNSET) -> ProcessBuilder:
"""
Cumulative sums
:param data: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting
this flag to `false` considers no-data values so that `null` is set for all the following elements.
:return: An array with the computed cumulative sums.
"""
return _process('cumsum', data=data, ignore_nodata=ignore_nodata)
def cumsum(data, ignore_nodata=UNSET) -> ProcessBuilder:
"""
Cumulative sums
:param data: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default.
Setting this flag to `false` considers no-data values so that `null` is set for all the following elements.
:return: An array with the computed cumulative sums.
"""
return _process('cumsum', data=data, ignore_nodata=ignore_nodata)
def date_shift(date, value, unit) -> ProcessBuilder:
"""
Manipulates dates and times by addition or subtraction
:param date: The date (and optionally time) to manipulate. If the given date doesn't include the time, the
process assumes that the time component is `00:00:00Z` (i.e. midnight, in UTC). The millisecond part of the
time is optional and defaults to `0` if not given.
:param value: The period of time in the unit given that is added (positive numbers) or subtracted (negative
numbers). The value `0` doesn't have any effect.
:param unit: The unit for the value given. The following pre-defined units are available: - millisecond:
Milliseconds - second: Seconds - leap seconds are ignored in computations. - minute: Minutes - hour: Hours
- day: Days - changes only the the day part of a date - week: Weeks (equivalent to 7 days) - month: Months
- year: Years Manipulations with the unit `year`, `month`, `week` or `day` do never change the time. If
any of the manipulations result in an invalid date or time, the corresponding part is rounded down to the
next valid date or time respectively. For example, adding a month to `2020-01-31` would result in
`2020-02-29`.
:return: The manipulated date. If a time component was given in the parameter `date`, the time component is
returned with the date.
"""
return _process('date_shift', date=date, value=value, unit=unit)
def debug(data, code=UNSET, level=UNSET, message=UNSET) -> ProcessBuilder:
"""
Publish debugging information
:param data: Data to publish.
:param code: An identifier to help identify the log entry in a bunch of other log entries.
:param level: The severity level of this message, defaults to `info`. Note that the level `error` forces
the computation to be stopped!
:param message: A message to send in addition to the data.
:return: Returns the data as passed to the `data` parameter.
"""
return _process('debug', data=data, code=code, level=level, message=message)
def debug(data, code=UNSET, level=UNSET, message=UNSET) -> ProcessBuilder:
"""
Publish debugging information
:param data: Data to publish.
:param code: An identifier to help identify the log entry in a bunch of other log entries.
:param level: The severity level of this message, defaults to `info`. Note that the level `error` forces
the computation to be stopped!
:param message: A message to send in addition to the data.
:return: The data as passed to the `data` parameter without any modification.
"""
return _process('debug', data=data, code=code, level=level, message=message)
def dimension_labels(data, dimension) -> ProcessBuilder:
"""
Get the dimension labels
:param data: The data cube.
:param dimension: The name of the dimension to get the labels for.
:return: The labels as an array.
"""
return _process('dimension_labels', data=data, dimension=dimension)
def divide(x, y) -> ProcessBuilder:
"""
Division of two numbers
:param x: The dividend.
:param y: The divisor.
:return: The computed result.
"""
return _process('divide', x=x, y=y)
def drop_dimension(data, name) -> ProcessBuilder:
"""
Remove a dimension
:param data: The data cube to drop a dimension from.
:param name: Name of the dimension to drop.
:return: A data cube without the specified dimension. The number of dimensions decreases by one, but the
dimension properties (name, type, labels, reference system and resolution) for all other dimensions remain
unchanged.
"""
return _process('drop_dimension', data=data, name=name)
def e() -> ProcessBuilder:
"""
Euler's number (e)
:return: The numerical value of Euler's number.
"""
return _process('e', )
def eq(x, y, delta=UNSET, case_sensitive=UNSET) -> ProcessBuilder:
"""
Equal to comparison
:param x: First operand.
:param y: Second operand.
:param delta: Only applicable for comparing two numbers. If this optional parameter is set to a positive
non-zero number the equality of two numbers is checked against a delta value. This is especially useful to
circumvent problems with floating-point inaccuracy in machine-based computation. This option is basically
an alias for the following computation: `lte(abs(minus([x, y]), delta)`
:param case_sensitive: Only applicable for comparing two strings. Case sensitive comparison can be disabled
by setting this parameter to `false`.
:return: `true` if `x` is equal to `y`, `null` if any operand is `null`, otherwise `false`.
"""
return _process('eq', x=x, y=y, delta=delta, case_sensitive=case_sensitive)
def exp(p) -> ProcessBuilder:
"""
Exponentiation to the base e
:param p: The numerical exponent.
:return: The computed value for *e* raised to the power of `p`.
"""
return _process('exp', p=p)
def extrema(data, ignore_nodata=UNSET) -> ProcessBuilder:
"""
Minimum and maximum values
:param data: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting
this flag to `false` considers no-data values so that an array with two `null` values is returned if any
value is such a value.
:return: An array containing the minimum and maximum values for the specified numbers. The first element is
the minimum, the second element is the maximum. If the input array is empty both elements are set to
`null`.
"""
return _process('extrema', data=data, ignore_nodata=ignore_nodata)
def filter_bands(data, bands=UNSET, wavelengths=UNSET) -> ProcessBuilder:
"""
Filter the bands by names
:param data: A data cube with bands.
:param bands: A list of band names. Either the unique band name (metadata field `name` in bands) or one of
the common band names (metadata field `common_name` in bands). If the unique band name and the common name
conflict, the unique band name has a higher priority. The order of the specified array defines the order
of the bands in the data cube. If multiple bands match a common name, all matched bands are included in the
original order.
:param wavelengths: A list of sub-lists with each sub-list consisting of two elements. The first element is
the minimum wavelength and the second element is the maximum wavelength. Wavelengths are specified in
micrometers (μm). The order of the specified array defines the order of the bands in the data cube. If
multiple bands match the wavelengths, all matched bands are included in the original order.
:return: A data cube limited to a subset of its original bands. The dimensions and dimension properties
(name, type, labels, reference system and resolution) remain unchanged, except that the dimension of type
`bands` has less (or the same) dimension labels.
"""
return _process('filter_bands', data=data, bands=bands, wavelengths=wavelengths)
def filter_bbox(data, extent) -> ProcessBuilder:
"""
Spatial filter using a bounding box
:param data: A data cube.
:param extent: A bounding box, which may include a vertical axis (see `base` and `height`).
:return: A data cube restricted to the bounding box. The dimensions and dimension properties (name, type,
labels, reference system and resolution) remain unchanged, except that the spatial dimensions have less (or
the same) dimension labels.
"""
return _process('filter_bbox', data=data, extent=extent)
def filter_labels(data, condition, dimension, context=UNSET) -> ProcessBuilder:
"""
Filter dimension labels based on a condition
:param data: A data cube.
:param condition: A condition that is evaluated against each dimension label in the specified dimension. A
dimension label and the corresponding data is preserved for the given dimension, if the condition returns
`true`.
:param dimension: The name of the dimension to filter on. Fails with a `DimensionNotAvailable` error if the
specified dimension does not exist.
:param context: Additional data to be passed to the condition.
:return: A data cube with the same dimensions. The dimension properties (name, type, labels, reference
system and resolution) remain unchanged, except that the given dimension has less (or the same) dimension
labels.
"""
return _process('filter_labels', data=data, condition=condition, dimension=dimension, context=context)
def filter_labels(data, condition, dimension, context=UNSET) -> ProcessBuilder:
"""
Filter dimension labels based on a condition
:param data: A data cube.
:param condition: A condition that is evaluated against each dimension label in the specified dimension. A
dimension label and the corresponding data is preserved for the given dimension, if the condition returns
`true`.
:param dimension: The name of the dimension to filter on. Fails with a `DimensionNotAvailable` exception if
the specified dimension does not exist.
:param context: Additional data to be passed to the condition.
:return: A data cube with the same dimensions. The dimension properties (name, type, labels, reference
system and resolution) remain unchanged, except that the given dimension has less (or the same) dimension
labels.
"""
return _process('filter_labels', data=data, condition=condition, dimension=dimension, context=context)
def filter_spatial(data, geometries) -> ProcessBuilder:
"""
Spatial filter using geometries
:param data: A data cube.
:param geometries: One or more geometries used for filtering, specified as GeoJSON.
:return: A data cube restricted to the specified geometries. The dimensions and dimension properties (name,
type, labels, reference system and resolution) remain unchanged, except that the spatial dimensions have
less (or the same) dimension labels.
"""
return _process('filter_spatial', data=data, geometries=geometries)
def filter_temporal(data, extent, dimension=UNSET) -> ProcessBuilder:
"""
Temporal filter for a temporal intervals
:param data: A data cube.
:param extent: Left-closed temporal interval, i.e. an array with exactly two elements: 1. The first
element is the start of the temporal interval. The specified instance in time is **included** in the
interval. 2. The second element is the end of the temporal interval. The specified instance in time is
**excluded** from the interval. The specified temporal strings follow [RFC 3339](https://www.rfc-
editor.org/rfc/rfc3339.html). Also supports open intervals by setting one of the boundaries to `null`, but
never both.
:param dimension: The name of the temporal dimension to filter on. If no specific dimension is specified or
it is set to `null`, the filter applies to all temporal dimensions. Fails with a `DimensionNotAvailable`
exception if the specified dimension does not exist.
:return: A data cube restricted to the specified temporal extent. The dimensions and dimension properties
(name, type, labels, reference system and resolution) remain unchanged, except that the temporal dimensions
(determined by `dimensions` parameter) may have less dimension labels.
"""
return _process('filter_temporal', data=data, extent=extent, dimension=dimension)
def first(data, ignore_nodata=UNSET) -> ProcessBuilder:
"""
First element
:param data: An array with elements of any data type.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting
this flag to `false` considers no-data values so that `null` is returned if the first value is such a
value.
:return: The first element of the input array.
"""
return _process('first', data=data, ignore_nodata=ignore_nodata)
def floor(x) -> ProcessBuilder:
"""
Round fractions down
:param x: A number to round down.
:return: The number rounded down.
"""
return _process('floor', x=x)
def gt(x, y) -> ProcessBuilder:
"""
Greater than comparison
:param x: First operand.
:param y: Second operand.
:return: `true` if `x` is strictly greater than `y` or `null` if any operand is `null`, otherwise `false`.
"""
return _process('gt', x=x, y=y)
def gte(x, y) -> ProcessBuilder:
"""
Greater than or equal to comparison
:param x: First operand.
:param y: Second operand.
:return: `true` if `x` is greater than or equal to `y`, `null` if any operand is `null`, otherwise `false`.
"""
return _process('gte', x=x, y=y)
def if_(value, accept, reject=UNSET) -> ProcessBuilder:
"""
If-Then-Else conditional
:param value: A boolean value.
:param accept: A value that is returned if the boolean value is `true`.
:param reject: A value that is returned if the boolean value is **not** `true`. Defaults to `null`.
:return: Either the `accept` or `reject` argument depending on the given boolean value.
"""
return _process('if', value=value, accept=accept, reject=reject)
def int(x) -> ProcessBuilder:
"""
Integer part of a number
:param x: A number.
:return: Integer part of the number.
"""
return _process('int', x=x)
def is_infinite(x) -> ProcessBuilder:
"""
Value is an infinite number
:param x: The data to check.
:return: `true` if the data is an infinite number, otherwise `false`.
"""
return _process('is_infinite', x=x)
def is_nan(x) -> ProcessBuilder:
"""
Value is not a number
:param x: The data to check.
:return: `true` if the data is not a number, otherwise `false`.
"""
return _process('is_nan', x=x)
def is_nodata(x) -> ProcessBuilder:
"""
Value is not a no-data value
:param x: The data to check.
:return: `true` if the data is a no-data value, otherwise `false`.
"""
return _process('is_nodata', x=x)
def is_valid(x) -> ProcessBuilder:
"""
Value is valid data
:param x: The data to check.
:return: `true` if the data is valid, otherwise `false`.
"""
return _process('is_valid', x=x)
def last(data, ignore_nodata=UNSET) -> ProcessBuilder:
"""
Last element
:param data: An array with elements of any data type.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting
this flag to `false` considers no-data values so that `null` is returned if the last value is such a value.
:return: The last element of the input array.
"""
return _process('last', data=data, ignore_nodata=ignore_nodata)
def linear_scale_range(x, inputMin, inputMax, outputMin=UNSET, outputMax=UNSET) -> ProcessBuilder:
"""
Linear transformation between two ranges
:param x: A number to transform. The number gets clipped to the bounds specified in `inputMin` and
`inputMax`.
:param inputMin: Minimum value the input can obtain.
:param inputMax: Maximum value the input can obtain.
:param outputMin: Minimum value of the desired output range.
:param outputMax: Maximum value of the desired output range.
:return: The transformed number.
"""
return _process('linear_scale_range', x=x, inputMin=inputMin, inputMax=inputMax, outputMin=outputMin, outputMax=outputMax)
def ln(x) -> ProcessBuilder:
"""
Natural logarithm
:param x: A number to compute the natural logarithm for.
:return: The computed natural logarithm.
"""
return _process('ln', x=x)
def load_collection(id, spatial_extent, temporal_extent, bands=UNSET, properties=UNSET) -> ProcessBuilder:
"""
Load a collection
:param id: The collection id.
:param spatial_extent: Limits the data to load from the collection to the specified bounding box or
polygons. The process puts a pixel into the data cube if the point at the pixel center intersects with the
bounding box or any of the polygons (as defined in the Simple Features standard by the OGC). The GeoJSON
can be one of the following feature types: * A `Polygon` or `MultiPolygon` geometry, * a `Feature` with a
`Polygon` or `MultiPolygon` geometry, * a `FeatureCollection` containing at least one `Feature` with
`Polygon` or `MultiPolygon` geometries, or * a `GeometryCollection` containing `Polygon` or `MultiPolygon`
geometries. To maximize interoperability, `GeometryCollection` should be avoided in favour of one of the
alternatives above. Set this parameter to `null` to set no limit for the spatial extent. Be careful with
this when loading large datasets! It is recommended to use this parameter instead of using
``filter_bbox()`` or ``filter_spatial()`` directly after loading unbounded data.
:param temporal_extent: Limits the data to load from the collection to the specified left-closed temporal
interval. Applies to all temporal dimensions. The interval has to be specified as an array with exactly two
elements: 1. The first element is the start of the temporal interval. The specified instance in time is
**included** in the interval. 2. The second element is the end of the temporal interval. The specified
instance in time is **excluded** from the interval. The specified temporal strings follow [RFC
3339](https://www.rfc-editor.org/rfc/rfc3339.html). Also supports open intervals by setting one of the
boundaries to `null`, but never both. Set this parameter to `null` to set no limit for the temporal
extent. Be careful with this when loading large datasets! It is recommended to use this parameter instead
of using ``filter_temporal()`` directly after loading unbounded data.
:param bands: Only adds the specified bands into the data cube so that bands that don't match the list of
band names are not available. Applies to all dimensions of type `bands`. Either the unique band name
(metadata field `name` in bands) or one of the common band names (metadata field `common_name` in bands)
can be specified. If the unique band name and the common name conflict, the unique band name has a higher
priority. The order of the specified array defines the order of the bands in the data cube. If multiple
bands match a common name, all matched bands are included in the original order. It is recommended to use
this parameter instead of using ``filter_bands()`` directly after loading unbounded data.
:param properties: Limits the data by metadata properties to include only data in the data cube which all
given conditions return `true` for (AND operation). Specify key-value-pairs with the key being the name of
the metadata property, which can be retrieved with the openEO Data Discovery for Collections. The value
must a condition (user-defined process) to be evaluated against the collection metadata, see the example.
:return: A data cube for further processing. The dimensions and dimension properties (name, type, labels,
reference system and resolution) correspond to the collection's metadata, but the dimension labels are
restricted as specified in the parameters.
"""
return _process('load_collection', id=id, spatial_extent=spatial_extent, temporal_extent=temporal_extent, bands=bands, properties=properties)
def load_result(id) -> ProcessBuilder:
"""
Load batch job results
:param id: The id of a batch job with results.
:return: A data cube for further processing.
"""
return _process('load_result', id=id)
def load_result(id) -> ProcessBuilder:
"""
Load batch job results
:param id: The id of a batch job with results.
:return: A data cube for further processing.
"""
return _process('load_result', id=id)
def load_uploaded_files(paths, format, options=UNSET) -> ProcessBuilder:
"""
Load files from the user workspace
:param paths: The files to read. Folders can't be specified, instead specify all files. An error is thrown
if a file can't be read.
:param format: The file format to read from. It must be one of the values that the server reports as
supported input file formats, which usually correspond to the short GDAL/OGR codes. If the format is not
suitable for loading the data, a `FormatUnsuitable` exception will be thrown. This parameter is *case
insensitive*.
:param options: The file format parameters to be used to read the files. Must correspond to the parameters
that the server reports as supported parameters for the chosen `format`. The parameter names and valid
values usually correspond to the GDAL/OGR format options.
:return: A data cube for further processing.
"""
return _process('load_uploaded_files', paths=paths, format=format, options=options)
def load_uploaded_files(paths, format, options=UNSET) -> ProcessBuilder:
"""
Load files from the user workspace
:param paths: The files to read. Folders can't be specified, specify all files instead. An exception is
thrown if a file can't be read.
:param format: The file format to read from. It must be one of the values that the server reports as
supported input file formats, which usually correspond to the short GDAL/OGR codes. If the format is not
suitable for loading the data, a `FormatUnsuitable` exception will be thrown. This parameter is *case
insensitive*.
:param options: The file format parameters to be used to read the files. Must correspond to the parameters
that the server reports as supported parameters for the chosen `format`. The parameter names and valid
values usually correspond to the GDAL/OGR format options.
:return: A data cube for further processing.
"""
return _process('load_uploaded_files', paths=paths, format=format, options=options)
def log(x, base) -> ProcessBuilder:
"""
Logarithm to a base
:param x: A number to compute the logarithm for.
:param base: The numerical base.
:return: The computed logarithm.
"""
return _process('log', x=x, base=base)
def lt(x, y) -> ProcessBuilder:
"""
Less than comparison
:param x: First operand.
:param y: Second operand.
:return: `true` if `x` is strictly less than `y`, `null` if any operand is `null`, otherwise `false`.
"""
return _process('lt', x=x, y=y)
def lte(x, y) -> ProcessBuilder:
"""
Less than or equal to comparison
:param x: First operand.
:param y: Second operand.
:return: `true` if `x` is less than or equal to `y`, `null` if any operand is `null`, otherwise `false`.
"""
return _process('lte', x=x, y=y)
def mask(data, mask, replacement=UNSET) -> ProcessBuilder:
"""
Apply a raster mask
:param data: A raster data cube.
:param mask: A mask as a raster data cube. Every pixel in `data` must have a corresponding element in
`mask`.
:param replacement: The value used to replace masked values with.
:return: A masked raster data cube with the same dimensions. The dimension properties (name, type, labels,
reference system and resolution) remain unchanged.
"""
return _process('mask', data=data, mask=mask, replacement=replacement)
def mask_polygon(data, mask, replacement=UNSET, inside=UNSET) -> ProcessBuilder:
"""
Apply a polygon mask
:param data: A raster data cube.
:param mask: A GeoJSON object containing at least one polygon. The provided feature types can be one of the
following: * A `Polygon` or `MultiPolygon` geometry, * a `Feature` with a `Polygon` or `MultiPolygon`
geometry, * a `FeatureCollection` containing at least one `Feature` with `Polygon` or `MultiPolygon`
geometries, or * a `GeometryCollection` containing `Polygon` or `MultiPolygon` geometries. To maximize
interoperability, `GeometryCollection` should be avoided in favour of one of the alternatives above.
:param replacement: The value used to replace masked values with.
:param inside: If set to `true` all pixels for which the point at the pixel center **does** intersect with
any polygon are replaced.
:return: A masked raster data cube with the same dimensions. The dimension properties (name, type, labels,
reference system and resolution) remain unchanged.
"""
return _process('mask_polygon', data=data, mask=mask, replacement=replacement, inside=inside)
def max(data, ignore_nodata=UNSET) -> ProcessBuilder:
"""
Maximum value
:param data: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting
this flag to `false` considers no-data values so that `null` is returned if any value is such a value.
:return: The maximum value.
"""
return _process('max', data=data, ignore_nodata=ignore_nodata)
def mean(data, ignore_nodata=UNSET) -> ProcessBuilder:
"""
Arithmetic mean (average)
:param data: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting
this flag to `false` considers no-data values so that `null` is returned if any value is such a value.
:return: The computed arithmetic mean.
"""
return _process('mean', data=data, ignore_nodata=ignore_nodata)
def median(data, ignore_nodata=UNSET) -> ProcessBuilder:
"""
Statistical median
:param data: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting
this flag to `false` considers no-data values so that `null` is returned if any value is such a value.
:return: The computed statistical median.
"""
return _process('median', data=data, ignore_nodata=ignore_nodata)
def merge_cubes(cube1, cube2, overlap_resolver=UNSET, context=UNSET) -> ProcessBuilder:
"""
Merge two data cubes
:param cube1: The first data cube.
:param cube2: The second data cube.
:param overlap_resolver: A reduction operator that resolves the conflict if the data overlaps. The reducer
must return a value of the same data type as the input values are. The reduction operator may be a single
process such as ``multiply()`` or consist of multiple sub-processes. `null` (the default) can be specified
if no overlap resolver is required.
:param context: Additional data to be passed to the overlap resolver.
:return: The merged data cube. See the process description for details regarding the dimensions and
dimension properties (name, type, labels, reference system and resolution).
"""
return _process('merge_cubes', cube1=cube1, cube2=cube2, overlap_resolver=overlap_resolver, context=context)
def min(data, ignore_nodata=UNSET) -> ProcessBuilder:
"""
Minimum value
:param data: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting
this flag to `false` considers no-data values so that `null` is returned if any value is such a value.
:return: The minimum value.
"""
return _process('min', data=data, ignore_nodata=ignore_nodata)
def mod(x, y) -> ProcessBuilder:
"""
Modulo
:param x: A number to be used as the dividend.
:param y: A number to be used as the divisor.
:return: The remainder after division.
"""
return _process('mod', x=x, y=y)
def multiply(x, y) -> ProcessBuilder:
"""
Multiplication of two numbers
:param x: The multiplier.
:param y: The multiplicand.
:return: The computed product of the two numbers.
"""
return _process('multiply', x=x, y=y)
def nan() -> ProcessBuilder:
"""
Not a Number (NaN)
:return: Returns `NaN`.
"""
return _process('nan', )
def ndvi(data, nir=UNSET, red=UNSET, target_band=UNSET) -> ProcessBuilder:
"""
Normalized Difference Vegetation Index
:param data: A raster data cube with two bands that have the common names `red` and `nir` assigned.
:param nir: The name of the NIR band. Defaults to the band that has the common name `nir` assigned. Either
the unique band name (metadata field `name` in bands) or one of the common band names (metadata field
`common_name` in bands) can be specified. If the unique band name and the common name conflict, the unique
band name has a higher priority.
:param red: The name of the red band. Defaults to the band that has the common name `red` assigned. Either
the unique band name (metadata field `name` in bands) or one of the common band names (metadata field
`common_name` in bands) can be specified. If the unique band name and the common name conflict, the unique
band name has a higher priority.
:param target_band: By default, the dimension of type `bands` is dropped. To keep the dimension specify a
new band name in this parameter so that a new dimension label with the specified name will be added for the
computed values.
:return: A raster data cube containing the computed NDVI values. The structure of the data cube differs
depending on the value passed to `target_band`: * `target_band` is `null`: The data cube does not contain
the dimension of type `bands`, the number of dimensions decreases by one. The dimension properties (name,
type, labels, reference system and resolution) for all other dimensions remain unchanged. * `target_band`
is a string: The data cube keeps the same dimensions. The dimension properties remain unchanged, but the
number of dimension labels for the dimension of type `bands` increases by one. The additional label is
named as specified in `target_band`.
"""
return _process('ndvi', data=data, nir=nir, red=red, target_band=target_band)
def neq(x, y, delta=UNSET, case_sensitive=UNSET) -> ProcessBuilder:
"""
Not equal to comparison
:param x: First operand.
:param y: Second operand.
:param delta: Only applicable for comparing two numbers. If this optional parameter is set to a positive
non-zero number the non-equality of two numbers is checked against a delta value. This is especially useful
to circumvent problems with floating-point inaccuracy in machine-based computation. This option is
basically an alias for the following computation: `gt(abs(minus([x, y]), delta)`
:param case_sensitive: Only applicable for comparing two strings. Case sensitive comparison can be disabled
by setting this parameter to `false`.
:return: `true` if `x` is *not* equal to `y`, `null` if any operand is `null`, otherwise `false`.
"""
return _process('neq', x=x, y=y, delta=delta, case_sensitive=case_sensitive)
def normalized_difference(x, y) -> ProcessBuilder:
"""
Normalized difference
:param x: The value for the first band.
:param y: The value for the second band.
:return: The computed normalized difference.
"""
return _process('normalized_difference', x=x, y=y)
def not_(x) -> ProcessBuilder:
"""
Inverting a boolean
:param x: Boolean value to invert.
:return: Inverted boolean value.
"""
return _process('not', x=x)
def or_(x, y) -> ProcessBuilder:
"""
Logical OR
:param x: A boolean value.
:param y: A boolean value.
:return: Boolean result of the logical OR.
"""
return _process('or', x=x, y=y)
def order(data, asc=UNSET, nodata=UNSET) -> ProcessBuilder:
"""
Create a permutation
:param data: An array to compute the order for.
:param asc: The default sort order is ascending, with smallest values first. To sort in reverse
(descending) order, set this parameter to `false`.
:param nodata: Controls the handling of no-data values (`null`). By default, they are removed. If set to
`true`, missing values in the data are put last; if set to `false`, they are put first.
:return: The computed permutation.
"""
return _process('order', data=data, asc=asc, nodata=nodata)
def pi() -> ProcessBuilder:
"""
Pi (π)
:return: The numerical value of Pi.
"""
return _process('pi', )
def power(base, p) -> ProcessBuilder:
"""
Exponentiation
:param base: The numerical base.
:param p: The numerical exponent.
:return: The computed value for `base` raised to the power of `p`.
"""
return _process('power', base=base, p=p)
def product(data, ignore_nodata=UNSET) -> ProcessBuilder:
"""
Compute the product by multiplying numbers
:param data: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting
this flag to `false` considers no-data values so that `null` is returned if any value is such a value.
:return: The computed product of the sequence of numbers.
"""
return _process('product', data=data, ignore_nodata=ignore_nodata)
def quantiles(data, probabilities=UNSET, q=UNSET, ignore_nodata=UNSET) -> ProcessBuilder:
"""
Quantiles
:param data: An array of numbers.
:param probabilities: A list of probabilities to calculate quantiles for. The probabilities must be between
0 and 1.
:param q: Intervals to calculate quantiles for. Calculates q-quantiles with (nearly) equal-sized intervals.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting
this flag to `false` considers no-data values so that an array with `null` values is returned if any
element is such a value.
:return: An array with the computed quantiles. The list has either * as many elements as the given list of
`probabilities` had or * *`q`-1* elements. If the input array is empty the resulting array is filled with
as many `null` values as required according to the list above. See the 'Empty array' example for an
example.
"""
return _process('quantiles', data=data, probabilities=probabilities, q=q, ignore_nodata=ignore_nodata)
def rearrange(data, order) -> ProcessBuilder:
"""
Rearrange an array based on a permutation
:param data: The array to rearrange.
:param order: The permutation used for rearranging.
:return: The rearranged array.
"""
return _process('rearrange', data=data, order=order)
def reduce_dimension(data, reducer, dimension, context=UNSET) -> ProcessBuilder:
"""
Reduce dimensions
:param data: A data cube.
:param reducer: A reducer to apply on the specified dimension. A reducer is a single process such as
``mean()`` or a set of processes, which computes a single value for a list of values, see the category
'reducer' for such processes.
:param dimension: The name of the dimension over which to reduce. Fails with a `DimensionNotAvailable`
exception if the specified dimension does not exist.
:param context: Additional data to be passed to the reducer.
:return: A data cube with the newly computed values. It is missing the given dimension, the number of
dimensions decreases by one. The dimension properties (name, type, labels, reference system and resolution)
for all other dimensions remain unchanged.
"""
return _process('reduce_dimension', data=data, reducer=reducer, dimension=dimension, context=context)
def reduce_dimension_binary(data, reducer, dimension, context=UNSET) -> ProcessBuilder:
"""
Reduce dimensions using binary reduction
:param data: A data cube.
:param reducer: A reduction operator to be applied consecutively on pairs of values. It must be both
associative and commutative as the execution may be executed in parallel and therefore the order of
execution is arbitrary. The reduction operator may be a single process such as ``multiply()`` or consist of
multiple sub-processes.
:param dimension: The name of the dimension over which to reduce. Fails with a `DimensionNotAvailable`
error if the specified dimension does not exist.
:param context: Additional data to be passed to the reducer.
:return: A data cube with the newly computed values. It is missing the given dimension, the number of
dimensions decreases by one. The dimension properties (name, type, labels, reference system and resolution)
for all other dimensions remain unchanged.
"""
return _process('reduce_dimension_binary', data=data, reducer=reducer, dimension=dimension, context=context)
def reduce_spatial(data, reducer, context=UNSET) -> ProcessBuilder:
"""
Reduce spatial dimensions 'x' and 'y'
:param data: A data cube.
:param reducer: A reducer to apply on the horizontal spatial dimensions. A reducer is a single process such
as ``mean()`` or a set of processes, which computes a single value for a list of values, see the category
'reducer' for such processes.
:param context: Additional data to be passed to the reducer.
:return: A data cube with the newly computed values. It is missing the horizontal spatial dimensions, the
number of dimensions decreases by two. The dimension properties (name, type, labels, reference system and
resolution) for all other dimensions remain unchanged.
"""
return _process('reduce_spatial', data=data, reducer=reducer, context=context)
def rename_dimension(data, source, target) -> ProcessBuilder:
"""
Rename a dimension
:param data: The data cube.
:param source: The current name of the dimension. Fails with a `DimensionNotAvailable` exception if the
specified dimension does not exist.
:param target: A new Name for the dimension. Fails with a `DimensionExists` exception if a dimension with
the specified name exists.
:return: A data cube with the same dimensions, but the name of one of the dimensions changes. The old name
can not be referred to any longer. The dimension properties (name, type, labels, reference system and
resolution) remain unchanged.
"""
return _process('rename_dimension', data=data, source=source, target=target)
def rename_labels(data, dimension, target, source=UNSET) -> ProcessBuilder:
"""
Rename dimension labels
:param data: The data cube.
:param dimension: The name of the dimension to rename the labels for.
:param target: The new names for the labels. The dimension labels in the data cube are expected to be
enumerated if the parameter `target` is not specified. If a target dimension label already exists in the
data cube, a `LabelExists` exception is thrown.
:param source: The names of the labels as they are currently in the data cube. The array defines an
unsorted and potentially incomplete list of labels that should be renamed to the names available in the
corresponding array elements in the parameter `target`. If one of the source dimension labels doesn't
exist, the `LabelNotAvailable` exception is thrown. By default, the array is empty so that the dimension
labels in the data cube are expected to be enumerated.
:return: The data cube with the same dimensions. The dimension properties (name, type, labels, reference
system and resolution) remain unchanged, except that for the given dimension the labels change. The old
labels can not be referred to any longer. The number of labels remains the same.
"""
return _process('rename_labels', data=data, dimension=dimension, target=target, source=source)
def resample_cube_spatial(data, target, method=UNSET) -> ProcessBuilder:
"""
Resample the spatial dimensions to match a target data cube
:param data: A data cube.
:param target: A data cube that describes the spatial target resolution.
:param method: Resampling method to use. The following options are available and are meant to align with
[`gdalwarp`](https://gdal.org/programs/gdalwarp.html#cmdoption-gdalwarp-r): * `average`: average (mean)
resampling, computes the weighted average of all valid pixels * `bilinear`: bilinear resampling * `cubic`:
cubic resampling * `cubicspline`: cubic spline resampling * `lanczos`: Lanczos windowed sinc resampling *
`max`: maximum resampling, selects the maximum value from all valid pixels * `med`: median resampling,
selects the median value of all valid pixels * `min`: minimum resampling, selects the minimum value from
all valid pixels * `mode`: mode resampling, selects the value which appears most often of all the sampled
points * `near`: nearest neighbour resampling (default) * `q1`: first quartile resampling, selects the
first quartile value of all valid pixels * `q3`: third quartile resampling, selects the third quartile
value of all valid pixels * `rms` root mean square (quadratic mean) of all valid pixels * `sum`: compute
the weighted sum of all valid pixels Valid pixels are determined based on the function ``is_valid()``.
:return: A data cube with the same dimensions. The dimension properties (name, type, labels, reference
system and resolution) remain unchanged, except for the resolution and dimension labels of the spatial
dimensions.
"""
return _process('resample_cube_spatial', data=data, target=target, method=method)
def resample_cube_temporal(data, target, method, dimension=UNSET, context=UNSET) -> ProcessBuilder:
"""
Resample a temporal dimension to match a target data cube
:param data: A data cube.
:param target: A data cube that describes the temporal target resolution.
:param method: A resampling method to be applied, could be a reducer for downsampling or other methods for
upsampling. A reducer is a single process such as ``mean()`` or a set of processes, which computes a single
value for a list of values, see the category 'reducer' for such processes.
:param dimension: The name of the temporal dimension to resample, which must exist with this name in both
data cubes. If the dimension is not set or is set to `null`, the data cube is expected to only have one
temporal dimension. Fails with a `TooManyDimensions` error if it has more dimensions. Fails with a
`DimensionNotAvailable` error if the specified dimension does not exist.
:param context: Additional data to be passed to the process specified for the parameter `method`.
:return: A raster data cube with the same dimensions and the same dimension properties (name, type, labels,
reference system and resolution) for all non-temporal dimensions. For the temporal dimension the name and
type remain unchanged, but the reference system changes and the labels and resolution may change.
"""
return _process('resample_cube_temporal', data=data, target=target, method=method, dimension=dimension, context=context)
def resample_cube_temporal(data, target, dimension=UNSET, valid_within=UNSET) -> ProcessBuilder:
"""
Resample temporal dimensions to match a target data cube
:param data: A data cube with one or more temporal dimensions.
:param target: A data cube that describes the temporal target resolution.
:param dimension: The name of the temporal dimension to resample, which must exist with this name in both
data cubes. If the dimension is not set or is set to `null`, the process resamples all temporal dimensions
that exist with the same names in both data cubes. The following exceptions may occur: * A dimension is
given, but it does not exist in any of the data cubes: `DimensionNotAvailable` * A dimension is given, but
one of them is not temporal: `DimensionMismatch` * No specific dimension name is given and there are no
temporal dimensions with the same name in the data: `DimensionMismatch`
:param valid_within: Setting this parameter to a numerical value enables that the process searches for
valid values within the given period of days before and after the target timestamps. Valid values are
determined based on the function ``is_valid()``. For example, the limit of `7` for the target timestamps
`2020-01-15 12:00:00` looks for a nearest neighbor after `2020-01-08 12:00:00` and before `2020-01-22
12:00:00`. If no valid value is found within the given period, the value will be set to no-data (`null`).
:return: A raster data cube with the same dimensions and the same dimension properties (name, type, labels,
reference system and resolution) for all non-temporal dimensions. For the temporal dimension, the name and
type remain unchanged, but the dimension labels, resolution and reference system may change.
"""
return _process('resample_cube_temporal', data=data, target=target, dimension=dimension, valid_within=valid_within)
def resample_spatial(data, resolution=UNSET, projection=UNSET, method=UNSET, align=UNSET) -> ProcessBuilder:
"""
Resample and warp the spatial dimensions
:param data: A raster data cube.
:param resolution: Resamples the data cube to the target resolution, which can be specified either as
separate values for x and y or as a single value for both axes. Specified in the units of the target
projection. Doesn't change the resolution by default (`0`).
:param projection: Warps the data cube to the target projection, specified as as [EPSG
code](http://www.epsg-registry.org/), [WKT2 (ISO 19162)
string](http://docs.opengeospatial.org/is/18-010r7/18-010r7.html), [PROJ definition
(deprecated)](https://proj.org/usage/quickstart.html). By default (`null`), the projection is not changed.
:param method: Resampling method to use. The following options are available and are meant to align with
[`gdalwarp`](https://gdal.org/programs/gdalwarp.html#cmdoption-gdalwarp-r): * `average`: average (mean)
resampling, computes the weighted average of all valid pixels * `bilinear`: bilinear resampling * `cubic`:
cubic resampling * `cubicspline`: cubic spline resampling * `lanczos`: Lanczos windowed sinc resampling *
`max`: maximum resampling, selects the maximum value from all valid pixels * `med`: median resampling,
selects the median value of all valid pixels * `min`: minimum resampling, selects the minimum value from
all valid pixels * `mode`: mode resampling, selects the value which appears most often of all the sampled
points * `near`: nearest neighbour resampling (default) * `q1`: first quartile resampling, selects the
first quartile value of all valid pixels * `q3`: third quartile resampling, selects the third quartile
value of all valid pixels * `rms` root mean square (quadratic mean) of all valid pixels * `sum`: compute
the weighted sum of all valid pixels Valid pixels are determined based on the function ``is_valid()``.
:param align: Specifies to which corner of the spatial extent the new resampled data is aligned to.
:return: A raster data cube with values warped onto the new projection. It has the same dimensions and the
same dimension properties (name, type, labels, reference system and resolution) for all non-spatial or
vertical spatial dimensions. For the horizontal spatial dimensions the name and type remain unchanged, but
reference system, labels and resolution may change depending on the given parameters.
"""
return _process('resample_spatial', data=data, resolution=resolution, projection=projection, method=method, align=align)
def round(x, p=UNSET) -> ProcessBuilder:
"""
Round to a specified precision
:param x: A number to round.
:param p: A positive number specifies the number of digits after the decimal point to round to. A negative
number means rounding to a power of ten, so for example *-2* rounds to the nearest hundred. Defaults to
*0*.
:return: The rounded number.
"""
return _process('round', x=x, p=p)
def run_udf(data, udf, runtime, version=UNSET, context=UNSET) -> ProcessBuilder:
"""
Run a UDF
:param data: The data to be passed to the UDF as an array or raster data cube.
:param udf: Either source code, an absolute URL or a path to a UDF script.
:param runtime: A UDF runtime identifier available at the back-end.
:param version: An UDF runtime version. If set to `null`, the default runtime version specified for each
runtime is used.
:param context: Additional data such as configuration options to be passed to the UDF.
:return: The data processed by the UDF. * Returns a raster data cube, if a raster data cube is passed for
`data`. Details on the dimensions and dimension properties (name, type, labels, reference system and
resolution) depend on the UDF. * If an array is passed for `data`, the returned value can be of any data
type, but is exactly what the UDF returns.
"""
return _process('run_udf', data=data, udf=udf, runtime=runtime, version=version, context=context)
def run_udf_externally(data, url, context=UNSET) -> ProcessBuilder:
"""
Run an externally hosted UDF container
:param data: The data to be passed to the UDF as array or raster data cube.
:param url: URL to a remote UDF service.
:param context: Additional data such as configuration options that should be passed to the UDF.
:return: The data processed by the UDF service. * Returns a raster data cube, if a raster data cube is
passed for `data`. Details on the dimensions and dimension properties (name, type, labels, reference system
and resolution) depend on the UDF. * If an array is passed for `data`, the returned value can be of any
data type, but is exactly what the UDF returns.
"""
return _process('run_udf_externally', data=data, url=url, context=context)
def run_udf_externally(data, url, context=UNSET) -> ProcessBuilder:
"""
Run an externally hosted UDF container
:param data: The data to be passed to the UDF as an array or raster data cube.
:param url: Absolute URL to a remote UDF service.
:param context: Additional data such as configuration options to be passed to the UDF.
:return: The data processed by the UDF service. * Returns a raster data cube if a raster data cube is
passed for `data`. Details on the dimensions and dimension properties (name, type, labels, reference system
and resolution) depend on the UDF. * If an array is passed for `data`, the returned value can be of any
data type, but is exactly what the UDF returns.
"""
return _process('run_udf_externally', data=data, url=url, context=context)
def sar_backscatter(data, coefficient=UNSET, elevation_model=UNSET, mask=UNSET, contributing_area=UNSET, local_incidence_angle=UNSET, ellipsoid_incidence_angle=UNSET, noise_removal=UNSET) -> ProcessBuilder:
"""
Computes backscatter from SAR input
:param data: The source data cube containing SAR input.
:param coefficient: Select the radiometric correction coefficient. The following options are available: *
`beta0`: radar brightness * `sigma0-ellipsoid`: ground area computed with ellipsoid earth model *
`sigma0-terrain`: ground area computed with terrain earth model * `gamma0-ellipsoid`: ground area computed
with ellipsoid earth model in sensor line of sight * `gamma0-terrain`: ground area computed with terrain
earth model in sensor line of sight (default) * `null`: non-normalized backscatter
:param elevation_model: The digital elevation model to use. Set to `null` (the default) to allow the back-
end to choose, which will improve portability, but reduce reproducibility.
:param mask: If set to `true`, a data mask is added to the bands with the name `mask`. It indicates which
values are valid (1), invalid (0) or contain no-data (null).
:param contributing_area: If set to `true`, a DEM-based local contributing area band named
`contributing_area` is added. The values are given in square meters.
:param local_incidence_angle: If set to `true`, a DEM-based local incidence angle band named
`local_incidence_angle` is added. The values are given in degrees.
:param ellipsoid_incidence_angle: If set to `true`, an ellipsoidal incidence angle band named
`ellipsoid_incidence_angle` is added. The values are given in degrees.
:param noise_removal: If set to `false`, no noise removal is applied. Defaults to `true`, which removes
noise.
:return: Backscatter values corresponding to the chosen parametrization. The values are given in linear
scale.
"""
return _process('sar_backscatter', data=data, coefficient=coefficient, elevation_model=elevation_model, mask=mask, contributing_area=contributing_area, local_incidence_angle=local_incidence_angle, ellipsoid_incidence_angle=ellipsoid_incidence_angle, noise_removal=noise_removal)
def save_result(data, format, options=UNSET) -> ProcessBuilder:
"""
Save processed data to storage
:param data: The data to save.
:param format: The file format to save to. It must be one of the values that the server reports as
supported output file formats, which usually correspond to the short GDAL/OGR codes. If the format is not
suitable for storing the underlying data structure, a `FormatUnsuitable` exception will be thrown. This
parameter is *case insensitive*.
:param options: The file format parameters to be used to create the file(s). Must correspond to the
parameters that the server reports as supported parameters for the chosen `format`. The parameter names and
valid values usually correspond to the GDAL/OGR format options.
:return: `false` if saving failed, `true` otherwise.
"""
return _process('save_result', data=data, format=format, options=options)
def sd(data, ignore_nodata=UNSET) -> ProcessBuilder:
"""
Standard deviation
:param data: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting
this flag to `false` considers no-data values so that `null` is returned if any value is such a value.
:return: The computed sample standard deviation.
"""
return _process('sd', data=data, ignore_nodata=ignore_nodata)
def sgn(x) -> ProcessBuilder:
"""
Signum
:param x: A number.
:return: The computed signum value of `x`.
"""
return _process('sgn', x=x)
def sin(x) -> ProcessBuilder:
"""
Sine
:param x: An angle in radians.
:return: The computed sine of `x`.
"""
return _process('sin', x=x)
def sinh(x) -> ProcessBuilder:
"""
Hyperbolic sine
:param x: An angle in radians.
:return: The computed hyperbolic sine of `x`.
"""
return _process('sinh', x=x)
def sort(data, asc=UNSET, nodata=UNSET) -> ProcessBuilder:
"""
Sort data
:param data: An array with data to sort.
:param asc: The default sort order is ascending, with smallest values first. To sort in reverse
(descending) order, set this parameter to `false`.
:param nodata: Controls the handling of no-data values (`null`). By default, they are removed. If set to
`true`, missing values in the data are put last; if set to `false`, they are put first.
:return: The sorted array.
"""
return _process('sort', data=data, asc=asc, nodata=nodata)
def sqrt(x) -> ProcessBuilder:
"""
Square root
:param x: A number.
:return: The computed square root.
"""
return _process('sqrt', x=x)
def subtract(x, y) -> ProcessBuilder:
"""
Subtraction of two numbers
:param x: The minuend.
:param y: The subtrahend.
:return: The computed result.
"""
return _process('subtract', x=x, y=y)
def sum(data, ignore_nodata=UNSET) -> ProcessBuilder:
"""
Compute the sum by adding up numbers
:param data: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting
this flag to `false` considers no-data values so that `null` is returned if any value is such a value.
:return: The computed sum of the sequence of numbers.
"""
return _process('sum', data=data, ignore_nodata=ignore_nodata)
def tan(x) -> ProcessBuilder:
"""
Tangent
:param x: An angle in radians.
:return: The computed tangent of `x`.
"""
return _process('tan', x=x)
def tanh(x) -> ProcessBuilder:
"""
Hyperbolic tangent
:param x: An angle in radians.
:return: The computed hyperbolic tangent of `x`.
"""
return _process('tanh', x=x)
def text_begins(data, pattern, case_sensitive=UNSET) -> ProcessBuilder:
"""
Text begins with another text
:param data: Text in which to find something at the beginning.
:param pattern: Text to find at the beginning of `data`. Regular expressions are not supported.
:param case_sensitive: Case sensitive comparison can be disabled by setting this parameter to `false`.
:return: `true` if `data` begins with `pattern`, false` otherwise.
"""
return _process('text_begins', data=data, pattern=pattern, case_sensitive=case_sensitive)
def text_contains(data, pattern, case_sensitive=UNSET) -> ProcessBuilder:
"""
Text contains another text
:param data: Text in which to find something in.
:param pattern: Text to find in `data`. Regular expressions are not supported.
:param case_sensitive: Case sensitive comparison can be disabled by setting this parameter to `false`.
:return: `true` if `data` contains the `pattern`, false` otherwise.
"""
return _process('text_contains', data=data, pattern=pattern, case_sensitive=case_sensitive)
def text_ends(data, pattern, case_sensitive=UNSET) -> ProcessBuilder:
"""
Text ends with another text
:param data: Text in which to find something at the end.
:param pattern: Text to find at the end of `data`. Regular expressions are not supported.
:param case_sensitive: Case sensitive comparison can be disabled by setting this parameter to `false`.
:return: `true` if `data` ends with `pattern`, false` otherwise.
"""
return _process('text_ends', data=data, pattern=pattern, case_sensitive=case_sensitive)
def text_merge(data, separator=UNSET) -> ProcessBuilder:
"""
Concatenate elements to a single text
:param data: A set of elements. Numbers, boolean values and null values get converted to their (lower case)
string representation. For example: `1` (integer), `-1.5` (number), `true` / `false` (boolean values)
:param separator: A separator to put between each of the individual texts. Defaults to an empty string.
:return: A string containing a string representation of all the array elements in the same order, with the
separator between each element.
"""
return _process('text_merge', data=data, separator=separator)
def trim_cube(data) -> ProcessBuilder:
"""
Remove dimension labels with no-data values
:param data: A raster data cube to trim.
:return: A trimmed raster data cube with the same dimensions. The dimension properties name, type,
reference system and resolution remain unchanged. The number of dimension labels may decrease.
"""
return _process('trim_cube', data=data)
def variance(data, ignore_nodata=UNSET) -> ProcessBuilder:
"""
Variance
:param data: An array of numbers.
:param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting
this flag to `false` considers no-data values so that `null` is returned if any value is such a value.
:return: The computed sample variance.
"""
return _process('variance', data=data, ignore_nodata=ignore_nodata)
def xor(x, y) -> ProcessBuilder:
"""
Logical XOR (exclusive or)
:param x: A boolean value.
:param y: A boolean value.
:return: Boolean result of the logical XOR.
"""
return _process('xor', x=x, y=y)
| 49.976754 | 310 | 0.687616 | 31,650 | 232,192 | 5.007362 | 0.038325 | 0.01373 | 0.005792 | 0.011244 | 0.961308 | 0.949174 | 0.938826 | 0.916193 | 0.904968 | 0.893194 | 0 | 0.004061 | 0.239556 | 232,192 | 4,645 | 311 | 49.987513 | 0.893509 | 0.736714 | 0 | 0.115756 | 1 | 0 | 0.085249 | 0.007089 | 0 | 0 | 0 | 0 | 0 | 1 | 0.493569 | false | 0 | 0.003215 | 0.019293 | 0.993569 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 9 |
aa075f3e7bfad6bdeef8e2e73d607be7cf75a80a | 150 | py | Python | tools/test_sh_file.py | insigh/Faster-RCNN-Tensorflow | 4f446a4c1ebefcf6d92b5e01d2b6396bcbbf1a8d | [
"MIT"
] | null | null | null | tools/test_sh_file.py | insigh/Faster-RCNN-Tensorflow | 4f446a4c1ebefcf6d92b5e01d2b6396bcbbf1a8d | [
"MIT"
] | 1 | 2019-04-04T14:19:40.000Z | 2019-04-06T03:32:22.000Z | tools/test_sh_file.py | insigh/Faster-RCNN-Tensorflow | 4f446a4c1ebefcf6d92b5e01d2b6396bcbbf1a8d | [
"MIT"
] | null | null | null | import os
os.system("bash /home/chaojie/github/tf-faster-rcnn/experiments/scripts/test_faster_rcnn.sh 0 pascal_voc_0712 res101")
# print("hahaha")
| 21.428571 | 118 | 0.786667 | 24 | 150 | 4.75 | 0.875 | 0.175439 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.057971 | 0.08 | 150 | 6 | 119 | 25 | 0.768116 | 0.1 | 0 | 0 | 0 | 0.5 | 0.789474 | 0.56391 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 7 |
aa23d06dce627c300497fe073f8ad758fa854eb5 | 70 | py | Python | tests/syntax/dict_value_missing_4.py | hoefling/friendly-traceback | 26acac903521c5f0e5cf837d32bda750918d4afb | [
"MIT"
] | 45 | 2021-07-06T03:30:20.000Z | 2022-03-16T17:30:58.000Z | tests/syntax/dict_value_missing_4.py | hoefling/friendly-traceback | 26acac903521c5f0e5cf837d32bda750918d4afb | [
"MIT"
] | 110 | 2021-06-28T11:48:46.000Z | 2022-03-25T20:41:25.000Z | tests/syntax/dict_value_missing_4.py | hoefling/friendly-traceback | 26acac903521c5f0e5cf837d32bda750918d4afb | [
"MIT"
] | 4 | 2021-07-05T20:56:39.000Z | 2021-11-11T20:24:34.000Z | # a = {1:2, 3}
# a = {1:2, 3:}
# a = {1:2, 3, 4:5}
a = {1:2, 3:, 4:5}
| 14 | 19 | 0.285714 | 20 | 70 | 1 | 0.3 | 0.4 | 0.6 | 0.8 | 1 | 1 | 0.6 | 0.6 | 0 | 0 | 0 | 0.326531 | 0.3 | 70 | 4 | 20 | 17.5 | 0.081633 | 0.628571 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0 | null | null | 0 | 1 | 0 | 1 | null | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 11 |
aa28e03629efadc4e5cc26f252584a74b351dcd7 | 13,561 | py | Python | Tools/pybench/Arithmetic.py | sireliah/polish-python | 605df4944c2d3bc25f8bf6964b274c0a0d297cc3 | [
"PSF-2.0"
] | 1 | 2018-06-21T18:21:24.000Z | 2018-06-21T18:21:24.000Z | Tools/pybench/Arithmetic.py | sireliah/polish-python | 605df4944c2d3bc25f8bf6964b274c0a0d297cc3 | [
"PSF-2.0"
] | null | null | null | Tools/pybench/Arithmetic.py | sireliah/polish-python | 605df4944c2d3bc25f8bf6964b274c0a0d297cc3 | [
"PSF-2.0"
] | null | null | null | z pybench zaimportuj Test
klasa SimpleIntegerArithmetic(Test):
version = 2.0
operations = 5 * (3 + 5 + 5 + 3 + 3 + 3)
rounds = 120000
def test(self):
dla i w range(self.rounds):
a = 2
b = 3
c = 3
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
a = 2
b = 3
c = 3
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
a = 2
b = 3
c = 3
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
a = 2
b = 3
c = 3
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
a = 2
b = 3
c = 3
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
def calibrate(self):
dla i w range(self.rounds):
dalej
klasa SimpleFloatArithmetic(Test):
version = 2.0
operations = 5 * (3 + 5 + 5 + 3 + 3 + 3)
rounds = 120000
def test(self):
dla i w range(self.rounds):
a = 2.1
b = 3.3332
c = 3.14159
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
a = 2.1
b = 3.3332
c = 3.14159
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
a = 2.1
b = 3.3332
c = 3.14159
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
a = 2.1
b = 3.3332
c = 3.14159
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
a = 2.1
b = 3.3332
c = 3.14159
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
def calibrate(self):
dla i w range(self.rounds):
dalej
klasa SimpleIntFloatArithmetic(Test):
version = 2.0
operations = 5 * (3 + 5 + 5 + 3 + 3 + 3)
rounds = 120000
def test(self):
dla i w range(self.rounds):
a = 2
b = 3
c = 3.14159
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
a = 2
b = 3
c = 3.14159
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
a = 2
b = 3
c = 3.14159
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
a = 2
b = 3
c = 3.14159
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
a = 2
b = 3
c = 3.14159
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
def calibrate(self):
dla i w range(self.rounds):
dalej
klasa SimpleLongArithmetic(Test):
version = 2.0
operations = 5 * (3 + 5 + 5 + 3 + 3 + 3)
rounds = 60000
def test(self):
dla i w range(self.rounds):
a = 2220001
b = 100001
c = 30005
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
a = 2220001
b = 100001
c = 30005
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
a = 2220001
b = 100001
c = 30005
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
a = 2220001
b = 100001
c = 30005
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
a = 2220001
b = 100001
c = 30005
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
def calibrate(self):
dla i w range(self.rounds):
dalej
klasa SimpleComplexArithmetic(Test):
version = 2.0
operations = 5 * (3 + 5 + 5 + 3 + 3 + 3)
rounds = 80000
def test(self):
dla i w range(self.rounds):
a = 2 + 3j
b = 2.5 + 4.5j
c = 1.2 + 6.2j
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
a = 2 + 3j
b = 2.5 + 4.5j
c = 1.2 + 6.2j
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
a = 2 + 3j
b = 2.5 + 4.5j
c = 1.2 + 6.2j
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
a = 2 + 3j
b = 2.5 + 4.5j
c = 1.2 + 6.2j
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
a = 2 + 3j
b = 2.5 + 4.5j
c = 1.2 + 6.2j
c = a + b
c = b + c
c = c + a
c = a + b
c = b + c
c = c - a
c = a - b
c = b - c
c = c - a
c = b - c
c = a / b
c = b / a
c = c / b
c = a * b
c = b * a
c = c * b
c = a / b
c = b / a
c = c / b
def calibrate(self):
dla i w range(self.rounds):
dalej
| 17.430591 | 44 | 0.184426 | 1,809 | 13,561 | 1.382532 | 0.023217 | 0.239904 | 0.179928 | 0.239904 | 0.940824 | 0.940824 | 0.940824 | 0.940824 | 0.940824 | 0.940824 | 0 | 0.089372 | 0.725242 | 13,561 | 777 | 45 | 17.453024 | 0.581857 | 0 | 0 | 0.986577 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0.001678 | null | null | 0 | 0 | 0 | 1 | null | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 12 |
a4b316e9ad441ba72ae0734905a35d9a33cedcab | 1,220 | py | Python | 07_Java_Experiment/PyTest/exception/exceptions.py | Robert-Stackflow/HUST-Courses | 300752552e7af035b0e5c7663953850c81871242 | [
"MIT"
] | 4 | 2021-11-01T09:27:32.000Z | 2022-03-07T14:24:10.000Z | 07_Java_Experiment/PyTest/exception/exceptions.py | Robert-Stackflow/HUST-Courses | 300752552e7af035b0e5c7663953850c81871242 | [
"MIT"
] | null | null | null | 07_Java_Experiment/PyTest/exception/exceptions.py | Robert-Stackflow/HUST-Courses | 300752552e7af035b0e5c7663953850c81871242 | [
"MIT"
] | null | null | null | class FileNameFormatError(Exception):
"""
压缩文件名格式错误异常
"""
def __init__(self, message):
"""
构造函数
:param message: 异常信息描述字符串
"""
self.message = message
# __str__相当于Java的toString函数，把对象转成字符串
def __str__(self):
return repr(self.message)
class CompressFormatError(Exception):
"""
压缩格式错误异常
"""
def __init__(self, message):
"""
构造函数
:param message: 异常信息描述字符串
"""
self.message = message
# __str__相当于Java的toString函数，把对象转成字符串
def __str__(self):
return repr(self.message)
class AutoTestDirError(Exception):
"""
自动测试目录异常
"""
def __init__(self, message):
"""
构造函数
:param message: 异常信息描述字符串
"""
self.message = message
# __str__相当于Java的toString函数，把对象转成字符串
def __str__(self):
return repr(self.message)
class UncompressError(Exception):
"""
解压异常
"""
def __init__(self, message):
"""
构造函数
:param message: 异常信息描述字符串
"""
self.message = message
# __str__相当于Java的toString函数，把对象转成字符串
def __str__(self):
return repr(self.message)
None
| 18.769231 | 44 | 0.567213 | 101 | 1,220 | 6.376238 | 0.227723 | 0.204969 | 0.068323 | 0.111801 | 0.774845 | 0.774845 | 0.774845 | 0.774845 | 0.774845 | 0.774845 | 0 | 0 | 0.331148 | 1,220 | 64 | 45 | 19.0625 | 0.789216 | 0.245082 | 0 | 0.761905 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.380952 | false | 0 | 0 | 0.190476 | 0.761905 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 10 |
353f5d359b556af4f4fa3ec86baa016a280d3e22 | 37,473 | py | Python | Src Code/Our Methods/hybrid_words_parser_method.py | kautsiitd/Unsupervised-Decomposition-of-a-Multi-Author-Document | 33dab2dce3de2c08c7ae1a34646059653e2fcccc | [
"MIT"
] | 4 | 2017-09-26T19:39:06.000Z | 2020-05-14T14:54:55.000Z | Src Code/Our Methods/hybrid_words_parser_method.py | kautsiitd/Unsupervised-Decomposition-of-a-Multi-Author-Document | 33dab2dce3de2c08c7ae1a34646059653e2fcccc | [
"MIT"
] | null | null | null | Src Code/Our Methods/hybrid_words_parser_method.py | kautsiitd/Unsupervised-Decomposition-of-a-Multi-Author-Document | 33dab2dce3de2c08c7ae1a34646059653e2fcccc | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
# encoding=utf8
from __future__ import unicode_literals
'''#############################'''
'''#####Importing Libraries#####'''
###################################
import sys
import os
import io
import re
import pickle
from random import randint as rnd
from random import shuffle
from itertools import groupby
from sklearn.feature_extraction.text import CountVectorizer as CV
from sklearn.mixture import GMM
from pprint import pprint
import operator
import math
import nltk
from sklearn.naive_bayes import MultinomialNB as BNB
import itertools
import numpy as np
from multiprocessing import Pool
from multiprocessing import Manager
import matplotlib.pyplot as plt
from scipy.interpolate import spline
# from pos_tag import pos_tagging
# from pq_gram import find_pq_grams
print "Import Done"
'''#############################'''
'''#####Importing Libraries#####'''
###################################
'''############################'''
'''#####Defining Variables#####'''
##################################
processors= 4
V = 200
b_num = 0
b = ["Becker-Posner","GC-TF-PK","MD-TF-PK","MD-GC-PK","MD-GC-TF-PK"]
gmm_initialisation = 5
# segment size
seg_size = 30
# number of most frequent features
max_features = 1500
# choosing top vital segment in a class
best_per = .5
# number of sentence to test on from final model
n_gram_size = 1
lowercase = True
tokenizer = None
token_pattern = u'(?u)\\b\\w\\w+\\b'
# threshold for pq_gram similiarity index
threshold = 1.0
# Whether plot graph for choosing threshold or not
do_plot = 0
# Whether or not comparte with baseline results
ignore_baseline = 0
# threshold for trusted sentence
trus_thrs = .95
'''############################'''
'''#####Defining Variables#####'''
##################################
'''######### Step 1 ##########'''
'''extracting and merging data'''
#################################
'''
books_names = ['a',b','c',....]
merged_data = ['sentence1','sentence2',.....]
label_sen = [0,0,0,1,2,.....] label of sentence in merged_data
segments_sen= [['sentence1','sentence2',... ],['sentence1','sentence2',... ],... number of segments]
segments = ['segment1','segment2',.....]
label_in_seg= [[0,0,0,1,2,0,0,..]
[0,1,1,2,1,0,1,..]
....
] label of sentences in individual segments
label_in_seg= [0,1,1,0,2,0,...] book with max count in segment
is_pure_seg = [True,True,False,True,... number of segments] True if segment is pure
randoms = [ [120,[2,0,1,.. number of Authors]], [180,[1,2,0,.. number of Authors]], .. ]
'''
folder = "../dataset/Original/"+b[b_num]
books_names = os.listdir(folder)
merged_data = []
label_sen = []
segments_sen= []
segments = []
label_seg = []
label_in_seg= []
is_pure_seg = []
randoms = []
# main
number_books= len(books_names)
books_data = []
for book in books_names:
path = os.path.join(folder,book)
f = io.open(path, encoding="ISO-8859-1")
books_data.append(f.readlines())
number_sen = [len(book_data) for book_data in books_data]
total_sen = sum(number_sen)
number_seg = int(math.ceil((total_sen/seg_size)))
count_sen = [0]*number_books
while(sum(count_sen) != total_sen):
size = rnd(1,V)
randoms.append([size,[]])
done_book = [0]*number_books
for i in range(number_books):
book_num = rnd(0,number_books-1)
while(done_book[book_num] != 0):
book_num = rnd(0,number_books-1)
randoms[-1][-1].append(book_num)
done_book[book_num] = 1
new_count_sen = count_sen[book_num] + min(size,number_sen[book_num]-count_sen[book_num])
for j in books_data[book_num][ count_sen[book_num]:new_count_sen ]:
merged_data.append( re.sub('[\r\n]','',j) )
label_sen.extend([book_num] * (new_count_sen - count_sen[book_num]) )
count_sen[book_num] = new_count_sen
for i in range(number_seg):
start = seg_size*i
end = min(seg_size*(i+1),total_sen)
seg_data = merged_data[start:end]
segments_sen.append(seg_data)
segments.append(' '.join(seg_data))
labels = label_sen[start:end]
label_in_seg.append(labels)
for i in range(number_seg):
label_seg.append(max(set(label_in_seg[i]), key=label_in_seg[i].count))
for i in range(number_seg):
is_pure_seg.append(sum(label_in_seg[i])%len(label_in_seg[i]) == 0)
'''######'''
'''Step 1'''
'''######'''
'''###########################'''
'''Printing Results of merging'''
'''###########################'''
'''
org_seg = [430,405,...,150] number of pure segments by author i, last one for mixed
'''
# calculating segments by each author
org_seg = [0 for i in range(number_books+1)]
for i in range(number_seg):
if( sum(label_in_seg[i])%len(label_in_seg[i]) == 0):
org_seg[ sum(label_in_seg[i])/len(label_in_seg[i]) ] += 1
else:
org_seg[-1] += 1
for i in range(number_books):
print "Author "+str(i)+":",org_seg[i]
print "Mixed :",org_seg[-1]
print "STEP 1 done"
'''###########################'''
'''Printing Results of merging'''
#################################
'''######### Step 2 #########'''
'''Get pq-gram of merged data'''
################################
'''
segments_parser = [ [[**ROOTNN*,*NN**JJ, ... pq-grams of Sentence 1],[**ROOTNN*,*NN**JJ, ... pq-grams of Sentence 2],....
... Number of Sentence in Segment 1]
[[**ROOTNN*,*NN**JJ, ... pq-grams of Sentence 1],[**ROOTNN*,*NN**JJ, ... pq-grams of Sentence 2],....
... Number of Sentence in Segment 2]
....
Number of segments
]
'''
folder = "../../dataset/Parser/"+b[b_num]
books_names = os.listdir(folder)
merged_parser = []
segments_parser = []
parser_data = []
count_sen = [0]*number_books
for book in books_names:
path = os.path.join(folder,book)
f = io.open(path, encoding="ISO-8859-1")
parser_data.append(f.readlines())
for random in randoms:
size = random[0]
for i in range(number_books):
book_num = random[-1][i]
new_count_sen = count_sen[book_num] + min(size,number_sen[book_num]-count_sen[book_num])
for j in parser_data[book_num][ count_sen[book_num]:new_count_sen ]:
merged_parser.append( re.sub('[\r\n]','',j) )
count_sen[book_num] = new_count_sen
for i in range(number_seg):
start = seg_size*i
end = min(seg_size*(i+1),total_sen)
seg_data = merged_parser[start:end]
segments_parser.append(seg_data)
print "Step 2 done"
'''######'''
'''Step 2'''
'''######'''
'''####################### STEP 3 ######################'''
'''Find If given Segment is Pure or Mix USING WORDS used'''
###########################################################
'''
Calculate Similiarity Index of Segment:
Higher Similiarity Index, Higher Pure
'''
n_gram_size_2 = 2
threshold_2 = 2200
number_seg = len(segments_parser)
score_true = Manager().list([])
score_false = Manager().list([])
mixed_segments = Manager().list([])
pure_segments = Manager().list([])
pure_data = Manager().list([])
mixed_data = Manager().list([])
pure = Manager().list([])
mixed = Manager().list([])
def score_word_similiarity(i):
seg_model = CV(binary = True, min_df=1, ngram_range=(1,n_gram_size_2), max_features=2000, lowercase=lowercase, tokenizer=tokenizer, token_pattern=token_pattern)
vec_seg = seg_model.fit_transform(segments_sen[i]).toarray()
similiarity_index = 0
seg_size = len(segments_sen[i])
for j in range(seg_size):
for k in range(j,seg_size):
similiarity_index += sum(x[0]*x[1] for x in zip(vec_seg[j],vec_seg[k]))
if similiarity_index > threshold_2:
pure_segments.append(segments[i])
pure_data.extend(segments_sen[i])
else:
mixed_segments.append(segments[i])
mixed_data.extend(segments_sen[i])
if is_pure_seg[i] == True:
score_true.append(similiarity_index)
if similiarity_index > threshold_2:
pure.append(1)
else:
mixed.append(0)
else:
score_false.append(similiarity_index)
if similiarity_index > threshold_2:
pure.append(0)
else:
mixed.append(1)
p = Pool(processors)
p.map(score_word_similiarity, range(number_seg))
score_true.sort()
score_false.sort()
print score_true
print score_false
print "Accuracy Initial",float(sum(org_seg)-org_seg[-1])/sum(org_seg),sum(org_seg)
print "Accuracy Final",pure.count(1),float(pure.count(1))/len(pure),len(pure)
print "Step 3 done"
'''######'''
'''Step 3'''
'''######'''
'''################## STEP ** #################'''
'''Plotting Graph for finding optimum threshold'''
##################################################
def plot_word_graph():
global score_true,score_false
accuracies = []
n_pure = []
data_size = []
fig, ax = plt.subplots()
axes = [ax, ax.twinx()]
for thr in range(1500,2500):
print thr
mixed = []
pure = []
threshold = float(thr)/1
for similiarity_index in score_true:
if similiarity_index > thr:
pure.append(1)
else:
mixed.append(0)
for similiarity_index in score_false:
if similiarity_index > thr:
pure.append(0)
else:
mixed.append(1)
accuracies.append(float(pure.count(1)*100)/len(pure))
n_pure.append(pure.count(1))
data_size.append(len(pure))
base = np.array([float(x)/1 for x in range(1500,2500)])
thr = np.linspace(base.min(),base.max(),2000)
accuracies_smooth = spline(base,accuracies,thr)
n_pure_smooth = spline(base,n_pure,thr)
data_size_smooth = spline(base,data_size,thr)
axes[1].plot(thr,accuracies_smooth,'r')
axes[0].plot(thr,n_pure_smooth,'b')
axes[0].plot(thr,data_size_smooth,'g')
plt.show()
if do_plot == 1:
plot_word_graph()
'''#######'''
'''Step **'''
'''#######'''
# sys.exit()
'''######################### STEP 4 ######################'''
'''Find If given Segment is Pure or Mix USING PQ GRAM used'''
#############################################################
'''
Calculate Similiarity Index of Segment:
Higher Similiarity Index, Higher Pure
'''
'''
pure_segments = ['segment1','segment2',.....]
pure_data = ['sentence1','sentence2',.....]
mixed_data = ['sentence1','sentence2',.....]
'''
# calculating sentence sizes in each segment
sentence_size = []
for segment in segments_parser:
sentence_size.append([])
for sentence in segment:
sentence_size[-1].append(len(sentence))
# calculating similiarity index for each segment
number_seg = len(segments_parser)
score_true = Manager().list([])
score_false = Manager().list([])
mixed_segments = Manager().list([])
pure_segments = Manager().list([])
pure_data = Manager().list([])
mixed_data = Manager().list([])
pure = Manager().list([])
mixed = Manager().list([])
def score_similiarity(i):
segment = segments_parser[i]
similiarity_index = 0
seg_size = len(segment)
'''iterating over sentences in a segment'''
for j in range(seg_size):
for pq_gram in segment[j]:
'''checking current pqgram is in how
many other sentences of same segment'''
for k in range(j,seg_size):
if pq_gram in segment[k]:
similiarity_index += 1.0/(sentence_size[i][j]*sentence_size[i][k])
if similiarity_index > threshold:
pure_segments.append(segments[i])
pure_data.extend(segments_sen[i])
else:
mixed_segments.append(segments[i])
mixed_data.extend(segments_sen[i])
if is_pure_seg[i] == True:
score_true.append(similiarity_index)
if similiarity_index > threshold:
pure.append(1)
else:
mixed.append(0)
else:
score_false.append(similiarity_index)
if similiarity_index > threshold:
pure.append(0)
else:
mixed.append(1)
p = Pool(processors)
p.map(score_similiarity, range(number_seg))
print "Accuracy Initial",float(sum(org_seg)-org_seg[-1])/sum(org_seg),sum(org_seg)
print "Accuracy Final",pure.count(1),float(pure.count(1))/len(pure),len(pure)
print "Step 4 done"
'''######'''
'''Step 4'''
'''######'''
'''################## STEP ** #################'''
'''Plotting Graph for finding optimum threshold'''
##################################################
def plot_graph():
global score_true,score_false
accuracies = []
n_pure = []
data_size = []
fig, ax = plt.subplots()
axes = [ax, ax.twinx()]
for thr in range(20,210):
mixed = []
pure = []
threshold = float(thr)/100
for similiarity_index in score_true:
if similiarity_index > threshold:
pure.append(1)
else:
mixed.append(0)
for similiarity_index in score_false:
if similiarity_index > threshold:
pure.append(0)
else:
mixed.append(1)
# print thr,"Accuracy Final",pure_segments.count(1),float(pure_segments.count(1))/len(pure_segments),len(pure_segments)
accuracies.append(float(pure.count(1)*100)/len(pure))
n_pure.append(pure.count(1))
data_size.append(len(pure))
base = np.array([float(x)/100 for x in range(20,210)])
thr = np.linspace(base.min(),base.max(),500)
accuracies_smooth = spline(base,accuracies,thr)
n_pure_smooth = spline(base,n_pure,thr)
data_size_smooth = spline(base,data_size,thr)
axes[1].plot(thr,accuracies_smooth,'r')
axes[0].plot(thr,n_pure_smooth,'b')
axes[0].plot(thr,data_size_smooth,'g')
plt.show()
if do_plot == 1:
plot_graph()
'''#######'''
'''Step **'''
'''#######'''
'''##############################################'''
'''################## Step 5 ####################'''
'''finding features and vectorising pure segments'''
'''##############################################'''
'''
model = model with feature words having atleast frequency = 3 = 11000
vec_seg_pure(sparse matrix) = [ [0,0,1,1,0,1,1,1,1,0,0,0,0,1,1,... number of feature words=11000]
[0,0,1,0,0,1,1,0,1,0,0,1,1,0,0,... whether word present or not]
....
number of segments
]
number_f_w = number of feature words extracted from merged data
'''
model = CV(binary = True, min_df = 3, ngram_range=(1,n_gram_size), max_features=20000, lowercase=lowercase, tokenizer=tokenizer, token_pattern=token_pattern)
model = model.fit(pure_data)
vec_seg_pure = model.transform(pure_segments)
vec_seg_mixed = model.transform(mixed_segments)
number_f_w = len(model.vocabulary_)
vec_seg_pure = vec_seg_pure.toarray()
max_features = min(max_features,number_f_w)
print "number of feature words:",number_f_w
print "STEP 5 done"
'''######'''
'''Step 5'''
'''######'''
'''############################################'''
'''################ Step 6 ####################'''
'''Unsupervised labelling of segments using GMM'''
'''############################################'''
'''
label_p = [0,1,0,1,2,0,1,.... number of segments] predicted label for each segment
count_mapping = [[20,3,450,... number of books] how much predicted label match to original label(max count)
[410,5,10,..]
...
number of books
]
mapping = [2,0,1,5,3,...] What predicted label match to in original label
clusters = [['sentence','sentence',..... in cluster 0]
['sentence','sentence',..... in cluster 1]
....
number of books
]
'''
number_pure_seg = len(pure_segments)
number_mixed_seg = len(mixed_segments)
mapping = [0 for i in range(number_books)]
while(len(set(mapping)) != number_books):
model1 = GMM(n_components = number_books, n_iter = 1000, covariance_type = 'diag', n_init = gmm_initialisation, verbose = 1)
model1 = model1.fit(vec_seg_pure)
label_p = model1.predict_proba(vec_seg_pure)
temp_label_p = []
for j in range(number_pure_seg):
temp_label_p.append(map(lambda x: (x),label_p[j]) . index(max(label_p[j])))
label_p = temp_label_p
count_mapping = [ [0 for j in range(number_books)] for i in range(number_books)]
for i,j in zip(label_p,label_seg):
count_mapping[i][j] += 1
for i in range(number_books):
max_frq = max(count_mapping[i])
mapping[i] = count_mapping[i].index(max_frq)
print "mapping:",mapping
print "count_mapping:",count_mapping
# updating label_p with mapping
for i in range(number_pure_seg):
label_p[i] = mapping[label_p[i]]
# segments in each clusters as sentences
clusters = [[] for i in range(number_books)]
for i in range(number_pure_seg):
clusters[label_p[i]].append(pure_segments[i])
'''######'''
'''Step 6'''
'''######'''
'''################################'''
'''Calculating Precision and Recall'''
'''################################'''
confusion_matrix = [ [0 for j in range(number_books)] for i in range(number_books)]
for i in range(number_pure_seg):
confusion_matrix[label_p[i]][label_seg[i]] += 1
recall = []
for i in range(number_books):
recall.append(float(confusion_matrix[i][i])/sum(zip(*confusion_matrix)[i]))
print "Recall:",recall
print float(sum(recall))/number_books
print "mapping:",mapping
print "confusion_matrix:",confusion_matrix
print "STEP 6 done"
'''################################'''
'''Calculating Precision and Recall'''
'''################################'''
'''############################################################'''
'''##################### Step 7 ###############################'''
'''Revectorising segments with max_features most frequent words'''
'''############################################################'''
'''
model2 = model with at most max_features=1500 feature words
vec_seg_cls(sparse matrix) = [[ [0,1,1,0,1,1,1,0,..... max_features=1500],[vector of segment 2],.... cluster 0]
[ [0,0,1,1,0,0,1,0,..... max_features=1500],[vector of segment 2],.... cluster 1]
....
number of books
] vector representation of each segment in corresponding cluster
vec_seg_new(sparse matrix) = [[0,1,1,0,1,1,1,0,..... max_features=1500]
[0,0,1,1,0,0,1,0,..... max_features=1500]
....
number of segments
] vector representation of each segment
'''
model2 = CV(ngram_range=(1,n_gram_size), max_features = max_features)
model2 = model2.fit(pure_data)
vec_seg_cls = [model2.transform(clusters[i]) for i in range(number_books)]
vec_seg_new = model2.transform(segments)
print "STEP 7 done"
'''######'''
'''Step 7'''
'''######'''
'''#####################################'''
'''############## Step 8 ###############'''
'''Applying SegmentElicitation Procedure'''
'''#####################################'''
'''
vec_seg_cls(dense_array) = vector representation of each segment in corresponding cluster
vec_seg_new(dense_array1) = vector representation of each segment
word_cls_frq = frequency of feature words(max_features=1500) in each cluster
= [[25,100,13,15,253,.... number of feature words] cluster 0
[65,200,123,10,15,.... number of feature words] cluster 1
....
number of clusters/books
]
word_frq = each feature word(max_features=1500) frequency in whole document
= [150,550,260,1021,.... number of feature words(max_features=1500)]
post_p_w = posterior probability of each feature word in each cluster/book
= [ [0.3,0.25,.... number of clusters/books] word 1
[0.1,0.15,.... number of clusters/books] word 2
....
number of feature words(max_features=1500)
]
post_p_seg = posterior probability of each segment in each cluster
= [ [[0.85,0.01,0.1,... number of books,0(segment number)], [segment 2],.... number of segments in this cluster] cluster 1
[[0.85,0.01,0.1,... number of books,1(segment number)], [segment 2],.... number of segments in this cluster] cluster 2
....
number of clusters/books
]
best_seg = 80% of post_p_seg for each cluster in same format
= [ [[0.85,0.01,0.1,... number of books,0(segment number)], [segment 2],.... number of segments in this cluster] cluster 1
[[0.85,0.01,0.1,... number of books,1(segment number)], [segment 2],.... number of segments in this cluster] cluster 2
....
number of clusters/books
]
'''
# calculating posterior probability of words
# variables
post_p_w = []
dense_array = [i.toarray() for i in vec_seg_cls]
dense_array1 = vec_seg_new.toarray()
word_cls_frq = [[sum(word_f) for word_f in zip(*cluster)] for cluster in dense_array]
word_frq = [sum(word_f) for word_f in zip(*word_cls_frq)]
# main
for i in range(max_features):
post_p_w.append([])
for j in range(number_books):
post_p_w[i].append(float(word_cls_frq[j][i])/word_frq[i])
# calculating posterior probability of segments in each cluster
post_p_seg = [[] for i in range(number_books)]
# jth segment ith cluster
'''calculating posterior probability of pure segments'''
for j in range(number_pure_seg):
cls_num = label_p[j]
temp = []
for i in range(number_books):
summation = 0
for k in range(max_features):
if (dense_array1[j][k]>0 and post_p_w[k][i]>0):
summation += math.log(post_p_w[k][i])
temp.append(summation)
temp.append(j)
post_p_seg[cls_num].append(temp)
'''calculating posterior probability of mixed segments'''
for j in range(number_mixed_seg):
temp = []
for i in range(number_books):
summation = 0
for k in range(max_features):
if (dense_array1[j][k]>0 and post_p_w[k][i]>0):
summation += math.log(post_p_w[k][i])
temp.append(summation)
cls_num = temp.index(max(temp))
temp.append(j)
post_p_seg[cls_num].append(temp)
'''################finding vital segment for each cluster####################'''
'''Choosing best 80%(best_per) of segments to represent corresponding cluster'''
'''##########################################################################'''
best_seg = []
for i in range(number_books):
end = int(best_per*len(post_p_seg[i]))
sort_seg = sorted(post_p_seg[i], key=lambda x:-x[i]+max(x[:i]+x[i+1:-1]))
best_seg.append(sort_seg[:end])
print "STEP 8 done"
'''######'''
'''Step 8'''
'''######'''
'''#################################################################################################'''
'''######################################## Step 9 #################################################'''
'''Representing vital segments in form of minimum 3 frq feature words for each corresponding cluster'''
'''#################################################################################################'''
'''
vec_seg(dense) = vector representation of each segment
vital_seg = [ [ [0,1,1,0,0,1,1,1,0,0,0,... ~1500 max_features(=1500)], [0,1,1,0,0,1,1,1,0,0,0,...],.... number of vital segments] cluster 0
[ [0,1,1,0,0,1,1,1,0,0,0,... ~1500 max_features(=1500)], [0,1,1,0,0,1,1,1,0,0,0,...],.... number of vital segments] cluster 1
....
number of clusters
]
'''
vital_seg = []
for cluster_n in range(number_books):
vital_seg.append([])
for seg in best_seg[cluster_n]:
vital_seg[cluster_n].append(dense_array1[seg[-1]])
print "STEP 9 done"
'''######'''
'''Step 9'''
'''######'''
'''###############################################################################'''
'''################################ Step 10 ######################################'''
'''Training using Bernouli Naive-Bayesian model to learn a classifier on vital_seg'''
'''###############################################################################'''
'''
vital_seg = 2*number of vital_seg*1500
train = 2*number of vital_seg*1500
'''
train = []
labels= []
for cluster_n in range(number_books):
for seg in vital_seg[cluster_n]:
train.append(seg.tolist())
labels.append(cluster_n)
model3 = BNB(fit_prior = True)
model3 = model3.fit(train, labels)
print "STEP 10 done"
'''########'''
'''Step 10'''
'''#######'''
'''################################################################'''
'''######################### Step 11 ##############################'''
'''classfying sentences on trained classifier and calculating score'''
'''################################################################'''
test_size = len(merged_data)
vec_sen = model2.transform(merged_data[:test_size])
auth_proba = model3.predict_proba(vec_sen)
predicted = [map(lambda x: (x),auth_proba[i]).index(max(auth_proba[i])) for i in range(test_size)]
org_label = label_sen[:test_size]
print model3.score(vec_sen, org_label)
print "STEP 11 done"
'''#######'''
'''Step 11'''
'''#######'''
'''#########################################'''
'''################Step 12##################'''
'''Applying Probability Indication Procedure'''
'''#########################################'''
# Rule 1
is_trusted = []
for i in range(test_size):
temp = sorted(auth_proba[i])
if(temp[-1]-temp[-2] > trus_thrs):
is_trusted.append(predicted[i])
else:
is_trusted.append(-1)
# Rule 2
if(is_trusted[0] == -1):
for i in range(1,test_size):
if(is_trusted[i] != -1):
is_trusted[0] = is_trusted[i]
break
if(is_trusted[0] == -1):
is_trusted[0] = map(lambda x: (x),auth_proba[0]).index(max(auth_proba[0]))
# Rule 3
if(is_trusted[-1] == -1):
for i in range(test_size-1, -1, -1):
if(is_trusted[i] != -1):
is_trusted[-1] = is_trusted[i]
break
if(is_trusted[-1] == -1):
is_trusted[-1] = map(lambda x: (x),auth_proba[-1]).index(max(auth_proba[-1]))
# Rule 4 & 5
before_label = -1
for i in range(test_size):
if(is_trusted[i] != -1):
before_label = is_trusted[i]
else:
after_label = -1
start = i
end = i
while(i < test_size):
i += 1
if(is_trusted[i] != -1):
after_label = is_trusted[i]
end = i
break
if(before_label == after_label):
for j in range(start,end):
is_trusted[j] = before_label
else:
for j in range(start,(start+end)/2):
is_trusted[j] = before_label
for j in range((start+end)/2,end):
is_trusted[j] = after_label
print "STEP 12 done"
'''######'''
'''Step 12'''
'''######'''
# Checking New Score
correct = 0
for i in range(test_size):
if(org_label[i] == is_trusted[i]):
correct += 1
print "New Accuracy:",float(correct*100)/test_size,"%"
if ignore_baseline == 0:
'''#########################################'''
'''################ Step 2 #################'''
'''finding features and vectorising segments'''
'''####### Comparing with baseline #########'''
'''#########################################'''
'''
model = model with feature words having atleast frequency = 3 = 11000
vec_seg(sparse matrix) = [ [0,0,1,1,0,1,1,1,1,0,0,0,0,1,1,... number of feature words=11000]
[0,0,1,0,0,1,1,0,1,0,0,1,1,0,0,... whether word present or not]
....
number of segments
]
number_f_w = number of feature words extracted from merged data
'''
model = CV(binary = True, min_df = 3, ngram_range=(1,n_gram_size), max_features=20000, lowercase=lowercase, tokenizer=tokenizer, token_pattern=token_pattern)
model = model.fit(merged_data)
vec_seg = model.transform(segments)
number_f_w = len(model.vocabulary_)
vec_seg = vec_seg.toarray()
max_features = min(max_features,number_f_w)
print "number of feature words:",number_f_w
print "STEP 2 done"
'''#######'''
'''Step 2'''
'''#######'''
'''############################################'''
'''################ Step 3 ####################'''
'''Unsupervised labelling of segments using GMM'''
'''############################################'''
'''
label_p = [0,1,0,1,2,0,1,.... number of segments] predicted label for each segment
count_mapping = [[20,3,450,... number of books] how much predicted label match to original label(max count)
[410,5,10,..]
...
number of books
]
mapping = [2,0,1,5,3,...] What predicted label match to in original label
clusters = [['sentence','sentence',..... in cluster 0]
['sentence','sentence',..... in cluster 1]
....
number of books
]
'''
mapping = [0 for i in range(number_books)]
while(len(set(mapping)) != number_books):
model1 = GMM(n_components = number_books, n_iter = 1000, covariance_type = 'diag', n_init = gmm_initialisation, verbose = 0)
model1 = model1.fit(vec_seg)
label_p = model1.predict_proba(vec_seg)
temp_label_p = []
for j in range(number_seg):
temp_label_p.append(map(lambda x: (x),label_p[j]) . index(max(label_p[j])))
label_p = temp_label_p
count_mapping = [ [0 for j in range(number_books)] for i in range(number_books)]
for i,j in zip(label_p,label_seg):
count_mapping[i][j] += 1
for i in range(number_books):
max_frq = max(count_mapping[i])
mapping[i] = count_mapping[i].index(max_frq)
print "baseline mapping:",mapping
print "baseline count_mapping:",count_mapping
# updating label_p with mapping
for i in range(number_seg):
label_p[i] = mapping[label_p[i]]
# segments in each clusters as sentences
clusters = [[] for i in range(number_books)]
for i in range(number_seg):
clusters[label_p[i]].append(segments[i])
'''######'''
'''Step 3'''
'''######'''
'''#############################################'''
'''Calculating Precision and Recall for baseline'''
'''#############################################'''
confusion_matrix = [ [0 for j in range(number_books)] for i in range(number_books)]
for i in range(number_seg):
confusion_matrix[label_p[i]][label_seg[i]] += 1
recall = []
for i in range(number_books):
recall.append(float(confusion_matrix[i][i])/sum(zip(*confusion_matrix)[i]))
print "baseline Recall:",recall
print float(sum(recall))/number_books
print "baseline mapping:",mapping
print "baseline confusion_matrix:",confusion_matrix
print "STEP 3 done"
'''#############################################'''
'''Calculating Precision and Recall for baseline'''
'''#############################################'''
'''############################################################'''
'''######################Step 4################################'''
'''Revectorising segments with max_features most frequent words'''
'''############################################################'''
'''
model2 = model with at most max_features=1500 feature words
vec_seg_cls(sparse matrix) = [[ [0,1,1,0,1,1,1,0,..... max_features=1500],[vector of segment 2],.... cluster 0]
[ [0,0,1,1,0,0,1,0,..... max_features=1500],[vector of segment 2],.... cluster 1]
....
number of books
] vector representation of each segment in corresponding cluster
vec_seg_new(sparse matrix) = [[0,1,1,0,1,1,1,0,..... max_features=1500]
[0,0,1,1,0,0,1,0,..... max_features=1500]
....
number of segments
] vector representation of each segment
'''
model2 = CV(ngram_range=(1,n_gram_size), max_features = max_features)
model2 = model2.fit(merged_data)
vec_seg_cls = [model2.transform(clusters[i]) for i in range(number_books)]
vec_seg_new = model2.transform(segments)
print "STEP 4 done"
'''#####################################'''
'''###############Step 5################'''
'''Applying SegmentElicitation Procedure'''
'''#####################################'''
'''
vec_seg_cls(dense) = vector representation of each segment in corresponding cluster
vec_seg_new(dense) = vector representation of each segment
word_cls_frq = frequency of feature words(max_features=1500) in each cluster
= [[25,100,13,15,253,.... number of feature words] cluster 0
[65,200,123,10,15,.... number of feature words] cluster 1
....
number of clusters/books
]
word_frq = each feature word(max_features=1500) frequency in whole document
= [150,550,260,1021,.... number of feature words(max_features=1500)]
post_p_w = posterior probability of each feature word in each cluster/book
= [ [0.3,0.25,.... number of clusters/books] word 1
[0.1,0.15,.... number of clusters/books] word 2
....
number of feature words(max_features=1500)
]
post_p_seg = posterior probability of each segment in each cluster
= [ [[0.85,0.01,0.1,... number of books,0(segment number)], [segment 2],.... number of segmensin this cluster] cluster 1
[[0.85,0.01,0.1,... number of books,1(segment number)], [segment 2],.... number of segmensin this cluster] cluster 2
....
number of clusters/books
]
best_seg = 80% of post_p_seg for each cluster in same format
= [ [[0.85,0.01,0.1,... number of books,0(segment number)], [segment 2],.... number of segments in this cluster] cluster 1
[[0.85,0.01,0.1,... number of books,1(segment number)], [segment 2],.... number of segments in this cluster] cluster 2
....
number of clusters/books
]
'''
# calculating posterior probability of words
# variables
post_p_w = []
dense_array = [i.toarray() for i in vec_seg_cls]
dense_array1 = vec_seg_new.toarray()
word_cls_frq = [[sum(word_f) for word_f in zip(*cluster)] for cluster in dense_array]
word_frq = [sum(word_f) for word_f in zip(*word_cls_frq)]
# main
for i in range(max_features):
post_p_w.append([])
for j in range(number_books):
post_p_w[i].append(float(word_cls_frq[j][i])/word_frq[i])
# calculating posterior probability of segments in each cluster
post_p_seg = [[] for i in range(number_books)]
# jth segment ith cluster
for j in range(number_seg):
cls_num = label_p[j]
temp = []
for i in range(number_books):
summation = 0
for k in range(max_features):
if (dense_array1[j][k]>0 and post_p_w[k][i]>0):
summation += math.log(post_p_w[k][i])
temp.append(summation)
temp.append(j)
post_p_seg[cls_num].append(temp)
# print post_p_seg[cls_num][-1]
'''################finding vital segment for each cluster####################'''
'''Choosing best 80%(best_per) of segments to represent corresponding cluster'''
'''##########################################################################'''
best_seg = []
for i in range(number_books):
end = int(best_per*len(post_p_seg[i]))
sort_seg = sorted(post_p_seg[i], key=lambda x:-x[i]+max(x[:i]+x[i+1:-1]))
best_seg.append(sort_seg[:end])
print "STEP 5 done"
'''######'''
'''Step 5'''
'''######'''
'''#################################################################################################'''
'''#########################################Step 6##################################################'''
'''Representing vital segments in form of minimum 3 frq feature words for each corresponding cluster'''
'''#################################################################################################'''
'''
vec_seg(dense) = vector representation of each segment
vital_seg = [ [ [0,1,1,0,0,1,1,1,0,0,0,... ~1500 max_features(=1500)], [0,1,1,0,0,1,1,1,0,0,0,...],.... number of vital segments] cluster 0
[ [0,1,1,0,0,1,1,1,0,0,0,... ~1500 max_features(=1500)], [0,1,1,0,0,1,1,1,0,0,0,...],.... number of vital segments] cluster 1
....
number of clusters
]
'''
print "STEP 5 done"
vital_seg = []
for cluster_n in range(number_books):
vital_seg.append([])
for seg in best_seg[cluster_n]:
vital_seg[cluster_n].append(dense_array1[seg[-1]])
print "STEP 6 done"
'''######'''
'''Step 6'''
'''######'''
'''###############################################################################'''
'''#################################Step 7########################################'''
'''Training using Bernouli Naive-Bayesian model to learn a classifier on vital_seg'''
'''###############################################################################'''
'''
vital_seg = 2*number of vital_seg*1500
train = 2*number of vital_seg*1500
'''
train = []
labels= []
for cluster_n in range(number_books):
for seg in vital_seg[cluster_n]:
train.append(seg.tolist())
labels.append(cluster_n)
model3 = BNB(fit_prior = True)
model3 = model3.fit(train, labels)
print "STEP 7 done"
'''######'''
'''Step 7'''
'''######'''
'''################################################################'''
'''##########################Step 8################################'''
'''classfying sentences on trained classifier and calculating score'''
'''################################################################'''
test_size = len(merged_data)
vec_sen = model2.transform(merged_data[:test_size])
auth_proba = model3.predict_proba(vec_sen)
predicted = [map(lambda x: (x),auth_proba[i]).index(max(auth_proba[i])) for i in range(test_size)]
org_label = label_sen[:test_size]
print model3.score(vec_sen, org_label)
print "STEP 8 done"
'''######'''
'''Step 8'''
'''######'''
'''#########################################'''
'''################Step 9###################'''
'''Applying Probability Indication Procedure'''
'''#########################################'''
# Rule 1
is_trusted = []
for i in range(test_size):
temp = sorted(auth_proba[i])
if(temp[-1]-temp[-2] > trus_thrs):
is_trusted.append(predicted[i])
else:
is_trusted.append(-1)
# Rule 2
if(is_trusted[0] == -1):
for i in range(1,test_size):
if(is_trusted[i] != -1):
is_trusted[0] = is_trusted[i]
break
if(is_trusted[0] == -1):
is_trusted[0] = map(lambda x: (x),auth_proba[0]).index(max(auth_proba[0]))
# Rule 3
if(is_trusted[-1] == -1):
for i in range(test_size-1, -1, -1):
if(is_trusted[i] != -1):
is_trusted[-1] = is_trusted[i]
break
if(is_trusted[-1] == -1):
is_trusted[-1] = map(lambda x: (x),auth_proba[-1]).index(max(auth_proba[-1]))
# Rule 4 & 5
before_label = -1
for i in range(test_size):
if(is_trusted[i] != -1):
before_label = is_trusted[i]
else:
after_label = -1
start = i
end = i
while(i < test_size):
i += 1
if(is_trusted[i] != -1):
after_label = is_trusted[i]
end = i
break
if(before_label == after_label):
for j in range(start,end):
is_trusted[j] = before_label
else:
for j in range(start,(start+end)/2):
is_trusted[j] = before_label
for j in range((start+end)/2,end):
is_trusted[j] = after_label
print "STEP 9 done"
'''######'''
'''Step 9'''
'''######'''
# Checking New Score
correct = 0
for i in range(test_size):
if(org_label[i] == is_trusted[i]):
correct += 1
print "New Accuracy:",float(correct*100)/test_size,"%" | 35.218985 | 161 | 0.586422 | 5,224 | 37,473 | 4.032542 | 0.072741 | 0.027248 | 0.014811 | 0.026108 | 0.808791 | 0.792462 | 0.766828 | 0.74428 | 0.729422 | 0.705734 | 0 | 0.034363 | 0.14808 | 37,473 | 1,064 | 162 | 35.218985 | 0.625517 | 0.03245 | 0 | 0.720613 | 0 | 0 | 0.035131 | 0.001048 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0.039182 | null | null | 0.085179 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
103ba8ba42568437de742c18c037ccdeff76f266 | 16,806 | py | Python | glance_store/tests/unit/test_driver.py | sokovnich/glance_store | 088a07e602825ae482ebf747cddc94d1996f04e6 | [
"Apache-2.0"
] | 49 | 2015-01-01T17:49:15.000Z | 2021-01-12T07:08:58.000Z | glance_store/tests/unit/test_driver.py | sokovnich/glance_store | 088a07e602825ae482ebf747cddc94d1996f04e6 | [
"Apache-2.0"
] | 4 | 2021-05-20T12:09:08.000Z | 2021-06-07T13:25:26.000Z | glance_store/tests/unit/test_driver.py | sokovnich/glance_store | 088a07e602825ae482ebf747cddc94d1996f04e6 | [
"Apache-2.0"
] | 50 | 2015-01-23T18:21:06.000Z | 2021-11-23T04:42:25.000Z | # Copyright 2018 Verizon Wireless
# 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. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License 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 hashlib
from oslo_utils.secretutils import md5
from oslotest import base
import glance_store.driver as driver
class _FakeStore(object):
@driver.back_compat_add
def add(self, image_id, image_file, image_size, hashing_algo,
context=None, verifier=None):
"""This is a 0.26.0+ add, returns a 5-tuple"""
if hashing_algo == 'md5':
hasher = md5(usedforsecurity=False)
else:
hasher = hashlib.new(str(hashing_algo))
# assume 'image_file' will be bytes for these tests
hasher.update(image_file)
backend_url = "backend://%s" % image_id
bytes_written = len(image_file)
checksum = md5(image_file, usedforsecurity=False).hexdigest()
multihash = hasher.hexdigest()
metadata_dict = {"verifier_obj":
verifier.name if verifier else None,
"context_obj":
context.name if context else None}
return (backend_url, bytes_written, checksum, multihash, metadata_dict)
class _FakeContext(object):
name = 'context'
class _FakeVerifier(object):
name = 'verifier'
class TestBackCompatWrapper(base.BaseTestCase):
def setUp(self):
super(TestBackCompatWrapper, self).setUp()
self.fake_store = _FakeStore()
self.fake_context = _FakeContext()
self.fake_verifier = _FakeVerifier()
self.img_id = '1234'
self.img_file = b'0123456789'
self.img_size = 10
self.img_checksum = md5(self.img_file,
usedforsecurity=False).hexdigest()
self.hashing_algo = 'sha256'
self.img_sha256 = hashlib.sha256(self.img_file).hexdigest()
def test_old_style_3_args(self):
x = self.fake_store.add(self.img_id, self.img_file, self.img_size)
self.assertEqual(tuple, type(x))
self.assertEqual(4, len(x))
self.assertIn(self.img_id, x[0])
self.assertEqual(self.img_size, x[1])
self.assertEqual(self.img_checksum, x[2])
self.assertTrue(dict, type(x[3]))
self.assertIsNone(x[3]['context_obj'])
self.assertIsNone(x[3]['verifier_obj'])
def test_old_style_4_args(self):
x = self.fake_store.add(self.img_id, self.img_file, self.img_size,
self.fake_context)
self.assertEqual(tuple, type(x))
self.assertEqual(4, len(x))
self.assertIn(self.img_id, x[0])
self.assertEqual(self.img_size, x[1])
self.assertEqual(self.img_checksum, x[2])
self.assertTrue(dict, type(x[3]))
self.assertEqual('context', x[3]['context_obj'])
self.assertIsNone(x[3]['verifier_obj'])
def test_old_style_5_args(self):
x = self.fake_store.add(self.img_id, self.img_file, self.img_size,
self.fake_context, self.fake_verifier)
self.assertEqual(tuple, type(x))
self.assertEqual(4, len(x))
self.assertIn(self.img_id, x[0])
self.assertEqual(self.img_size, x[1])
self.assertEqual(self.img_checksum, x[2])
self.assertTrue(dict, type(x[3]))
self.assertEqual('context', x[3]['context_obj'])
self.assertEqual('verifier', x[3]['verifier_obj'])
def test_old_style_3_args_kw_context(self):
x = self.fake_store.add(self.img_id, self.img_file, self.img_size,
context=self.fake_context)
self.assertEqual(tuple, type(x))
self.assertEqual(4, len(x))
self.assertIn(self.img_id, x[0])
self.assertEqual(self.img_size, x[1])
self.assertEqual(self.img_checksum, x[2])
self.assertTrue(dict, type(x[3]))
self.assertEqual('context', x[3]['context_obj'])
self.assertIsNone(x[3]['verifier_obj'])
def test_old_style_3_args_kw_verifier(self):
x = self.fake_store.add(self.img_id, self.img_file, self.img_size,
verifier=self.fake_verifier)
self.assertEqual(tuple, type(x))
self.assertEqual(4, len(x))
self.assertIn(self.img_id, x[0])
self.assertEqual(self.img_size, x[1])
self.assertEqual(self.img_checksum, x[2])
self.assertTrue(dict, type(x[3]))
self.assertIsNone(x[3]['context_obj'])
self.assertEqual('verifier', x[3]['verifier_obj'])
def test_old_style_4_args_kw_verifier(self):
x = self.fake_store.add(self.img_id, self.img_file, self.img_size,
self.fake_context, verifier=self.fake_verifier)
self.assertEqual(tuple, type(x))
self.assertEqual(4, len(x))
self.assertIn(self.img_id, x[0])
self.assertEqual(self.img_size, x[1])
self.assertEqual(self.img_checksum, x[2])
self.assertTrue(dict, type(x[3]))
self.assertEqual('context', x[3]['context_obj'])
self.assertEqual('verifier', x[3]['verifier_obj'])
def test_old_style_3_args_kws_context_verifier(self):
x = self.fake_store.add(self.img_id, self.img_file, self.img_size,
context=self.fake_context,
verifier=self.fake_verifier)
self.assertEqual(tuple, type(x))
self.assertEqual(4, len(x))
self.assertIn(self.img_id, x[0])
self.assertEqual(self.img_size, x[1])
self.assertEqual(self.img_checksum, x[2])
self.assertTrue(dict, type(x[3]))
self.assertEqual('context', x[3]['context_obj'])
self.assertEqual('verifier', x[3]['verifier_obj'])
def test_old_style_all_kw_in_order(self):
x = self.fake_store.add(image_id=self.img_id,
image_file=self.img_file,
image_size=self.img_size,
context=self.fake_context,
verifier=self.fake_verifier)
self.assertEqual(tuple, type(x))
self.assertEqual(4, len(x))
self.assertIn(self.img_id, x[0])
self.assertEqual(self.img_size, x[1])
self.assertEqual(self.img_checksum, x[2])
self.assertTrue(dict, type(x[3]))
self.assertEqual('context', x[3]['context_obj'])
self.assertEqual('verifier', x[3]['verifier_obj'])
def test_old_style_all_kw_random_order(self):
x = self.fake_store.add(image_file=self.img_file,
context=self.fake_context,
image_size=self.img_size,
verifier=self.fake_verifier,
image_id=self.img_id)
self.assertEqual(tuple, type(x))
self.assertEqual(4, len(x))
self.assertIn(self.img_id, x[0])
self.assertEqual(self.img_size, x[1])
self.assertEqual(self.img_checksum, x[2])
self.assertTrue(dict, type(x[3]))
self.assertEqual('context', x[3]['context_obj'])
self.assertEqual('verifier', x[3]['verifier_obj'])
def test_new_style_6_args(self):
x = self.fake_store.add(self.img_id, self.img_file, self.img_size,
self.hashing_algo, self.fake_context,
self.fake_verifier)
self.assertEqual(tuple, type(x))
self.assertEqual(5, len(x))
self.assertIn(self.img_id, x[0])
self.assertEqual(self.img_size, x[1])
self.assertEqual(self.img_checksum, x[2])
self.assertEqual(self.img_sha256, x[3])
self.assertTrue(dict, type(x[4]))
self.assertEqual('context', x[4]['context_obj'])
self.assertEqual('verifier', x[4]['verifier_obj'])
def test_new_style_3_args_kw_hash(self):
x = self.fake_store.add(self.img_id, self.img_file, self.img_size,
hashing_algo=self.hashing_algo)
self.assertEqual(tuple, type(x))
self.assertEqual(5, len(x))
self.assertIn(self.img_id, x[0])
self.assertEqual(self.img_size, x[1])
self.assertEqual(self.img_checksum, x[2])
self.assertEqual(self.img_sha256, x[3])
self.assertTrue(dict, type(x[4]))
self.assertIsNone(x[4]['context_obj'])
self.assertIsNone(x[4]['verifier_obj'])
def test_new_style_3_args_kws_context_hash(self):
x = self.fake_store.add(self.img_id, self.img_file, self.img_size,
context=self.fake_context,
hashing_algo=self.hashing_algo)
self.assertEqual(tuple, type(x))
self.assertEqual(5, len(x))
self.assertIn(self.img_id, x[0])
self.assertEqual(self.img_size, x[1])
self.assertEqual(self.img_checksum, x[2])
self.assertEqual(self.img_sha256, x[3])
self.assertTrue(dict, type(x[4]))
self.assertEqual('context', x[4]['context_obj'])
self.assertIsNone(x[4]['verifier_obj'])
def test_new_style_3_args_kws_verifier_hash(self):
x = self.fake_store.add(self.img_id, self.img_file, self.img_size,
hashing_algo=self.hashing_algo,
verifier=self.fake_verifier)
self.assertEqual(tuple, type(x))
self.assertEqual(5, len(x))
self.assertIn(self.img_id, x[0])
self.assertEqual(self.img_size, x[1])
self.assertEqual(self.img_checksum, x[2])
self.assertEqual(self.img_sha256, x[3])
self.assertTrue(dict, type(x[4]))
self.assertIsNone(x[4]['context_obj'])
self.assertEqual('verifier', x[4]['verifier_obj'])
def test_new_style_3_args_kws_hash_context_verifier(self):
x = self.fake_store.add(self.img_id, self.img_file, self.img_size,
hashing_algo=self.hashing_algo,
context=self.fake_context,
verifier=self.fake_verifier)
self.assertEqual(tuple, type(x))
self.assertEqual(5, len(x))
self.assertIn(self.img_id, x[0])
self.assertEqual(self.img_size, x[1])
self.assertEqual(self.img_checksum, x[2])
self.assertEqual(self.img_sha256, x[3])
self.assertTrue(dict, type(x[4]))
self.assertEqual('context', x[4]['context_obj'])
self.assertEqual('verifier', x[4]['verifier_obj'])
def test_new_style_4_args(self):
x = self.fake_store.add(self.img_id, self.img_file, self.img_size,
self.hashing_algo)
self.assertEqual(tuple, type(x))
self.assertEqual(5, len(x))
self.assertIn(self.img_id, x[0])
self.assertEqual(self.img_size, x[1])
self.assertEqual(self.img_checksum, x[2])
self.assertEqual(self.img_sha256, x[3])
self.assertTrue(dict, type(x[4]))
self.assertIsNone(x[4]['context_obj'])
self.assertIsNone(x[4]['verifier_obj'])
def test_new_style_4_args_kw_context(self):
x = self.fake_store.add(self.img_id, self.img_file, self.img_size,
self.hashing_algo, context=self.fake_context)
self.assertEqual(tuple, type(x))
self.assertEqual(5, len(x))
self.assertIn(self.img_id, x[0])
self.assertEqual(self.img_size, x[1])
self.assertEqual(self.img_checksum, x[2])
self.assertEqual(self.img_sha256, x[3])
self.assertTrue(dict, type(x[4]))
self.assertEqual('context', x[4]['context_obj'])
self.assertIsNone(x[4]['verifier_obj'])
def test_new_style_4_args_kws_verifier_context(self):
x = self.fake_store.add(self.img_id, self.img_file, self.img_size,
self.hashing_algo,
context=self.fake_context,
verifier=self.fake_verifier)
self.assertEqual(tuple, type(x))
self.assertEqual(5, len(x))
self.assertIn(self.img_id, x[0])
self.assertEqual(self.img_size, x[1])
self.assertEqual(self.img_checksum, x[2])
self.assertEqual(self.img_sha256, x[3])
self.assertTrue(dict, type(x[4]))
self.assertEqual('context', x[4]['context_obj'])
self.assertEqual('verifier', x[4]['verifier_obj'])
def test_new_style_5_args_kw_verifier(self):
x = self.fake_store.add(self.img_id, self.img_file, self.img_size,
self.hashing_algo, self.fake_context,
verifier=self.fake_verifier)
self.assertEqual(tuple, type(x))
self.assertEqual(5, len(x))
self.assertIn(self.img_id, x[0])
self.assertEqual(self.img_size, x[1])
self.assertEqual(self.img_checksum, x[2])
self.assertEqual(self.img_sha256, x[3])
self.assertTrue(dict, type(x[4]))
self.assertEqual('context', x[4]['context_obj'])
self.assertEqual('verifier', x[4]['verifier_obj'])
def test_new_style_6_args_no_kw(self):
x = self.fake_store.add(self.img_id, self.img_file, self.img_size,
self.hashing_algo, self.fake_context,
self.fake_verifier)
self.assertEqual(tuple, type(x))
self.assertEqual(5, len(x))
self.assertIn(self.img_id, x[0])
self.assertEqual(self.img_size, x[1])
self.assertEqual(self.img_checksum, x[2])
self.assertEqual(self.img_sha256, x[3])
self.assertTrue(dict, type(x[4]))
self.assertEqual('context', x[4]['context_obj'])
self.assertEqual('verifier', x[4]['verifier_obj'])
def test_new_style_all_kw_in_order(self):
x = self.fake_store.add(image_id=self.img_id,
image_file=self.img_file,
image_size=self.img_size,
hashing_algo=self.hashing_algo,
context=self.fake_context,
verifier=self.fake_verifier)
self.assertEqual(tuple, type(x))
self.assertEqual(5, len(x))
self.assertIn(self.img_id, x[0])
self.assertEqual(self.img_size, x[1])
self.assertEqual(self.img_checksum, x[2])
self.assertEqual(self.img_sha256, x[3])
self.assertTrue(dict, type(x[4]))
self.assertEqual('context', x[4]['context_obj'])
self.assertEqual('verifier', x[4]['verifier_obj'])
def test_new_style_all_kw_random_order(self):
x = self.fake_store.add(hashing_algo=self.hashing_algo,
image_file=self.img_file,
context=self.fake_context,
image_size=self.img_size,
verifier=self.fake_verifier,
image_id=self.img_id)
self.assertEqual(tuple, type(x))
self.assertEqual(5, len(x))
self.assertIn(self.img_id, x[0])
self.assertEqual(self.img_size, x[1])
self.assertEqual(self.img_checksum, x[2])
self.assertEqual(self.img_sha256, x[3])
self.assertTrue(dict, type(x[4]))
self.assertEqual('context', x[4]['context_obj'])
self.assertEqual('verifier', x[4]['verifier_obj'])
def test_neg_too_few_args(self):
self.assertRaises(TypeError,
self.fake_store.add,
self.img_id,
self.img_file)
def test_neg_too_few_kw_args(self):
self.assertRaises(TypeError,
self.fake_store.add,
self.img_file,
self.img_size,
self.fake_context,
self.fake_verifier,
image_id=self.img_id)
def test_neg_bogus_kw_args(self):
self.assertRaises(TypeError,
self.fake_store.add,
thrashing_algo=self.hashing_algo,
image_file=self.img_file,
context=self.fake_context,
image_size=self.img_size,
verifier=self.fake_verifier,
image_id=self.img_id)
| 43.994764 | 79 | 0.594371 | 2,188 | 16,806 | 4.35649 | 0.075411 | 0.112358 | 0.107637 | 0.124633 | 0.835711 | 0.831305 | 0.829627 | 0.829627 | 0.826479 | 0.826479 | 0 | 0.021146 | 0.282459 | 16,806 | 381 | 80 | 44.110236 | 0.769301 | 0.041295 | 0 | 0.755352 | 0 | 0 | 0.048471 | 0 | 0 | 0 | 0 | 0 | 0.559633 | 1 | 0.079511 | false | 0 | 0.012232 | 0 | 0.11315 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
105ed6e108255e3a17a0719d906ef6b7af77821a | 5,275 | py | Python | audit_history/tests/test_audit_history.py | smileback-com/django-model-audit-history | 0a127303d7bf4c998772c20f54611265f03f0d71 | [
"MIT"
] | 1 | 2019-01-23T11:47:33.000Z | 2019-01-23T11:47:33.000Z | audit_history/tests/test_audit_history.py | nexto/django-model-audit-history | 0a127303d7bf4c998772c20f54611265f03f0d71 | [
"MIT"
] | 3 | 2019-01-25T11:11:17.000Z | 2019-05-20T11:44:22.000Z | audit_history/tests/test_audit_history.py | smileback-com/django-model-audit-history | 0a127303d7bf4c998772c20f54611265f03f0d71 | [
"MIT"
] | 1 | 2019-01-24T14:17:26.000Z | 2019-01-24T14:17:26.000Z | import datetime
from .main import BaseTestSetUp
from test_app.models import BlogPost
from audit_history.settings import TIMESTAMP_FORMAT
class AuditHistoryTest(BaseTestSetUp):
def test_create_instance(self):
self.blog_post.save()
self.assertEqual(1, BlogPost.objects.count())
def test_empty_history_after_save(self):
self.blog_post.save()
self.assertEqual([], self.blog_post.history)
def test_default_timestamp_in_audit_history(self):
self.blog_post.save_with_audit_record(None, self.history_event)
timestamp = self.blog_post.history[0].get('timestamp')
try:
dt = datetime.datetime.strptime(timestamp, TIMESTAMP_FORMAT)
except ValueError:
dt = None
self.assertTrue(dt)
def test_not_used_timestamp_in_audit_history(self):
self.blog_post.save_with_audit_record(None, self.history_event)
timestamp = self.blog_post.history[0].get('timestamp')
try:
dt = datetime.datetime.strptime(timestamp, self.not_used_timestamp_format)
except ValueError:
dt = None
self.assertFalse(dt)
def test_history_after_save_with_audit(self):
self.blog_post.save_with_audit_record(None, self.history_event, payload=self.payload)
self.assertEqual(self.payload['a'], self.blog_post.history[0]['payload']['a'])
def test_save_with_audit_record_with_staff_user(self):
self.blog_post.save_with_audit_record(self.user, self.history_event, payload=self.payload)
self.assertEqual(self.user_name, self.blog_post.history[0]['actor']['name'])
self.assertEqual(self.user_email, self.blog_post.history[0]['actor']['email'])
self.assertEqual(True, self.blog_post.history[0]['actor']['is_staff'])
self.assertEqual(self.payload['a'], self.blog_post.history[0]['payload']['a'])
self.assertEqual(self.payload['b'], self.blog_post.history[0]['payload']['b'])
def test_save_with_audit_record_without_user(self):
self.blog_post.save_with_audit_record(None, self.history_event, payload=self.payload)
self.assertEqual(None, self.blog_post.history[0]['actor'])
self.assertEqual(self.payload['a'], self.blog_post.history[0]['payload']['a'])
self.assertEqual(self.payload['b'], self.blog_post.history[0]['payload']['b'])
def test_n_usages_of_save_with_audit(self):
for _ in range(100):
self.blog_post.save_with_audit_record(None, self.history_event, payload=self.payload)
self.assertEqual(100, len(self.blog_post.history))
def test_append_audit_record_with_staff_user(self):
self.blog_post.save()
self.blog_post.append_audit_record(self.user, self.history_event, payload=self.payload)
self.assertEqual(self.user_name, self.blog_post.history[0]['actor']['name'])
self.assertEqual(self.user_email, self.blog_post.history[0]['actor']['email'])
self.assertEqual(True, self.blog_post.history[0]['actor']['is_staff'])
self.assertEqual(self.payload['a'], self.blog_post.history[0]['payload']['a'])
self.assertEqual(self.payload['b'], self.blog_post.history[0]['payload']['b'])
def test_append_audit_record_without_user(self):
self.blog_post.save()
self.blog_post.append_audit_record(None, self.history_event, payload=self.payload)
self.assertEqual(None, self.blog_post.history[0]['actor'])
self.assertEqual(self.payload['a'], self.blog_post.history[0]['payload']['a'])
self.assertEqual(self.payload['b'], self.blog_post.history[0]['payload']['b'])
def test_n_usages_of_append_audit_record(self):
self.blog_post.save()
for _ in range(100):
self.blog_post.append_audit_record(None, self.history_event, payload=self.payload)
self.assertEqual(100, len(self.blog_post.history))
def test_update_with_audit_record_with_staff_user(self):
self.blog_post.save()
self.blog_post.update_with_audit_record(self.user, self.history_event, **self.payload_for_update)
self.assertEqual(self.user_name, self.blog_post.history[0]['actor']['name'])
self.assertEqual(self.user_email, self.blog_post.history[0]['actor']['email'])
self.assertEqual(True, self.blog_post.history[0]['actor']['is_staff'])
self.assertEqual(self.payload_for_update['title'], self.blog_post.history[0]['title'])
self.assertEqual(self.payload_for_update['position'], int(self.blog_post.history[0]['position']))
def test_update_with_audit_record_without_user(self):
self.blog_post.save()
self.blog_post.update_with_audit_record(None, self.history_event, **self.payload_for_update)
self.assertEqual(None, self.blog_post.history[0]['actor'])
self.assertEqual(self.payload_for_update['title'], self.blog_post.history[0]['title'])
self.assertEqual(self.payload_for_update['position'], int(self.blog_post.history[0]['position']))
def test_n_usages_of_update_with_audit_record(self):
self.blog_post.save()
for _ in range(100):
self.blog_post.update_with_audit_record(None, self.history_event, **self.payload_for_update)
self.assertEqual(100, len(self.blog_post.history))
| 51.715686 | 105 | 0.708815 | 730 | 5,275 | 4.838356 | 0.094521 | 0.115515 | 0.173273 | 0.166761 | 0.905719 | 0.896942 | 0.881937 | 0.835221 | 0.825878 | 0.814553 | 0 | 0.010295 | 0.152986 | 5,275 | 101 | 106 | 52.227723 | 0.780215 | 0 | 0 | 0.666667 | 0 | 0 | 0.049668 | 0 | 0 | 0 | 0 | 0 | 0.380952 | 1 | 0.166667 | false | 0 | 0.047619 | 0 | 0.22619 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
10b906d7e2f402082ce9a44dd1e77bcab1a22325 | 378 | py | Python | terrascript/data/stackpath.py | mjuenema/python-terrascript | 6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d | [
"BSD-2-Clause"
] | 507 | 2017-07-26T02:58:38.000Z | 2022-01-21T12:35:13.000Z | terrascript/data/stackpath.py | mjuenema/python-terrascript | 6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d | [
"BSD-2-Clause"
] | 135 | 2017-07-20T12:01:59.000Z | 2021-10-04T22:25:40.000Z | terrascript/data/stackpath.py | mjuenema/python-terrascript | 6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d | [
"BSD-2-Clause"
] | 81 | 2018-02-20T17:55:28.000Z | 2022-01-31T07:08:40.000Z | # terrascript/data/stackpath.py
# Automatically generated by tools/makecode.py (24-Sep-2021 15:27:49 UTC)
#
# For imports without namespace, e.g.
#
# >>> import terrascript.data.stackpath
#
# instead of
#
# >>> import terrascript.data.stackpath.stackpath
#
# This is only available for 'official' and 'partner' providers.
from terrascript.data.stackpath.stackpath import *
| 25.2 | 73 | 0.743386 | 49 | 378 | 5.734694 | 0.693878 | 0.213523 | 0.341637 | 0.213523 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.036697 | 0.134921 | 378 | 14 | 74 | 27 | 0.82263 | 0.796296 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
5e16812609f0418e9fb2003df9152566c3346074 | 25,687 | py | Python | tests/functional-tests/remote_snapshot_test.py | leoluan1/ibm-spectrum-scale-csi | 27118d22292030eb89df6850eec742b146ce928f | [
"Apache-2.0"
] | 46 | 2020-01-17T19:08:44.000Z | 2022-03-29T15:19:07.000Z | tests/functional-tests/remote_snapshot_test.py | leoluan1/ibm-spectrum-scale-csi | 27118d22292030eb89df6850eec742b146ce928f | [
"Apache-2.0"
] | 428 | 2020-01-17T19:17:00.000Z | 2022-03-31T12:47:11.000Z | tests/functional-tests/remote_snapshot_test.py | leoluan1/ibm-spectrum-scale-csi | 27118d22292030eb89df6850eec742b146ce928f | [
"Apache-2.0"
] | 42 | 2020-01-17T20:39:31.000Z | 2022-03-25T11:38:27.000Z | import copy
import logging
import pytest
import utils.fileset_functions as ff
import scale_operator as scaleop
LOGGER = logging.getLogger()
@pytest.fixture(scope='session', autouse=True)
def values(request):
global data, remote_data, snapshot_object, kubeconfig_value # are required in every testcase
kubeconfig_value, clusterconfig_value, operator_namespace, test_namespace, runslow_val = scaleop.get_cmd_values(request)
data = scaleop.read_driver_data(clusterconfig_value, test_namespace, operator_namespace, kubeconfig_value)
operator_data = scaleop.read_operator_data(clusterconfig_value, operator_namespace, kubeconfig_value)
keep_objects = data["keepobjects"]
if not("remote" in data):
LOGGER.error("remote data is not provided in cr file")
assert False
remote_data = get_remote_data(data)
ff.cred_check(data)
ff.cred_check(remote_data)
ff.set_data(remote_data)
operator = scaleop.Scaleoperator(kubeconfig_value, operator_namespace)
operator_object = scaleop.Scaleoperatorobject(operator_data, kubeconfig_value)
condition = scaleop.check_ns_exists(kubeconfig_value, operator_namespace)
if condition is True:
if not(operator_object.check(data["csiscaleoperator_name"])):
LOGGER.error("Operator custom object is not deployed succesfully")
assert False
else:
operator.create()
operator.check()
scaleop.check_nodes_available(operator_data["pluginNodeSelector"], "pluginNodeSelector")
scaleop.check_nodes_available(
operator_data["provisionerNodeSelector"], "provisionerNodeSelector")
scaleop.check_nodes_available(
operator_data["attacherNodeSelector"], "attacherNodeSelector")
operator_object.create()
val = operator_object.check()
if val is True:
LOGGER.info("Operator custom object is deployed succesfully")
else:
LOGGER.error("Operator custom object is not deployed succesfully")
assert False
if runslow_val:
value_pvc = [{"access_modes": "ReadWriteMany", "storage": "1Gi"},
{"access_modes": "ReadWriteOnce", "storage": "1Gi"}]
else:
value_pvc = [{"access_modes": "ReadWriteMany", "storage": "1Gi"}]
value_vs_class = {"deletionPolicy": "Delete"}
number_of_snapshots = 1
snapshot_object = scaleop.Snapshot(kubeconfig_value, test_namespace, keep_objects, value_pvc, value_vs_class,
number_of_snapshots, data["image_name"], remote_data["id"], data["pluginNodeSelector"])
ff.create_dir(remote_data["volDirBasePath"])
yield
if condition is False and not(keep_objects):
operator_object.delete()
operator.delete()
if(ff.fileset_exists(data)):
ff.delete_fileset(data)
def get_remote_data(data_passed):
remote_data = copy.deepcopy(data_passed)
remote_data["remoteFs_remote_name"] = ff.get_remoteFs_remotename(data)
if remote_data["remoteFs_remote_name"] is None:
LOGGER.error("Unable to get remoteFs , name on remote cluster")
assert False
remote_data["primaryFs"] = remote_data["remoteFs_remote_name"]
remote_data["id"] = remote_data["remoteid"]
remote_data["port"] = remote_data["remote_port"]
for cluster in remote_data["clusters"]:
if cluster["id"] == remote_data["remoteid"]:
remote_data["guiHost"] = cluster["restApi"][0]["guiHost"]
remote_sec_name = cluster["secrets"]
remote_data["username"] = remote_data["remote_username"][remote_sec_name]
remote_data["password"] = remote_data["remote_password"][remote_sec_name]
remote_data["volDirBasePath"] = remote_data["r_volDirBasePath"]
remote_data["parentFileset"] = remote_data["r_parentFileset"]
remote_data["gid_name"] = remote_data["r_gid_name"]
remote_data["uid_name"] = remote_data["r_uid_name"]
remote_data["gid_number"] = remote_data["r_gid_number"]
remote_data["uid_number"] = remote_data["r_uid_number"]
remote_data["inodeLimit"] = remote_data["r_inodeLimit"]
# for get_mount_point function
remote_data["type_remote"] = {"username": data_passed["username"],
"password": data_passed["password"],
"port": data_passed["port"],
"guiHost": data_passed["guiHost"]}
return remote_data
@pytest.mark.regression
def test_get_version():
LOGGER.info("Remote Cluster Details:")
LOGGER.info("-----------------------")
ff.get_scale_version(remote_data)
LOGGER.info("Local Cluster Details:")
LOGGER.info("-----------------------")
ff.get_scale_version(data)
scaleop.get_kubernetes_version(kubeconfig_value)
scaleop.scale_function.get_operator_image()
scaleop.ob.get_driver_image()
@pytest.mark.regression
def test_snapshot_static_pass_1():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"]}
snapshot_object.test_static(value_sc, test_restore=True)
@pytest.mark.regression
def test_snapshot_static_multiple_snapshots():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"]}
snapshot_object.test_static(value_sc, test_restore=True, number_of_snapshots=3)
def test_snapshot_static_pass_3():
value_sc = {"volBackendFs": data["remoteFs"],
"clusterId": data["remoteid"], "gid": data["r_gid_number"]}
snapshot_object.test_static(value_sc, test_restore=True)
def test_snapshot_static_pass_4():
value_sc = {"volBackendFs": data["remoteFs"],
"clusterId": data["remoteid"], "inodeLimit": data["r_inodeLimit"]}
snapshot_object.test_static(value_sc, test_restore=True)
def test_snapshot_static_pass_5():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"],
"inodeLimit": data["r_inodeLimit"], "uid": data["r_uid_number"]}
snapshot_object.test_static(value_sc, test_restore=True)
def test_snapshot_static_pass_6():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"],
"gid": data["r_gid_number"], "uid": data["r_uid_number"]}
snapshot_object.test_static(value_sc, test_restore=True)
def test_snapshot_static_pass_7():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"],
"inodeLimit": data["r_inodeLimit"], "gid": data["r_gid_number"]}
snapshot_object.test_static(value_sc, test_restore=True)
def test_snapshot_static_pass_8():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"],
"inodeLimit": data["r_inodeLimit"], "uid": data["r_uid_number"],
"gid": data["r_gid_number"]}
snapshot_object.test_static(value_sc, test_restore=True)
def test_snapshot_static_pass_9():
value_sc = {"volBackendFs": data["remoteFs"],
"clusterId": data["remoteid"], "uid": data["r_uid_number"]}
snapshot_object.test_static(value_sc, test_restore=True)
def test_snapshot_static_pass_10():
value_sc = {"volBackendFs": data["remoteFs"],
"inodeLimit": data["r_inodeLimit"],
"clusterId": data["remoteid"], "filesetType": "independent"}
snapshot_object.test_static(value_sc, test_restore=True)
def test_snapshot_static_pass_11():
value_sc = {"volBackendFs": data["remoteFs"], "gid": data["r_gid_number"],
"uid": data["r_uid_number"], "clusterId": data["remoteid"],
"filesetType": "independent", "inodeLimit": data["r_inodeLimit"]}
snapshot_object.test_static(value_sc, test_restore=True)
def test_snapshot_static_pass_12():
value_sc = {"clusterId": data["remoteid"], "gid": data["r_gid_number"],
"uid": data["r_uid_number"], "volBackendFs": data["remoteFs"]}
snapshot_object.test_static(value_sc, test_restore=True)
def test_snapshot_static_pass_13():
value_sc = {"clusterId": data["remoteid"], "uid": data["r_uid_number"],
"inodeLimit": data["r_inodeLimit"],
"volBackendFs": data["remoteFs"]}
snapshot_object.test_static(value_sc, test_restore=True)
def test_snapshot_static_pass_14():
value_sc = {"clusterId": data["remoteid"], "gid": data["r_gid_number"],
"inodeLimit": data["r_inodeLimit"],
"volBackendFs": data["remoteFs"]}
snapshot_object.test_static(value_sc, test_restore=True)
def test_snapshot_static_pass_15():
value_sc = {"clusterId": data["remoteid"], "volBackendFs": data["remoteFs"],
"gid": data["r_gid_number"], "uid": data["r_uid_number"],
"inodeLimit": data["r_inodeLimit"]}
snapshot_object.test_static(value_sc, test_restore=True)
def test_snapshot_static_pass_16():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"]}
snapshot_object.test_static(value_sc, test_restore=False)
def test_snapshot_static_pass_17():
value_sc = {"volBackendFs": data["remoteFs"], "gid": data["r_gid_number"],
"uid": data["r_uid_number"], "clusterId": data["remoteid"],
"filesetType": "independent", "inodeLimit": data["r_inodeLimit"]}
snapshot_object.test_static(value_sc, test_restore=False)
def test_snapshot_static_pass_18():
value_sc = {"clusterId": data["remoteid"], "gid": data["r_gid_number"],
"inodeLimit": data["r_inodeLimit"],
"volBackendFs": data["remoteFs"]}
snapshot_object.test_static(value_sc, test_restore=False)
@pytest.mark.regression
def test_snapshot_dynamic_pass_1():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"]}
snapshot_object.test_dynamic(value_sc, test_restore=True)
def test_snapshot_dynamic_pass_2():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"]}
snapshot_object.test_dynamic(value_sc, test_restore=True, value_vs_class={"deletionPolicy": "Retain"})
@pytest.mark.regression
def test_snapshot_dynamic_expected_fail_1():
value_sc = {"volBackendFs": data["remoteFs"],
"filesetType": "dependent", "clusterId": data["remoteid"]}
snapshot_object.test_dynamic(value_sc, test_restore=False, reason="Volume snapshot can only be created when source volume is independent fileset")
@pytest.mark.regression
def test_snapshot_dynamic_expected_fail_2():
value_sc = {"volBackendFs": data["remoteFs"],
"volDirBasePath": data["r_volDirBasePath"]}
snapshot_object.test_dynamic(value_sc, test_restore=False, reason="Volume snapshot can only be created when source volume is independent fileset")
@pytest.mark.regression
def test_snapshot_dynamic_multiple_snapshots():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"]}
snapshot_object.test_dynamic(value_sc, test_restore=True, number_of_snapshots=3)
@pytest.mark.slow
def test_snapshot_dynamic_multiple_snapshots_256():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"]}
snapshot_object.test_dynamic(value_sc, test_restore=True, number_of_snapshots=256)
@pytest.mark.slow
def test_snapshot_dynamic_multiple_snapshots_257():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"]}
snapshot_object.test_dynamic(value_sc, test_restore=True, number_of_snapshots=257)
def test_snapshot_dynamic_pass_3():
value_sc = {"volBackendFs": data["remoteFs"],
"clusterId": data["remoteid"], "gid": data["r_gid_number"]}
snapshot_object.test_dynamic(value_sc, test_restore=True)
def test_snapshot_dynamic_pass_4():
value_sc = {"volBackendFs": data["remoteFs"],
"clusterId": data["remoteid"], "inodeLimit": data["r_inodeLimit"]}
snapshot_object.test_dynamic(value_sc, test_restore=True)
def test_snapshot_dynamic_pass_5():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"],
"inodeLimit": data["r_inodeLimit"], "uid": data["r_uid_number"]}
snapshot_object.test_dynamic(value_sc, test_restore=True)
def test_snapshot_dynamic_pass_6():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"],
"gid": data["r_gid_number"], "uid": data["r_uid_number"]}
snapshot_object.test_dynamic(value_sc, test_restore=True)
def test_snapshot_dynamic_pass_7():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"],
"inodeLimit": data["r_inodeLimit"], "gid": data["r_gid_number"]}
snapshot_object.test_dynamic(value_sc, test_restore=True)
def test_snapshot_dynamic_pass_8():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"],
"inodeLimit": data["r_inodeLimit"], "uid": data["r_uid_number"],
"gid": data["r_gid_number"]}
snapshot_object.test_dynamic(value_sc, test_restore=True)
def test_snapshot_dynamic_pass_9():
value_sc = {"volBackendFs": data["remoteFs"],
"clusterId": data["remoteid"], "uid": data["r_uid_number"]}
snapshot_object.test_dynamic(value_sc, test_restore=True)
def test_snapshot_dynamic_pass_10():
value_sc = {"volBackendFs": data["remoteFs"],
"inodeLimit": data["r_inodeLimit"],
"clusterId": data["remoteid"], "filesetType": "independent"}
snapshot_object.test_dynamic(value_sc, test_restore=True)
def test_snapshot_dynamic_pass_11():
value_sc = {"volBackendFs": data["remoteFs"], "gid": data["r_gid_number"],
"uid": data["r_uid_number"], "clusterId": data["remoteid"],
"filesetType": "independent", "inodeLimit": data["r_inodeLimit"]}
snapshot_object.test_dynamic(value_sc, test_restore=True)
def test_snapshot_dynamic_pass_12():
value_sc = {"clusterId": data["remoteid"], "gid": data["r_gid_number"],
"uid": data["r_uid_number"], "volBackendFs": data["remoteFs"]}
snapshot_object.test_dynamic(value_sc, test_restore=True)
def test_snapshot_dynamic_pass_13():
value_sc = {"clusterId": data["remoteid"], "uid": data["r_uid_number"],
"inodeLimit": data["r_inodeLimit"],
"volBackendFs": data["remoteFs"]}
snapshot_object.test_dynamic(value_sc, test_restore=True)
def test_snapshot_dynamic_pass_14():
value_sc = {"clusterId": data["remoteid"], "gid": data["r_gid_number"],
"inodeLimit": data["r_inodeLimit"],
"volBackendFs": data["remoteFs"]}
snapshot_object.test_dynamic(value_sc, test_restore=True)
def test_snapshot_dynamic_pass_15():
value_sc = {"clusterId": data["remoteid"], "volBackendFs": data["remoteFs"],
"gid": data["r_gid_number"], "uid": data["r_uid_number"],
"inodeLimit": data["r_inodeLimit"]}
snapshot_object.test_dynamic(value_sc, test_restore=True)
def test_snapshot_dynamic_pass_16():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"]}
snapshot_object.test_dynamic(value_sc, test_restore=False)
def test_snapshot_dynamic_pass_17():
value_sc = {"volBackendFs": data["remoteFs"], "gid": data["r_gid_number"],
"uid": data["r_uid_number"], "clusterId": data["remoteid"],
"filesetType": "independent", "inodeLimit": data["r_inodeLimit"]}
snapshot_object.test_dynamic(value_sc, test_restore=False)
def test_snapshot_dynamic_pass_18():
value_sc = {"clusterId": data["remoteid"], "gid": data["r_gid_number"],
"inodeLimit": data["r_inodeLimit"],
"volBackendFs": data["remoteFs"]}
snapshot_object.test_dynamic(value_sc, test_restore=False)
@pytest.mark.regression
def test_snapshot_dynamic_different_sc_1():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"]}
restore_sc = {"volBackendFs": data["remoteFs"], "volDirBasePath": data["r_volDirBasePath"]}
snapshot_object.test_dynamic(value_sc, test_restore=True, restore_sc=restore_sc)
@pytest.mark.regression
def test_snapshot_dynamic_different_sc_2():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"]}
restore_sc = {"volBackendFs": data["remoteFs"],
"filesetType": "dependent", "clusterId": data["remoteid"]}
snapshot_object.test_dynamic(value_sc, test_restore=True, restore_sc=restore_sc)
def test_snapshot_dynamic_different_sc_3():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"],
"inodeLimit": data["r_inodeLimit"], "uid": data["r_uid_number"],
"gid": data["r_gid_number"]}
restore_sc = {"volBackendFs": data["remoteFs"], "volDirBasePath": data["r_volDirBasePath"]}
snapshot_object.test_dynamic(value_sc, test_restore=True, restore_sc=restore_sc)
def test_snapshot_dynamic_different_sc_4():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"],
"inodeLimit": data["r_inodeLimit"], "uid": data["r_uid_number"],
"gid": data["r_gid_number"]}
restore_sc = {"volBackendFs": data["remoteFs"],
"filesetType": "dependent", "clusterId": data["remoteid"]}
snapshot_object.test_dynamic(value_sc, test_restore=True, restore_sc=restore_sc)
def test_snapshot_dynamic_different_sc_5():
value_sc = {"volBackendFs": data["remoteFs"],
"inodeLimit": data["r_inodeLimit"],
"clusterId": data["remoteid"], "filesetType": "independent"}
restore_sc = {"volBackendFs": data["remoteFs"], "volDirBasePath": data["r_volDirBasePath"]}
snapshot_object.test_dynamic(value_sc, test_restore=True, restore_sc=restore_sc)
def test_snapshot_dynamic_different_sc_6():
value_sc = {"volBackendFs": data["remoteFs"],
"inodeLimit": data["r_inodeLimit"],
"clusterId": data["remoteid"], "filesetType": "independent"}
restore_sc = {"volBackendFs": data["remoteFs"],
"filesetType": "dependent", "clusterId": data["remoteid"]}
snapshot_object.test_dynamic(value_sc, test_restore=True, restore_sc=restore_sc)
def test_snapshot_static_different_sc_1():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"]}
restore_sc = {"volBackendFs": data["remoteFs"], "volDirBasePath": data["r_volDirBasePath"]}
snapshot_object.test_static(value_sc, test_restore=True, restore_sc=restore_sc)
def test_snapshot_static_different_sc_2():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"]}
restore_sc = {"volBackendFs": data["remoteFs"],
"filesetType": "dependent", "clusterId": data["remoteid"]}
snapshot_object.test_static(value_sc, test_restore=True, restore_sc=restore_sc)
def test_snapshot_static_different_sc_3():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"],
"inodeLimit": data["r_inodeLimit"], "uid": data["r_uid_number"],
"gid": data["r_gid_number"]}
restore_sc = {"volBackendFs": data["remoteFs"], "volDirBasePath": data["r_volDirBasePath"]}
snapshot_object.test_static(value_sc, test_restore=True, restore_sc=restore_sc)
def test_snapshot_static_different_sc_4():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"],
"inodeLimit": data["r_inodeLimit"], "uid": data["r_uid_number"],
"gid": data["r_gid_number"]}
restore_sc = {"volBackendFs": data["remoteFs"],
"filesetType": "dependent", "clusterId": data["remoteid"]}
snapshot_object.test_static(value_sc, test_restore=True, restore_sc=restore_sc)
def test_snapshot_static_different_sc_5():
value_sc = {"volBackendFs": data["remoteFs"],
"inodeLimit": data["r_inodeLimit"],
"clusterId": data["remoteid"], "filesetType": "independent"}
restore_sc = {"volBackendFs": data["remoteFs"], "volDirBasePath": data["r_volDirBasePath"]}
snapshot_object.test_static(value_sc, test_restore=True, restore_sc=restore_sc)
def test_snapshot_static_different_sc_6():
value_sc = {"volBackendFs": data["remoteFs"],
"inodeLimit": data["r_inodeLimit"],
"clusterId": data["remoteid"], "filesetType": "independent"}
restore_sc = {"volBackendFs": data["remoteFs"],
"filesetType": "dependent", "clusterId": data["remoteid"]}
snapshot_object.test_static(value_sc, test_restore=True, restore_sc=restore_sc)
@pytest.mark.regression
def test_snapshot_dynamic_nodeclass_1():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"]}
restore_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"], "nodeClass": "GUI_MGMT_SERVERS"}
snapshot_object.test_dynamic(value_sc, test_restore=True, restore_sc=restore_sc)
@pytest.mark.regression
def test_snapshot_dynamic_nodeclass_2():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"]}
restore_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"], "nodeClass": "GUI_SERVERS"}
snapshot_object.test_dynamic(value_sc, test_restore=True, restore_sc=restore_sc)
def test_snapshot_dynamic_nodeclass_3():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"]}
restore_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"], "nodeClass": "randomnodeclassx"}
restore_pvc = {"access_modes": "ReadWriteMany", "storage": "1Gi", "reason": "NotFound desc = nodeclass"}
snapshot_object.test_dynamic(value_sc, test_restore=True, restore_sc=restore_sc, restore_pvc=restore_pvc)
def test_snapshot_static_nodeclass_1():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"]}
restore_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"], "nodeClass": "GUI_MGMT_SERVERS"}
snapshot_object.test_static(value_sc, test_restore=True, restore_sc=restore_sc)
def test_snapshot_static_nodeclass_2():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"]}
restore_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"], "nodeClass": "GUI_SERVERS"}
snapshot_object.test_static(value_sc, test_restore=True, restore_sc=restore_sc)
def test_snapshot_static_nodeclass_3():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"]}
restore_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"], "nodeClass": "randomnodeclassx"}
restore_pvc = {"access_modes": "ReadWriteMany", "storage": "1Gi", "reason": "NotFound desc = nodeclass"}
snapshot_object.test_static(value_sc, test_restore=True, restore_sc=restore_sc, restore_pvc=restore_pvc)
def test_snapshot_dynamic_permissions_777_independent():
LOGGER.warning("Testcase will fail if scale version < 5.1.1-4")
value_pod = {"mount_path": "/usr/share/nginx/html/scale", "read_only": "False", "sub_path": ["sub_path_mnt"],
"volumemount_readonly": [False]}
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"], "permissions": "777",
"gid": data["r_gid_number"], "uid": data["r_uid_number"]}
snapshot_object.test_dynamic(value_sc, test_restore=True, value_pod=value_pod)
def test_snapshot_dynamic_volume_expansion_1():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"], "allow_volume_expansion": True}
value_pvc = [{"access_modes": "ReadWriteMany", "storage": "1Gi", "presnap_volume_expansion_storage": ["2Gi"],
"post_presnap_volume_expansion_storage": ["5Gi", "15Gi"], "postsnap_volume_expansion_storage": ["10Gi", "15Gi"]}]
snapshot_object.test_dynamic(value_sc, test_restore=True, value_pvc=value_pvc)
def test_snapshot_dynamic_volume_expansion_2():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"], "allow_volume_expansion": True}
restore_sc = {"volBackendFs": data["remoteFs"],
"filesetType": "dependent", "clusterId": data["remoteid"], "allow_volume_expansion": True}
value_pvc = [{"access_modes": "ReadWriteMany", "storage": "1Gi", "presnap_volume_expansion_storage": ["3Gi"],
"post_presnap_volume_expansion_storage": ["5Gi", "12Gi"], "postsnap_volume_expansion_storage": ["8Gi", "12Gi"]}]
snapshot_object.test_dynamic(value_sc, test_restore=True, value_pvc=value_pvc, restore_sc=restore_sc)
def test_snapshot_dynamic_volume_expansion_3():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"], "allow_volume_expansion": True}
restore_sc = {"volBackendFs": data["remoteFs"], "volDirBasePath": data["r_volDirBasePath"],
"allow_volume_expansion": True}
value_pvc = [{"access_modes": "ReadWriteMany", "storage": "1Gi", "presnap_volume_expansion_storage": ["2Gi"],
"post_presnap_volume_expansion_storage": ["5Gi", "15Gi"], "postsnap_volume_expansion_storage": ["10Gi", "15Gi"]}]
snapshot_object.test_dynamic(value_sc, test_restore=True, value_pvc=value_pvc, restore_sc=restore_sc)
def test_snapshot_dynamic_volume_cloning_1():
value_sc = {"volBackendFs": data["remoteFs"], "clusterId": data["remoteid"]}
value_pvc = [{"access_modes": "ReadWriteMany", "storage": "1Gi"}]
value_clone_passed = {"clone_pvc": [{"access_modes": "ReadWriteMany", "storage": "1Gi"}, {"access_modes": "ReadWriteOnce", "storage": "1Gi"}]}
snapshot_object.test_dynamic(value_sc, test_restore=True, value_pvc=value_pvc, value_clone_passed=value_clone_passed)
| 46.874088 | 150 | 0.692685 | 3,003 | 25,687 | 5.571762 | 0.070929 | 0.05355 | 0.120488 | 0.114989 | 0.829249 | 0.816519 | 0.798291 | 0.793091 | 0.779465 | 0.76267 | 0 | 0.006352 | 0.160392 | 25,687 | 547 | 151 | 46.959781 | 0.769463 | 0.002297 | 0 | 0.591133 | 0 | 0 | 0.285854 | 0.021698 | 0 | 0 | 0 | 0 | 0.009852 | 1 | 0.165025 | false | 0.108374 | 0.012315 | 0 | 0.179803 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 7 |
eac0677cb910e01532d0d4b534681adc03eeeaaf | 138 | py | Python | topcoder/memory.py | leetcode-notes/daily-algorithms-practice | 2a03499ed0b403d79f6c8451c9a839991b23e188 | [
"Unlicense"
] | null | null | null | topcoder/memory.py | leetcode-notes/daily-algorithms-practice | 2a03499ed0b403d79f6c8451c9a839991b23e188 | [
"Unlicense"
] | null | null | null | topcoder/memory.py | leetcode-notes/daily-algorithms-practice | 2a03499ed0b403d79f6c8451c9a839991b23e188 | [
"Unlicense"
] | null | null | null | '''
https://community.topcoder.com/stat?c=problem_statement&pm=16009https://community.topcoder.com/stat?c=problem_statement&pm=16009'
'''
| 34.5 | 129 | 0.782609 | 19 | 138 | 5.578947 | 0.578947 | 0.320755 | 0.377358 | 0.45283 | 0.811321 | 0.811321 | 0.811321 | 0.811321 | 0 | 0 | 0 | 0.074074 | 0.021739 | 138 | 3 | 130 | 46 | 0.711111 | 0.934783 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 0 | 0 | null | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 11 |
eadf20db5d51ec98e024641cbd9fd2865afe42de | 36,763 | py | Python | venv/lib/python3.6/site-packages/ansible_collections/cisco/ios/tests/unit/modules/network/ios/test_ios_bgp_address_family.py | usegalaxy-no/usegalaxy | 75dad095769fe918eb39677f2c887e681a747f3a | [
"MIT"
] | 1 | 2020-01-22T13:11:23.000Z | 2020-01-22T13:11:23.000Z | venv/lib/python3.6/site-packages/ansible_collections/cisco/ios/tests/unit/modules/network/ios/test_ios_bgp_address_family.py | usegalaxy-no/usegalaxy | 75dad095769fe918eb39677f2c887e681a747f3a | [
"MIT"
] | 12 | 2020-02-21T07:24:52.000Z | 2020-04-14T09:54:32.000Z | venv/lib/python3.6/site-packages/ansible_collections/cisco/ios/tests/unit/modules/network/ios/test_ios_bgp_address_family.py | usegalaxy-no/usegalaxy | 75dad095769fe918eb39677f2c887e681a747f3a | [
"MIT"
] | null | null | null | #
# (c) 2019, Ansible by Red Hat, inc
# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
#
from __future__ import absolute_import, division, print_function
__metaclass__ = type
from ansible_collections.cisco.ios.tests.unit.compat.mock import patch
from ansible_collections.cisco.ios.plugins.modules import (
ios_bgp_address_family,
)
from ansible_collections.cisco.ios.tests.unit.modules.utils import (
set_module_args,
)
from .ios_module import TestIosModule, load_fixture
class TestIosBgpAddressFamilyModule(TestIosModule):
module = ios_bgp_address_family
def setUp(self):
super(TestIosBgpAddressFamilyModule, self).setUp()
self.mock_get_config = patch(
"ansible_collections.ansible.netcommon.plugins.module_utils.network.common.network.Config.get_config"
)
self.get_config = self.mock_get_config.start()
self.mock_load_config = patch(
"ansible_collections.ansible.netcommon.plugins.module_utils.network.common.network.Config.load_config"
)
self.load_config = self.mock_load_config.start()
self.mock_get_resource_connection_config = patch(
"ansible_collections.ansible.netcommon.plugins.module_utils.network.common.cfg.base."
"get_resource_connection"
)
self.get_resource_connection_config = (
self.mock_get_resource_connection_config.start()
)
self.mock_get_resource_connection_facts = patch(
"ansible_collections.ansible.netcommon.plugins.module_utils.network.common.rm_base.resource_module_base."
"get_resource_connection"
)
self.get_resource_connection_facts = (
self.mock_get_resource_connection_facts.start()
)
self.mock_edit_config = patch(
"ansible_collections.cisco.ios.plugins.module_utils.network.ios.providers.providers.CliProvider.edit_config"
)
self.edit_config = self.mock_edit_config.start()
self.mock_execute_show_command = patch(
"ansible_collections.cisco.ios.plugins.module_utils.network.ios.facts.bgp_address_family.bgp_address_family."
"Bgp_address_familyFacts.get_bgp_address_family_data"
)
self.execute_show_command = self.mock_execute_show_command.start()
def tearDown(self):
super(TestIosBgpAddressFamilyModule, self).tearDown()
self.mock_get_resource_connection_config.stop()
self.mock_get_resource_connection_facts.stop()
self.mock_edit_config.stop()
self.mock_get_config.stop()
self.mock_load_config.stop()
self.mock_execute_show_command.stop()
def load_fixtures(self, commands=None):
def load_from_file(*args, **kwargs):
return load_fixture("ios_bgp_address_family.cfg")
self.execute_show_command.side_effect = load_from_file
def test_ios_bgp_address_family_merged(self):
set_module_args(
dict(
config=dict(
as_number="65000",
address_family=[
dict(
afi="ipv4",
safi="multicast",
vrf="blue",
aggregate_address=[
dict(
address="192.0.3.1",
netmask="255.255.255.255",
as_confed_set=True,
)
],
bgp=dict(
dampening=dict(
penalty_half_time=10,
reuse_route_val=10,
suppress_route_val=10,
max_suppress=10,
)
),
neighbor=[
dict(
address="198.51.100.1",
remote_as=65100,
route_maps=[
dict(name="test-route-out", out="true")
],
prefix_lists=[
dict(
name="AS65100-PREFIX-OUT",
out="true",
)
],
)
],
),
dict(
afi="nsap",
bgp=dict(
aggregate_timer=20,
dmzlink_bw=True,
scan_time=10,
),
default_metric=10,
network=[
dict(
address="192.0.1.1", route_map="test_route"
)
],
),
],
),
state="merged",
)
)
commands = [
"router bgp 65000",
"address-family ipv4 multicast vrf blue",
"bgp dampening 10 10 10 10",
"aggregate-address 192.0.3.1 255.255.255.255 as-confed-set",
"address-family nsap",
"bgp aggregate-timer 20",
"bgp dmzlink-bw",
"bgp scan-time 10",
"neighbor 198.51.100.1 remote-as 65100",
"neighbor 198.51.100.1 route-map test-route-out out",
"network 192.0.1.1 route-map test_route",
"default-metric 10",
]
result = self.execute_module(changed=True)
self.assertEqual(sorted(result["commands"]), sorted(commands))
def test_ios_bgp_address_family_merged_2(self):
set_module_args(
dict(
config=dict(
as_number="65000",
address_family=[
dict(
afi="ipv4",
safi="unicast",
vrf="blue",
neighbor=[
dict(
address="192.0.3.1",
remote_as=65001,
soft_reconfiguration=True,
prefix_list=dict(
name="PREFIX-OUT", out=True
),
)
],
network=[
dict(address="192.0.3.1", mask="255.255.255.0")
],
)
],
),
state="merged",
)
)
commands = [
"router bgp 65000",
"address-family ipv4 unicast vrf blue",
"neighbor 192.0.3.1 remote-as 65001",
"neighbor 192.0.3.1 prefix-list PREFIX-OUT out",
"neighbor 192.0.3.1 soft-reconfiguration inbound",
"network 192.0.3.1 mask 255.255.255.0",
]
result = self.execute_module(changed=True)
self.assertEqual(sorted(result["commands"]), sorted(commands))
def test_ios_bgp_address_family_merged_idempotent(self):
set_module_args(
dict(
config=dict(
as_number="65000",
address_family=[
dict(
afi="ipv4",
safi="multicast",
vrf="blue",
aggregate_address=[
dict(
address="192.0.2.1",
netmask="255.255.255.255",
as_confed_set=True,
)
],
bgp=dict(
aggregate_timer=10,
dampening=dict(
penalty_half_time=1,
reuse_route_val=1,
suppress_route_val=1,
max_suppress=1,
),
slow_peer=[
dict(detection=dict(threshold=150))
],
),
neighbor=[
dict(
activate=True,
address="198.51.100.1",
aigp=dict(
send=dict(
cost_community=dict(
id=100,
poi=dict(
igp_cost=True,
transitive=True,
),
)
)
),
next_hop_self=True,
nexthop_self=dict(all=True),
prefix_lists=[
dict(
name="AS65100-PREFIX-OUT",
out="true",
)
],
slow_peer=[
dict(detection=dict(threshold=150))
],
remote_as=10,
route_maps=[
dict(name="test-out", out=True)
],
route_server_client=True,
)
],
network=[
dict(
address="198.51.110.10",
mask="255.255.255.255",
backdoor=True,
)
],
),
dict(
afi="ipv4",
safi="mdt",
bgp=dict(
dmzlink_bw=True,
dampening=dict(
penalty_half_time=1,
reuse_route_val=10,
suppress_route_val=100,
max_suppress=5,
),
soft_reconfig_backup=True,
),
),
dict(
afi="ipv4",
safi="multicast",
aggregate_address=[
dict(
address="192.0.3.1",
netmask="255.255.255.255",
as_confed_set=True,
)
],
default_metric=12,
distance=dict(external=10, internal=10, local=100),
network=[
dict(
address="198.51.111.11",
mask="255.255.255.255",
route_map="test",
)
],
table_map=dict(name="test_tableMap", filter=True),
),
],
),
state="merged",
)
)
self.execute_module(changed=False, commands=[])
def test_ios_bgp_address_family_replaced(self):
set_module_args(
dict(
config=dict(
as_number="65000",
address_family=[
dict(
afi="ipv4",
safi="multicast",
vrf="blue",
aggregate_address=[
dict(
address="192.0.2.1",
netmask="255.255.255.255",
as_confed_set=True,
)
],
bgp=dict(
aggregate_timer=10,
slow_peer=[
dict(detection=dict(threshold=200))
],
),
redistribute=[dict(connected=dict(metric=10))],
neighbor=[
dict(
address="198.51.110.1",
activate=True,
remote_as=200,
route_maps=[
dict(
name="test-replaced-route",
out=True,
)
],
)
],
)
],
),
state="replaced",
)
)
commands = [
"router bgp 65000",
"address-family ipv4 multicast vrf blue",
"no bgp dampening 1 1 1 1",
"bgp slow-peer detection threshold 200",
"no neighbor 198.51.100.1 activate",
"no neighbor 198.51.100.1 next-hop-self all",
"no neighbor 198.51.100.1 remote-as 10",
"no neighbor 198.51.100.1 aigp send cost-community 100 poi igp-cost transitive",
"no neighbor 198.51.100.1 route-server-client",
"no neighbor 198.51.100.1 slow-peer detection threshold 150",
"neighbor 198.51.110.1 activate",
"neighbor 198.51.110.1 remote-as 200",
"neighbor 198.51.110.1 route-map test-replaced-route out",
"no network 198.51.110.10 mask 255.255.255.255 backdoor",
]
result = self.execute_module(changed=True)
self.assertEqual(sorted(result["commands"]), sorted(commands))
def test_ios_bgp_address_family_replaced_idempotent(self):
set_module_args(
dict(
config=dict(
as_number="65000",
address_family=[
dict(
afi="ipv4",
safi="multicast",
vrf="blue",
aggregate_address=[
dict(
address="192.0.2.1",
netmask="255.255.255.255",
as_confed_set=True,
)
],
bgp=dict(
aggregate_timer=10,
dampening=dict(
penalty_half_time=1,
reuse_route_val=1,
suppress_route_val=1,
max_suppress=1,
),
slow_peer=[
dict(detection=dict(threshold=150))
],
),
neighbor=[
dict(
activate=True,
address="198.51.100.1",
aigp=dict(
send=dict(
cost_community=dict(
id=100,
poi=dict(
igp_cost=True,
transitive=True,
),
)
)
),
nexthop_self=dict(all=True),
prefix_lists=[
dict(
name="AS65100-PREFIX-OUT",
out="true",
)
],
slow_peer=[
dict(detection=dict(threshold=150))
],
remote_as=10,
route_maps=[
dict(name="test-out", out=True)
],
route_server_client=True,
)
],
network=[
dict(
address="198.51.110.10",
mask="255.255.255.255",
backdoor=True,
)
],
),
dict(
afi="ipv4",
safi="mdt",
bgp=dict(
dmzlink_bw=True,
dampening=dict(
penalty_half_time=1,
reuse_route_val=10,
suppress_route_val=100,
max_suppress=5,
),
soft_reconfig_backup=True,
),
),
dict(
afi="ipv4",
safi="multicast",
aggregate_address=[
dict(
address="192.0.3.1",
netmask="255.255.255.255",
as_confed_set=True,
)
],
default_metric=12,
distance=dict(external=10, internal=10, local=100),
network=[
dict(
address="198.51.111.11",
mask="255.255.255.255",
route_map="test",
)
],
table_map=dict(name="test_tableMap", filter=True),
),
],
),
state="replaced",
)
)
self.execute_module(changed=False, commands=[])
def test_ios_bgp_address_family_overridden_idempotent(self):
set_module_args(
dict(
config=dict(
as_number="65000",
address_family=[
dict(
afi="ipv4",
safi="multicast",
vrf="blue",
aggregate_address=[
dict(
address="192.0.2.1",
netmask="255.255.255.255",
as_confed_set=True,
)
],
bgp=dict(
aggregate_timer=10,
dampening=dict(
penalty_half_time=1,
reuse_route_val=1,
suppress_route_val=1,
max_suppress=1,
),
slow_peer=[
dict(detection=dict(threshold=150))
],
),
neighbor=[
dict(
activate=True,
address="198.51.100.1",
aigp=dict(
send=dict(
cost_community=dict(
id=100,
poi=dict(
igp_cost=True,
transitive=True,
),
)
)
),
nexthop_self=dict(all=True),
prefix_lists=[
dict(
name="AS65100-PREFIX-OUT",
out="true",
)
],
slow_peer=[
dict(detection=dict(threshold=150))
],
remote_as=10,
route_maps=[
dict(name="test-out", out=True)
],
route_server_client=True,
)
],
network=[
dict(
address="198.51.110.10",
mask="255.255.255.255",
backdoor=True,
)
],
),
dict(
afi="ipv4",
safi="mdt",
bgp=dict(
dmzlink_bw=True,
dampening=dict(
penalty_half_time=1,
reuse_route_val=10,
suppress_route_val=100,
max_suppress=5,
),
soft_reconfig_backup=True,
),
),
dict(
afi="ipv4",
safi="multicast",
aggregate_address=[
dict(
address="192.0.3.1",
netmask="255.255.255.255",
as_confed_set=True,
)
],
default_metric=12,
distance=dict(external=10, internal=10, local=100),
network=[
dict(
address="198.51.111.11",
mask="255.255.255.255",
route_map="test",
)
],
table_map=dict(name="test_tableMap", filter=True),
),
],
),
state="overridden",
)
)
self.execute_module(changed=False, commands=[])
def test_ios_bgp_address_family_deleted(self):
set_module_args(dict(state="deleted"))
commands = [
"router bgp 65000",
"no address-family ipv4 multicast vrf blue",
"no address-family ipv4 mdt",
"no address-family ipv4 multicast",
]
result = self.execute_module(changed=True)
self.assertEqual(sorted(result["commands"]), sorted(commands))
def test_ios_bgp_address_family_delete_without_config(self):
set_module_args(
dict(
config=dict(
as_number="65000",
address_family=[
dict(afi="ipv4", safi="multicast"),
dict(afi="ipv4", safi="mdt"),
],
),
state="deleted",
)
)
commands = [
"router bgp 65000",
"no address-family ipv4 mdt",
"no address-family ipv4 multicast",
]
result = self.execute_module(changed=True)
self.assertEqual(sorted(result["commands"]), sorted(commands))
def test_ios_bgp_address_family_rendered(self):
set_module_args(
dict(
config=dict(
as_number="65000",
address_family=[
dict(
afi="ipv4",
safi="multicast",
vrf="blue",
aggregate_address=[
dict(
address="192.0.2.1",
netmask="255.255.255.255",
as_confed_set=True,
)
],
bgp=dict(
dampening=dict(
penalty_half_time=1,
reuse_route_val=1,
suppress_route_val=1,
max_suppress=1,
)
),
neighbor=[
dict(
activate=True,
address="198.51.100.1",
aigp=dict(
send=dict(
cost_community=dict(
id=100,
poi=dict(
igp_cost=True,
transitive=True,
),
)
)
),
slow_peer=[
dict(detection=dict(threshold=150))
],
remote_as=10,
route_maps=[
dict(name="test-route", out=True)
],
route_server_client=True,
)
],
network=[
dict(
address="198.51.110.10",
mask="255.255.255.255",
backdoor=True,
)
],
),
dict(
afi="ipv4",
safi="multicast",
aggregate_address=[
dict(
address="192.0.3.1",
netmask="255.255.255.255",
as_confed_set=True,
)
],
default_metric=12,
distance=dict(external=10, internal=10, local=100),
network=[
dict(
address="198.51.111.11",
mask="255.255.255.255",
route_map="test",
)
],
table_map=dict(name="test_tableMap", filter=True),
),
],
),
state="rendered",
)
)
commands = [
"router bgp 65000",
"address-family ipv4 multicast vrf blue",
"bgp dampening 1 1 1 1",
"neighbor 198.51.100.1 remote-as 10",
"neighbor 198.51.100.1 activate",
"neighbor 198.51.100.1 aigp send cost-community 100 poi igp-cost transitive",
"neighbor 198.51.100.1 route-map test-route out",
"neighbor 198.51.100.1 route-server-client",
"neighbor 198.51.100.1 slow-peer detection threshold 150",
"network 198.51.110.10 mask 255.255.255.255 backdoor",
"aggregate-address 192.0.2.1 255.255.255.255 as-confed-set",
"address-family ipv4 multicast",
"network 198.51.111.11 mask 255.255.255.255 route-map test",
"aggregate-address 192.0.3.1 255.255.255.255 as-confed-set",
"default-metric 12",
"distance bgp 10 10 100",
"table-map test_tableMap filter",
]
result = self.execute_module(changed=False)
self.assertEqual(sorted(result["rendered"]), sorted(commands))
def test_ios_bgp_address_family_parsed(self):
set_module_args(
dict(
running_config="router bgp 65000\n address-family ipv4 multicast vrf blue\n bgp aggregate-timer 10\n bgp slow-peer detection threshold 150",
state="parsed",
)
)
result = self.execute_module(changed=False)
parsed_list = {
"address_family": [
{
"afi": "ipv4",
"bgp": {
"aggregate_timer": 10,
"slow_peer": [{"detection": {"threshold": 150}}],
},
"safi": "multicast",
"vrf": "blue",
}
],
"as_number": "65000",
}
self.assertEqual(parsed_list, result["parsed"])
def test_ios_bgp_address_family_merged_multiple_neighbor(self):
set_module_args(
dict(
config=dict(
as_number="65000",
address_family=[
dict(
afi="ipv4",
neighbor=[
dict(
address="192.31.39.212",
soft_reconfiguration=True,
activate=True,
),
dict(
address="192.31.47.206",
soft_reconfiguration=True,
activate=True,
),
],
network=[
dict(
address="192.0.3.1", mask="255.255.255.0"
),
dict(
address="192.0.2.1", mask="255.255.255.0"
),
dict(
address="192.0.4.1", mask="255.255.255.0"
),
],
)
],
),
state="merged",
)
)
commands = [
"router bgp 65000",
"address-family ipv4",
"neighbor 192.31.39.212 activate",
"neighbor 192.31.39.212 soft-reconfiguration inbound",
"neighbor 192.31.47.206 activate",
"neighbor 192.31.47.206 soft-reconfiguration inbound",
"network 192.0.3.1 mask 255.255.255.0",
"network 192.0.2.1 mask 255.255.255.0",
"network 192.0.4.1 mask 255.255.255.0",
]
result = self.execute_module(changed=True)
self.assertEqual(sorted(result["commands"]), sorted(commands))
def test_ios_bgp_address_family_overridden_multiple_neighbor(self):
set_module_args(
dict(
config=dict(
as_number="65000",
address_family=[
dict(
afi="ipv4",
neighbor=[
dict(
address="192.31.39.212",
soft_reconfiguration=True,
activate=True,
),
dict(
address="192.31.47.206",
soft_reconfiguration=True,
activate=True,
),
],
network=[
dict(
address="192.0.3.1", mask="255.255.255.0"
),
dict(
address="192.0.2.1", mask="255.255.255.0"
),
dict(
address="192.0.4.1", mask="255.255.255.0"
),
],
)
],
),
state="overridden",
)
)
commands = [
"router bgp 65000",
"no address-family ipv4 multicast",
"no address-family ipv4 mdt",
"no address-family ipv4 multicast vrf blue",
"address-family ipv4",
"neighbor 192.31.39.212 activate",
"neighbor 192.31.39.212 soft-reconfiguration inbound",
"neighbor 192.31.47.206 activate",
"neighbor 192.31.47.206 soft-reconfiguration inbound",
"network 192.0.3.1 mask 255.255.255.0",
"network 192.0.2.1 mask 255.255.255.0",
"network 192.0.4.1 mask 255.255.255.0",
]
result = self.execute_module(changed=True)
self.assertEqual(sorted(result["commands"]), sorted(commands))
| 42.847319 | 156 | 0.323722 | 2,483 | 36,763 | 4.616996 | 0.084575 | 0.052338 | 0.048674 | 0.02835 | 0.845865 | 0.801727 | 0.763957 | 0.729676 | 0.699669 | 0.693562 | 0 | 0.099134 | 0.601039 | 36,763 | 857 | 157 | 42.897316 | 0.682484 | 0.003373 | 0 | 0.726061 | 0 | 0.006061 | 0.139215 | 0.019681 | 0 | 0 | 0 | 0 | 0.010909 | 1 | 0.019394 | false | 0 | 0.006061 | 0.001212 | 0.029091 | 0.001212 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
d82d22e7b47203684156102a82e1b3876589bb62 | 36,681 | py | Python | src/ebay_rest/api/commerce_notification/api/subscription_api.py | gbm001/ebay_rest | 077d3478423ccd80ff35e0361821d6a11180bc54 | [
"MIT"
] | 3 | 2021-12-12T04:28:03.000Z | 2022-03-10T03:29:18.000Z | src/ebay_rest/api/commerce_notification/api/subscription_api.py | jdavv/ebay_rest | 20fc88c6aefdae9ab90f9c1330e79abddcd750cd | [
"MIT"
] | 33 | 2021-06-16T20:44:36.000Z | 2022-03-30T14:55:06.000Z | src/ebay_rest/api/commerce_notification/api/subscription_api.py | jdavv/ebay_rest | 20fc88c6aefdae9ab90f9c1330e79abddcd750cd | [
"MIT"
] | 7 | 2021-06-03T09:30:23.000Z | 2022-03-08T19:51:33.000Z | # coding: utf-8
"""
Notification API
The eBay Notification API enables management of the entire end-to-end eBay notification experience by allowing users to:<ul><li>Browse for supported notification topics and retrieve topic details</li><li>Create, configure, and manage notification destination endpionts</li><li>Configure, manage, and test notification subscriptions</li><li>Process eBay notifications and verify the integrity of the message payload</li></ul> # noqa: E501
OpenAPI spec version: v1.2.0
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
from __future__ import absolute_import
import re # noqa: F401
# python 2 and python 3 compatibility library
import six
from ...commerce_notification.api_client import ApiClient
class SubscriptionApi(object):
"""NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
Ref: https://github.com/swagger-api/swagger-codegen
"""
def __init__(self, api_client=None):
if api_client is None:
api_client = ApiClient()
self.api_client = api_client
def create_subscription(self, **kwargs): # noqa: E501
"""create_subscription # noqa: E501
This method allows applications to create a subscription for a topic and supported schema version. Subscriptions allow applications to express interest in notifications and keep receiving the information relevant to their business.<br/><br/>Each application and topic-schema pairing to a subscription should have a 1:1 cardinality.<br/><br/>You can create the subscription in disabled mode, test it (see the <b>test</b> method), and when everything is ready, you can enable the subscription (see the <b>enableSubscription</b> method).<br /><br /><span class=\"tablenote\"><b>Note:</b> If an application is not authorized to subscribe to a topic, for example, if your authorization does not include the list of scopes required for the topic, an error code of 195011 is returned.</span> # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.create_subscription(async_req=True)
>>> result = thread.get()
:param async_req bool
:param CreateSubscriptionRequest body: The create subscription request.
:return: object
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.create_subscription_with_http_info(**kwargs) # noqa: E501
else:
(data) = self.create_subscription_with_http_info(**kwargs) # noqa: E501
return data
def create_subscription_with_http_info(self, **kwargs): # noqa: E501
"""create_subscription # noqa: E501
This method allows applications to create a subscription for a topic and supported schema version. Subscriptions allow applications to express interest in notifications and keep receiving the information relevant to their business.<br/><br/>Each application and topic-schema pairing to a subscription should have a 1:1 cardinality.<br/><br/>You can create the subscription in disabled mode, test it (see the <b>test</b> method), and when everything is ready, you can enable the subscription (see the <b>enableSubscription</b> method).<br /><br /><span class=\"tablenote\"><b>Note:</b> If an application is not authorized to subscribe to a topic, for example, if your authorization does not include the list of scopes required for the topic, an error code of 195011 is returned.</span> # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.create_subscription_with_http_info(async_req=True)
>>> result = thread.get()
:param async_req bool
:param CreateSubscriptionRequest body: The create subscription request.
:return: object
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['body'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method create_subscription" % key
)
params[key] = val
del params['kwargs']
collection_formats = {}
path_params = {}
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'body' in params:
body_params = params['body']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json']) # noqa: E501
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501
['application/json']) # noqa: E501
# Authentication setting
auth_settings = ['api_auth'] # noqa: E501
return self.api_client.call_api(
'/subscription', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='object', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def delete_subscription(self, subscription_id, **kwargs): # noqa: E501
"""delete_subscription # noqa: E501
This method allows applications to delete a subscription. Subscriptions can be deleted regardless of status. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.delete_subscription(subscription_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str subscription_id: The unique identifier for the subscription. (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.delete_subscription_with_http_info(subscription_id, **kwargs) # noqa: E501
else:
(data) = self.delete_subscription_with_http_info(subscription_id, **kwargs) # noqa: E501
return data
def delete_subscription_with_http_info(self, subscription_id, **kwargs): # noqa: E501
"""delete_subscription # noqa: E501
This method allows applications to delete a subscription. Subscriptions can be deleted regardless of status. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.delete_subscription_with_http_info(subscription_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str subscription_id: The unique identifier for the subscription. (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['subscription_id'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method delete_subscription" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'subscription_id' is set
if ('subscription_id' not in params or
params['subscription_id'] is None):
raise ValueError("Missing the required parameter `subscription_id` when calling `delete_subscription`") # noqa: E501
collection_formats = {}
path_params = {}
if 'subscription_id' in params:
path_params['subscription_id'] = params['subscription_id'] # noqa: E501
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# Authentication setting
auth_settings = ['api_auth'] # noqa: E501
return self.api_client.call_api(
'/subscription/{subscription_id}', 'DELETE',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type=None, # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def disable_subscription(self, subscription_id, **kwargs): # noqa: E501
"""disable_subscription # noqa: E501
This method disables a subscription, which prevents the subscription from providing notifications. To restart a subscription, call <strong>enableSubscription</strong>. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.disable_subscription(subscription_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str subscription_id: The unique identifier for the subscription. (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.disable_subscription_with_http_info(subscription_id, **kwargs) # noqa: E501
else:
(data) = self.disable_subscription_with_http_info(subscription_id, **kwargs) # noqa: E501
return data
def disable_subscription_with_http_info(self, subscription_id, **kwargs): # noqa: E501
"""disable_subscription # noqa: E501
This method disables a subscription, which prevents the subscription from providing notifications. To restart a subscription, call <strong>enableSubscription</strong>. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.disable_subscription_with_http_info(subscription_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str subscription_id: The unique identifier for the subscription. (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['subscription_id'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method disable_subscription" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'subscription_id' is set
if ('subscription_id' not in params or
params['subscription_id'] is None):
raise ValueError("Missing the required parameter `subscription_id` when calling `disable_subscription`") # noqa: E501
collection_formats = {}
path_params = {}
if 'subscription_id' in params:
path_params['subscription_id'] = params['subscription_id'] # noqa: E501
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# Authentication setting
auth_settings = ['api_auth'] # noqa: E501
return self.api_client.call_api(
'/subscription/{subscription_id}/disable', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type=None, # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def enable_subscription(self, subscription_id, **kwargs): # noqa: E501
"""enable_subscription # noqa: E501
This method allows applications to enable a disabled subscription. To pause (or disable) an enabled subscription, call <strong>disableSubscription</strong>. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.enable_subscription(subscription_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str subscription_id: The unique identifier for the subscription. (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.enable_subscription_with_http_info(subscription_id, **kwargs) # noqa: E501
else:
(data) = self.enable_subscription_with_http_info(subscription_id, **kwargs) # noqa: E501
return data
def enable_subscription_with_http_info(self, subscription_id, **kwargs): # noqa: E501
"""enable_subscription # noqa: E501
This method allows applications to enable a disabled subscription. To pause (or disable) an enabled subscription, call <strong>disableSubscription</strong>. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.enable_subscription_with_http_info(subscription_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str subscription_id: The unique identifier for the subscription. (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['subscription_id'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method enable_subscription" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'subscription_id' is set
if ('subscription_id' not in params or
params['subscription_id'] is None):
raise ValueError("Missing the required parameter `subscription_id` when calling `enable_subscription`") # noqa: E501
collection_formats = {}
path_params = {}
if 'subscription_id' in params:
path_params['subscription_id'] = params['subscription_id'] # noqa: E501
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# Authentication setting
auth_settings = ['api_auth'] # noqa: E501
return self.api_client.call_api(
'/subscription/{subscription_id}/enable', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type=None, # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def get_subscription(self, subscription_id, **kwargs): # noqa: E501
"""get_subscription # noqa: E501
This method allows applications to retrieve subscription details for the specified subscription.<br /><br />Specify the subscription to retrieve using the <strong>subscription_id</strong>. Use the <strong>getSubscriptions</strong> method to browse all subscriptions if you do not know the <strong>subscription_id</strong>.<br /><br />Subscriptions allow applications to express interest in notifications and keep receiving the information relevant to their business. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.get_subscription(subscription_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str subscription_id: The unique identifier for the subscription. (required)
:return: Subscription
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.get_subscription_with_http_info(subscription_id, **kwargs) # noqa: E501
else:
(data) = self.get_subscription_with_http_info(subscription_id, **kwargs) # noqa: E501
return data
def get_subscription_with_http_info(self, subscription_id, **kwargs): # noqa: E501
"""get_subscription # noqa: E501
This method allows applications to retrieve subscription details for the specified subscription.<br /><br />Specify the subscription to retrieve using the <strong>subscription_id</strong>. Use the <strong>getSubscriptions</strong> method to browse all subscriptions if you do not know the <strong>subscription_id</strong>.<br /><br />Subscriptions allow applications to express interest in notifications and keep receiving the information relevant to their business. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.get_subscription_with_http_info(subscription_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str subscription_id: The unique identifier for the subscription. (required)
:return: Subscription
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['subscription_id'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method get_subscription" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'subscription_id' is set
if ('subscription_id' not in params or
params['subscription_id'] is None):
raise ValueError("Missing the required parameter `subscription_id` when calling `get_subscription`") # noqa: E501
collection_formats = {}
path_params = {}
if 'subscription_id' in params:
path_params['subscription_id'] = params['subscription_id'] # noqa: E501
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json']) # noqa: E501
# Authentication setting
auth_settings = ['api_auth'] # noqa: E501
return self.api_client.call_api(
'/subscription/{subscription_id}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='Subscription', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def get_subscriptions(self, **kwargs): # noqa: E501
"""get_subscriptions # noqa: E501
This method allows applications to retrieve a list of all subscriptions. The list returned is a paginated collection of subscription resources.<br /><br />Subscriptions allow applications to express interest in notifications and keep receiving the information relevant to their business. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.get_subscriptions(async_req=True)
>>> result = thread.get()
:param async_req bool
:param str limit: The number of items, from the result set, returned in a single page. Range is from 10-100. If this parameter is omitted, the default value is used.<br/><br/><b>Default:</b> 20<br/><br/><b>Maximum:</b> 100 items per page
:param str continuation_token: The continuation token for the next set of results.
:return: SubscriptionSearchResponse
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.get_subscriptions_with_http_info(**kwargs) # noqa: E501
else:
(data) = self.get_subscriptions_with_http_info(**kwargs) # noqa: E501
return data
def get_subscriptions_with_http_info(self, **kwargs): # noqa: E501
"""get_subscriptions # noqa: E501
This method allows applications to retrieve a list of all subscriptions. The list returned is a paginated collection of subscription resources.<br /><br />Subscriptions allow applications to express interest in notifications and keep receiving the information relevant to their business. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.get_subscriptions_with_http_info(async_req=True)
>>> result = thread.get()
:param async_req bool
:param str limit: The number of items, from the result set, returned in a single page. Range is from 10-100. If this parameter is omitted, the default value is used.<br/><br/><b>Default:</b> 20<br/><br/><b>Maximum:</b> 100 items per page
:param str continuation_token: The continuation token for the next set of results.
:return: SubscriptionSearchResponse
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['limit', 'continuation_token'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method get_subscriptions" % key
)
params[key] = val
del params['kwargs']
collection_formats = {}
path_params = {}
query_params = []
if 'limit' in params:
query_params.append(('limit', params['limit'])) # noqa: E501
if 'continuation_token' in params:
query_params.append(('continuation_token', params['continuation_token'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json']) # noqa: E501
# Authentication setting
auth_settings = ['api_auth'] # noqa: E501
return self.api_client.call_api(
'/subscription', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='SubscriptionSearchResponse', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def test(self, subscription_id, **kwargs): # noqa: E501
"""test # noqa: E501
This method triggers a mocked test payload that includes a notification ID, publish date, and so on. Use this method to test your subscription end-to-end.<br /><br />You can create the subscription in disabled mode, test it using this method, and when everything is ready, you can enable the subscription (see the <strong>enableSubscription</strong> method).<br /><br /><span class=\"tablenote\"><b>Note:</b> Use the <strong>notificationId</strong> to tell the difference between a test payload and a real payload.</span> # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.test(subscription_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str subscription_id: The unique identifier for the subscription. (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.test_with_http_info(subscription_id, **kwargs) # noqa: E501
else:
(data) = self.test_with_http_info(subscription_id, **kwargs) # noqa: E501
return data
def test_with_http_info(self, subscription_id, **kwargs): # noqa: E501
"""test # noqa: E501
This method triggers a mocked test payload that includes a notification ID, publish date, and so on. Use this method to test your subscription end-to-end.<br /><br />You can create the subscription in disabled mode, test it using this method, and when everything is ready, you can enable the subscription (see the <strong>enableSubscription</strong> method).<br /><br /><span class=\"tablenote\"><b>Note:</b> Use the <strong>notificationId</strong> to tell the difference between a test payload and a real payload.</span> # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.test_with_http_info(subscription_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str subscription_id: The unique identifier for the subscription. (required)
:return: None
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['subscription_id'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method test" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'subscription_id' is set
if ('subscription_id' not in params or
params['subscription_id'] is None):
raise ValueError("Missing the required parameter `subscription_id` when calling `test`") # noqa: E501
collection_formats = {}
path_params = {}
if 'subscription_id' in params:
path_params['subscription_id'] = params['subscription_id'] # noqa: E501
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# Authentication setting
auth_settings = ['api_auth'] # noqa: E501
return self.api_client.call_api(
'/subscription/{subscription_id}/test', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type=None, # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def update_subscription(self, subscription_id, **kwargs): # noqa: E501
"""update_subscription # noqa: E501
This method allows applications to update a subscription. Subscriptions allow applications to express interest in notifications and keep receiving the information relevant to their business.<br /><br /><span class=\"tablenote\"><b>Note:</b> This call returns an error if an application is not authorized to subscribe to a topic.</span><br/><br/>You can pause and restart a subscription. See the <b>disableSubscription</b> and <b>enableSubscription</b> methods. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.update_subscription(subscription_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str subscription_id: The unique identifier for the subscription. (required)
:param UpdateSubscriptionRequest body: The create subscription request.
:return: None
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.update_subscription_with_http_info(subscription_id, **kwargs) # noqa: E501
else:
(data) = self.update_subscription_with_http_info(subscription_id, **kwargs) # noqa: E501
return data
def update_subscription_with_http_info(self, subscription_id, **kwargs): # noqa: E501
"""update_subscription # noqa: E501
This method allows applications to update a subscription. Subscriptions allow applications to express interest in notifications and keep receiving the information relevant to their business.<br /><br /><span class=\"tablenote\"><b>Note:</b> This call returns an error if an application is not authorized to subscribe to a topic.</span><br/><br/>You can pause and restart a subscription. See the <b>disableSubscription</b> and <b>enableSubscription</b> methods. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.update_subscription_with_http_info(subscription_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str subscription_id: The unique identifier for the subscription. (required)
:param UpdateSubscriptionRequest body: The create subscription request.
:return: None
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['subscription_id', 'body'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method update_subscription" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'subscription_id' is set
if ('subscription_id' not in params or
params['subscription_id'] is None):
raise ValueError("Missing the required parameter `subscription_id` when calling `update_subscription`") # noqa: E501
collection_formats = {}
path_params = {}
if 'subscription_id' in params:
path_params['subscription_id'] = params['subscription_id'] # noqa: E501
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'body' in params:
body_params = params['body']
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501
['application/json']) # noqa: E501
# Authentication setting
auth_settings = ['api_auth'] # noqa: E501
return self.api_client.call_api(
'/subscription/{subscription_id}', 'PUT',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type=None, # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
| 46.90665 | 806 | 0.646356 | 4,307 | 36,681 | 5.30137 | 0.064314 | 0.038541 | 0.019621 | 0.025227 | 0.95235 | 0.947707 | 0.947707 | 0.940437 | 0.939912 | 0.929795 | 0 | 0.013979 | 0.268668 | 36,681 | 781 | 807 | 46.966709 | 0.837173 | 0.446198 | 0 | 0.805755 | 0 | 0 | 0.188755 | 0.045376 | 0 | 0 | 0 | 0 | 0 | 1 | 0.040767 | false | 0 | 0.009592 | 0 | 0.110312 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
dc22263b520403eec348d8dfed0eb9bde4f70e28 | 67,078 | py | Python | python/paddle/fluid/tests/unittests/auto_parallel/test_cluster.py | RangeKing/Paddle | 2d87300809ae75d76f5b0b457d8112cb88dc3e27 | [
"Apache-2.0"
] | 8 | 2016-08-15T07:02:27.000Z | 2016-08-24T09:34:00.000Z | python/paddle/fluid/tests/unittests/auto_parallel/test_cluster.py | RangeKing/Paddle | 2d87300809ae75d76f5b0b457d8112cb88dc3e27 | [
"Apache-2.0"
] | 1 | 2022-01-28T07:23:22.000Z | 2022-01-28T07:23:22.000Z | python/paddle/fluid/tests/unittests/auto_parallel/test_cluster.py | RangeKing/Paddle | 2d87300809ae75d76f5b0b457d8112cb88dc3e27 | [
"Apache-2.0"
] | null | null | null | # Copyright (c) 2022 PaddlePaddle Authors. 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.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License 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 unittest
import os
import json
import paddle
from paddle.distributed.auto_parallel.cluster import Cluster
cluster_json = """
{
"alpha_latency": {"inter": {"ring": "NET", "tree": "NET"},
"intra": {"ring": "NVL", "tree": "PHB"},
"base": {"ring": 8.4, "tree": 0},
"switch": 10.0},
"machines": [
{
"hostname": "yq01-sys-hic-v100-box-a225-0266",
"addr": "10.127.9.147",
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"""
multi_cluster_json = """{
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{
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"""
class TestCluster(unittest.TestCase):
def test_single_machine(self):
# Build cluster
file_dir = os.path.dirname(os.path.abspath(__file__))
cluster_json_path = os.path.join(file_dir, "auto_parallel_cluster.json")
cluster_json_object = json.loads(cluster_json)
with open(cluster_json_path, "w") as cluster_json_file:
json.dump(cluster_json_object, cluster_json_file)
cluster = Cluster()
cluster.build_from_file(cluster_json_path)
beta = cluster.get_beta(0, 1)
hop = cluster.get_hop(0, 1)
cross_machine = cluster.cross_machine([0, 1])
devices = cluster.convert_rank_to_device_id([0, 1, 2, 3])
involved_machine_count = cluster.get_involved_machine_count(devices)
self.assertTrue(beta > 0)
self.assertTrue(hop == 0)
self.assertTrue(not cross_machine)
self.assertTrue(devices == [0, 1, 2, 3])
self.assertTrue(involved_machine_count == 1)
# Remove unnecessary files
if os.path.exists(cluster_json_path):
os.remove(cluster_json_path)
def test_multi_machine(self):
# Build cluster
file_dir = os.path.dirname(os.path.abspath(__file__))
cluster_json_path = os.path.join(file_dir, "auto_parallel_cluster.json")
cluster_json_object = json.loads(multi_cluster_json)
with open(cluster_json_path, "w") as cluster_json_file:
json.dump(cluster_json_object, cluster_json_file)
cluster = Cluster()
cluster.build_from_file(cluster_json_path)
beta = cluster.get_beta(0, 11)
hop = cluster.get_hop(0, 11)
cross_machine = cluster.cross_machine([0, 11])
devices = cluster.convert_rank_to_device_id([5, 6, 7, 8])
involved_machine_count = cluster.get_involved_machine_count(devices)
self.assertTrue(beta > 0)
self.assertTrue(hop >= 0)
self.assertTrue(cross_machine)
self.assertTrue(devices == [5, 6, 7, 10])
self.assertTrue(involved_machine_count == 2)
# Remove unnecessary files
if os.path.exists(cluster_json_path):
os.remove(cluster_json_path)
if __name__ == "__main__":
unittest.main()
| 33.157687 | 80 | 0.292674 | 4,664 | 67,078 | 3.927744 | 0.043739 | 0.250669 | 0.207872 | 0.220263 | 0.952072 | 0.939353 | 0.935859 | 0.931164 | 0.929472 | 0.929472 | 0 | 0.089037 | 0.596142 | 67,078 | 2,022 | 81 | 33.174085 | 0.587191 | 0.009854 | 0 | 0.665161 | 0 | 0 | 0.965798 | 0.00238 | 0 | 0 | 0 | 0 | 0.00502 | 1 | 0.001004 | false | 0 | 0.00251 | 0 | 0.004016 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 11 |
dc2b972249ec2aa30aeca24de7c1c755a711e488 | 26,626 | py | Python | tb_rest_client/api/api_pe/asset_controller_api.py | maksonlee/python_tb_rest_client | a6cd17ef4de31f68c3226b7a9835292fbac4b1fa | [
"Apache-2.0"
] | 1 | 2021-07-19T10:09:04.000Z | 2021-07-19T10:09:04.000Z | tb_rest_client/api/api_pe/asset_controller_api.py | moravcik94/python_tb_rest_client | 985361890cdf4ccce93d2b24905ad9003c8dfcaa | [
"Apache-2.0"
] | null | null | null | tb_rest_client/api/api_pe/asset_controller_api.py | moravcik94/python_tb_rest_client | 985361890cdf4ccce93d2b24905ad9003c8dfcaa | [
"Apache-2.0"
] | null | null | null | # coding: utf-8
# Copyright 2020. ThingsBoard
# #
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# #
# http://www.apache.org/licenses/LICENSE-2.0
# #
# Unless required by applicable law or agreed to in writing, software
# distributed under the License 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.
#
from __future__ import absolute_import
import re # noqa: F401
# python 2 and python 3 compatibility library
import six
from tb_rest_client.api_client import ApiClient
from tb_rest_client.api.api_ce import AssetControllerApi
class AssetControllerApi(AssetControllerApi):
"""NOTE: This class is auto generated by the swagger code generator program.
Ref: https://github.com/swagger-api/swagger-codegen
"""
def __init__(self, api_client=None):
super().__init__(api_client)
def get_assets_by_entity_group_id_using_get(self, entity_group_id, page_size, page, **kwargs): # noqa: E501
"""getAssetsByEntityGroupId # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api_pe.get_assets_by_entity_group_id_using_get(entity_group_id, page_size, page, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_group_id: entityGroupId (required)
:param str page_size: Page size (required)
:param str page: Page (required)
:param str text_search: textSearch
:param str sort_property: sortProperty
:param str sort_order: sortOrder
:return: PageDataAsset
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.get_assets_by_entity_group_id_using_get_with_http_info(entity_group_id, page_size, page, **kwargs) # noqa: E501
else:
(data) = self.get_assets_by_entity_group_id_using_get_with_http_info(entity_group_id, page_size, page, **kwargs) # noqa: E501
return data
def get_assets_by_entity_group_id_using_get_with_http_info(self, entity_group_id, page_size, page, **kwargs): # noqa: E501
"""getAssetsByEntityGroupId # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api_pe.get_assets_by_entity_group_id_using_get_with_http_info(entity_group_id, page_size, page, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str entity_group_id: entityGroupId (required)
:param str page_size: Page size (required)
:param str page: Page (required)
:param str text_search: textSearch
:param str sort_property: sortProperty
:param str sort_order: sortOrder
:return: PageDataAsset
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['entity_group_id', 'page_size', 'page', 'text_search', 'sort_property', 'sort_order'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
params[key] = val
del params['kwargs']
# verify the required parameter 'entity_group_id' is set
if ('entity_group_id' not in params or
params['entity_group_id'] is None):
raise ValueError("Missing the required parameter `entity_group_id` when calling `get_assets_by_entity_group_id_using_get`") # noqa: E501
# verify the required parameter 'page_size' is set
if ('page_size' not in params or
params['page_size'] is None):
raise ValueError("Missing the required parameter `page_size` when calling `get_assets_by_entity_group_id_using_get`") # noqa: E501
# verify the required parameter 'page' is set
if ('page' not in params or
params['page'] is None):
raise ValueError("Missing the required parameter `page` when calling `get_assets_by_entity_group_id_using_get`") # noqa: E501
if 'page_size' in params and params['page_size'] < 1.0: # noqa: E501
raise ValueError("Invalid value for parameter `page_size` when calling `get_assets_by_entity_group_id_using_get`, must be a value greater than or equal to `1.0`") # noqa: E501
if 'page' in params and params['page'] < 0.0: # noqa: E501
raise ValueError("Invalid value for parameter `page` when calling `get_assets_by_entity_group_id_using_get`, must be a value greater than or equal to `0.0`") # noqa: E501
collection_formats = {}
path_params = {}
if 'entity_group_id' in params:
path_params['entityGroupId'] = params['entity_group_id'] # noqa: E501
query_params = []
if 'text_search' in params:
query_params.append(('textSearch', params['text_search'])) # noqa: E501
if 'sort_property' in params:
query_params.append(('sortProperty', params['sort_property'])) # noqa: E501
if 'sort_order' in params:
query_params.append(('sortOrder', params['sort_order'])) # noqa: E501
if 'page_size' in params:
query_params.append(('pageSize', params['page_size'])) # noqa: E501
if 'page' in params:
query_params.append(('page', params['page'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['*/*']) # noqa: E501
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501
['application/json']) # noqa: E501
# Authentication setting
auth_settings = ['X-Authorization'] # noqa: E501
return self.api_client.call_api(
'/api/entityGroup/{entityGroupId}/assets{?textSearch,sortProperty,sortOrder,pageSize,page}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='PageDataAsset', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def get_customer_assets_using_get(self, customer_id, page_size, page, **kwargs): # noqa: E501
"""getCustomerAssets # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api_pe.get_customer_assets_using_get(customer_id, page_size, page, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str customer_id: customerId (required)
:param str page_size: pageSize (required)
:param str page: page (required)
:param str type: type
:param str text_search: textSearch
:param str sort_property: sortProperty
:param str sort_order: sortOrder
:return: PageDataAsset
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.get_customer_assets_using_get_with_http_info(customer_id, page_size, page, **kwargs) # noqa: E501
else:
(data) = self.get_customer_assets_using_get_with_http_info(customer_id, page_size, page, **kwargs) # noqa: E501
return data
def get_customer_assets_using_get_with_http_info(self, customer_id, page_size, page, **kwargs): # noqa: E501
"""getCustomerAssets # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api_pe.get_customer_assets_using_get_with_http_info(customer_id, page_size, page, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str customer_id: customerId (required)
:param str page_size: pageSize (required)
:param str page: page (required)
:param str type: type
:param str text_search: textSearch
:param str sort_property: sortProperty
:param str sort_order: sortOrder
:return: PageDataAsset
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['customer_id', 'page_size', 'page', 'type', 'text_search', 'sort_property', 'sort_order'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
params[key] = val
del params['kwargs']
# verify the required parameter 'customer_id' is set
if ('customer_id' not in params or
params['customer_id'] is None):
raise ValueError("Missing the required parameter `customer_id` when calling `get_customer_assets_using_get`") # noqa: E501
# verify the required parameter 'page_size' is set
if ('page_size' not in params or
params['page_size'] is None):
raise ValueError("Missing the required parameter `page_size` when calling `get_customer_assets_using_get`") # noqa: E501
# verify the required parameter 'page' is set
if ('page' not in params or
params['page'] is None):
raise ValueError("Missing the required parameter `page` when calling `get_customer_assets_using_get`") # noqa: E501
collection_formats = {}
path_params = {}
if 'customer_id' in params:
path_params['customerId'] = params['customer_id'] # noqa: E501
query_params = []
if 'type' in params:
query_params.append(('type', params['type'])) # noqa: E501
if 'text_search' in params:
query_params.append(('textSearch', params['text_search'])) # noqa: E501
if 'sort_property' in params:
query_params.append(('sortProperty', params['sort_property'])) # noqa: E501
if 'sort_order' in params:
query_params.append(('sortOrder', params['sort_order'])) # noqa: E501
if 'page_size' in params:
query_params.append(('pageSize', params['page_size'])) # noqa: E501
if 'page' in params:
query_params.append(('page', params['page'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['*/*']) # noqa: E501
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501
['application/json']) # noqa: E501
# Authentication setting
auth_settings = ['X-Authorization'] # noqa: E501
return self.api_client.call_api(
'/api/customer/{customerId}/assets{?type,textSearch,sortProperty,sortOrder,pageSize,page}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='PageDataAsset', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def get_tenant_assets_using_get(self, page_size, page, **kwargs): # noqa: E501
"""getTenantAssets # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api_pe.get_tenant_assets_using_get(page_size, page, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str page_size: pageSize (required)
:param str page: page (required)
:param str type: type
:param str text_search: textSearch
:param str sort_property: sortProperty
:param str sort_order: sortOrder
:return: PageDataAsset
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.get_tenant_assets_using_get_with_http_info(page_size, page, **kwargs) # noqa: E501
else:
(data) = self.get_tenant_assets_using_get_with_http_info(page_size, page, **kwargs) # noqa: E501
return data
def get_tenant_assets_using_get_with_http_info(self, page_size, page, **kwargs): # noqa: E501
"""getTenantAssets # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api_pe.get_tenant_assets_using_get_with_http_info(page_size, page, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str page_size: pageSize (required)
:param str page: page (required)
:param str type: type
:param str text_search: textSearch
:param str sort_property: sortProperty
:param str sort_order: sortOrder
:return: PageDataAsset
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['page_size', 'page', 'type', 'text_search', 'sort_property', 'sort_order'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
params[key] = val
del params['kwargs']
# verify the required parameter 'page_size' is set
if ('page_size' not in params or
params['page_size'] is None):
raise ValueError("Missing the required parameter `page_size` when calling `get_tenant_assets_using_get`") # noqa: E501
# verify the required parameter 'page' is set
if ('page' not in params or
params['page'] is None):
raise ValueError("Missing the required parameter `page` when calling `get_tenant_assets_using_get`") # noqa: E501
collection_formats = {}
path_params = {}
query_params = []
if 'type' in params:
query_params.append(('type', params['type'])) # noqa: E501
if 'text_search' in params:
query_params.append(('textSearch', params['text_search'])) # noqa: E501
if 'sort_property' in params:
query_params.append(('sortProperty', params['sort_property'])) # noqa: E501
if 'sort_order' in params:
query_params.append(('sortOrder', params['sort_order'])) # noqa: E501
if 'page_size' in params:
query_params.append(('pageSize', params['page_size'])) # noqa: E501
if 'page' in params:
query_params.append(('page', params['page'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['*/*']) # noqa: E501
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501
['application/json']) # noqa: E501
# Authentication setting
auth_settings = ['X-Authorization'] # noqa: E501
return self.api_client.call_api(
'/api/tenant/assets{?type,textSearch,sortProperty,sortOrder,pageSize,page}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='PageDataAsset', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def get_user_assets_using_get(self, page_size, page, **kwargs): # noqa: E501
"""getUserAssets # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api_pe.get_user_assets_using_get(page_size, page, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str page_size: pageSize (required)
:param str page: page (required)
:param str type: type
:param str text_search: textSearch
:param str sort_property: sortProperty
:param str sort_order: sortOrder
:return: PageDataAsset
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.get_user_assets_using_get_with_http_info(page_size, page, **kwargs) # noqa: E501
else:
(data) = self.get_user_assets_using_get_with_http_info(page_size, page, **kwargs) # noqa: E501
return data
def get_user_assets_using_get_with_http_info(self, page_size, page, **kwargs): # noqa: E501
"""getUserAssets # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api_pe.get_user_assets_using_get_with_http_info(page_size, page, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str page_size: pageSize (required)
:param str page: page (required)
:param str type: type
:param str text_search: textSearch
:param str sort_property: sortProperty
:param str sort_order: sortOrder
:return: PageDataAsset
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['page_size', 'page', 'type', 'text_search', 'sort_property', 'sort_order'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
params[key] = val
del params['kwargs']
# verify the required parameter 'page_size' is set
if ('page_size' not in params or
params['page_size'] is None):
raise ValueError("Missing the required parameter `page_size` when calling `get_user_assets_using_get`") # noqa: E501
# verify the required parameter 'page' is set
if ('page' not in params or
params['page'] is None):
raise ValueError("Missing the required parameter `page` when calling `get_user_assets_using_get`") # noqa: E501
collection_formats = {}
path_params = {}
query_params = []
if 'type' in params:
query_params.append(('type', params['type'])) # noqa: E501
if 'text_search' in params:
query_params.append(('textSearch', params['text_search'])) # noqa: E501
if 'sort_property' in params:
query_params.append(('sortProperty', params['sort_property'])) # noqa: E501
if 'sort_order' in params:
query_params.append(('sortOrder', params['sort_order'])) # noqa: E501
if 'page_size' in params:
query_params.append(('pageSize', params['page_size'])) # noqa: E501
if 'page' in params:
query_params.append(('page', params['page'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['*/*']) # noqa: E501
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501
['application/json']) # noqa: E501
# Authentication setting
auth_settings = ['X-Authorization'] # noqa: E501
return self.api_client.call_api(
'/api/user/assets{?type,textSearch,sortProperty,sortOrder,pageSize,page}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='PageDataAsset', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def save_asset_using_post(self, asset, **kwargs): # noqa: E501
"""saveAsset # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api_pe.save_asset_using_post(asset, async_req=True)
>>> result = thread.get()
:param async_req bool
:param Asset asset: asset (required)
:param str entity_group_id: entityGroupId
:return: Asset
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.save_asset_using_post_with_http_info(asset, **kwargs) # noqa: E501
else:
(data) = self.save_asset_using_post_with_http_info(asset, **kwargs) # noqa: E501
return data
def save_asset_using_post_with_http_info(self, asset, **kwargs): # noqa: E501
"""saveAsset # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api_pe.save_asset_using_post_with_http_info(asset, async_req=True)
>>> result = thread.get()
:param async_req bool
:param Asset asset: asset (required)
:param str entity_group_id: entityGroupId
:return: Asset
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['asset', 'entity_group_id'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
params[key] = val
del params['kwargs']
# verify the required parameter 'asset' is set
if ('asset' not in params or
params['asset'] is None):
raise ValueError("Missing the required parameter `asset` when calling `save_asset_using_post`") # noqa: E501
collection_formats = {}
path_params = {}
query_params = []
if 'entity_group_id' in params:
query_params.append(('entityGroupId', params['entity_group_id'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
if 'asset' in params:
body_params = params['asset']
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['*/*']) # noqa: E501
# HTTP header `Content-Type`
header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501
['application/json']) # noqa: E501
# Authentication setting
auth_settings = ['X-Authorization'] # noqa: E501
return self.api_client.call_api(
'/api/asset{?entityGroupId}', 'POST',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='Asset', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
| 43.224026 | 188 | 0.630436 | 3,189 | 26,626 | 4.989652 | 0.066792 | 0.050779 | 0.034188 | 0.028658 | 0.933886 | 0.921883 | 0.910005 | 0.897373 | 0.890837 | 0.874497 | 0 | 0.016795 | 0.273229 | 26,626 | 615 | 189 | 43.294309 | 0.805488 | 0.325509 | 0 | 0.799373 | 0 | 0.009404 | 0.235298 | 0.067004 | 0 | 0 | 0 | 0 | 0 | 1 | 0.034483 | false | 0 | 0.015674 | 0 | 0.100313 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
dc733ac0f7945f7164f6e9169f16c18ea6f4a084 | 433,911 | py | Python | tests/test_nist_meta_10609.py | tefra/xsdata-w3c-tests | b6b6a4ac4e0ab610e4b50d868510a8b7105b1a5f | [
"MIT"
] | 1 | 2021-08-14T17:59:21.000Z | 2021-08-14T17:59:21.000Z | tests/test_nist_meta_10609.py | tefra/xsdata-w3c-tests | b6b6a4ac4e0ab610e4b50d868510a8b7105b1a5f | [
"MIT"
] | 4 | 2020-02-12T21:30:44.000Z | 2020-04-15T20:06:46.000Z | tests/test_nist_meta_10609.py | tefra/xsdata-w3c-tests | b6b6a4ac4e0ab610e4b50d868510a8b7105b1a5f | [
"MIT"
] | null | null | null | from tests.utils import assert_bindings
def test_atomic_negative_integer_max_inclusive_4_nistxml_sv_iv_atomic_negative_integer_max_inclusive_5_3(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxInclusive with
value -1.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxInclusive-5.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxInclusive-5-3.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxInclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_inclusive_4_nistxml_sv_iv_atomic_negative_integer_max_inclusive_5_4(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxInclusive with
value -1.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxInclusive-5.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxInclusive-5-4.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxInclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_inclusive_4_nistxml_sv_iv_atomic_negative_integer_max_inclusive_5_5(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxInclusive with
value -1.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxInclusive-5.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxInclusive-5-5.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxInclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_inclusive_3_nistxml_sv_iv_atomic_negative_integer_max_inclusive_4_1(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxInclusive with
value -666057423564200834.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxInclusive-4.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxInclusive-4-1.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_inclusive_3_nistxml_sv_iv_atomic_negative_integer_max_inclusive_4_2(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxInclusive with
value -666057423564200834.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxInclusive-4.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxInclusive-4-2.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_inclusive_3_nistxml_sv_iv_atomic_negative_integer_max_inclusive_4_3(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxInclusive with
value -666057423564200834.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxInclusive-4.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxInclusive-4-3.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_inclusive_3_nistxml_sv_iv_atomic_negative_integer_max_inclusive_4_4(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxInclusive with
value -666057423564200834.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxInclusive-4.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxInclusive-4-4.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_inclusive_3_nistxml_sv_iv_atomic_negative_integer_max_inclusive_4_5(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxInclusive with
value -666057423564200834.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxInclusive-4.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxInclusive-4-5.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_inclusive_2_nistxml_sv_iv_atomic_negative_integer_max_inclusive_3_1(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxInclusive with
value -34749374507754505.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxInclusive-3.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxInclusive-3-1.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_inclusive_2_nistxml_sv_iv_atomic_negative_integer_max_inclusive_3_2(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxInclusive with
value -34749374507754505.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxInclusive-3.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxInclusive-3-2.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_inclusive_2_nistxml_sv_iv_atomic_negative_integer_max_inclusive_3_3(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxInclusive with
value -34749374507754505.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxInclusive-3.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxInclusive-3-3.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_inclusive_2_nistxml_sv_iv_atomic_negative_integer_max_inclusive_3_4(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxInclusive with
value -34749374507754505.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxInclusive-3.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxInclusive-3-4.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_inclusive_2_nistxml_sv_iv_atomic_negative_integer_max_inclusive_3_5(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxInclusive with
value -34749374507754505.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxInclusive-3.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxInclusive-3-5.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_inclusive_1_nistxml_sv_iv_atomic_negative_integer_max_inclusive_2_1(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxInclusive with
value -922333322214573646.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxInclusive-2.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxInclusive-2-1.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_inclusive_1_nistxml_sv_iv_atomic_negative_integer_max_inclusive_2_2(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxInclusive with
value -922333322214573646.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxInclusive-2.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxInclusive-2-2.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_inclusive_1_nistxml_sv_iv_atomic_negative_integer_max_inclusive_2_3(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxInclusive with
value -922333322214573646.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxInclusive-2.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxInclusive-2-3.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_inclusive_1_nistxml_sv_iv_atomic_negative_integer_max_inclusive_2_4(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxInclusive with
value -922333322214573646.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxInclusive-2.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxInclusive-2-4.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_inclusive_1_nistxml_sv_iv_atomic_negative_integer_max_inclusive_2_5(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxInclusive with
value -922333322214573646.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxInclusive-2.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxInclusive-2-5.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_inclusive_nistxml_sv_iv_atomic_negative_integer_max_inclusive_1_1(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxInclusive with
value -999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxInclusive-1.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxInclusive-1-1.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_exclusive_4_nistxml_sv_iv_atomic_negative_integer_max_exclusive_5_1(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxExclusive with
value -1.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxExclusive-5.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxExclusive-5-1.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_exclusive_4_nistxml_sv_iv_atomic_negative_integer_max_exclusive_5_2(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxExclusive with
value -1.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxExclusive-5.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxExclusive-5-2.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_exclusive_4_nistxml_sv_iv_atomic_negative_integer_max_exclusive_5_3(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxExclusive with
value -1.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxExclusive-5.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxExclusive-5-3.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_exclusive_4_nistxml_sv_iv_atomic_negative_integer_max_exclusive_5_4(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxExclusive with
value -1.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxExclusive-5.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxExclusive-5-4.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_exclusive_4_nistxml_sv_iv_atomic_negative_integer_max_exclusive_5_5(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxExclusive with
value -1.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxExclusive-5.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxExclusive-5-5.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_exclusive_3_nistxml_sv_iv_atomic_negative_integer_max_exclusive_4_1(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxExclusive with
value -572450131914860271.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxExclusive-4.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxExclusive-4-1.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_exclusive_3_nistxml_sv_iv_atomic_negative_integer_max_exclusive_4_2(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxExclusive with
value -572450131914860271.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxExclusive-4.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxExclusive-4-2.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_exclusive_3_nistxml_sv_iv_atomic_negative_integer_max_exclusive_4_3(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxExclusive with
value -572450131914860271.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxExclusive-4.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxExclusive-4-3.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_exclusive_3_nistxml_sv_iv_atomic_negative_integer_max_exclusive_4_4(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxExclusive with
value -572450131914860271.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxExclusive-4.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxExclusive-4-4.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_exclusive_3_nistxml_sv_iv_atomic_negative_integer_max_exclusive_4_5(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxExclusive with
value -572450131914860271.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxExclusive-4.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxExclusive-4-5.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_exclusive_2_nistxml_sv_iv_atomic_negative_integer_max_exclusive_3_1(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxExclusive with
value -184935339155753553.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxExclusive-3.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxExclusive-3-1.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_exclusive_2_nistxml_sv_iv_atomic_negative_integer_max_exclusive_3_2(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxExclusive with
value -184935339155753553.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxExclusive-3.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxExclusive-3-2.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_exclusive_2_nistxml_sv_iv_atomic_negative_integer_max_exclusive_3_3(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxExclusive with
value -184935339155753553.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxExclusive-3.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxExclusive-3-3.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_exclusive_2_nistxml_sv_iv_atomic_negative_integer_max_exclusive_3_4(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxExclusive with
value -184935339155753553.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxExclusive-3.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxExclusive-3-4.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_exclusive_2_nistxml_sv_iv_atomic_negative_integer_max_exclusive_3_5(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxExclusive with
value -184935339155753553.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxExclusive-3.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxExclusive-3-5.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_exclusive_1_nistxml_sv_iv_atomic_negative_integer_max_exclusive_2_1(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxExclusive with
value -866521354558973720.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxExclusive-2.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxExclusive-2-1.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_exclusive_1_nistxml_sv_iv_atomic_negative_integer_max_exclusive_2_2(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxExclusive with
value -866521354558973720.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxExclusive-2.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxExclusive-2-2.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_exclusive_1_nistxml_sv_iv_atomic_negative_integer_max_exclusive_2_3(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxExclusive with
value -866521354558973720.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxExclusive-2.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxExclusive-2-3.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_exclusive_1_nistxml_sv_iv_atomic_negative_integer_max_exclusive_2_4(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxExclusive with
value -866521354558973720.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxExclusive-2.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxExclusive-2-4.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_exclusive_1_nistxml_sv_iv_atomic_negative_integer_max_exclusive_2_5(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxExclusive with
value -866521354558973720.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxExclusive-2.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxExclusive-2-5.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_max_exclusive_nistxml_sv_iv_atomic_negative_integer_max_exclusive_1_1(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet maxExclusive with
value -999999999999999998.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-maxExclusive-1.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-maxExclusive-1-1.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMaxExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_inclusive_4_nistxml_sv_iv_atomic_negative_integer_min_inclusive_5_1(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minInclusive with
value -1.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minInclusive-5.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minInclusive-5-1.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinInclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_inclusive_3_nistxml_sv_iv_atomic_negative_integer_min_inclusive_4_1(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minInclusive with
value -947674826094804355.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minInclusive-4.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minInclusive-4-1.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_inclusive_3_nistxml_sv_iv_atomic_negative_integer_min_inclusive_4_2(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minInclusive with
value -947674826094804355.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minInclusive-4.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minInclusive-4-2.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_inclusive_3_nistxml_sv_iv_atomic_negative_integer_min_inclusive_4_3(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minInclusive with
value -947674826094804355.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minInclusive-4.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minInclusive-4-3.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_inclusive_3_nistxml_sv_iv_atomic_negative_integer_min_inclusive_4_4(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minInclusive with
value -947674826094804355.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minInclusive-4.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minInclusive-4-4.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_inclusive_3_nistxml_sv_iv_atomic_negative_integer_min_inclusive_4_5(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minInclusive with
value -947674826094804355.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minInclusive-4.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minInclusive-4-5.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_inclusive_2_nistxml_sv_iv_atomic_negative_integer_min_inclusive_3_1(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minInclusive with
value -539945622984702833.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minInclusive-3.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minInclusive-3-1.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_inclusive_2_nistxml_sv_iv_atomic_negative_integer_min_inclusive_3_2(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minInclusive with
value -539945622984702833.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minInclusive-3.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minInclusive-3-2.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_inclusive_2_nistxml_sv_iv_atomic_negative_integer_min_inclusive_3_3(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minInclusive with
value -539945622984702833.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minInclusive-3.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minInclusive-3-3.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_inclusive_2_nistxml_sv_iv_atomic_negative_integer_min_inclusive_3_4(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minInclusive with
value -539945622984702833.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minInclusive-3.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minInclusive-3-4.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_inclusive_2_nistxml_sv_iv_atomic_negative_integer_min_inclusive_3_5(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minInclusive with
value -539945622984702833.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minInclusive-3.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minInclusive-3-5.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_inclusive_1_nistxml_sv_iv_atomic_negative_integer_min_inclusive_2_1(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minInclusive with
value -440277848538184635.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minInclusive-2.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minInclusive-2-1.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_inclusive_1_nistxml_sv_iv_atomic_negative_integer_min_inclusive_2_2(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minInclusive with
value -440277848538184635.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minInclusive-2.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minInclusive-2-2.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_inclusive_1_nistxml_sv_iv_atomic_negative_integer_min_inclusive_2_3(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minInclusive with
value -440277848538184635.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minInclusive-2.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minInclusive-2-3.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_inclusive_1_nistxml_sv_iv_atomic_negative_integer_min_inclusive_2_4(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minInclusive with
value -440277848538184635.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minInclusive-2.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minInclusive-2-4.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_inclusive_1_nistxml_sv_iv_atomic_negative_integer_min_inclusive_2_5(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minInclusive with
value -440277848538184635.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minInclusive-2.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minInclusive-2-5.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_inclusive_nistxml_sv_iv_atomic_negative_integer_min_inclusive_1_1(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minInclusive with
value -999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minInclusive-1.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minInclusive-1-1.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_inclusive_nistxml_sv_iv_atomic_negative_integer_min_inclusive_1_2(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minInclusive with
value -999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minInclusive-1.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minInclusive-1-2.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_inclusive_nistxml_sv_iv_atomic_negative_integer_min_inclusive_1_3(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minInclusive with
value -999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minInclusive-1.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minInclusive-1-3.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_inclusive_nistxml_sv_iv_atomic_negative_integer_min_inclusive_1_4(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minInclusive with
value -999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minInclusive-1.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minInclusive-1-4.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_inclusive_nistxml_sv_iv_atomic_negative_integer_min_inclusive_1_5(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minInclusive with
value -999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minInclusive-1.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minInclusive-1-5.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_exclusive_4_nistxml_sv_iv_atomic_negative_integer_min_exclusive_5_1(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minExclusive with
value -2.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minExclusive-5.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minExclusive-5-1.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_exclusive_3_nistxml_sv_iv_atomic_negative_integer_min_exclusive_4_1(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minExclusive with
value -495295756372066909.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minExclusive-4.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minExclusive-4-1.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_exclusive_3_nistxml_sv_iv_atomic_negative_integer_min_exclusive_4_2(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minExclusive with
value -495295756372066909.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minExclusive-4.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minExclusive-4-2.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_exclusive_3_nistxml_sv_iv_atomic_negative_integer_min_exclusive_4_3(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minExclusive with
value -495295756372066909.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minExclusive-4.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minExclusive-4-3.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_exclusive_3_nistxml_sv_iv_atomic_negative_integer_min_exclusive_4_4(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minExclusive with
value -495295756372066909.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minExclusive-4.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minExclusive-4-4.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_exclusive_3_nistxml_sv_iv_atomic_negative_integer_min_exclusive_4_5(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minExclusive with
value -495295756372066909.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minExclusive-4.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minExclusive-4-5.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_exclusive_2_nistxml_sv_iv_atomic_negative_integer_min_exclusive_3_1(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minExclusive with
value -900435039333670416.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minExclusive-3.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minExclusive-3-1.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_exclusive_2_nistxml_sv_iv_atomic_negative_integer_min_exclusive_3_2(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minExclusive with
value -900435039333670416.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minExclusive-3.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minExclusive-3-2.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_exclusive_2_nistxml_sv_iv_atomic_negative_integer_min_exclusive_3_3(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minExclusive with
value -900435039333670416.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minExclusive-3.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minExclusive-3-3.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_exclusive_2_nistxml_sv_iv_atomic_negative_integer_min_exclusive_3_4(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minExclusive with
value -900435039333670416.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minExclusive-3.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minExclusive-3-4.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_exclusive_2_nistxml_sv_iv_atomic_negative_integer_min_exclusive_3_5(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minExclusive with
value -900435039333670416.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minExclusive-3.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minExclusive-3-5.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_exclusive_1_nistxml_sv_iv_atomic_negative_integer_min_exclusive_2_1(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minExclusive with
value -435976618086570511.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minExclusive-2.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minExclusive-2-1.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_exclusive_1_nistxml_sv_iv_atomic_negative_integer_min_exclusive_2_2(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minExclusive with
value -435976618086570511.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minExclusive-2.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minExclusive-2-2.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_exclusive_1_nistxml_sv_iv_atomic_negative_integer_min_exclusive_2_3(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minExclusive with
value -435976618086570511.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minExclusive-2.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minExclusive-2-3.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_exclusive_1_nistxml_sv_iv_atomic_negative_integer_min_exclusive_2_4(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minExclusive with
value -435976618086570511.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minExclusive-2.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minExclusive-2-4.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_exclusive_1_nistxml_sv_iv_atomic_negative_integer_min_exclusive_2_5(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minExclusive with
value -435976618086570511.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minExclusive-2.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minExclusive-2-5.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_exclusive_nistxml_sv_iv_atomic_negative_integer_min_exclusive_1_1(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minExclusive with
value -999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minExclusive-1.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minExclusive-1-1.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_exclusive_nistxml_sv_iv_atomic_negative_integer_min_exclusive_1_2(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minExclusive with
value -999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minExclusive-1.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minExclusive-1-2.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_exclusive_nistxml_sv_iv_atomic_negative_integer_min_exclusive_1_3(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minExclusive with
value -999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minExclusive-1.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minExclusive-1-3.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_exclusive_nistxml_sv_iv_atomic_negative_integer_min_exclusive_1_4(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minExclusive with
value -999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minExclusive-1.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minExclusive-1-4.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_negative_integer_min_exclusive_nistxml_sv_iv_atomic_negative_integer_min_exclusive_1_5(mode, save_output, output_format):
"""
Type atomic/negativeInteger is restricted by facet minExclusive with
value -999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/negativeInteger/Schema+Instance/NISTSchema-SV-IV-atomic-negativeInteger-minExclusive-1.xsd",
instance="nistData/atomic/negativeInteger/Schema+Instance/NISTXML-SV-IV-atomic-negativeInteger-minExclusive-1-5.xml",
class_name="NistschemaSvIvAtomicNegativeIntegerMinExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_white_space_nistxml_sv_iv_atomic_non_positive_integer_white_space_1_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet whiteSpace with
value collapse.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-whiteSpace-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-whiteSpace-1-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerWhiteSpace1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_white_space_nistxml_sv_iv_atomic_non_positive_integer_white_space_1_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet whiteSpace with
value collapse.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-whiteSpace-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-whiteSpace-1-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerWhiteSpace1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_white_space_nistxml_sv_iv_atomic_non_positive_integer_white_space_1_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet whiteSpace with
value collapse.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-whiteSpace-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-whiteSpace-1-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerWhiteSpace1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_white_space_nistxml_sv_iv_atomic_non_positive_integer_white_space_1_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet whiteSpace with
value collapse.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-whiteSpace-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-whiteSpace-1-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerWhiteSpace1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_white_space_nistxml_sv_iv_atomic_non_positive_integer_white_space_1_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet whiteSpace with
value collapse.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-whiteSpace-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-whiteSpace-1-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerWhiteSpace1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_4_nistxml_sv_iv_atomic_non_positive_integer_enumeration_5_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-5-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_4_nistxml_sv_iv_atomic_non_positive_integer_enumeration_5_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-5-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_4_nistxml_sv_iv_atomic_non_positive_integer_enumeration_5_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-5-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_4_nistxml_sv_iv_atomic_non_positive_integer_enumeration_5_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-5-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_4_nistxml_sv_iv_atomic_non_positive_integer_enumeration_5_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-5-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_3_nistxml_sv_iv_atomic_non_positive_integer_enumeration_4_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-4-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_3_nistxml_sv_iv_atomic_non_positive_integer_enumeration_4_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-4-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_3_nistxml_sv_iv_atomic_non_positive_integer_enumeration_4_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-4-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_3_nistxml_sv_iv_atomic_non_positive_integer_enumeration_4_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-4-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_3_nistxml_sv_iv_atomic_non_positive_integer_enumeration_4_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-4-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_2_nistxml_sv_iv_atomic_non_positive_integer_enumeration_3_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-3-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_2_nistxml_sv_iv_atomic_non_positive_integer_enumeration_3_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-3-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_2_nistxml_sv_iv_atomic_non_positive_integer_enumeration_3_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-3-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_2_nistxml_sv_iv_atomic_non_positive_integer_enumeration_3_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-3-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_2_nistxml_sv_iv_atomic_non_positive_integer_enumeration_3_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-3-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_1_nistxml_sv_iv_atomic_non_positive_integer_enumeration_2_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-2-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_1_nistxml_sv_iv_atomic_non_positive_integer_enumeration_2_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-2-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_1_nistxml_sv_iv_atomic_non_positive_integer_enumeration_2_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-2-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_1_nistxml_sv_iv_atomic_non_positive_integer_enumeration_2_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-2-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_1_nistxml_sv_iv_atomic_non_positive_integer_enumeration_2_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-2-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_nistxml_sv_iv_atomic_non_positive_integer_enumeration_1_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-1-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_nistxml_sv_iv_atomic_non_positive_integer_enumeration_1_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-1-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_nistxml_sv_iv_atomic_non_positive_integer_enumeration_1_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-1-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_nistxml_sv_iv_atomic_non_positive_integer_enumeration_1_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-1-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_enumeration_nistxml_sv_iv_atomic_non_positive_integer_enumeration_1_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-enumeration-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-enumeration-1-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerEnumeration1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_4_nistxml_sv_iv_atomic_non_positive_integer_pattern_5_1(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{18}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-5-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_4_nistxml_sv_iv_atomic_non_positive_integer_pattern_5_2(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{18}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-5-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_4_nistxml_sv_iv_atomic_non_positive_integer_pattern_5_3(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{18}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-5-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_4_nistxml_sv_iv_atomic_non_positive_integer_pattern_5_4(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{18}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-5-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_4_nistxml_sv_iv_atomic_non_positive_integer_pattern_5_5(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{18}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-5-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_3_nistxml_sv_iv_atomic_non_positive_integer_pattern_4_1(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{13}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-4-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_3_nistxml_sv_iv_atomic_non_positive_integer_pattern_4_2(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{13}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-4-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_3_nistxml_sv_iv_atomic_non_positive_integer_pattern_4_3(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{13}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-4-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_3_nistxml_sv_iv_atomic_non_positive_integer_pattern_4_4(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{13}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-4-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_3_nistxml_sv_iv_atomic_non_positive_integer_pattern_4_5(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{13}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-4-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_2_nistxml_sv_iv_atomic_non_positive_integer_pattern_3_1(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{9}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-3-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_2_nistxml_sv_iv_atomic_non_positive_integer_pattern_3_2(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{9}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-3-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_2_nistxml_sv_iv_atomic_non_positive_integer_pattern_3_3(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{9}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-3-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_2_nistxml_sv_iv_atomic_non_positive_integer_pattern_3_4(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{9}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-3-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_2_nistxml_sv_iv_atomic_non_positive_integer_pattern_3_5(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{9}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-3-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_1_nistxml_sv_iv_atomic_non_positive_integer_pattern_2_1(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{5}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-2-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_1_nistxml_sv_iv_atomic_non_positive_integer_pattern_2_2(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{5}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-2-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_1_nistxml_sv_iv_atomic_non_positive_integer_pattern_2_3(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{5}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-2-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_1_nistxml_sv_iv_atomic_non_positive_integer_pattern_2_4(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{5}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-2-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_1_nistxml_sv_iv_atomic_non_positive_integer_pattern_2_5(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{5}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-2-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_nistxml_sv_iv_atomic_non_positive_integer_pattern_1_1(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{1}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-1-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_nistxml_sv_iv_atomic_non_positive_integer_pattern_1_2(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{1}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-1-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_nistxml_sv_iv_atomic_non_positive_integer_pattern_1_3(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{1}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-1-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_nistxml_sv_iv_atomic_non_positive_integer_pattern_1_4(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{1}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-1-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_pattern_nistxml_sv_iv_atomic_non_positive_integer_pattern_1_5(mode, save_output, output_format):
r"""
Type atomic/nonPositiveInteger is restricted by facet pattern with
value \-\d{1}.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-pattern-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-pattern-1-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerPattern1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_4_nistxml_sv_iv_atomic_non_positive_integer_total_digits_5_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 18.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-5-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_4_nistxml_sv_iv_atomic_non_positive_integer_total_digits_5_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 18.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-5-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_4_nistxml_sv_iv_atomic_non_positive_integer_total_digits_5_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 18.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-5-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_4_nistxml_sv_iv_atomic_non_positive_integer_total_digits_5_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 18.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-5-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_4_nistxml_sv_iv_atomic_non_positive_integer_total_digits_5_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 18.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-5-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_3_nistxml_sv_iv_atomic_non_positive_integer_total_digits_4_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 13.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-4-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_3_nistxml_sv_iv_atomic_non_positive_integer_total_digits_4_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 13.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-4-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_3_nistxml_sv_iv_atomic_non_positive_integer_total_digits_4_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 13.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-4-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_3_nistxml_sv_iv_atomic_non_positive_integer_total_digits_4_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 13.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-4-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_3_nistxml_sv_iv_atomic_non_positive_integer_total_digits_4_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 13.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-4-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_2_nistxml_sv_iv_atomic_non_positive_integer_total_digits_3_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 9.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-3-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_2_nistxml_sv_iv_atomic_non_positive_integer_total_digits_3_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 9.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-3-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_2_nistxml_sv_iv_atomic_non_positive_integer_total_digits_3_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 9.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-3-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_2_nistxml_sv_iv_atomic_non_positive_integer_total_digits_3_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 9.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-3-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_2_nistxml_sv_iv_atomic_non_positive_integer_total_digits_3_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 9.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-3-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_1_nistxml_sv_iv_atomic_non_positive_integer_total_digits_2_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 5.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-2-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_1_nistxml_sv_iv_atomic_non_positive_integer_total_digits_2_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 5.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-2-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_1_nistxml_sv_iv_atomic_non_positive_integer_total_digits_2_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 5.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-2-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_1_nistxml_sv_iv_atomic_non_positive_integer_total_digits_2_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 5.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-2-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_1_nistxml_sv_iv_atomic_non_positive_integer_total_digits_2_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 5.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-2-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_nistxml_sv_iv_atomic_non_positive_integer_total_digits_1_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 1.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-1-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_nistxml_sv_iv_atomic_non_positive_integer_total_digits_1_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 1.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-1-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_nistxml_sv_iv_atomic_non_positive_integer_total_digits_1_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 1.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-1-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_nistxml_sv_iv_atomic_non_positive_integer_total_digits_1_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 1.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-1-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_total_digits_nistxml_sv_iv_atomic_non_positive_integer_total_digits_1_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet totalDigits with
value 1.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-totalDigits-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-totalDigits-1-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerTotalDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_fraction_digits_nistxml_sv_iv_atomic_non_positive_integer_fraction_digits_1_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet fractionDigits
with value 0.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-fractionDigits-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-fractionDigits-1-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerFractionDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_fraction_digits_nistxml_sv_iv_atomic_non_positive_integer_fraction_digits_1_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet fractionDigits
with value 0.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-fractionDigits-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-fractionDigits-1-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerFractionDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_fraction_digits_nistxml_sv_iv_atomic_non_positive_integer_fraction_digits_1_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet fractionDigits
with value 0.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-fractionDigits-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-fractionDigits-1-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerFractionDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_fraction_digits_nistxml_sv_iv_atomic_non_positive_integer_fraction_digits_1_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet fractionDigits
with value 0.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-fractionDigits-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-fractionDigits-1-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerFractionDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_fraction_digits_nistxml_sv_iv_atomic_non_positive_integer_fraction_digits_1_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet fractionDigits
with value 0.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-fractionDigits-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-fractionDigits-1-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerFractionDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_inclusive_4_nistxml_sv_iv_atomic_non_positive_integer_max_inclusive_5_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxInclusive
with value 0.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxInclusive-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxInclusive-5-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxInclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_inclusive_4_nistxml_sv_iv_atomic_non_positive_integer_max_inclusive_5_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxInclusive
with value 0.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxInclusive-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxInclusive-5-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxInclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_inclusive_4_nistxml_sv_iv_atomic_non_positive_integer_max_inclusive_5_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxInclusive
with value 0.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxInclusive-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxInclusive-5-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxInclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_inclusive_4_nistxml_sv_iv_atomic_non_positive_integer_max_inclusive_5_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxInclusive
with value 0.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxInclusive-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxInclusive-5-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxInclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_inclusive_4_nistxml_sv_iv_atomic_non_positive_integer_max_inclusive_5_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxInclusive
with value 0.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxInclusive-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxInclusive-5-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxInclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_inclusive_3_nistxml_sv_iv_atomic_non_positive_integer_max_inclusive_4_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxInclusive
with value -686635117591375964.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxInclusive-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxInclusive-4-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_inclusive_3_nistxml_sv_iv_atomic_non_positive_integer_max_inclusive_4_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxInclusive
with value -686635117591375964.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxInclusive-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxInclusive-4-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_inclusive_3_nistxml_sv_iv_atomic_non_positive_integer_max_inclusive_4_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxInclusive
with value -686635117591375964.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxInclusive-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxInclusive-4-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_inclusive_3_nistxml_sv_iv_atomic_non_positive_integer_max_inclusive_4_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxInclusive
with value -686635117591375964.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxInclusive-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxInclusive-4-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_inclusive_3_nistxml_sv_iv_atomic_non_positive_integer_max_inclusive_4_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxInclusive
with value -686635117591375964.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxInclusive-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxInclusive-4-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_inclusive_2_nistxml_sv_iv_atomic_non_positive_integer_max_inclusive_3_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxInclusive
with value -78303033269241706.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxInclusive-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxInclusive-3-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_inclusive_2_nistxml_sv_iv_atomic_non_positive_integer_max_inclusive_3_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxInclusive
with value -78303033269241706.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxInclusive-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxInclusive-3-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_inclusive_2_nistxml_sv_iv_atomic_non_positive_integer_max_inclusive_3_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxInclusive
with value -78303033269241706.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxInclusive-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxInclusive-3-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_inclusive_2_nistxml_sv_iv_atomic_non_positive_integer_max_inclusive_3_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxInclusive
with value -78303033269241706.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxInclusive-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxInclusive-3-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_inclusive_2_nistxml_sv_iv_atomic_non_positive_integer_max_inclusive_3_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxInclusive
with value -78303033269241706.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxInclusive-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxInclusive-3-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_inclusive_1_nistxml_sv_iv_atomic_non_positive_integer_max_inclusive_2_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxInclusive
with value -63404852978511949.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxInclusive-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxInclusive-2-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_inclusive_1_nistxml_sv_iv_atomic_non_positive_integer_max_inclusive_2_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxInclusive
with value -63404852978511949.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxInclusive-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxInclusive-2-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_inclusive_1_nistxml_sv_iv_atomic_non_positive_integer_max_inclusive_2_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxInclusive
with value -63404852978511949.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxInclusive-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxInclusive-2-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_inclusive_1_nistxml_sv_iv_atomic_non_positive_integer_max_inclusive_2_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxInclusive
with value -63404852978511949.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxInclusive-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxInclusive-2-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_inclusive_1_nistxml_sv_iv_atomic_non_positive_integer_max_inclusive_2_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxInclusive
with value -63404852978511949.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxInclusive-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxInclusive-2-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_inclusive_nistxml_sv_iv_atomic_non_positive_integer_max_inclusive_1_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxInclusive
with value -999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxInclusive-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxInclusive-1-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_exclusive_4_nistxml_sv_iv_atomic_non_positive_integer_max_exclusive_5_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxExclusive
with value 0.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxExclusive-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxExclusive-5-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_exclusive_4_nistxml_sv_iv_atomic_non_positive_integer_max_exclusive_5_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxExclusive
with value 0.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxExclusive-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxExclusive-5-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_exclusive_4_nistxml_sv_iv_atomic_non_positive_integer_max_exclusive_5_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxExclusive
with value 0.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxExclusive-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxExclusive-5-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_exclusive_4_nistxml_sv_iv_atomic_non_positive_integer_max_exclusive_5_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxExclusive
with value 0.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxExclusive-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxExclusive-5-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_exclusive_4_nistxml_sv_iv_atomic_non_positive_integer_max_exclusive_5_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxExclusive
with value 0.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxExclusive-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxExclusive-5-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_exclusive_3_nistxml_sv_iv_atomic_non_positive_integer_max_exclusive_4_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxExclusive
with value -398718969796236887.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxExclusive-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxExclusive-4-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_exclusive_3_nistxml_sv_iv_atomic_non_positive_integer_max_exclusive_4_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxExclusive
with value -398718969796236887.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxExclusive-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxExclusive-4-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_exclusive_3_nistxml_sv_iv_atomic_non_positive_integer_max_exclusive_4_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxExclusive
with value -398718969796236887.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxExclusive-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxExclusive-4-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_exclusive_3_nistxml_sv_iv_atomic_non_positive_integer_max_exclusive_4_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxExclusive
with value -398718969796236887.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxExclusive-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxExclusive-4-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_exclusive_3_nistxml_sv_iv_atomic_non_positive_integer_max_exclusive_4_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxExclusive
with value -398718969796236887.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxExclusive-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxExclusive-4-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_exclusive_2_nistxml_sv_iv_atomic_non_positive_integer_max_exclusive_3_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxExclusive
with value -64116953963150757.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxExclusive-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxExclusive-3-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_exclusive_2_nistxml_sv_iv_atomic_non_positive_integer_max_exclusive_3_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxExclusive
with value -64116953963150757.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxExclusive-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxExclusive-3-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_exclusive_2_nistxml_sv_iv_atomic_non_positive_integer_max_exclusive_3_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxExclusive
with value -64116953963150757.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxExclusive-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxExclusive-3-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_exclusive_2_nistxml_sv_iv_atomic_non_positive_integer_max_exclusive_3_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxExclusive
with value -64116953963150757.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxExclusive-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxExclusive-3-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_exclusive_2_nistxml_sv_iv_atomic_non_positive_integer_max_exclusive_3_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxExclusive
with value -64116953963150757.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxExclusive-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxExclusive-3-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_exclusive_1_nistxml_sv_iv_atomic_non_positive_integer_max_exclusive_2_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxExclusive
with value -267691436022826633.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxExclusive-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxExclusive-2-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_exclusive_1_nistxml_sv_iv_atomic_non_positive_integer_max_exclusive_2_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxExclusive
with value -267691436022826633.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxExclusive-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxExclusive-2-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_exclusive_1_nistxml_sv_iv_atomic_non_positive_integer_max_exclusive_2_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxExclusive
with value -267691436022826633.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxExclusive-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxExclusive-2-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_exclusive_1_nistxml_sv_iv_atomic_non_positive_integer_max_exclusive_2_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxExclusive
with value -267691436022826633.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxExclusive-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxExclusive-2-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_exclusive_1_nistxml_sv_iv_atomic_non_positive_integer_max_exclusive_2_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxExclusive
with value -267691436022826633.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxExclusive-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxExclusive-2-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_max_exclusive_nistxml_sv_iv_atomic_non_positive_integer_max_exclusive_1_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet maxExclusive
with value -999999999999999998.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-maxExclusive-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-maxExclusive-1-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMaxExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_inclusive_4_nistxml_sv_iv_atomic_non_positive_integer_min_inclusive_5_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minInclusive
with value 0.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minInclusive-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minInclusive-5-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinInclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_inclusive_3_nistxml_sv_iv_atomic_non_positive_integer_min_inclusive_4_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minInclusive
with value -911248228325171715.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minInclusive-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minInclusive-4-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_inclusive_3_nistxml_sv_iv_atomic_non_positive_integer_min_inclusive_4_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minInclusive
with value -911248228325171715.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minInclusive-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minInclusive-4-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_inclusive_3_nistxml_sv_iv_atomic_non_positive_integer_min_inclusive_4_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minInclusive
with value -911248228325171715.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minInclusive-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minInclusive-4-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_inclusive_3_nistxml_sv_iv_atomic_non_positive_integer_min_inclusive_4_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minInclusive
with value -911248228325171715.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minInclusive-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minInclusive-4-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_inclusive_3_nistxml_sv_iv_atomic_non_positive_integer_min_inclusive_4_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minInclusive
with value -911248228325171715.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minInclusive-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minInclusive-4-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_inclusive_2_nistxml_sv_iv_atomic_non_positive_integer_min_inclusive_3_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minInclusive
with value -214379312213180406.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minInclusive-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minInclusive-3-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_inclusive_2_nistxml_sv_iv_atomic_non_positive_integer_min_inclusive_3_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minInclusive
with value -214379312213180406.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minInclusive-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minInclusive-3-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_inclusive_2_nistxml_sv_iv_atomic_non_positive_integer_min_inclusive_3_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minInclusive
with value -214379312213180406.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minInclusive-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minInclusive-3-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_inclusive_2_nistxml_sv_iv_atomic_non_positive_integer_min_inclusive_3_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minInclusive
with value -214379312213180406.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minInclusive-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minInclusive-3-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_inclusive_2_nistxml_sv_iv_atomic_non_positive_integer_min_inclusive_3_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minInclusive
with value -214379312213180406.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minInclusive-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minInclusive-3-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_inclusive_1_nistxml_sv_iv_atomic_non_positive_integer_min_inclusive_2_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minInclusive
with value -927820889571802863.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minInclusive-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minInclusive-2-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_inclusive_1_nistxml_sv_iv_atomic_non_positive_integer_min_inclusive_2_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minInclusive
with value -927820889571802863.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minInclusive-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minInclusive-2-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_inclusive_1_nistxml_sv_iv_atomic_non_positive_integer_min_inclusive_2_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minInclusive
with value -927820889571802863.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minInclusive-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minInclusive-2-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_inclusive_1_nistxml_sv_iv_atomic_non_positive_integer_min_inclusive_2_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minInclusive
with value -927820889571802863.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minInclusive-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minInclusive-2-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_inclusive_1_nistxml_sv_iv_atomic_non_positive_integer_min_inclusive_2_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minInclusive
with value -927820889571802863.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minInclusive-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minInclusive-2-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_inclusive_nistxml_sv_iv_atomic_non_positive_integer_min_inclusive_1_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minInclusive
with value -999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minInclusive-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minInclusive-1-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_inclusive_nistxml_sv_iv_atomic_non_positive_integer_min_inclusive_1_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minInclusive
with value -999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minInclusive-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minInclusive-1-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_inclusive_nistxml_sv_iv_atomic_non_positive_integer_min_inclusive_1_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minInclusive
with value -999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minInclusive-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minInclusive-1-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_inclusive_nistxml_sv_iv_atomic_non_positive_integer_min_inclusive_1_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minInclusive
with value -999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minInclusive-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minInclusive-1-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_inclusive_nistxml_sv_iv_atomic_non_positive_integer_min_inclusive_1_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minInclusive
with value -999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minInclusive-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minInclusive-1-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_exclusive_4_nistxml_sv_iv_atomic_non_positive_integer_min_exclusive_5_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minExclusive
with value -1.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minExclusive-5.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minExclusive-5-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_exclusive_3_nistxml_sv_iv_atomic_non_positive_integer_min_exclusive_4_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minExclusive
with value -594976296252018754.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minExclusive-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minExclusive-4-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_exclusive_3_nistxml_sv_iv_atomic_non_positive_integer_min_exclusive_4_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minExclusive
with value -594976296252018754.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minExclusive-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minExclusive-4-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_exclusive_3_nistxml_sv_iv_atomic_non_positive_integer_min_exclusive_4_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minExclusive
with value -594976296252018754.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minExclusive-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minExclusive-4-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_exclusive_3_nistxml_sv_iv_atomic_non_positive_integer_min_exclusive_4_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minExclusive
with value -594976296252018754.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minExclusive-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minExclusive-4-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_exclusive_3_nistxml_sv_iv_atomic_non_positive_integer_min_exclusive_4_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minExclusive
with value -594976296252018754.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minExclusive-4.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minExclusive-4-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_exclusive_2_nistxml_sv_iv_atomic_non_positive_integer_min_exclusive_3_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minExclusive
with value -406392790344449528.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minExclusive-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minExclusive-3-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_exclusive_2_nistxml_sv_iv_atomic_non_positive_integer_min_exclusive_3_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minExclusive
with value -406392790344449528.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minExclusive-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minExclusive-3-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_exclusive_2_nistxml_sv_iv_atomic_non_positive_integer_min_exclusive_3_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minExclusive
with value -406392790344449528.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minExclusive-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minExclusive-3-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_exclusive_2_nistxml_sv_iv_atomic_non_positive_integer_min_exclusive_3_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minExclusive
with value -406392790344449528.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minExclusive-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minExclusive-3-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_exclusive_2_nistxml_sv_iv_atomic_non_positive_integer_min_exclusive_3_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minExclusive
with value -406392790344449528.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minExclusive-3.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minExclusive-3-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_exclusive_1_nistxml_sv_iv_atomic_non_positive_integer_min_exclusive_2_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minExclusive
with value -482054947069493477.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minExclusive-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minExclusive-2-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_exclusive_1_nistxml_sv_iv_atomic_non_positive_integer_min_exclusive_2_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minExclusive
with value -482054947069493477.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minExclusive-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minExclusive-2-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_exclusive_1_nistxml_sv_iv_atomic_non_positive_integer_min_exclusive_2_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minExclusive
with value -482054947069493477.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minExclusive-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minExclusive-2-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_exclusive_1_nistxml_sv_iv_atomic_non_positive_integer_min_exclusive_2_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minExclusive
with value -482054947069493477.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minExclusive-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minExclusive-2-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_exclusive_1_nistxml_sv_iv_atomic_non_positive_integer_min_exclusive_2_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minExclusive
with value -482054947069493477.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minExclusive-2.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minExclusive-2-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_exclusive_nistxml_sv_iv_atomic_non_positive_integer_min_exclusive_1_1(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minExclusive
with value -999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minExclusive-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minExclusive-1-1.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_exclusive_nistxml_sv_iv_atomic_non_positive_integer_min_exclusive_1_2(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minExclusive
with value -999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minExclusive-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minExclusive-1-2.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_exclusive_nistxml_sv_iv_atomic_non_positive_integer_min_exclusive_1_3(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minExclusive
with value -999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minExclusive-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minExclusive-1-3.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_exclusive_nistxml_sv_iv_atomic_non_positive_integer_min_exclusive_1_4(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minExclusive
with value -999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minExclusive-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minExclusive-1-4.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_non_positive_integer_min_exclusive_nistxml_sv_iv_atomic_non_positive_integer_min_exclusive_1_5(mode, save_output, output_format):
"""
Type atomic/nonPositiveInteger is restricted by facet minExclusive
with value -999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTSchema-SV-IV-atomic-nonPositiveInteger-minExclusive-1.xsd",
instance="nistData/atomic/nonPositiveInteger/Schema+Instance/NISTXML-SV-IV-atomic-nonPositiveInteger-minExclusive-1-5.xml",
class_name="NistschemaSvIvAtomicNonPositiveIntegerMinExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_white_space_nistxml_sv_iv_atomic_integer_white_space_1_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet whiteSpace with value
collapse.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-whiteSpace-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-whiteSpace-1-1.xml",
class_name="NistschemaSvIvAtomicIntegerWhiteSpace1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_white_space_nistxml_sv_iv_atomic_integer_white_space_1_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet whiteSpace with value
collapse.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-whiteSpace-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-whiteSpace-1-2.xml",
class_name="NistschemaSvIvAtomicIntegerWhiteSpace1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_white_space_nistxml_sv_iv_atomic_integer_white_space_1_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet whiteSpace with value
collapse.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-whiteSpace-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-whiteSpace-1-3.xml",
class_name="NistschemaSvIvAtomicIntegerWhiteSpace1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_white_space_nistxml_sv_iv_atomic_integer_white_space_1_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet whiteSpace with value
collapse.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-whiteSpace-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-whiteSpace-1-4.xml",
class_name="NistschemaSvIvAtomicIntegerWhiteSpace1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_white_space_nistxml_sv_iv_atomic_integer_white_space_1_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet whiteSpace with value
collapse.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-whiteSpace-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-whiteSpace-1-5.xml",
class_name="NistschemaSvIvAtomicIntegerWhiteSpace1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_4_nistxml_sv_iv_atomic_integer_enumeration_5_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-5-1.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_4_nistxml_sv_iv_atomic_integer_enumeration_5_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-5-2.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_4_nistxml_sv_iv_atomic_integer_enumeration_5_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-5-3.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_4_nistxml_sv_iv_atomic_integer_enumeration_5_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-5-4.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_4_nistxml_sv_iv_atomic_integer_enumeration_5_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-5-5.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_3_nistxml_sv_iv_atomic_integer_enumeration_4_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-4-1.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_3_nistxml_sv_iv_atomic_integer_enumeration_4_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-4-2.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_3_nistxml_sv_iv_atomic_integer_enumeration_4_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-4-3.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_3_nistxml_sv_iv_atomic_integer_enumeration_4_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-4-4.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_3_nistxml_sv_iv_atomic_integer_enumeration_4_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-4-5.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_2_nistxml_sv_iv_atomic_integer_enumeration_3_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-3-1.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_2_nistxml_sv_iv_atomic_integer_enumeration_3_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-3-2.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_2_nistxml_sv_iv_atomic_integer_enumeration_3_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-3-3.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_2_nistxml_sv_iv_atomic_integer_enumeration_3_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-3-4.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_2_nistxml_sv_iv_atomic_integer_enumeration_3_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-3-5.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_1_nistxml_sv_iv_atomic_integer_enumeration_2_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-2-1.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_1_nistxml_sv_iv_atomic_integer_enumeration_2_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-2-2.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_1_nistxml_sv_iv_atomic_integer_enumeration_2_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-2-3.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_1_nistxml_sv_iv_atomic_integer_enumeration_2_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-2-4.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_1_nistxml_sv_iv_atomic_integer_enumeration_2_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-2-5.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_nistxml_sv_iv_atomic_integer_enumeration_1_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-1-1.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_nistxml_sv_iv_atomic_integer_enumeration_1_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-1-2.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_nistxml_sv_iv_atomic_integer_enumeration_1_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-1-3.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_nistxml_sv_iv_atomic_integer_enumeration_1_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-1-4.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_enumeration_nistxml_sv_iv_atomic_integer_enumeration_1_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-enumeration-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-enumeration-1-5.xml",
class_name="NistschemaSvIvAtomicIntegerEnumeration1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_4_nistxml_sv_iv_atomic_integer_pattern_5_1(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value \d{18}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-5-1.xml",
class_name="NistschemaSvIvAtomicIntegerPattern5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_4_nistxml_sv_iv_atomic_integer_pattern_5_2(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value \d{18}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-5-2.xml",
class_name="NistschemaSvIvAtomicIntegerPattern5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_4_nistxml_sv_iv_atomic_integer_pattern_5_3(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value \d{18}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-5-3.xml",
class_name="NistschemaSvIvAtomicIntegerPattern5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_4_nistxml_sv_iv_atomic_integer_pattern_5_4(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value \d{18}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-5-4.xml",
class_name="NistschemaSvIvAtomicIntegerPattern5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_4_nistxml_sv_iv_atomic_integer_pattern_5_5(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value \d{18}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-5-5.xml",
class_name="NistschemaSvIvAtomicIntegerPattern5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_3_nistxml_sv_iv_atomic_integer_pattern_4_1(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value \d{5}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-4-1.xml",
class_name="NistschemaSvIvAtomicIntegerPattern4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_3_nistxml_sv_iv_atomic_integer_pattern_4_2(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value \d{5}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-4-2.xml",
class_name="NistschemaSvIvAtomicIntegerPattern4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_3_nistxml_sv_iv_atomic_integer_pattern_4_3(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value \d{5}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-4-3.xml",
class_name="NistschemaSvIvAtomicIntegerPattern4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_3_nistxml_sv_iv_atomic_integer_pattern_4_4(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value \d{5}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-4-4.xml",
class_name="NistschemaSvIvAtomicIntegerPattern4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_3_nistxml_sv_iv_atomic_integer_pattern_4_5(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value \d{5}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-4-5.xml",
class_name="NistschemaSvIvAtomicIntegerPattern4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_2_nistxml_sv_iv_atomic_integer_pattern_3_1(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value \-\d{1}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-3-1.xml",
class_name="NistschemaSvIvAtomicIntegerPattern3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_2_nistxml_sv_iv_atomic_integer_pattern_3_2(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value \-\d{1}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-3-2.xml",
class_name="NistschemaSvIvAtomicIntegerPattern3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_2_nistxml_sv_iv_atomic_integer_pattern_3_3(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value \-\d{1}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-3-3.xml",
class_name="NistschemaSvIvAtomicIntegerPattern3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_2_nistxml_sv_iv_atomic_integer_pattern_3_4(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value \-\d{1}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-3-4.xml",
class_name="NistschemaSvIvAtomicIntegerPattern3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_2_nistxml_sv_iv_atomic_integer_pattern_3_5(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value \-\d{1}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-3-5.xml",
class_name="NistschemaSvIvAtomicIntegerPattern3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_1_nistxml_sv_iv_atomic_integer_pattern_2_1(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value \-\d{9}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-2-1.xml",
class_name="NistschemaSvIvAtomicIntegerPattern2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_1_nistxml_sv_iv_atomic_integer_pattern_2_2(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value \-\d{9}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-2-2.xml",
class_name="NistschemaSvIvAtomicIntegerPattern2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_1_nistxml_sv_iv_atomic_integer_pattern_2_3(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value \-\d{9}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-2-3.xml",
class_name="NistschemaSvIvAtomicIntegerPattern2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_1_nistxml_sv_iv_atomic_integer_pattern_2_4(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value \-\d{9}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-2-4.xml",
class_name="NistschemaSvIvAtomicIntegerPattern2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_1_nistxml_sv_iv_atomic_integer_pattern_2_5(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value \-\d{9}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-2-5.xml",
class_name="NistschemaSvIvAtomicIntegerPattern2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_nistxml_sv_iv_atomic_integer_pattern_1_1(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value
\-\d{18}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-1-1.xml",
class_name="NistschemaSvIvAtomicIntegerPattern1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_nistxml_sv_iv_atomic_integer_pattern_1_2(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value
\-\d{18}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-1-2.xml",
class_name="NistschemaSvIvAtomicIntegerPattern1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_nistxml_sv_iv_atomic_integer_pattern_1_3(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value
\-\d{18}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-1-3.xml",
class_name="NistschemaSvIvAtomicIntegerPattern1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_nistxml_sv_iv_atomic_integer_pattern_1_4(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value
\-\d{18}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-1-4.xml",
class_name="NistschemaSvIvAtomicIntegerPattern1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_pattern_nistxml_sv_iv_atomic_integer_pattern_1_5(mode, save_output, output_format):
r"""
Type atomic/integer is restricted by facet pattern with value
\-\d{18}.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-pattern-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-pattern-1-5.xml",
class_name="NistschemaSvIvAtomicIntegerPattern1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_4_nistxml_sv_iv_atomic_integer_total_digits_5_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 18.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-5-1.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_4_nistxml_sv_iv_atomic_integer_total_digits_5_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 18.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-5-2.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_4_nistxml_sv_iv_atomic_integer_total_digits_5_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 18.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-5-3.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_4_nistxml_sv_iv_atomic_integer_total_digits_5_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 18.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-5-4.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_4_nistxml_sv_iv_atomic_integer_total_digits_5_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 18.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-5-5.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_3_nistxml_sv_iv_atomic_integer_total_digits_4_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 13.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-4-1.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_3_nistxml_sv_iv_atomic_integer_total_digits_4_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 13.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-4-2.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_3_nistxml_sv_iv_atomic_integer_total_digits_4_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 13.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-4-3.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_3_nistxml_sv_iv_atomic_integer_total_digits_4_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 13.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-4-4.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_3_nistxml_sv_iv_atomic_integer_total_digits_4_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 13.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-4-5.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_2_nistxml_sv_iv_atomic_integer_total_digits_3_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 9.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-3-1.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_2_nistxml_sv_iv_atomic_integer_total_digits_3_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 9.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-3-2.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_2_nistxml_sv_iv_atomic_integer_total_digits_3_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 9.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-3-3.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_2_nistxml_sv_iv_atomic_integer_total_digits_3_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 9.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-3-4.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_2_nistxml_sv_iv_atomic_integer_total_digits_3_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 9.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-3-5.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_1_nistxml_sv_iv_atomic_integer_total_digits_2_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 5.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-2-1.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_1_nistxml_sv_iv_atomic_integer_total_digits_2_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 5.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-2-2.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_1_nistxml_sv_iv_atomic_integer_total_digits_2_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 5.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-2-3.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_1_nistxml_sv_iv_atomic_integer_total_digits_2_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 5.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-2-4.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_1_nistxml_sv_iv_atomic_integer_total_digits_2_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 5.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-2-5.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_nistxml_sv_iv_atomic_integer_total_digits_1_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 1.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-1-1.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_nistxml_sv_iv_atomic_integer_total_digits_1_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 1.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-1-2.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_nistxml_sv_iv_atomic_integer_total_digits_1_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 1.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-1-3.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_nistxml_sv_iv_atomic_integer_total_digits_1_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 1.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-1-4.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_total_digits_nistxml_sv_iv_atomic_integer_total_digits_1_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet totalDigits with value 1.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-totalDigits-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-totalDigits-1-5.xml",
class_name="NistschemaSvIvAtomicIntegerTotalDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_fraction_digits_nistxml_sv_iv_atomic_integer_fraction_digits_1_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet fractionDigits with value
0.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-fractionDigits-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-fractionDigits-1-1.xml",
class_name="NistschemaSvIvAtomicIntegerFractionDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_fraction_digits_nistxml_sv_iv_atomic_integer_fraction_digits_1_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet fractionDigits with value
0.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-fractionDigits-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-fractionDigits-1-2.xml",
class_name="NistschemaSvIvAtomicIntegerFractionDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_fraction_digits_nistxml_sv_iv_atomic_integer_fraction_digits_1_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet fractionDigits with value
0.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-fractionDigits-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-fractionDigits-1-3.xml",
class_name="NistschemaSvIvAtomicIntegerFractionDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_fraction_digits_nistxml_sv_iv_atomic_integer_fraction_digits_1_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet fractionDigits with value
0.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-fractionDigits-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-fractionDigits-1-4.xml",
class_name="NistschemaSvIvAtomicIntegerFractionDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_fraction_digits_nistxml_sv_iv_atomic_integer_fraction_digits_1_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet fractionDigits with value
0.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-fractionDigits-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-fractionDigits-1-5.xml",
class_name="NistschemaSvIvAtomicIntegerFractionDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_inclusive_4_nistxml_sv_iv_atomic_integer_max_inclusive_5_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxInclusive with value
999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxInclusive-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxInclusive-5-1.xml",
class_name="NistschemaSvIvAtomicIntegerMaxInclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_inclusive_4_nistxml_sv_iv_atomic_integer_max_inclusive_5_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxInclusive with value
999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxInclusive-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxInclusive-5-2.xml",
class_name="NistschemaSvIvAtomicIntegerMaxInclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_inclusive_4_nistxml_sv_iv_atomic_integer_max_inclusive_5_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxInclusive with value
999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxInclusive-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxInclusive-5-3.xml",
class_name="NistschemaSvIvAtomicIntegerMaxInclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_inclusive_4_nistxml_sv_iv_atomic_integer_max_inclusive_5_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxInclusive with value
999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxInclusive-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxInclusive-5-4.xml",
class_name="NistschemaSvIvAtomicIntegerMaxInclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_inclusive_4_nistxml_sv_iv_atomic_integer_max_inclusive_5_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxInclusive with value
999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxInclusive-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxInclusive-5-5.xml",
class_name="NistschemaSvIvAtomicIntegerMaxInclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_inclusive_3_nistxml_sv_iv_atomic_integer_max_inclusive_4_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxInclusive with value
-2761698266856349.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxInclusive-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxInclusive-4-1.xml",
class_name="NistschemaSvIvAtomicIntegerMaxInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_inclusive_3_nistxml_sv_iv_atomic_integer_max_inclusive_4_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxInclusive with value
-2761698266856349.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxInclusive-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxInclusive-4-2.xml",
class_name="NistschemaSvIvAtomicIntegerMaxInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_inclusive_3_nistxml_sv_iv_atomic_integer_max_inclusive_4_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxInclusive with value
-2761698266856349.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxInclusive-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxInclusive-4-3.xml",
class_name="NistschemaSvIvAtomicIntegerMaxInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_inclusive_3_nistxml_sv_iv_atomic_integer_max_inclusive_4_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxInclusive with value
-2761698266856349.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxInclusive-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxInclusive-4-4.xml",
class_name="NistschemaSvIvAtomicIntegerMaxInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_inclusive_3_nistxml_sv_iv_atomic_integer_max_inclusive_4_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxInclusive with value
-2761698266856349.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxInclusive-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxInclusive-4-5.xml",
class_name="NistschemaSvIvAtomicIntegerMaxInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_inclusive_2_nistxml_sv_iv_atomic_integer_max_inclusive_3_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxInclusive with value
705179181121327491.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxInclusive-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxInclusive-3-1.xml",
class_name="NistschemaSvIvAtomicIntegerMaxInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_inclusive_2_nistxml_sv_iv_atomic_integer_max_inclusive_3_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxInclusive with value
705179181121327491.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxInclusive-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxInclusive-3-2.xml",
class_name="NistschemaSvIvAtomicIntegerMaxInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_inclusive_2_nistxml_sv_iv_atomic_integer_max_inclusive_3_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxInclusive with value
705179181121327491.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxInclusive-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxInclusive-3-3.xml",
class_name="NistschemaSvIvAtomicIntegerMaxInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_inclusive_2_nistxml_sv_iv_atomic_integer_max_inclusive_3_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxInclusive with value
705179181121327491.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxInclusive-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxInclusive-3-4.xml",
class_name="NistschemaSvIvAtomicIntegerMaxInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_inclusive_2_nistxml_sv_iv_atomic_integer_max_inclusive_3_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxInclusive with value
705179181121327491.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxInclusive-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxInclusive-3-5.xml",
class_name="NistschemaSvIvAtomicIntegerMaxInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_inclusive_1_nistxml_sv_iv_atomic_integer_max_inclusive_2_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxInclusive with value
828008406281169228.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxInclusive-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxInclusive-2-1.xml",
class_name="NistschemaSvIvAtomicIntegerMaxInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_inclusive_1_nistxml_sv_iv_atomic_integer_max_inclusive_2_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxInclusive with value
828008406281169228.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxInclusive-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxInclusive-2-2.xml",
class_name="NistschemaSvIvAtomicIntegerMaxInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_inclusive_1_nistxml_sv_iv_atomic_integer_max_inclusive_2_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxInclusive with value
828008406281169228.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxInclusive-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxInclusive-2-3.xml",
class_name="NistschemaSvIvAtomicIntegerMaxInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_inclusive_1_nistxml_sv_iv_atomic_integer_max_inclusive_2_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxInclusive with value
828008406281169228.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxInclusive-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxInclusive-2-4.xml",
class_name="NistschemaSvIvAtomicIntegerMaxInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_inclusive_1_nistxml_sv_iv_atomic_integer_max_inclusive_2_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxInclusive with value
828008406281169228.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxInclusive-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxInclusive-2-5.xml",
class_name="NistschemaSvIvAtomicIntegerMaxInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_inclusive_nistxml_sv_iv_atomic_integer_max_inclusive_1_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxInclusive with value
-999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxInclusive-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxInclusive-1-1.xml",
class_name="NistschemaSvIvAtomicIntegerMaxInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_exclusive_4_nistxml_sv_iv_atomic_integer_max_exclusive_5_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxExclusive with value
999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxExclusive-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxExclusive-5-1.xml",
class_name="NistschemaSvIvAtomicIntegerMaxExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_exclusive_4_nistxml_sv_iv_atomic_integer_max_exclusive_5_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxExclusive with value
999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxExclusive-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxExclusive-5-2.xml",
class_name="NistschemaSvIvAtomicIntegerMaxExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_exclusive_4_nistxml_sv_iv_atomic_integer_max_exclusive_5_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxExclusive with value
999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxExclusive-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxExclusive-5-3.xml",
class_name="NistschemaSvIvAtomicIntegerMaxExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_exclusive_4_nistxml_sv_iv_atomic_integer_max_exclusive_5_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxExclusive with value
999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxExclusive-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxExclusive-5-4.xml",
class_name="NistschemaSvIvAtomicIntegerMaxExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_exclusive_4_nistxml_sv_iv_atomic_integer_max_exclusive_5_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxExclusive with value
999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxExclusive-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxExclusive-5-5.xml",
class_name="NistschemaSvIvAtomicIntegerMaxExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_exclusive_3_nistxml_sv_iv_atomic_integer_max_exclusive_4_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxExclusive with value
-839533034801862807.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxExclusive-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxExclusive-4-1.xml",
class_name="NistschemaSvIvAtomicIntegerMaxExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_exclusive_3_nistxml_sv_iv_atomic_integer_max_exclusive_4_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxExclusive with value
-839533034801862807.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxExclusive-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxExclusive-4-2.xml",
class_name="NistschemaSvIvAtomicIntegerMaxExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_exclusive_3_nistxml_sv_iv_atomic_integer_max_exclusive_4_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxExclusive with value
-839533034801862807.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxExclusive-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxExclusive-4-3.xml",
class_name="NistschemaSvIvAtomicIntegerMaxExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_exclusive_3_nistxml_sv_iv_atomic_integer_max_exclusive_4_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxExclusive with value
-839533034801862807.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxExclusive-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxExclusive-4-4.xml",
class_name="NistschemaSvIvAtomicIntegerMaxExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_exclusive_3_nistxml_sv_iv_atomic_integer_max_exclusive_4_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxExclusive with value
-839533034801862807.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxExclusive-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxExclusive-4-5.xml",
class_name="NistschemaSvIvAtomicIntegerMaxExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_exclusive_2_nistxml_sv_iv_atomic_integer_max_exclusive_3_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxExclusive with value
549869808681548999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxExclusive-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxExclusive-3-1.xml",
class_name="NistschemaSvIvAtomicIntegerMaxExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_exclusive_2_nistxml_sv_iv_atomic_integer_max_exclusive_3_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxExclusive with value
549869808681548999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxExclusive-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxExclusive-3-2.xml",
class_name="NistschemaSvIvAtomicIntegerMaxExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_exclusive_2_nistxml_sv_iv_atomic_integer_max_exclusive_3_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxExclusive with value
549869808681548999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxExclusive-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxExclusive-3-3.xml",
class_name="NistschemaSvIvAtomicIntegerMaxExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_exclusive_2_nistxml_sv_iv_atomic_integer_max_exclusive_3_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxExclusive with value
549869808681548999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxExclusive-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxExclusive-3-4.xml",
class_name="NistschemaSvIvAtomicIntegerMaxExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_exclusive_2_nistxml_sv_iv_atomic_integer_max_exclusive_3_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxExclusive with value
549869808681548999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxExclusive-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxExclusive-3-5.xml",
class_name="NistschemaSvIvAtomicIntegerMaxExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_exclusive_1_nistxml_sv_iv_atomic_integer_max_exclusive_2_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxExclusive with value
-863230876206589446.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxExclusive-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxExclusive-2-1.xml",
class_name="NistschemaSvIvAtomicIntegerMaxExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_exclusive_1_nistxml_sv_iv_atomic_integer_max_exclusive_2_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxExclusive with value
-863230876206589446.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxExclusive-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxExclusive-2-2.xml",
class_name="NistschemaSvIvAtomicIntegerMaxExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_exclusive_1_nistxml_sv_iv_atomic_integer_max_exclusive_2_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxExclusive with value
-863230876206589446.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxExclusive-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxExclusive-2-3.xml",
class_name="NistschemaSvIvAtomicIntegerMaxExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_exclusive_1_nistxml_sv_iv_atomic_integer_max_exclusive_2_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxExclusive with value
-863230876206589446.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxExclusive-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxExclusive-2-4.xml",
class_name="NistschemaSvIvAtomicIntegerMaxExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_exclusive_1_nistxml_sv_iv_atomic_integer_max_exclusive_2_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxExclusive with value
-863230876206589446.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxExclusive-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxExclusive-2-5.xml",
class_name="NistschemaSvIvAtomicIntegerMaxExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_max_exclusive_nistxml_sv_iv_atomic_integer_max_exclusive_1_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet maxExclusive with value
-999999999999999998.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-maxExclusive-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-maxExclusive-1-1.xml",
class_name="NistschemaSvIvAtomicIntegerMaxExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_inclusive_4_nistxml_sv_iv_atomic_integer_min_inclusive_5_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minInclusive with value
999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minInclusive-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minInclusive-5-1.xml",
class_name="NistschemaSvIvAtomicIntegerMinInclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_inclusive_3_nistxml_sv_iv_atomic_integer_min_inclusive_4_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minInclusive with value
-183640263935870295.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minInclusive-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minInclusive-4-1.xml",
class_name="NistschemaSvIvAtomicIntegerMinInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_inclusive_3_nistxml_sv_iv_atomic_integer_min_inclusive_4_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minInclusive with value
-183640263935870295.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minInclusive-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minInclusive-4-2.xml",
class_name="NistschemaSvIvAtomicIntegerMinInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_inclusive_3_nistxml_sv_iv_atomic_integer_min_inclusive_4_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minInclusive with value
-183640263935870295.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minInclusive-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minInclusive-4-3.xml",
class_name="NistschemaSvIvAtomicIntegerMinInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_inclusive_3_nistxml_sv_iv_atomic_integer_min_inclusive_4_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minInclusive with value
-183640263935870295.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minInclusive-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minInclusive-4-4.xml",
class_name="NistschemaSvIvAtomicIntegerMinInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_inclusive_3_nistxml_sv_iv_atomic_integer_min_inclusive_4_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minInclusive with value
-183640263935870295.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minInclusive-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minInclusive-4-5.xml",
class_name="NistschemaSvIvAtomicIntegerMinInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_inclusive_2_nistxml_sv_iv_atomic_integer_min_inclusive_3_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minInclusive with value
-362471093580558400.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minInclusive-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minInclusive-3-1.xml",
class_name="NistschemaSvIvAtomicIntegerMinInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_inclusive_2_nistxml_sv_iv_atomic_integer_min_inclusive_3_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minInclusive with value
-362471093580558400.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minInclusive-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minInclusive-3-2.xml",
class_name="NistschemaSvIvAtomicIntegerMinInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_inclusive_2_nistxml_sv_iv_atomic_integer_min_inclusive_3_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minInclusive with value
-362471093580558400.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minInclusive-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minInclusive-3-3.xml",
class_name="NistschemaSvIvAtomicIntegerMinInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_inclusive_2_nistxml_sv_iv_atomic_integer_min_inclusive_3_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minInclusive with value
-362471093580558400.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minInclusive-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minInclusive-3-4.xml",
class_name="NistschemaSvIvAtomicIntegerMinInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_inclusive_2_nistxml_sv_iv_atomic_integer_min_inclusive_3_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minInclusive with value
-362471093580558400.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minInclusive-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minInclusive-3-5.xml",
class_name="NistschemaSvIvAtomicIntegerMinInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_inclusive_1_nistxml_sv_iv_atomic_integer_min_inclusive_2_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minInclusive with value
156487900906511434.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minInclusive-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minInclusive-2-1.xml",
class_name="NistschemaSvIvAtomicIntegerMinInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_inclusive_1_nistxml_sv_iv_atomic_integer_min_inclusive_2_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minInclusive with value
156487900906511434.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minInclusive-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minInclusive-2-2.xml",
class_name="NistschemaSvIvAtomicIntegerMinInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_inclusive_1_nistxml_sv_iv_atomic_integer_min_inclusive_2_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minInclusive with value
156487900906511434.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minInclusive-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minInclusive-2-3.xml",
class_name="NistschemaSvIvAtomicIntegerMinInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_inclusive_1_nistxml_sv_iv_atomic_integer_min_inclusive_2_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minInclusive with value
156487900906511434.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minInclusive-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minInclusive-2-4.xml",
class_name="NistschemaSvIvAtomicIntegerMinInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_inclusive_1_nistxml_sv_iv_atomic_integer_min_inclusive_2_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minInclusive with value
156487900906511434.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minInclusive-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minInclusive-2-5.xml",
class_name="NistschemaSvIvAtomicIntegerMinInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_inclusive_nistxml_sv_iv_atomic_integer_min_inclusive_1_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minInclusive with value
-999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minInclusive-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minInclusive-1-1.xml",
class_name="NistschemaSvIvAtomicIntegerMinInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_inclusive_nistxml_sv_iv_atomic_integer_min_inclusive_1_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minInclusive with value
-999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minInclusive-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minInclusive-1-2.xml",
class_name="NistschemaSvIvAtomicIntegerMinInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_inclusive_nistxml_sv_iv_atomic_integer_min_inclusive_1_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minInclusive with value
-999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minInclusive-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minInclusive-1-3.xml",
class_name="NistschemaSvIvAtomicIntegerMinInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_inclusive_nistxml_sv_iv_atomic_integer_min_inclusive_1_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minInclusive with value
-999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minInclusive-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minInclusive-1-4.xml",
class_name="NistschemaSvIvAtomicIntegerMinInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_inclusive_nistxml_sv_iv_atomic_integer_min_inclusive_1_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minInclusive with value
-999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minInclusive-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minInclusive-1-5.xml",
class_name="NistschemaSvIvAtomicIntegerMinInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_exclusive_4_nistxml_sv_iv_atomic_integer_min_exclusive_5_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minExclusive with value
999999999999999998.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minExclusive-5.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minExclusive-5-1.xml",
class_name="NistschemaSvIvAtomicIntegerMinExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_exclusive_3_nistxml_sv_iv_atomic_integer_min_exclusive_4_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minExclusive with value
470740450062970382.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minExclusive-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minExclusive-4-1.xml",
class_name="NistschemaSvIvAtomicIntegerMinExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_exclusive_3_nistxml_sv_iv_atomic_integer_min_exclusive_4_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minExclusive with value
470740450062970382.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minExclusive-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minExclusive-4-2.xml",
class_name="NistschemaSvIvAtomicIntegerMinExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_exclusive_3_nistxml_sv_iv_atomic_integer_min_exclusive_4_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minExclusive with value
470740450062970382.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minExclusive-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minExclusive-4-3.xml",
class_name="NistschemaSvIvAtomicIntegerMinExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_exclusive_3_nistxml_sv_iv_atomic_integer_min_exclusive_4_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minExclusive with value
470740450062970382.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minExclusive-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minExclusive-4-4.xml",
class_name="NistschemaSvIvAtomicIntegerMinExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_exclusive_3_nistxml_sv_iv_atomic_integer_min_exclusive_4_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minExclusive with value
470740450062970382.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minExclusive-4.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minExclusive-4-5.xml",
class_name="NistschemaSvIvAtomicIntegerMinExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_exclusive_2_nistxml_sv_iv_atomic_integer_min_exclusive_3_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minExclusive with value
389578809107570477.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minExclusive-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minExclusive-3-1.xml",
class_name="NistschemaSvIvAtomicIntegerMinExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_exclusive_2_nistxml_sv_iv_atomic_integer_min_exclusive_3_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minExclusive with value
389578809107570477.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minExclusive-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minExclusive-3-2.xml",
class_name="NistschemaSvIvAtomicIntegerMinExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_exclusive_2_nistxml_sv_iv_atomic_integer_min_exclusive_3_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minExclusive with value
389578809107570477.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minExclusive-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minExclusive-3-3.xml",
class_name="NistschemaSvIvAtomicIntegerMinExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_exclusive_2_nistxml_sv_iv_atomic_integer_min_exclusive_3_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minExclusive with value
389578809107570477.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minExclusive-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minExclusive-3-4.xml",
class_name="NistschemaSvIvAtomicIntegerMinExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_exclusive_2_nistxml_sv_iv_atomic_integer_min_exclusive_3_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minExclusive with value
389578809107570477.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minExclusive-3.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minExclusive-3-5.xml",
class_name="NistschemaSvIvAtomicIntegerMinExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_exclusive_1_nistxml_sv_iv_atomic_integer_min_exclusive_2_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minExclusive with value
511594901568435787.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minExclusive-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minExclusive-2-1.xml",
class_name="NistschemaSvIvAtomicIntegerMinExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_exclusive_1_nistxml_sv_iv_atomic_integer_min_exclusive_2_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minExclusive with value
511594901568435787.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minExclusive-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minExclusive-2-2.xml",
class_name="NistschemaSvIvAtomicIntegerMinExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_exclusive_1_nistxml_sv_iv_atomic_integer_min_exclusive_2_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minExclusive with value
511594901568435787.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minExclusive-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minExclusive-2-3.xml",
class_name="NistschemaSvIvAtomicIntegerMinExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_exclusive_1_nistxml_sv_iv_atomic_integer_min_exclusive_2_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minExclusive with value
511594901568435787.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minExclusive-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minExclusive-2-4.xml",
class_name="NistschemaSvIvAtomicIntegerMinExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_exclusive_1_nistxml_sv_iv_atomic_integer_min_exclusive_2_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minExclusive with value
511594901568435787.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minExclusive-2.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minExclusive-2-5.xml",
class_name="NistschemaSvIvAtomicIntegerMinExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_exclusive_nistxml_sv_iv_atomic_integer_min_exclusive_1_1(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minExclusive with value
-999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minExclusive-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minExclusive-1-1.xml",
class_name="NistschemaSvIvAtomicIntegerMinExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_exclusive_nistxml_sv_iv_atomic_integer_min_exclusive_1_2(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minExclusive with value
-999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minExclusive-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minExclusive-1-2.xml",
class_name="NistschemaSvIvAtomicIntegerMinExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_exclusive_nistxml_sv_iv_atomic_integer_min_exclusive_1_3(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minExclusive with value
-999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minExclusive-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minExclusive-1-3.xml",
class_name="NistschemaSvIvAtomicIntegerMinExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_exclusive_nistxml_sv_iv_atomic_integer_min_exclusive_1_4(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minExclusive with value
-999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minExclusive-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minExclusive-1-4.xml",
class_name="NistschemaSvIvAtomicIntegerMinExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_integer_min_exclusive_nistxml_sv_iv_atomic_integer_min_exclusive_1_5(mode, save_output, output_format):
"""
Type atomic/integer is restricted by facet minExclusive with value
-999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/integer/Schema+Instance/NISTSchema-SV-IV-atomic-integer-minExclusive-1.xsd",
instance="nistData/atomic/integer/Schema+Instance/NISTXML-SV-IV-atomic-integer-minExclusive-1-5.xml",
class_name="NistschemaSvIvAtomicIntegerMinExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_white_space_nistxml_sv_iv_atomic_decimal_white_space_1_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet whiteSpace with value
collapse.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-whiteSpace-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-whiteSpace-1-1.xml",
class_name="NistschemaSvIvAtomicDecimalWhiteSpace1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_white_space_nistxml_sv_iv_atomic_decimal_white_space_1_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet whiteSpace with value
collapse.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-whiteSpace-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-whiteSpace-1-2.xml",
class_name="NistschemaSvIvAtomicDecimalWhiteSpace1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_white_space_nistxml_sv_iv_atomic_decimal_white_space_1_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet whiteSpace with value
collapse.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-whiteSpace-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-whiteSpace-1-3.xml",
class_name="NistschemaSvIvAtomicDecimalWhiteSpace1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_white_space_nistxml_sv_iv_atomic_decimal_white_space_1_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet whiteSpace with value
collapse.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-whiteSpace-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-whiteSpace-1-4.xml",
class_name="NistschemaSvIvAtomicDecimalWhiteSpace1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_white_space_nistxml_sv_iv_atomic_decimal_white_space_1_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet whiteSpace with value
collapse.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-whiteSpace-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-whiteSpace-1-5.xml",
class_name="NistschemaSvIvAtomicDecimalWhiteSpace1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_4_nistxml_sv_iv_atomic_decimal_enumeration_5_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-5-1.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_4_nistxml_sv_iv_atomic_decimal_enumeration_5_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-5-2.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_4_nistxml_sv_iv_atomic_decimal_enumeration_5_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-5-3.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_4_nistxml_sv_iv_atomic_decimal_enumeration_5_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-5-4.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_4_nistxml_sv_iv_atomic_decimal_enumeration_5_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-5-5.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_3_nistxml_sv_iv_atomic_decimal_enumeration_4_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-4-1.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_3_nistxml_sv_iv_atomic_decimal_enumeration_4_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-4-2.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_3_nistxml_sv_iv_atomic_decimal_enumeration_4_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-4-3.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_3_nistxml_sv_iv_atomic_decimal_enumeration_4_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-4-4.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_3_nistxml_sv_iv_atomic_decimal_enumeration_4_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-4-5.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_2_nistxml_sv_iv_atomic_decimal_enumeration_3_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-3-1.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_2_nistxml_sv_iv_atomic_decimal_enumeration_3_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-3-2.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_2_nistxml_sv_iv_atomic_decimal_enumeration_3_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-3-3.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_2_nistxml_sv_iv_atomic_decimal_enumeration_3_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-3-4.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_2_nistxml_sv_iv_atomic_decimal_enumeration_3_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-3-5.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_1_nistxml_sv_iv_atomic_decimal_enumeration_2_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-2-1.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_1_nistxml_sv_iv_atomic_decimal_enumeration_2_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-2-2.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_1_nistxml_sv_iv_atomic_decimal_enumeration_2_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-2-3.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_1_nistxml_sv_iv_atomic_decimal_enumeration_2_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-2-4.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_1_nistxml_sv_iv_atomic_decimal_enumeration_2_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-2-5.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_nistxml_sv_iv_atomic_decimal_enumeration_1_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-1-1.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_nistxml_sv_iv_atomic_decimal_enumeration_1_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-1-2.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_nistxml_sv_iv_atomic_decimal_enumeration_1_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-1-3.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_nistxml_sv_iv_atomic_decimal_enumeration_1_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-1-4.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_enumeration_nistxml_sv_iv_atomic_decimal_enumeration_1_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet enumeration.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-enumeration-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-enumeration-1-5.xml",
class_name="NistschemaSvIvAtomicDecimalEnumeration1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_4_nistxml_sv_iv_atomic_decimal_pattern_5_1(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value
\d{5}\.\d{13}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-5-1.xml",
class_name="NistschemaSvIvAtomicDecimalPattern5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_4_nistxml_sv_iv_atomic_decimal_pattern_5_2(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value
\d{5}\.\d{13}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-5-2.xml",
class_name="NistschemaSvIvAtomicDecimalPattern5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_4_nistxml_sv_iv_atomic_decimal_pattern_5_3(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value
\d{5}\.\d{13}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-5-3.xml",
class_name="NistschemaSvIvAtomicDecimalPattern5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_4_nistxml_sv_iv_atomic_decimal_pattern_5_4(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value
\d{5}\.\d{13}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-5-4.xml",
class_name="NistschemaSvIvAtomicDecimalPattern5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_4_nistxml_sv_iv_atomic_decimal_pattern_5_5(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value
\d{5}\.\d{13}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-5-5.xml",
class_name="NistschemaSvIvAtomicDecimalPattern5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_3_nistxml_sv_iv_atomic_decimal_pattern_4_1(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value
\.\d{13}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-4-1.xml",
class_name="NistschemaSvIvAtomicDecimalPattern4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_3_nistxml_sv_iv_atomic_decimal_pattern_4_2(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value
\.\d{13}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-4-2.xml",
class_name="NistschemaSvIvAtomicDecimalPattern4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_3_nistxml_sv_iv_atomic_decimal_pattern_4_3(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value
\.\d{13}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-4-3.xml",
class_name="NistschemaSvIvAtomicDecimalPattern4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_3_nistxml_sv_iv_atomic_decimal_pattern_4_4(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value
\.\d{13}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-4-4.xml",
class_name="NistschemaSvIvAtomicDecimalPattern4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_3_nistxml_sv_iv_atomic_decimal_pattern_4_5(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value
\.\d{13}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-4-5.xml",
class_name="NistschemaSvIvAtomicDecimalPattern4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_2_nistxml_sv_iv_atomic_decimal_pattern_3_1(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value
\-\d{1}\.\d{8}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-3-1.xml",
class_name="NistschemaSvIvAtomicDecimalPattern3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_2_nistxml_sv_iv_atomic_decimal_pattern_3_2(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value
\-\d{1}\.\d{8}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-3-2.xml",
class_name="NistschemaSvIvAtomicDecimalPattern3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_2_nistxml_sv_iv_atomic_decimal_pattern_3_3(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value
\-\d{1}\.\d{8}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-3-3.xml",
class_name="NistschemaSvIvAtomicDecimalPattern3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_2_nistxml_sv_iv_atomic_decimal_pattern_3_4(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value
\-\d{1}\.\d{8}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-3-4.xml",
class_name="NistschemaSvIvAtomicDecimalPattern3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_2_nistxml_sv_iv_atomic_decimal_pattern_3_5(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value
\-\d{1}\.\d{8}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-3-5.xml",
class_name="NistschemaSvIvAtomicDecimalPattern3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_1_nistxml_sv_iv_atomic_decimal_pattern_2_1(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value
\-\d{2}\.\d{3}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-2-1.xml",
class_name="NistschemaSvIvAtomicDecimalPattern2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_1_nistxml_sv_iv_atomic_decimal_pattern_2_2(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value
\-\d{2}\.\d{3}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-2-2.xml",
class_name="NistschemaSvIvAtomicDecimalPattern2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_1_nistxml_sv_iv_atomic_decimal_pattern_2_3(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value
\-\d{2}\.\d{3}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-2-3.xml",
class_name="NistschemaSvIvAtomicDecimalPattern2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_1_nistxml_sv_iv_atomic_decimal_pattern_2_4(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value
\-\d{2}\.\d{3}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-2-4.xml",
class_name="NistschemaSvIvAtomicDecimalPattern2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_1_nistxml_sv_iv_atomic_decimal_pattern_2_5(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value
\-\d{2}\.\d{3}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-2-5.xml",
class_name="NistschemaSvIvAtomicDecimalPattern2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_nistxml_sv_iv_atomic_decimal_pattern_1_1(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value \d{1}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-1-1.xml",
class_name="NistschemaSvIvAtomicDecimalPattern1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_nistxml_sv_iv_atomic_decimal_pattern_1_2(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value \d{1}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-1-2.xml",
class_name="NistschemaSvIvAtomicDecimalPattern1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_nistxml_sv_iv_atomic_decimal_pattern_1_3(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value \d{1}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-1-3.xml",
class_name="NistschemaSvIvAtomicDecimalPattern1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_nistxml_sv_iv_atomic_decimal_pattern_1_4(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value \d{1}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-1-4.xml",
class_name="NistschemaSvIvAtomicDecimalPattern1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_pattern_nistxml_sv_iv_atomic_decimal_pattern_1_5(mode, save_output, output_format):
r"""
Type atomic/decimal is restricted by facet pattern with value \d{1}.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-pattern-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-pattern-1-5.xml",
class_name="NistschemaSvIvAtomicDecimalPattern1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_4_nistxml_sv_iv_atomic_decimal_total_digits_5_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 18.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-5-1.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_4_nistxml_sv_iv_atomic_decimal_total_digits_5_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 18.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-5-2.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_4_nistxml_sv_iv_atomic_decimal_total_digits_5_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 18.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-5-3.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_4_nistxml_sv_iv_atomic_decimal_total_digits_5_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 18.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-5-4.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_4_nistxml_sv_iv_atomic_decimal_total_digits_5_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 18.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-5-5.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_3_nistxml_sv_iv_atomic_decimal_total_digits_4_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 13.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-4-1.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_3_nistxml_sv_iv_atomic_decimal_total_digits_4_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 13.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-4-2.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_3_nistxml_sv_iv_atomic_decimal_total_digits_4_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 13.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-4-3.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_3_nistxml_sv_iv_atomic_decimal_total_digits_4_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 13.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-4-4.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_3_nistxml_sv_iv_atomic_decimal_total_digits_4_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 13.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-4-5.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_2_nistxml_sv_iv_atomic_decimal_total_digits_3_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 9.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-3-1.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_2_nistxml_sv_iv_atomic_decimal_total_digits_3_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 9.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-3-2.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_2_nistxml_sv_iv_atomic_decimal_total_digits_3_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 9.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-3-3.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_2_nistxml_sv_iv_atomic_decimal_total_digits_3_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 9.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-3-4.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_2_nistxml_sv_iv_atomic_decimal_total_digits_3_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 9.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-3-5.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_1_nistxml_sv_iv_atomic_decimal_total_digits_2_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 5.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-2-1.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_1_nistxml_sv_iv_atomic_decimal_total_digits_2_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 5.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-2-2.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_1_nistxml_sv_iv_atomic_decimal_total_digits_2_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 5.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-2-3.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_1_nistxml_sv_iv_atomic_decimal_total_digits_2_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 5.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-2-4.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_1_nistxml_sv_iv_atomic_decimal_total_digits_2_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 5.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-2-5.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_nistxml_sv_iv_atomic_decimal_total_digits_1_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 1.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-1-1.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_nistxml_sv_iv_atomic_decimal_total_digits_1_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 1.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-1-2.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_nistxml_sv_iv_atomic_decimal_total_digits_1_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 1.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-1-3.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_nistxml_sv_iv_atomic_decimal_total_digits_1_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 1.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-1-4.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_total_digits_nistxml_sv_iv_atomic_decimal_total_digits_1_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet totalDigits with value 1.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-totalDigits-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-totalDigits-1-5.xml",
class_name="NistschemaSvIvAtomicDecimalTotalDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_4_nistxml_sv_iv_atomic_decimal_fraction_digits_5_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
18.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-5-1.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_4_nistxml_sv_iv_atomic_decimal_fraction_digits_5_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
18.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-5-2.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_4_nistxml_sv_iv_atomic_decimal_fraction_digits_5_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
18.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-5-3.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_4_nistxml_sv_iv_atomic_decimal_fraction_digits_5_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
18.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-5-4.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_4_nistxml_sv_iv_atomic_decimal_fraction_digits_5_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
18.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-5-5.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_3_nistxml_sv_iv_atomic_decimal_fraction_digits_4_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
12.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-4-1.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_3_nistxml_sv_iv_atomic_decimal_fraction_digits_4_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
12.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-4-2.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_3_nistxml_sv_iv_atomic_decimal_fraction_digits_4_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
12.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-4-3.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_3_nistxml_sv_iv_atomic_decimal_fraction_digits_4_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
12.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-4-4.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_3_nistxml_sv_iv_atomic_decimal_fraction_digits_4_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
12.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-4-5.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_2_nistxml_sv_iv_atomic_decimal_fraction_digits_3_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
8.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-3-1.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_2_nistxml_sv_iv_atomic_decimal_fraction_digits_3_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
8.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-3-2.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_2_nistxml_sv_iv_atomic_decimal_fraction_digits_3_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
8.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-3-3.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_2_nistxml_sv_iv_atomic_decimal_fraction_digits_3_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
8.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-3-4.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_2_nistxml_sv_iv_atomic_decimal_fraction_digits_3_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
8.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-3-5.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_1_nistxml_sv_iv_atomic_decimal_fraction_digits_2_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
4.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-2-1.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_1_nistxml_sv_iv_atomic_decimal_fraction_digits_2_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
4.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-2-2.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_1_nistxml_sv_iv_atomic_decimal_fraction_digits_2_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
4.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-2-3.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_1_nistxml_sv_iv_atomic_decimal_fraction_digits_2_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
4.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-2-4.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_1_nistxml_sv_iv_atomic_decimal_fraction_digits_2_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
4.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-2-5.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_nistxml_sv_iv_atomic_decimal_fraction_digits_1_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
0.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-1-1.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_nistxml_sv_iv_atomic_decimal_fraction_digits_1_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
0.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-1-2.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_nistxml_sv_iv_atomic_decimal_fraction_digits_1_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
0.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-1-3.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_nistxml_sv_iv_atomic_decimal_fraction_digits_1_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
0.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-1-4.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_fraction_digits_nistxml_sv_iv_atomic_decimal_fraction_digits_1_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet fractionDigits with value
0.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-fractionDigits-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-fractionDigits-1-5.xml",
class_name="NistschemaSvIvAtomicDecimalFractionDigits1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_inclusive_4_nistxml_sv_iv_atomic_decimal_max_inclusive_5_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxInclusive with value
999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxInclusive-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxInclusive-5-1.xml",
class_name="NistschemaSvIvAtomicDecimalMaxInclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_inclusive_4_nistxml_sv_iv_atomic_decimal_max_inclusive_5_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxInclusive with value
999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxInclusive-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxInclusive-5-2.xml",
class_name="NistschemaSvIvAtomicDecimalMaxInclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_inclusive_4_nistxml_sv_iv_atomic_decimal_max_inclusive_5_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxInclusive with value
999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxInclusive-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxInclusive-5-3.xml",
class_name="NistschemaSvIvAtomicDecimalMaxInclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_inclusive_4_nistxml_sv_iv_atomic_decimal_max_inclusive_5_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxInclusive with value
999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxInclusive-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxInclusive-5-4.xml",
class_name="NistschemaSvIvAtomicDecimalMaxInclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_inclusive_4_nistxml_sv_iv_atomic_decimal_max_inclusive_5_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxInclusive with value
999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxInclusive-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxInclusive-5-5.xml",
class_name="NistschemaSvIvAtomicDecimalMaxInclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_inclusive_3_nistxml_sv_iv_atomic_decimal_max_inclusive_4_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxInclusive with value
-95776055693671313.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxInclusive-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxInclusive-4-1.xml",
class_name="NistschemaSvIvAtomicDecimalMaxInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_inclusive_3_nistxml_sv_iv_atomic_decimal_max_inclusive_4_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxInclusive with value
-95776055693671313.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxInclusive-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxInclusive-4-2.xml",
class_name="NistschemaSvIvAtomicDecimalMaxInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_inclusive_3_nistxml_sv_iv_atomic_decimal_max_inclusive_4_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxInclusive with value
-95776055693671313.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxInclusive-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxInclusive-4-3.xml",
class_name="NistschemaSvIvAtomicDecimalMaxInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_inclusive_3_nistxml_sv_iv_atomic_decimal_max_inclusive_4_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxInclusive with value
-95776055693671313.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxInclusive-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxInclusive-4-4.xml",
class_name="NistschemaSvIvAtomicDecimalMaxInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_inclusive_3_nistxml_sv_iv_atomic_decimal_max_inclusive_4_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxInclusive with value
-95776055693671313.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxInclusive-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxInclusive-4-5.xml",
class_name="NistschemaSvIvAtomicDecimalMaxInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_inclusive_2_nistxml_sv_iv_atomic_decimal_max_inclusive_3_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxInclusive with value
-888403528420030673.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxInclusive-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxInclusive-3-1.xml",
class_name="NistschemaSvIvAtomicDecimalMaxInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_inclusive_2_nistxml_sv_iv_atomic_decimal_max_inclusive_3_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxInclusive with value
-888403528420030673.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxInclusive-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxInclusive-3-2.xml",
class_name="NistschemaSvIvAtomicDecimalMaxInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_inclusive_2_nistxml_sv_iv_atomic_decimal_max_inclusive_3_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxInclusive with value
-888403528420030673.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxInclusive-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxInclusive-3-3.xml",
class_name="NistschemaSvIvAtomicDecimalMaxInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_inclusive_2_nistxml_sv_iv_atomic_decimal_max_inclusive_3_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxInclusive with value
-888403528420030673.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxInclusive-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxInclusive-3-4.xml",
class_name="NistschemaSvIvAtomicDecimalMaxInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_inclusive_2_nistxml_sv_iv_atomic_decimal_max_inclusive_3_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxInclusive with value
-888403528420030673.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxInclusive-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxInclusive-3-5.xml",
class_name="NistschemaSvIvAtomicDecimalMaxInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_inclusive_1_nistxml_sv_iv_atomic_decimal_max_inclusive_2_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxInclusive with value
625897845365533055.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxInclusive-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxInclusive-2-1.xml",
class_name="NistschemaSvIvAtomicDecimalMaxInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_inclusive_1_nistxml_sv_iv_atomic_decimal_max_inclusive_2_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxInclusive with value
625897845365533055.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxInclusive-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxInclusive-2-2.xml",
class_name="NistschemaSvIvAtomicDecimalMaxInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_inclusive_1_nistxml_sv_iv_atomic_decimal_max_inclusive_2_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxInclusive with value
625897845365533055.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxInclusive-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxInclusive-2-3.xml",
class_name="NistschemaSvIvAtomicDecimalMaxInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_inclusive_1_nistxml_sv_iv_atomic_decimal_max_inclusive_2_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxInclusive with value
625897845365533055.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxInclusive-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxInclusive-2-4.xml",
class_name="NistschemaSvIvAtomicDecimalMaxInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_inclusive_1_nistxml_sv_iv_atomic_decimal_max_inclusive_2_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxInclusive with value
625897845365533055.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxInclusive-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxInclusive-2-5.xml",
class_name="NistschemaSvIvAtomicDecimalMaxInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_inclusive_nistxml_sv_iv_atomic_decimal_max_inclusive_1_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxInclusive with value
-999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxInclusive-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxInclusive-1-1.xml",
class_name="NistschemaSvIvAtomicDecimalMaxInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_exclusive_4_nistxml_sv_iv_atomic_decimal_max_exclusive_5_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxExclusive with value
999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxExclusive-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxExclusive-5-1.xml",
class_name="NistschemaSvIvAtomicDecimalMaxExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_exclusive_4_nistxml_sv_iv_atomic_decimal_max_exclusive_5_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxExclusive with value
999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxExclusive-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxExclusive-5-2.xml",
class_name="NistschemaSvIvAtomicDecimalMaxExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_exclusive_4_nistxml_sv_iv_atomic_decimal_max_exclusive_5_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxExclusive with value
999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxExclusive-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxExclusive-5-3.xml",
class_name="NistschemaSvIvAtomicDecimalMaxExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_exclusive_4_nistxml_sv_iv_atomic_decimal_max_exclusive_5_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxExclusive with value
999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxExclusive-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxExclusive-5-4.xml",
class_name="NistschemaSvIvAtomicDecimalMaxExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_exclusive_4_nistxml_sv_iv_atomic_decimal_max_exclusive_5_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxExclusive with value
999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxExclusive-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxExclusive-5-5.xml",
class_name="NistschemaSvIvAtomicDecimalMaxExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_exclusive_3_nistxml_sv_iv_atomic_decimal_max_exclusive_4_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxExclusive with value
-214771926190724381.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxExclusive-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxExclusive-4-1.xml",
class_name="NistschemaSvIvAtomicDecimalMaxExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_exclusive_3_nistxml_sv_iv_atomic_decimal_max_exclusive_4_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxExclusive with value
-214771926190724381.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxExclusive-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxExclusive-4-2.xml",
class_name="NistschemaSvIvAtomicDecimalMaxExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_exclusive_3_nistxml_sv_iv_atomic_decimal_max_exclusive_4_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxExclusive with value
-214771926190724381.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxExclusive-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxExclusive-4-3.xml",
class_name="NistschemaSvIvAtomicDecimalMaxExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_exclusive_3_nistxml_sv_iv_atomic_decimal_max_exclusive_4_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxExclusive with value
-214771926190724381.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxExclusive-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxExclusive-4-4.xml",
class_name="NistschemaSvIvAtomicDecimalMaxExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_exclusive_3_nistxml_sv_iv_atomic_decimal_max_exclusive_4_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxExclusive with value
-214771926190724381.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxExclusive-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxExclusive-4-5.xml",
class_name="NistschemaSvIvAtomicDecimalMaxExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_exclusive_2_nistxml_sv_iv_atomic_decimal_max_exclusive_3_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxExclusive with value
171942968603657986.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxExclusive-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxExclusive-3-1.xml",
class_name="NistschemaSvIvAtomicDecimalMaxExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_exclusive_2_nistxml_sv_iv_atomic_decimal_max_exclusive_3_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxExclusive with value
171942968603657986.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxExclusive-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxExclusive-3-2.xml",
class_name="NistschemaSvIvAtomicDecimalMaxExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_exclusive_2_nistxml_sv_iv_atomic_decimal_max_exclusive_3_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxExclusive with value
171942968603657986.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxExclusive-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxExclusive-3-3.xml",
class_name="NistschemaSvIvAtomicDecimalMaxExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_exclusive_2_nistxml_sv_iv_atomic_decimal_max_exclusive_3_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxExclusive with value
171942968603657986.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxExclusive-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxExclusive-3-4.xml",
class_name="NistschemaSvIvAtomicDecimalMaxExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_exclusive_2_nistxml_sv_iv_atomic_decimal_max_exclusive_3_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxExclusive with value
171942968603657986.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxExclusive-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxExclusive-3-5.xml",
class_name="NistschemaSvIvAtomicDecimalMaxExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_exclusive_1_nistxml_sv_iv_atomic_decimal_max_exclusive_2_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxExclusive with value
78119693427168402.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxExclusive-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxExclusive-2-1.xml",
class_name="NistschemaSvIvAtomicDecimalMaxExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_exclusive_1_nistxml_sv_iv_atomic_decimal_max_exclusive_2_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxExclusive with value
78119693427168402.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxExclusive-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxExclusive-2-2.xml",
class_name="NistschemaSvIvAtomicDecimalMaxExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_exclusive_1_nistxml_sv_iv_atomic_decimal_max_exclusive_2_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxExclusive with value
78119693427168402.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxExclusive-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxExclusive-2-3.xml",
class_name="NistschemaSvIvAtomicDecimalMaxExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_exclusive_1_nistxml_sv_iv_atomic_decimal_max_exclusive_2_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxExclusive with value
78119693427168402.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxExclusive-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxExclusive-2-4.xml",
class_name="NistschemaSvIvAtomicDecimalMaxExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_exclusive_1_nistxml_sv_iv_atomic_decimal_max_exclusive_2_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxExclusive with value
78119693427168402.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxExclusive-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxExclusive-2-5.xml",
class_name="NistschemaSvIvAtomicDecimalMaxExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_max_exclusive_nistxml_sv_iv_atomic_decimal_max_exclusive_1_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet maxExclusive with value
-999999999999999998.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-maxExclusive-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-maxExclusive-1-1.xml",
class_name="NistschemaSvIvAtomicDecimalMaxExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_inclusive_4_nistxml_sv_iv_atomic_decimal_min_inclusive_5_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minInclusive with value
999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minInclusive-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minInclusive-5-1.xml",
class_name="NistschemaSvIvAtomicDecimalMinInclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_inclusive_3_nistxml_sv_iv_atomic_decimal_min_inclusive_4_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minInclusive with value
325207740352921658.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minInclusive-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minInclusive-4-1.xml",
class_name="NistschemaSvIvAtomicDecimalMinInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_inclusive_3_nistxml_sv_iv_atomic_decimal_min_inclusive_4_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minInclusive with value
325207740352921658.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minInclusive-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minInclusive-4-2.xml",
class_name="NistschemaSvIvAtomicDecimalMinInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_inclusive_3_nistxml_sv_iv_atomic_decimal_min_inclusive_4_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minInclusive with value
325207740352921658.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minInclusive-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minInclusive-4-3.xml",
class_name="NistschemaSvIvAtomicDecimalMinInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_inclusive_3_nistxml_sv_iv_atomic_decimal_min_inclusive_4_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minInclusive with value
325207740352921658.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minInclusive-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minInclusive-4-4.xml",
class_name="NistschemaSvIvAtomicDecimalMinInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_inclusive_3_nistxml_sv_iv_atomic_decimal_min_inclusive_4_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minInclusive with value
325207740352921658.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minInclusive-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minInclusive-4-5.xml",
class_name="NistschemaSvIvAtomicDecimalMinInclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_inclusive_2_nistxml_sv_iv_atomic_decimal_min_inclusive_3_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minInclusive with value
-785368448026986020.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minInclusive-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minInclusive-3-1.xml",
class_name="NistschemaSvIvAtomicDecimalMinInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_inclusive_2_nistxml_sv_iv_atomic_decimal_min_inclusive_3_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minInclusive with value
-785368448026986020.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minInclusive-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minInclusive-3-2.xml",
class_name="NistschemaSvIvAtomicDecimalMinInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_inclusive_2_nistxml_sv_iv_atomic_decimal_min_inclusive_3_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minInclusive with value
-785368448026986020.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minInclusive-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minInclusive-3-3.xml",
class_name="NistschemaSvIvAtomicDecimalMinInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_inclusive_2_nistxml_sv_iv_atomic_decimal_min_inclusive_3_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minInclusive with value
-785368448026986020.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minInclusive-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minInclusive-3-4.xml",
class_name="NistschemaSvIvAtomicDecimalMinInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_inclusive_2_nistxml_sv_iv_atomic_decimal_min_inclusive_3_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minInclusive with value
-785368448026986020.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minInclusive-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minInclusive-3-5.xml",
class_name="NistschemaSvIvAtomicDecimalMinInclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_inclusive_1_nistxml_sv_iv_atomic_decimal_min_inclusive_2_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minInclusive with value
229822855408968073.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minInclusive-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minInclusive-2-1.xml",
class_name="NistschemaSvIvAtomicDecimalMinInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_inclusive_1_nistxml_sv_iv_atomic_decimal_min_inclusive_2_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minInclusive with value
229822855408968073.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minInclusive-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minInclusive-2-2.xml",
class_name="NistschemaSvIvAtomicDecimalMinInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_inclusive_1_nistxml_sv_iv_atomic_decimal_min_inclusive_2_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minInclusive with value
229822855408968073.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minInclusive-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minInclusive-2-3.xml",
class_name="NistschemaSvIvAtomicDecimalMinInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_inclusive_1_nistxml_sv_iv_atomic_decimal_min_inclusive_2_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minInclusive with value
229822855408968073.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minInclusive-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minInclusive-2-4.xml",
class_name="NistschemaSvIvAtomicDecimalMinInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_inclusive_1_nistxml_sv_iv_atomic_decimal_min_inclusive_2_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minInclusive with value
229822855408968073.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minInclusive-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minInclusive-2-5.xml",
class_name="NistschemaSvIvAtomicDecimalMinInclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_inclusive_nistxml_sv_iv_atomic_decimal_min_inclusive_1_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minInclusive with value
-999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minInclusive-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minInclusive-1-1.xml",
class_name="NistschemaSvIvAtomicDecimalMinInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_inclusive_nistxml_sv_iv_atomic_decimal_min_inclusive_1_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minInclusive with value
-999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minInclusive-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minInclusive-1-2.xml",
class_name="NistschemaSvIvAtomicDecimalMinInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_inclusive_nistxml_sv_iv_atomic_decimal_min_inclusive_1_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minInclusive with value
-999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minInclusive-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minInclusive-1-3.xml",
class_name="NistschemaSvIvAtomicDecimalMinInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_inclusive_nistxml_sv_iv_atomic_decimal_min_inclusive_1_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minInclusive with value
-999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minInclusive-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minInclusive-1-4.xml",
class_name="NistschemaSvIvAtomicDecimalMinInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_inclusive_nistxml_sv_iv_atomic_decimal_min_inclusive_1_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minInclusive with value
-999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minInclusive-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minInclusive-1-5.xml",
class_name="NistschemaSvIvAtomicDecimalMinInclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_exclusive_4_nistxml_sv_iv_atomic_decimal_min_exclusive_5_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minExclusive with value
999999999999999998.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minExclusive-5.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minExclusive-5-1.xml",
class_name="NistschemaSvIvAtomicDecimalMinExclusive5",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_exclusive_3_nistxml_sv_iv_atomic_decimal_min_exclusive_4_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minExclusive with value
-294253147230818967.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minExclusive-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minExclusive-4-1.xml",
class_name="NistschemaSvIvAtomicDecimalMinExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_exclusive_3_nistxml_sv_iv_atomic_decimal_min_exclusive_4_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minExclusive with value
-294253147230818967.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minExclusive-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minExclusive-4-2.xml",
class_name="NistschemaSvIvAtomicDecimalMinExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_exclusive_3_nistxml_sv_iv_atomic_decimal_min_exclusive_4_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minExclusive with value
-294253147230818967.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minExclusive-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minExclusive-4-3.xml",
class_name="NistschemaSvIvAtomicDecimalMinExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_exclusive_3_nistxml_sv_iv_atomic_decimal_min_exclusive_4_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minExclusive with value
-294253147230818967.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minExclusive-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minExclusive-4-4.xml",
class_name="NistschemaSvIvAtomicDecimalMinExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_exclusive_3_nistxml_sv_iv_atomic_decimal_min_exclusive_4_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minExclusive with value
-294253147230818967.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minExclusive-4.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minExclusive-4-5.xml",
class_name="NistschemaSvIvAtomicDecimalMinExclusive4",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_exclusive_2_nistxml_sv_iv_atomic_decimal_min_exclusive_3_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minExclusive with value
-67428259604688900.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minExclusive-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minExclusive-3-1.xml",
class_name="NistschemaSvIvAtomicDecimalMinExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_exclusive_2_nistxml_sv_iv_atomic_decimal_min_exclusive_3_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minExclusive with value
-67428259604688900.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minExclusive-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minExclusive-3-2.xml",
class_name="NistschemaSvIvAtomicDecimalMinExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_exclusive_2_nistxml_sv_iv_atomic_decimal_min_exclusive_3_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minExclusive with value
-67428259604688900.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minExclusive-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minExclusive-3-3.xml",
class_name="NistschemaSvIvAtomicDecimalMinExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_exclusive_2_nistxml_sv_iv_atomic_decimal_min_exclusive_3_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minExclusive with value
-67428259604688900.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minExclusive-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minExclusive-3-4.xml",
class_name="NistschemaSvIvAtomicDecimalMinExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_exclusive_2_nistxml_sv_iv_atomic_decimal_min_exclusive_3_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minExclusive with value
-67428259604688900.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minExclusive-3.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minExclusive-3-5.xml",
class_name="NistschemaSvIvAtomicDecimalMinExclusive3",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_exclusive_1_nistxml_sv_iv_atomic_decimal_min_exclusive_2_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minExclusive with value
631308414640570968.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minExclusive-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minExclusive-2-1.xml",
class_name="NistschemaSvIvAtomicDecimalMinExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_exclusive_1_nistxml_sv_iv_atomic_decimal_min_exclusive_2_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minExclusive with value
631308414640570968.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minExclusive-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minExclusive-2-2.xml",
class_name="NistschemaSvIvAtomicDecimalMinExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_exclusive_1_nistxml_sv_iv_atomic_decimal_min_exclusive_2_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minExclusive with value
631308414640570968.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minExclusive-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minExclusive-2-3.xml",
class_name="NistschemaSvIvAtomicDecimalMinExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_exclusive_1_nistxml_sv_iv_atomic_decimal_min_exclusive_2_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minExclusive with value
631308414640570968.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minExclusive-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minExclusive-2-4.xml",
class_name="NistschemaSvIvAtomicDecimalMinExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_exclusive_1_nistxml_sv_iv_atomic_decimal_min_exclusive_2_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minExclusive with value
631308414640570968.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minExclusive-2.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minExclusive-2-5.xml",
class_name="NistschemaSvIvAtomicDecimalMinExclusive2",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_exclusive_nistxml_sv_iv_atomic_decimal_min_exclusive_1_1(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minExclusive with value
-999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minExclusive-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minExclusive-1-1.xml",
class_name="NistschemaSvIvAtomicDecimalMinExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_exclusive_nistxml_sv_iv_atomic_decimal_min_exclusive_1_2(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minExclusive with value
-999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minExclusive-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minExclusive-1-2.xml",
class_name="NistschemaSvIvAtomicDecimalMinExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_exclusive_nistxml_sv_iv_atomic_decimal_min_exclusive_1_3(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minExclusive with value
-999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minExclusive-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minExclusive-1-3.xml",
class_name="NistschemaSvIvAtomicDecimalMinExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_exclusive_nistxml_sv_iv_atomic_decimal_min_exclusive_1_4(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minExclusive with value
-999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minExclusive-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minExclusive-1-4.xml",
class_name="NistschemaSvIvAtomicDecimalMinExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
def test_atomic_decimal_min_exclusive_nistxml_sv_iv_atomic_decimal_min_exclusive_1_5(mode, save_output, output_format):
"""
Type atomic/decimal is restricted by facet minExclusive with value
-999999999999999999.
"""
assert_bindings(
schema="nistData/atomic/decimal/Schema+Instance/NISTSchema-SV-IV-atomic-decimal-minExclusive-1.xsd",
instance="nistData/atomic/decimal/Schema+Instance/NISTXML-SV-IV-atomic-decimal-minExclusive-1-5.xml",
class_name="NistschemaSvIvAtomicDecimalMinExclusive1",
version="1.1",
mode=mode,
save_output=save_output,
output_format=output_format,
structure_style="filenames",
)
| 42.519451 | 149 | 0.743563 | 50,316 | 433,911 | 6.125586 | 0.005147 | 0.023711 | 0.059277 | 0.06718 | 0.997563 | 0.997499 | 0.995237 | 0.994809 | 0.994037 | 0.993667 | 0 | 0.030819 | 0.160915 | 433,911 | 10,204 | 150 | 42.523618 | 0.81572 | 0.114924 | 0 | 0.714391 | 0 | 0.179779 | 0.406889 | 0.387301 | 0 | 0 | 0 | 0 | 0.090037 | 1 | 0.089889 | false | 0 | 0.000148 | 0 | 0.090037 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
dc9ce4fab2e970720267a662df0bca01bd98647e | 59 | py | Python | gym-number-link/gym_number_link/envs/__init__.py | EmpereurCC/Spinningup_uptodate | f93e7edf778237a0e79bfdb45f7529522bd34ed4 | [
"MIT"
] | null | null | null | gym-number-link/gym_number_link/envs/__init__.py | EmpereurCC/Spinningup_uptodate | f93e7edf778237a0e79bfdb45f7529522bd34ed4 | [
"MIT"
] | 2 | 2019-06-18T14:12:26.000Z | 2019-06-18T14:55:10.000Z | gym-number-link/gym_number_link/envs/__init__.py | EmpereurCC/Spinningup_uptodate | f93e7edf778237a0e79bfdb45f7529522bd34ed4 | [
"MIT"
] | 1 | 2019-06-11T15:07:59.000Z | 2019-06-11T15:07:59.000Z | from gym_number_link.envs.gym_number_link import NumberLink | 59 | 59 | 0.915254 | 10 | 59 | 5 | 0.7 | 0.36 | 0.52 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.050847 | 59 | 1 | 59 | 59 | 0.892857 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
dcb5e9cc6724b53d26e396d8f3bac72a88a02169 | 113 | py | Python | _package/xms/grid/ugrid/__init__.py | kwryankrattiger/xmsgrid | a7b0058b7ae783db37638f83433cf7127efbcea4 | [
"BSD-2-Clause"
] | 1 | 2018-07-19T14:53:52.000Z | 2018-07-19T14:53:52.000Z | _package/xms/grid/ugrid/__init__.py | kwryankrattiger/xmsgrid | a7b0058b7ae783db37638f83433cf7127efbcea4 | [
"BSD-2-Clause"
] | 11 | 2018-10-09T12:39:24.000Z | 2022-03-16T18:16:27.000Z | _package/xms/grid/ugrid/__init__.py | kwryankrattiger/xmsgrid | a7b0058b7ae783db37638f83433cf7127efbcea4 | [
"BSD-2-Clause"
] | 2 | 2020-09-24T22:38:54.000Z | 2021-04-14T21:05:34.000Z | from . import ugrid # NOQA: F401
from . import ugrid_utils # NOQA: F401
from .ugrid import UGrid # NOQA: F401
| 28.25 | 39 | 0.707965 | 17 | 113 | 4.647059 | 0.352941 | 0.417722 | 0.379747 | 0.481013 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.101124 | 0.212389 | 113 | 3 | 40 | 37.666667 | 0.786517 | 0.283186 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 8 |
f4b6cc6bf760c38dadb69536b36255dde31922a0 | 2,370 | py | Python | src/draw.py | Sayeem2004/Porcelain | ead84fb85807dad102fe53d426dae19ce0f6654d | [
"MIT"
] | null | null | null | src/draw.py | Sayeem2004/Porcelain | ead84fb85807dad102fe53d426dae19ce0f6654d | [
"MIT"
] | null | null | null | src/draw.py | Sayeem2004/Porcelain | ead84fb85807dad102fe53d426dae19ce0f6654d | [
"MIT"
] | null | null | null | # Imports
import var
# Function for M1 button click
def get_coords(event):
# Drawing Point
var.prev_x, var.prev_y = event.x, event.y
curr = var.canvas.create_line((var.prev_x, var.prev_y, var.prev_x+1, var.prev_y+1), fill=var.line_color, width=var.line_width)
# Adding point to list of canvas objects
if (len(var.lines) == 0):
var.lines.append([curr, var.canvas.coords(curr)])
elif (var.line_ind == len(var.lines)-1):
var.line_ind += 1
var.lines.append([curr, var.canvas.coords(curr)])
else:
var.line_ind += 1
var.lines = var.lines[:var.line_ind]
var.lines.append([curr, var.canvas.coords(curr)])
# Function for M1 button movement
def draw_line(event):
# Drawing line
curr = var.canvas.create_line((var.prev_x, var.prev_y, event.x, event.y), fill=var.line_color, width=var.line_width)
var.prev_x, var.prev_y = event.x, event.y
# Adding line to list of canvas objects
if (len(var.lines) == 0):
var.lines.append([curr, var.canvas.coords(curr)])
elif (var.line_ind == len(var.lines)-1):
var.line_ind += 1
var.lines.append([curr, var.canvas.coords(curr)])
else:
var.line_ind += 1
var.lines = var.lines[:var.line_ind]
var.lines.append([curr, var.canvas.coords(curr)])
# Function for Ctrl-Z
def undo_line(event):
# Undoing multiple lines
for _ in range(var.ch_line):
# Casework for undoing lines
if (var.line_ind > 0):
var.canvas.delete(var.lines[var.line_ind][0])
var.line_ind -= 1
else:
var.canvas.delete(var.lines[var.line_ind][0])
# Function for Ctrl-Y
def redo_line(event):
# Redoing multiple lines
for _ in range(var.ch_line):
# Casework for redoing lines
if (var.line_ind < len(var.lines)-1):
var.line_ind += 1
crds = var.lines[var.line_ind][1]
var.canvas.delete(var.lines[var.line_ind][0])
curr = var.canvas.create_line(crds, fill=var.line_color, width=var.line_width)
var.lines[var.line_ind][0] = curr
else:
crds = var.lines[var.line_ind][1]
var.canvas.delete(var.lines[var.line_ind][0])
curr = var.canvas.create_line(crds, fill=var.line_color, width=var.line_width)
var.lines[var.line_ind][0] = curr
| 36.461538 | 130 | 0.622363 | 372 | 2,370 | 3.830645 | 0.142473 | 0.137544 | 0.140351 | 0.105263 | 0.825965 | 0.806316 | 0.806316 | 0.806316 | 0.783158 | 0.712281 | 0 | 0.013274 | 0.237131 | 2,370 | 64 | 131 | 37.03125 | 0.774889 | 0.131646 | 0 | 0.777778 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.088889 | false | 0 | 0.022222 | 0 | 0.111111 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
52079f658ac8b57446fdd45c2c3fb3dbfb2827fc | 140 | py | Python | exceptions.py | kelvin-jose/stackX | 329246225f847dbe8045992222fec2ddacdbcbfc | [
"MIT"
] | null | null | null | exceptions.py | kelvin-jose/stackX | 329246225f847dbe8045992222fec2ddacdbcbfc | [
"MIT"
] | null | null | null | exceptions.py | kelvin-jose/stackX | 329246225f847dbe8045992222fec2ddacdbcbfc | [
"MIT"
] | null | null | null | class StackOverflow(Exception):
def __init__(self):
pass
class StackUnderflow(Exception):
def __init__(self):
pass | 17.5 | 32 | 0.664286 | 14 | 140 | 6.071429 | 0.571429 | 0.282353 | 0.376471 | 0.470588 | 0.564706 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.25 | 140 | 8 | 33 | 17.5 | 0.809524 | 0 | 0 | 0.666667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | false | 0.333333 | 0 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 8 |
520a44a5e393aaff00752a66a623a6c3b5959e0e | 40,185 | py | Python | limonero/schema.py | eubr-bigsea/limonero | 54851b73bb1e4f5626b3d38ea7eeb50f3ed2e3c5 | [
"Apache-2.0"
] | 1 | 2018-01-01T20:35:43.000Z | 2018-01-01T20:35:43.000Z | limonero/schema.py | eubr-bigsea/limonero | 54851b73bb1e4f5626b3d38ea7eeb50f3ed2e3c5 | [
"Apache-2.0"
] | 37 | 2017-02-24T17:07:25.000Z | 2021-09-02T14:49:19.000Z | limonero/schema.py | eubr-bigsea/limonero | 54851b73bb1e4f5626b3d38ea7eeb50f3ed2e3c5 | [
"Apache-2.0"
] | 2 | 2019-11-05T13:45:45.000Z | 2020-11-13T22:02:37.000Z | # -*- coding: utf-8 -*-
import datetime
import json
from copy import deepcopy
from marshmallow import Schema, fields, post_load, post_dump, EXCLUDE, INCLUDE
from marshmallow.validate import OneOf
from flask_babel import gettext
from limonero.models import *
def partial_schema_factory(schema_cls):
schema = schema_cls(partial=True)
for field_name, field in list(schema.fields.items()):
if isinstance(field, fields.Nested):
new_field = deepcopy(field)
new_field.schema.partial = True
schema.fields[field_name] = new_field
return schema
def translate_validation(validation_errors):
for field, errors in list(validation_errors.items()):
if isinstance(errors, dict):
validation_errors[field] = translate_validation(errors)
else:
validation_errors[field] = [gettext(error) for error in errors]
return validation_errors
def load_json(str_value):
try:
return json.loads(str_value)
except BaseException:
return None
# region Protected
def generate_download_token(identifier, expires=None):
from flask import current_app
from cryptography.fernet import Fernet
import time
f = current_app.fernet
if expires is None:
f_expires = 0
else:
f_expires = time.time() + expires
return f.encrypt('{{"id": {}, "expires": {} }}'.format(
identifier, f_expires).encode('utf8')).decode('utf8')
# endregion
class BaseSchema(Schema):
@post_dump
def remove_skip_values(self, data, **kwargs):
return {
key: value for key, value in data.items()
if value is not None # Empty lists must be kept!
}
class AttributeListResponseSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(required=True)
name = fields.String(required=True)
description = fields.String(required=False, allow_none=True)
type = fields.String(required=True,
validate=[OneOf(list(DataType.__dict__.keys()))])
size = fields.Integer(required=False, allow_none=True)
precision = fields.Integer(required=False, allow_none=True)
scale = fields.Integer(required=False, allow_none=True)
nullable = fields.Boolean(
required=False,
allow_none=True,
missing=False,
default=False)
enumeration = fields.Boolean(
required=False,
allow_none=True,
missing=False,
default=False)
missing_representation = fields.String(required=False, allow_none=True)
feature = fields.Boolean(
required=False,
allow_none=True,
missing=True,
default=True)
label = fields.Boolean(
required=False,
allow_none=True,
missing=True,
default=True)
distinct_values = fields.Integer(required=False, allow_none=True)
mean_value = fields.Float(required=False, allow_none=True)
median_value = fields.String(required=False, allow_none=True)
max_value = fields.String(required=False, allow_none=True)
min_value = fields.String(required=False, allow_none=True)
std_deviation = fields.Float(required=False, allow_none=True)
missing_total = fields.String(required=False, allow_none=True)
deciles = fields.String(required=False, allow_none=True)
format = fields.String(required=False, allow_none=True)
key = fields.Boolean(
required=False,
allow_none=True,
missing=False,
default=False)
attribute_privacy = fields.Nested(
'limonero.schema.AttributePrivacyListResponseSchema',
allow_none=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of Attribute"""
return Attribute(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class AttributeItemResponseSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(required=True)
name = fields.String(required=True)
description = fields.String(required=False, allow_none=True)
type = fields.String(required=True,
validate=[OneOf(list(DataType.__dict__.keys()))])
size = fields.Integer(required=False, allow_none=True)
precision = fields.Integer(required=False, allow_none=True)
scale = fields.Integer(required=False, allow_none=True)
nullable = fields.Boolean(
required=False,
allow_none=True,
missing=False,
default=False)
enumeration = fields.Boolean(
required=False,
allow_none=True,
missing=False,
default=False)
missing_representation = fields.String(required=False, allow_none=True)
feature = fields.Boolean(
required=False,
allow_none=True,
missing=True,
default=True)
label = fields.Boolean(
required=False,
allow_none=True,
missing=True,
default=True)
distinct_values = fields.Integer(required=False, allow_none=True)
mean_value = fields.Float(required=False, allow_none=True)
median_value = fields.String(required=False, allow_none=True)
max_value = fields.String(required=False, allow_none=True)
min_value = fields.String(required=False, allow_none=True)
std_deviation = fields.Float(required=False, allow_none=True)
missing_total = fields.String(required=False, allow_none=True)
deciles = fields.String(required=False, allow_none=True)
format = fields.String(required=False, allow_none=True)
key = fields.Boolean(
required=False,
allow_none=True,
missing=False,
default=False)
attribute_privacy = fields.Nested(
'limonero.schema.AttributePrivacyItemResponseSchema',
allow_none=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of Attribute"""
return Attribute(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class AttributeCreateRequestSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(allow_none=True)
name = fields.String(required=True)
description = fields.String(required=False, allow_none=True)
type = fields.String(required=True,
validate=[OneOf(list(DataType.__dict__.keys()))])
size = fields.Integer(required=False, allow_none=True)
precision = fields.Integer(required=False, allow_none=True)
scale = fields.Integer(required=False, allow_none=True)
nullable = fields.Boolean(
required=False,
allow_none=True,
missing=False,
default=False)
enumeration = fields.Boolean(
required=False,
allow_none=True,
missing=False,
default=False)
missing_representation = fields.String(required=False, allow_none=True)
feature = fields.Boolean(
required=False,
allow_none=True,
missing=True,
default=True)
label = fields.Boolean(
required=False,
allow_none=True,
missing=True,
default=True)
distinct_values = fields.Integer(required=False, allow_none=True)
mean_value = fields.Float(required=False, allow_none=True)
median_value = fields.String(required=False, allow_none=True)
max_value = fields.String(required=False, allow_none=True)
min_value = fields.String(required=False, allow_none=True)
std_deviation = fields.Float(required=False, allow_none=True)
missing_total = fields.String(required=False, allow_none=True)
deciles = fields.String(required=False, allow_none=True)
format = fields.String(required=False, allow_none=True)
key = fields.Boolean(
required=False,
allow_none=True,
missing=False,
default=False)
attribute_privacy = fields.Nested(
'limonero.schema.AttributePrivacyCreateRequestSchema',
allow_none=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of Attribute"""
return Attribute(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class AttributePrivacyResponseSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(required=True)
name = fields.String(required=True)
attribute_privacy = fields.Nested(
'limonero.schema.AttributePrivacyItemResponseSchema',
allow_none=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of Attribute"""
return Attribute(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class AttributePrivacyListResponseSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(required=True)
attribute_name = fields.String(required=True)
data_type = fields.String(required=False, allow_none=True,
validate=[OneOf(list(DataType.__dict__.keys()))])
privacy_type = fields.String(required=True,
validate=[OneOf(list(PrivacyType.__dict__.keys()))])
category_technique = fields.String(required=False, allow_none=True)
anonymization_technique = fields.String(required=True,
validate=[OneOf(list(AnonymizationTechnique.__dict__.keys()))])
hierarchical_structure_type = fields.String(
required=False, allow_none=True)
privacy_model_technique = fields.String(required=False, allow_none=True)
hierarchy = fields.String(required=False, allow_none=True)
category_model = fields.String(required=False, allow_none=True)
privacy_model = fields.String(required=False, allow_none=True)
privacy_model_parameters = fields.String(required=False, allow_none=True)
unlock_privacy_key = fields.String(required=False, allow_none=True)
is_global_law = fields.Boolean(
required=False,
allow_none=True,
missing=False,
default=False)
attribute_privacy_group = fields.Nested(
'limonero.schema.AttributePrivacyGroupListResponseSchema',
allow_none=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of AttributePrivacy"""
return AttributePrivacy(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class AttributePrivacyItemResponseSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(required=True)
attribute_name = fields.String(required=True)
data_type = fields.String(required=False, allow_none=True,
validate=[OneOf(list(DataType.__dict__.keys()))])
privacy_type = fields.String(required=True,
validate=[OneOf(list(PrivacyType.__dict__.keys()))])
category_technique = fields.String(required=False, allow_none=True)
anonymization_technique = fields.String(required=True,
validate=[OneOf(list(AnonymizationTechnique.__dict__.keys()))])
hierarchical_structure_type = fields.String(
required=False, allow_none=True)
privacy_model_technique = fields.String(required=False, allow_none=True)
hierarchy = fields.String(required=False, allow_none=True)
category_model = fields.String(required=False, allow_none=True)
privacy_model = fields.String(required=False, allow_none=True)
privacy_model_parameters = fields.String(required=False, allow_none=True)
unlock_privacy_key = fields.String(required=False, allow_none=True)
is_global_law = fields.Boolean(
required=False,
allow_none=True,
missing=False,
default=False)
attribute_privacy_group_id = fields.Integer(
required=False, allow_none=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of AttributePrivacy"""
return AttributePrivacy(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class AttributePrivacyCreateRequestSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(allow_none=True)
attribute_name = fields.String(required=True)
data_type = fields.String(required=False, allow_none=True,
validate=[OneOf(list(DataType.__dict__.keys()))])
privacy_type = fields.String(required=True,
validate=[OneOf(list(PrivacyType.__dict__.keys()))])
category_technique = fields.String(required=False, allow_none=True)
anonymization_technique = fields.String(required=True,
validate=[OneOf(list(AnonymizationTechnique.__dict__.keys()))])
hierarchical_structure_type = fields.String(
required=False, allow_none=True)
privacy_model_technique = fields.String(required=False, allow_none=True)
hierarchy = fields.String(required=False, allow_none=True)
category_model = fields.String(required=False, allow_none=True)
privacy_model = fields.String(required=False, allow_none=True)
privacy_model_parameters = fields.String(required=False, allow_none=True)
unlock_privacy_key = fields.String(required=False, allow_none=True)
attribute_id = fields.Integer(required=False, allow_none=True)
attribute_privacy_group_id = fields.Integer(
required=False, allow_none=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of AttributePrivacy"""
return AttributePrivacy(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class AttributePrivacyPrivacyResponseSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(required=True)
data_type = fields.String(required=False, allow_none=True,
validate=[OneOf(list(DataType.__dict__.keys()))])
privacy_type = fields.String(required=True,
validate=[OneOf(list(PrivacyType.__dict__.keys()))])
category_technique = fields.String(required=False, allow_none=True)
anonymization_technique = fields.String(required=True,
validate=[OneOf(list(AnonymizationTechnique.__dict__.keys()))])
hierarchical_structure_type = fields.String(
required=False, allow_none=True)
privacy_model_technique = fields.String(required=False, allow_none=True)
hierarchy = fields.String(required=False, allow_none=True)
category_model = fields.String(required=False, allow_none=True)
privacy_model = fields.String(required=False, allow_none=True)
privacy_model_parameters = fields.String(required=False, allow_none=True)
unlock_privacy_key = fields.String(required=False, allow_none=True)
is_global_law = fields.Boolean(
required=False,
allow_none=True,
missing=False,
default=False)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of AttributePrivacy"""
return AttributePrivacy(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class AttributePrivacyGroupListResponseSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(required=True)
name = fields.String(required=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of AttributePrivacyGroup"""
return AttributePrivacyGroup(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class AttributePrivacyGroupItemResponseSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(required=True)
name = fields.String(required=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of AttributePrivacyGroup"""
return AttributePrivacyGroup(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class AttributePrivacyGroupCreateRequestSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(allow_none=True)
name = fields.String(required=True)
user_id = fields.Integer(required=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of AttributePrivacyGroup"""
return AttributePrivacyGroup(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class DataSourceExecuteRequestSchema(BaseSchema):
""" JSON schema for executing tasks """
id = fields.Integer(required=True)
name = fields.String(required=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of DataSource"""
return DataSource(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class DataSourceListResponseSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(required=True)
name = fields.String(required=True)
description = fields.String(required=False, allow_none=True)
enabled = fields.Boolean(
required=False,
allow_none=True,
missing=True,
default=True)
statistics_process_counter = fields.Integer(
required=False, allow_none=True, missing=0, default=0)
read_only = fields.Boolean(
required=False,
allow_none=True,
missing=True,
default=True)
privacy_aware = fields.Boolean(
required=False,
allow_none=True,
missing=False,
default=False)
url = fields.String(required=True)
created = fields.DateTime(required=False, allow_none=True)
updated = fields.DateTime(
required=False,
allow_none=True,
missing=datetime.datetime.utcnow,
default=datetime.datetime.utcnow)
format = fields.String(required=True,
validate=[OneOf(list(DataSourceFormat.__dict__.keys()))])
initialization = fields.String(required=False, allow_none=True, missing=DataSourceInitialization.INITIALIZED, default=DataSourceInitialization.INITIALIZED,
validate=[OneOf(list(DataSourceInitialization.__dict__.keys()))])
initialization_job_id = fields.String(required=False, allow_none=True)
provenience = fields.String(required=False, allow_none=True)
estimated_rows = fields.Integer(
required=False,
allow_none=True,
missing=0,
default=0)
estimated_size_in_mega_bytes = fields.Decimal(
required=False, allow_none=True)
expiration = fields.String(required=False, allow_none=True)
user_id = fields.Integer(required=False, allow_none=True)
user_login = fields.String(required=False, allow_none=True)
user_name = fields.String(required=False, allow_none=True)
tags = fields.String(required=False, allow_none=True)
temporary = fields.Boolean(
required=False,
allow_none=True,
missing=False,
default=False)
workflow_id = fields.Integer(required=False, allow_none=True)
task_id = fields.String(required=False, allow_none=True)
attribute_delimiter = fields.String(required=False, allow_none=True)
record_delimiter = fields.String(required=False, allow_none=True)
text_delimiter = fields.String(required=False, allow_none=True)
is_public = fields.Boolean(
required=False,
allow_none=True,
missing=False,
default=False)
treat_as_missing = fields.String(required=False, allow_none=True)
encoding = fields.String(required=False, allow_none=True)
is_first_line_header = fields.Boolean(
required=False, allow_none=True, missing=0, default=0)
is_multiline = fields.Boolean(
required=False,
allow_none=True,
missing=0,
default=0)
command = fields.String(required=False, allow_none=True)
is_lookup = fields.Boolean(
required=False,
allow_none=True,
missing=0,
default=0)
use_in_workflow = fields.Boolean(
required=False,
allow_none=True,
missing=0,
default=0)
attributes = fields.Nested(
'limonero.schema.AttributeListResponseSchema',
allow_none=True,
many=True)
permissions = fields.Nested(
'limonero.schema.DataSourcePermissionListResponseSchema',
allow_none=True,
many=True)
storage = fields.Nested(
'limonero.schema.StorageListResponseSchema',
required=True)
download_token = fields.Function(
lambda d: generate_download_token(d.id, 600))
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of DataSource"""
return DataSource(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class DataSourceCreateRequestSchema(BaseSchema):
""" JSON serialization schema """
name = fields.String(required=True)
description = fields.String(required=False, allow_none=True)
enabled = fields.Boolean(
required=False,
allow_none=True,
missing=True,
default=True)
statistics_process_counter = fields.Integer(
required=False, allow_none=True, missing=0, default=0)
read_only = fields.Boolean(
required=False,
allow_none=True,
missing=True,
default=True)
privacy_aware = fields.Boolean(
required=False,
allow_none=True,
missing=False,
default=False)
url = fields.String(required=True)
format = fields.String(required=True,
validate=[OneOf(list(DataSourceFormat.__dict__.keys()))])
initialization = fields.String(required=False, allow_none=True, missing=DataSourceInitialization.INITIALIZED, default=DataSourceInitialization.INITIALIZED,
validate=[OneOf(list(DataSourceInitialization.__dict__.keys()))])
initialization_job_id = fields.String(required=False, allow_none=True)
provenience = fields.String(required=False, allow_none=True)
expiration = fields.String(required=False, allow_none=True)
user_id = fields.Integer(required=False, allow_none=True)
user_login = fields.String(required=False, allow_none=True)
user_name = fields.String(required=False, allow_none=True)
tags = fields.String(required=False, allow_none=True)
temporary = fields.Boolean(
required=False,
allow_none=True,
missing=False,
default=False)
workflow_id = fields.Integer(required=False, allow_none=True)
task_id = fields.String(required=False, allow_none=True)
attribute_delimiter = fields.String(required=False, allow_none=True)
record_delimiter = fields.String(required=False, allow_none=True)
text_delimiter = fields.String(required=False, allow_none=True)
is_public = fields.Boolean(
required=False,
allow_none=True,
missing=False,
default=False)
treat_as_missing = fields.String(required=False, allow_none=True)
encoding = fields.String(required=False, allow_none=True)
is_first_line_header = fields.Boolean(
required=False, allow_none=True, missing=0, default=0)
is_multiline = fields.Boolean(
required=False,
allow_none=True,
missing=0,
default=0)
command = fields.String(required=False, allow_none=True)
is_lookup = fields.Boolean(
required=False,
allow_none=True,
missing=0,
default=0)
use_in_workflow = fields.Boolean(
required=False,
allow_none=True,
missing=0,
default=0)
attributes = fields.Nested(
'limonero.schema.AttributeCreateRequestSchema',
allow_none=True,
many=True)
permissions = fields.Nested(
'limonero.schema.DataSourcePermissionCreateRequestSchema',
allow_none=True,
many=True)
storage_id = fields.Integer(required=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of DataSource"""
return DataSource(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class DataSourceItemResponseSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(required=True)
name = fields.String(required=True)
description = fields.String(required=False, allow_none=True)
enabled = fields.Boolean(
required=False,
allow_none=True,
missing=True,
default=True)
statistics_process_counter = fields.Integer(
required=False, allow_none=True, missing=0, default=0)
read_only = fields.Boolean(
required=False,
allow_none=True,
missing=True,
default=True)
privacy_aware = fields.Boolean(
required=False,
allow_none=True,
missing=False,
default=False)
url = fields.String(required=True)
created = fields.DateTime(required=False, allow_none=True)
updated = fields.DateTime(
required=False,
allow_none=True,
missing=datetime.datetime.utcnow,
default=datetime.datetime.utcnow)
format = fields.String(required=True,
validate=[OneOf(list(DataSourceFormat.__dict__.keys()))])
initialization = fields.String(required=False, allow_none=True, missing=DataSourceInitialization.INITIALIZED, default=DataSourceInitialization.INITIALIZED,
validate=[OneOf(list(DataSourceInitialization.__dict__.keys()))])
initialization_job_id = fields.String(required=False, allow_none=True)
provenience = fields.String(required=False, allow_none=True)
estimated_rows = fields.Integer(
required=False,
allow_none=True,
missing=0,
default=0)
estimated_size_in_mega_bytes = fields.Decimal(
required=False, allow_none=True)
expiration = fields.String(required=False, allow_none=True)
user_id = fields.Integer(required=False, allow_none=True)
user_login = fields.String(required=False, allow_none=True)
user_name = fields.String(required=False, allow_none=True)
tags = fields.String(required=False, allow_none=True)
temporary = fields.Boolean(
required=False,
allow_none=True,
missing=False,
default=False)
workflow_id = fields.Integer(required=False, allow_none=True)
task_id = fields.String(required=False, allow_none=True)
attribute_delimiter = fields.String(required=False, allow_none=True)
record_delimiter = fields.String(required=False, allow_none=True)
text_delimiter = fields.String(required=False, allow_none=True)
is_public = fields.Boolean(
required=False,
allow_none=True,
missing=False,
default=False)
treat_as_missing = fields.String(required=False, allow_none=True)
encoding = fields.String(required=False, allow_none=True)
is_first_line_header = fields.Boolean(
required=False, allow_none=True, missing=0, default=0)
is_multiline = fields.Boolean(
required=False,
allow_none=True,
missing=0,
default=0)
command = fields.String(required=False, allow_none=True)
is_lookup = fields.Boolean(
required=False,
allow_none=True,
missing=0,
default=0)
use_in_workflow = fields.Boolean(
required=False,
allow_none=True,
missing=0,
default=0)
attributes = fields.Nested(
'limonero.schema.AttributeItemResponseSchema',
allow_none=True,
many=True)
permissions = fields.Nested(
'limonero.schema.DataSourcePermissionItemResponseSchema',
allow_none=True,
many=True)
storage = fields.Nested(
'limonero.schema.StorageItemResponseSchema',
required=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of DataSource"""
return DataSource(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class DataSourcePrivacyResponseSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(required=True)
name = fields.String(required=True)
privacy_aware = fields.Boolean(
required=False,
allow_none=True,
missing=False,
default=False)
attributes = fields.Nested(
'limonero.schema.AttributePrivacyResponseSchema',
allow_none=True,
many=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of DataSource"""
return DataSource(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class DataSourcePermissionListResponseSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(required=True)
permission = fields.String(required=True,
validate=[OneOf(list(PermissionType.__dict__.keys()))])
user_id = fields.Integer(required=True)
user_login = fields.String(required=True)
user_name = fields.String(required=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of DataSourcePermission"""
return DataSourcePermission(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class DataSourcePermissionItemResponseSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(required=True)
permission = fields.String(required=True,
validate=[OneOf(list(PermissionType.__dict__.keys()))])
user_id = fields.Integer(required=True)
user_login = fields.String(required=True)
user_name = fields.String(required=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of DataSourcePermission"""
return DataSourcePermission(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class DataSourcePermissionCreateRequestSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(required=True)
permission = fields.String(required=True,
validate=[OneOf(list(PermissionType.__dict__.keys()))])
user_id = fields.Integer(required=True)
user_login = fields.String(required=True)
user_name = fields.String(required=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of DataSourcePermission"""
return DataSourcePermission(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class ModelListResponseSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(required=True)
name = fields.String(required=True)
enabled = fields.Boolean(
required=False,
allow_none=True,
missing=True,
default=True)
created = fields.DateTime(required=False, allow_none=True)
path = fields.String(required=True)
class_name = fields.String(required=True)
type = fields.String(required=False, allow_none=True, missing=ModelType.UNSPECIFIED, default=ModelType.UNSPECIFIED,
validate=[OneOf(list(ModelType.__dict__.keys()))])
deployment_status = fields.String(required=False, allow_none=True, missing=DeploymentStatus.NOT_DEPLOYED, default=DeploymentStatus.NOT_DEPLOYED,
validate=[OneOf(list(DeploymentStatus.__dict__.keys()))])
user_id = fields.Integer(required=True)
user_login = fields.String(required=True)
user_name = fields.String(required=True)
workflow_id = fields.Integer(required=False, allow_none=True)
workflow_name = fields.String(required=False, allow_none=True)
task_id = fields.String(required=False, allow_none=True)
job_id = fields.Integer(required=False, allow_none=True)
storage = fields.Nested(
'limonero.schema.StorageListResponseSchema',
required=True)
download_token = fields.Function(
lambda d: generate_download_token(d.id, 600))
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of Model"""
return Model(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class ModelCreateRequestSchema(BaseSchema):
""" JSON serialization schema """
name = fields.String(required=True)
enabled = fields.Boolean(
required=False,
allow_none=True,
missing=True,
default=True)
path = fields.String(required=True)
class_name = fields.String(required=True)
type = fields.String(required=False, allow_none=True, missing=ModelType.UNSPECIFIED, default=ModelType.UNSPECIFIED,
validate=[OneOf(list(ModelType.__dict__.keys()))])
deployment_status = fields.String(required=False, allow_none=True, missing=DeploymentStatus.NOT_DEPLOYED, default=DeploymentStatus.NOT_DEPLOYED,
validate=[OneOf(list(DeploymentStatus.__dict__.keys()))])
user_id = fields.Integer(required=True)
user_login = fields.String(required=True)
user_name = fields.String(required=True)
workflow_id = fields.Integer(required=False, allow_none=True)
workflow_name = fields.String(required=False, allow_none=True)
task_id = fields.String(required=False, allow_none=True)
job_id = fields.Integer(required=False, allow_none=True)
storage_id = fields.Integer(required=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of Model"""
return Model(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class ModelItemResponseSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(required=True)
name = fields.String(required=True)
enabled = fields.Boolean(
required=False,
allow_none=True,
missing=True,
default=True)
created = fields.DateTime(required=False, allow_none=True)
path = fields.String(required=True)
class_name = fields.String(required=True)
type = fields.String(required=False, allow_none=True, missing=ModelType.UNSPECIFIED, default=ModelType.UNSPECIFIED,
validate=[OneOf(list(ModelType.__dict__.keys()))])
deployment_status = fields.String(required=False, allow_none=True, missing=DeploymentStatus.NOT_DEPLOYED, default=DeploymentStatus.NOT_DEPLOYED,
validate=[OneOf(list(DeploymentStatus.__dict__.keys()))])
user_id = fields.Integer(required=True)
user_login = fields.String(required=True)
user_name = fields.String(required=True)
workflow_id = fields.Integer(required=False, allow_none=True)
workflow_name = fields.String(required=False, allow_none=True)
task_id = fields.String(required=False, allow_none=True)
job_id = fields.Integer(required=False, allow_none=True)
storage = fields.Nested(
'limonero.schema.StorageItemResponseSchema',
required=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of Model"""
return Model(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class ModelPermissionListResponseSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(required=True)
permission = fields.String(required=True,
validate=[OneOf(list(PermissionType.__dict__.keys()))])
user_id = fields.Integer(required=True)
user_login = fields.String(required=True)
user_name = fields.String(required=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of ModelPermission"""
return ModelPermission(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class ModelPermissionItemResponseSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(required=True)
permission = fields.String(required=True,
validate=[OneOf(list(PermissionType.__dict__.keys()))])
user_id = fields.Integer(required=True)
user_login = fields.String(required=True)
user_name = fields.String(required=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of ModelPermission"""
return ModelPermission(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class StorageListResponseSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(required=True)
name = fields.String(required=True)
type = fields.String(required=True,
validate=[OneOf(list(StorageType.__dict__.keys()))])
enabled = fields.Boolean(
required=False,
allow_none=True,
missing=True,
default=True)
url = fields.String(required=True)
client_url = fields.String(required=False, allow_none=True)
extra_params = fields.String(required=False, allow_none=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of Storage"""
return Storage(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class StorageItemResponseSchema(BaseSchema):
""" JSON serialization schema """
id = fields.Integer(required=True)
name = fields.String(required=True)
type = fields.String(required=True,
validate=[OneOf(list(StorageType.__dict__.keys()))])
enabled = fields.Boolean(
required=False,
allow_none=True,
missing=True,
default=True)
url = fields.String(required=True)
client_url = fields.String(required=False, allow_none=True)
extra_params = fields.String(required=False, allow_none=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of Storage"""
return Storage(**data)
class Meta:
ordered = True
unknown = EXCLUDE
class StorageCreateRequestSchema(BaseSchema):
""" JSON serialization schema """
name = fields.String(required=True)
type = fields.String(required=True,
validate=[OneOf(list(StorageType.__dict__.keys()))])
enabled = fields.Boolean(
required=False,
allow_none=True,
missing=True,
default=True)
url = fields.String(required=True)
client_url = fields.String(required=False, allow_none=True)
extra_params = fields.String(required=False, allow_none=True)
# noinspection PyUnresolvedReferences
@post_load
def make_object(self, data, **kwargs):
""" Deserialize data into an instance of Storage"""
return Storage(**data)
class Meta:
ordered = True
unknown = EXCLUDE
| 37.002762 | 159 | 0.677666 | 4,307 | 40,185 | 6.157883 | 0.057349 | 0.080084 | 0.115678 | 0.18332 | 0.910753 | 0.908755 | 0.907963 | 0.907963 | 0.906078 | 0.900535 | 0 | 0.00141 | 0.223342 | 40,185 | 1,085 | 160 | 37.036866 | 0.848382 | 0.078313 | 0 | 0.906924 | 0 | 0 | 0.021673 | 0.020691 | 0 | 0 | 0 | 0 | 0 | 1 | 0.036322 | false | 0 | 0.011351 | 0.001135 | 0.53916 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 9 |
52139b7b13caef6b61235dc05744f6fb1327b120 | 60,165 | py | Python | socialNetwork/gen-py/social_network/UserService.py | rodrigo-bruno/DeathStarBench | c9ce09aaf7c1298a7c88efacd1010a71db0fa59d | [
"Apache-2.0"
] | 364 | 2019-04-28T01:45:37.000Z | 2022-03-31T15:08:03.000Z | socialNetwork/gen-py/social_network/UserService.py | rodrigo-bruno/DeathStarBench | c9ce09aaf7c1298a7c88efacd1010a71db0fa59d | [
"Apache-2.0"
] | 111 | 2019-04-15T11:08:49.000Z | 2022-03-31T17:39:16.000Z | socialNetwork/gen-py/social_network/UserService.py | rodrigo-bruno/DeathStarBench | c9ce09aaf7c1298a7c88efacd1010a71db0fa59d | [
"Apache-2.0"
] | 229 | 2019-05-14T08:55:57.000Z | 2022-03-31T03:14:55.000Z | #
# Autogenerated by Thrift Compiler (0.12.0)
#
# DO NOT EDIT UNLESS YOU ARE SURE THAT YOU KNOW WHAT YOU ARE DOING
#
# options string: py
#
from thrift.Thrift import TType, TMessageType, TFrozenDict, TException, TApplicationException
from thrift.protocol.TProtocol import TProtocolException
from thrift.TRecursive import fix_spec
import sys
import logging
from .ttypes import *
from thrift.Thrift import TProcessor
from thrift.transport import TTransport
all_structs = []
class Iface(object):
def RegisterUser(self, req_id, first_name, last_name, username, password, carrier):
"""
Parameters:
- req_id
- first_name
- last_name
- username
- password
- carrier
"""
pass
def RegisterUserWithId(self, req_id, first_name, last_name, username, password, user_id, carrier):
"""
Parameters:
- req_id
- first_name
- last_name
- username
- password
- user_id
- carrier
"""
pass
def Login(self, req_id, username, password, carrier):
"""
Parameters:
- req_id
- username
- password
- carrier
"""
pass
def ComposeCreatorWithUserId(self, req_id, user_id, username, carrier):
"""
Parameters:
- req_id
- user_id
- username
- carrier
"""
pass
def ComposeCreatorWithUsername(self, req_id, username, carrier):
"""
Parameters:
- req_id
- username
- carrier
"""
pass
def GetUserId(self, req_id, username, carrier):
"""
Parameters:
- req_id
- username
- carrier
"""
pass
class Client(Iface):
def __init__(self, iprot, oprot=None):
self._iprot = self._oprot = iprot
if oprot is not None:
self._oprot = oprot
self._seqid = 0
def RegisterUser(self, req_id, first_name, last_name, username, password, carrier):
"""
Parameters:
- req_id
- first_name
- last_name
- username
- password
- carrier
"""
self.send_RegisterUser(req_id, first_name, last_name, username, password, carrier)
self.recv_RegisterUser()
def send_RegisterUser(self, req_id, first_name, last_name, username, password, carrier):
self._oprot.writeMessageBegin('RegisterUser', TMessageType.CALL, self._seqid)
args = RegisterUser_args()
args.req_id = req_id
args.first_name = first_name
args.last_name = last_name
args.username = username
args.password = password
args.carrier = carrier
args.write(self._oprot)
self._oprot.writeMessageEnd()
self._oprot.trans.flush()
def recv_RegisterUser(self):
iprot = self._iprot
(fname, mtype, rseqid) = iprot.readMessageBegin()
if mtype == TMessageType.EXCEPTION:
x = TApplicationException()
x.read(iprot)
iprot.readMessageEnd()
raise x
result = RegisterUser_result()
result.read(iprot)
iprot.readMessageEnd()
if result.se is not None:
raise result.se
return
def RegisterUserWithId(self, req_id, first_name, last_name, username, password, user_id, carrier):
"""
Parameters:
- req_id
- first_name
- last_name
- username
- password
- user_id
- carrier
"""
self.send_RegisterUserWithId(req_id, first_name, last_name, username, password, user_id, carrier)
self.recv_RegisterUserWithId()
def send_RegisterUserWithId(self, req_id, first_name, last_name, username, password, user_id, carrier):
self._oprot.writeMessageBegin('RegisterUserWithId', TMessageType.CALL, self._seqid)
args = RegisterUserWithId_args()
args.req_id = req_id
args.first_name = first_name
args.last_name = last_name
args.username = username
args.password = password
args.user_id = user_id
args.carrier = carrier
args.write(self._oprot)
self._oprot.writeMessageEnd()
self._oprot.trans.flush()
def recv_RegisterUserWithId(self):
iprot = self._iprot
(fname, mtype, rseqid) = iprot.readMessageBegin()
if mtype == TMessageType.EXCEPTION:
x = TApplicationException()
x.read(iprot)
iprot.readMessageEnd()
raise x
result = RegisterUserWithId_result()
result.read(iprot)
iprot.readMessageEnd()
if result.se is not None:
raise result.se
return
def Login(self, req_id, username, password, carrier):
"""
Parameters:
- req_id
- username
- password
- carrier
"""
self.send_Login(req_id, username, password, carrier)
return self.recv_Login()
def send_Login(self, req_id, username, password, carrier):
self._oprot.writeMessageBegin('Login', TMessageType.CALL, self._seqid)
args = Login_args()
args.req_id = req_id
args.username = username
args.password = password
args.carrier = carrier
args.write(self._oprot)
self._oprot.writeMessageEnd()
self._oprot.trans.flush()
def recv_Login(self):
iprot = self._iprot
(fname, mtype, rseqid) = iprot.readMessageBegin()
if mtype == TMessageType.EXCEPTION:
x = TApplicationException()
x.read(iprot)
iprot.readMessageEnd()
raise x
result = Login_result()
result.read(iprot)
iprot.readMessageEnd()
if result.success is not None:
return result.success
if result.se is not None:
raise result.se
raise TApplicationException(TApplicationException.MISSING_RESULT, "Login failed: unknown result")
def ComposeCreatorWithUserId(self, req_id, user_id, username, carrier):
"""
Parameters:
- req_id
- user_id
- username
- carrier
"""
self.send_ComposeCreatorWithUserId(req_id, user_id, username, carrier)
return self.recv_ComposeCreatorWithUserId()
def send_ComposeCreatorWithUserId(self, req_id, user_id, username, carrier):
self._oprot.writeMessageBegin('ComposeCreatorWithUserId', TMessageType.CALL, self._seqid)
args = ComposeCreatorWithUserId_args()
args.req_id = req_id
args.user_id = user_id
args.username = username
args.carrier = carrier
args.write(self._oprot)
self._oprot.writeMessageEnd()
self._oprot.trans.flush()
def recv_ComposeCreatorWithUserId(self):
iprot = self._iprot
(fname, mtype, rseqid) = iprot.readMessageBegin()
if mtype == TMessageType.EXCEPTION:
x = TApplicationException()
x.read(iprot)
iprot.readMessageEnd()
raise x
result = ComposeCreatorWithUserId_result()
result.read(iprot)
iprot.readMessageEnd()
if result.success is not None:
return result.success
if result.se is not None:
raise result.se
raise TApplicationException(TApplicationException.MISSING_RESULT, "ComposeCreatorWithUserId failed: unknown result")
def ComposeCreatorWithUsername(self, req_id, username, carrier):
"""
Parameters:
- req_id
- username
- carrier
"""
self.send_ComposeCreatorWithUsername(req_id, username, carrier)
return self.recv_ComposeCreatorWithUsername()
def send_ComposeCreatorWithUsername(self, req_id, username, carrier):
self._oprot.writeMessageBegin('ComposeCreatorWithUsername', TMessageType.CALL, self._seqid)
args = ComposeCreatorWithUsername_args()
args.req_id = req_id
args.username = username
args.carrier = carrier
args.write(self._oprot)
self._oprot.writeMessageEnd()
self._oprot.trans.flush()
def recv_ComposeCreatorWithUsername(self):
iprot = self._iprot
(fname, mtype, rseqid) = iprot.readMessageBegin()
if mtype == TMessageType.EXCEPTION:
x = TApplicationException()
x.read(iprot)
iprot.readMessageEnd()
raise x
result = ComposeCreatorWithUsername_result()
result.read(iprot)
iprot.readMessageEnd()
if result.success is not None:
return result.success
if result.se is not None:
raise result.se
raise TApplicationException(TApplicationException.MISSING_RESULT, "ComposeCreatorWithUsername failed: unknown result")
def GetUserId(self, req_id, username, carrier):
"""
Parameters:
- req_id
- username
- carrier
"""
self.send_GetUserId(req_id, username, carrier)
return self.recv_GetUserId()
def send_GetUserId(self, req_id, username, carrier):
self._oprot.writeMessageBegin('GetUserId', TMessageType.CALL, self._seqid)
args = GetUserId_args()
args.req_id = req_id
args.username = username
args.carrier = carrier
args.write(self._oprot)
self._oprot.writeMessageEnd()
self._oprot.trans.flush()
def recv_GetUserId(self):
iprot = self._iprot
(fname, mtype, rseqid) = iprot.readMessageBegin()
if mtype == TMessageType.EXCEPTION:
x = TApplicationException()
x.read(iprot)
iprot.readMessageEnd()
raise x
result = GetUserId_result()
result.read(iprot)
iprot.readMessageEnd()
if result.success is not None:
return result.success
if result.se is not None:
raise result.se
raise TApplicationException(TApplicationException.MISSING_RESULT, "GetUserId failed: unknown result")
class Processor(Iface, TProcessor):
def __init__(self, handler):
self._handler = handler
self._processMap = {}
self._processMap["RegisterUser"] = Processor.process_RegisterUser
self._processMap["RegisterUserWithId"] = Processor.process_RegisterUserWithId
self._processMap["Login"] = Processor.process_Login
self._processMap["ComposeCreatorWithUserId"] = Processor.process_ComposeCreatorWithUserId
self._processMap["ComposeCreatorWithUsername"] = Processor.process_ComposeCreatorWithUsername
self._processMap["GetUserId"] = Processor.process_GetUserId
def process(self, iprot, oprot):
(name, type, seqid) = iprot.readMessageBegin()
if name not in self._processMap:
iprot.skip(TType.STRUCT)
iprot.readMessageEnd()
x = TApplicationException(TApplicationException.UNKNOWN_METHOD, 'Unknown function %s' % (name))
oprot.writeMessageBegin(name, TMessageType.EXCEPTION, seqid)
x.write(oprot)
oprot.writeMessageEnd()
oprot.trans.flush()
return
else:
self._processMap[name](self, seqid, iprot, oprot)
return True
def process_RegisterUser(self, seqid, iprot, oprot):
args = RegisterUser_args()
args.read(iprot)
iprot.readMessageEnd()
result = RegisterUser_result()
try:
self._handler.RegisterUser(args.req_id, args.first_name, args.last_name, args.username, args.password, args.carrier)
msg_type = TMessageType.REPLY
except TTransport.TTransportException:
raise
except ServiceException as se:
msg_type = TMessageType.REPLY
result.se = se
except TApplicationException as ex:
logging.exception('TApplication exception in handler')
msg_type = TMessageType.EXCEPTION
result = ex
except Exception:
logging.exception('Unexpected exception in handler')
msg_type = TMessageType.EXCEPTION
result = TApplicationException(TApplicationException.INTERNAL_ERROR, 'Internal error')
oprot.writeMessageBegin("RegisterUser", msg_type, seqid)
result.write(oprot)
oprot.writeMessageEnd()
oprot.trans.flush()
def process_RegisterUserWithId(self, seqid, iprot, oprot):
args = RegisterUserWithId_args()
args.read(iprot)
iprot.readMessageEnd()
result = RegisterUserWithId_result()
try:
self._handler.RegisterUserWithId(args.req_id, args.first_name, args.last_name, args.username, args.password, args.user_id, args.carrier)
msg_type = TMessageType.REPLY
except TTransport.TTransportException:
raise
except ServiceException as se:
msg_type = TMessageType.REPLY
result.se = se
except TApplicationException as ex:
logging.exception('TApplication exception in handler')
msg_type = TMessageType.EXCEPTION
result = ex
except Exception:
logging.exception('Unexpected exception in handler')
msg_type = TMessageType.EXCEPTION
result = TApplicationException(TApplicationException.INTERNAL_ERROR, 'Internal error')
oprot.writeMessageBegin("RegisterUserWithId", msg_type, seqid)
result.write(oprot)
oprot.writeMessageEnd()
oprot.trans.flush()
def process_Login(self, seqid, iprot, oprot):
args = Login_args()
args.read(iprot)
iprot.readMessageEnd()
result = Login_result()
try:
result.success = self._handler.Login(args.req_id, args.username, args.password, args.carrier)
msg_type = TMessageType.REPLY
except TTransport.TTransportException:
raise
except ServiceException as se:
msg_type = TMessageType.REPLY
result.se = se
except TApplicationException as ex:
logging.exception('TApplication exception in handler')
msg_type = TMessageType.EXCEPTION
result = ex
except Exception:
logging.exception('Unexpected exception in handler')
msg_type = TMessageType.EXCEPTION
result = TApplicationException(TApplicationException.INTERNAL_ERROR, 'Internal error')
oprot.writeMessageBegin("Login", msg_type, seqid)
result.write(oprot)
oprot.writeMessageEnd()
oprot.trans.flush()
def process_ComposeCreatorWithUserId(self, seqid, iprot, oprot):
args = ComposeCreatorWithUserId_args()
args.read(iprot)
iprot.readMessageEnd()
result = ComposeCreatorWithUserId_result()
try:
result.success = self._handler.ComposeCreatorWithUserId(args.req_id, args.user_id, args.username, args.carrier)
msg_type = TMessageType.REPLY
except TTransport.TTransportException:
raise
except ServiceException as se:
msg_type = TMessageType.REPLY
result.se = se
except TApplicationException as ex:
logging.exception('TApplication exception in handler')
msg_type = TMessageType.EXCEPTION
result = ex
except Exception:
logging.exception('Unexpected exception in handler')
msg_type = TMessageType.EXCEPTION
result = TApplicationException(TApplicationException.INTERNAL_ERROR, 'Internal error')
oprot.writeMessageBegin("ComposeCreatorWithUserId", msg_type, seqid)
result.write(oprot)
oprot.writeMessageEnd()
oprot.trans.flush()
def process_ComposeCreatorWithUsername(self, seqid, iprot, oprot):
args = ComposeCreatorWithUsername_args()
args.read(iprot)
iprot.readMessageEnd()
result = ComposeCreatorWithUsername_result()
try:
result.success = self._handler.ComposeCreatorWithUsername(args.req_id, args.username, args.carrier)
msg_type = TMessageType.REPLY
except TTransport.TTransportException:
raise
except ServiceException as se:
msg_type = TMessageType.REPLY
result.se = se
except TApplicationException as ex:
logging.exception('TApplication exception in handler')
msg_type = TMessageType.EXCEPTION
result = ex
except Exception:
logging.exception('Unexpected exception in handler')
msg_type = TMessageType.EXCEPTION
result = TApplicationException(TApplicationException.INTERNAL_ERROR, 'Internal error')
oprot.writeMessageBegin("ComposeCreatorWithUsername", msg_type, seqid)
result.write(oprot)
oprot.writeMessageEnd()
oprot.trans.flush()
def process_GetUserId(self, seqid, iprot, oprot):
args = GetUserId_args()
args.read(iprot)
iprot.readMessageEnd()
result = GetUserId_result()
try:
result.success = self._handler.GetUserId(args.req_id, args.username, args.carrier)
msg_type = TMessageType.REPLY
except TTransport.TTransportException:
raise
except ServiceException as se:
msg_type = TMessageType.REPLY
result.se = se
except TApplicationException as ex:
logging.exception('TApplication exception in handler')
msg_type = TMessageType.EXCEPTION
result = ex
except Exception:
logging.exception('Unexpected exception in handler')
msg_type = TMessageType.EXCEPTION
result = TApplicationException(TApplicationException.INTERNAL_ERROR, 'Internal error')
oprot.writeMessageBegin("GetUserId", msg_type, seqid)
result.write(oprot)
oprot.writeMessageEnd()
oprot.trans.flush()
# HELPER FUNCTIONS AND STRUCTURES
class RegisterUser_args(object):
"""
Attributes:
- req_id
- first_name
- last_name
- username
- password
- carrier
"""
def __init__(self, req_id=None, first_name=None, last_name=None, username=None, password=None, carrier=None,):
self.req_id = req_id
self.first_name = first_name
self.last_name = last_name
self.username = username
self.password = password
self.carrier = carrier
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.I64:
self.req_id = iprot.readI64()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.STRING:
self.first_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 3:
if ftype == TType.STRING:
self.last_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 4:
if ftype == TType.STRING:
self.username = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 5:
if ftype == TType.STRING:
self.password = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 6:
if ftype == TType.MAP:
self.carrier = {}
(_ktype40, _vtype41, _size39) = iprot.readMapBegin()
for _i43 in range(_size39):
_key44 = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
_val45 = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
self.carrier[_key44] = _val45
iprot.readMapEnd()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('RegisterUser_args')
if self.req_id is not None:
oprot.writeFieldBegin('req_id', TType.I64, 1)
oprot.writeI64(self.req_id)
oprot.writeFieldEnd()
if self.first_name is not None:
oprot.writeFieldBegin('first_name', TType.STRING, 2)
oprot.writeString(self.first_name.encode('utf-8') if sys.version_info[0] == 2 else self.first_name)
oprot.writeFieldEnd()
if self.last_name is not None:
oprot.writeFieldBegin('last_name', TType.STRING, 3)
oprot.writeString(self.last_name.encode('utf-8') if sys.version_info[0] == 2 else self.last_name)
oprot.writeFieldEnd()
if self.username is not None:
oprot.writeFieldBegin('username', TType.STRING, 4)
oprot.writeString(self.username.encode('utf-8') if sys.version_info[0] == 2 else self.username)
oprot.writeFieldEnd()
if self.password is not None:
oprot.writeFieldBegin('password', TType.STRING, 5)
oprot.writeString(self.password.encode('utf-8') if sys.version_info[0] == 2 else self.password)
oprot.writeFieldEnd()
if self.carrier is not None:
oprot.writeFieldBegin('carrier', TType.MAP, 6)
oprot.writeMapBegin(TType.STRING, TType.STRING, len(self.carrier))
for kiter46, viter47 in self.carrier.items():
oprot.writeString(kiter46.encode('utf-8') if sys.version_info[0] == 2 else kiter46)
oprot.writeString(viter47.encode('utf-8') if sys.version_info[0] == 2 else viter47)
oprot.writeMapEnd()
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
all_structs.append(RegisterUser_args)
RegisterUser_args.thrift_spec = (
None, # 0
(1, TType.I64, 'req_id', None, None, ), # 1
(2, TType.STRING, 'first_name', 'UTF8', None, ), # 2
(3, TType.STRING, 'last_name', 'UTF8', None, ), # 3
(4, TType.STRING, 'username', 'UTF8', None, ), # 4
(5, TType.STRING, 'password', 'UTF8', None, ), # 5
(6, TType.MAP, 'carrier', (TType.STRING, 'UTF8', TType.STRING, 'UTF8', False), None, ), # 6
)
class RegisterUser_result(object):
"""
Attributes:
- se
"""
def __init__(self, se=None,):
self.se = se
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRUCT:
self.se = ServiceException()
self.se.read(iprot)
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('RegisterUser_result')
if self.se is not None:
oprot.writeFieldBegin('se', TType.STRUCT, 1)
self.se.write(oprot)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
all_structs.append(RegisterUser_result)
RegisterUser_result.thrift_spec = (
None, # 0
(1, TType.STRUCT, 'se', [ServiceException, None], None, ), # 1
)
class RegisterUserWithId_args(object):
"""
Attributes:
- req_id
- first_name
- last_name
- username
- password
- user_id
- carrier
"""
def __init__(self, req_id=None, first_name=None, last_name=None, username=None, password=None, user_id=None, carrier=None,):
self.req_id = req_id
self.first_name = first_name
self.last_name = last_name
self.username = username
self.password = password
self.user_id = user_id
self.carrier = carrier
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.I64:
self.req_id = iprot.readI64()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.STRING:
self.first_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 3:
if ftype == TType.STRING:
self.last_name = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 4:
if ftype == TType.STRING:
self.username = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 5:
if ftype == TType.STRING:
self.password = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 6:
if ftype == TType.I64:
self.user_id = iprot.readI64()
else:
iprot.skip(ftype)
elif fid == 7:
if ftype == TType.MAP:
self.carrier = {}
(_ktype49, _vtype50, _size48) = iprot.readMapBegin()
for _i52 in range(_size48):
_key53 = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
_val54 = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
self.carrier[_key53] = _val54
iprot.readMapEnd()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('RegisterUserWithId_args')
if self.req_id is not None:
oprot.writeFieldBegin('req_id', TType.I64, 1)
oprot.writeI64(self.req_id)
oprot.writeFieldEnd()
if self.first_name is not None:
oprot.writeFieldBegin('first_name', TType.STRING, 2)
oprot.writeString(self.first_name.encode('utf-8') if sys.version_info[0] == 2 else self.first_name)
oprot.writeFieldEnd()
if self.last_name is not None:
oprot.writeFieldBegin('last_name', TType.STRING, 3)
oprot.writeString(self.last_name.encode('utf-8') if sys.version_info[0] == 2 else self.last_name)
oprot.writeFieldEnd()
if self.username is not None:
oprot.writeFieldBegin('username', TType.STRING, 4)
oprot.writeString(self.username.encode('utf-8') if sys.version_info[0] == 2 else self.username)
oprot.writeFieldEnd()
if self.password is not None:
oprot.writeFieldBegin('password', TType.STRING, 5)
oprot.writeString(self.password.encode('utf-8') if sys.version_info[0] == 2 else self.password)
oprot.writeFieldEnd()
if self.user_id is not None:
oprot.writeFieldBegin('user_id', TType.I64, 6)
oprot.writeI64(self.user_id)
oprot.writeFieldEnd()
if self.carrier is not None:
oprot.writeFieldBegin('carrier', TType.MAP, 7)
oprot.writeMapBegin(TType.STRING, TType.STRING, len(self.carrier))
for kiter55, viter56 in self.carrier.items():
oprot.writeString(kiter55.encode('utf-8') if sys.version_info[0] == 2 else kiter55)
oprot.writeString(viter56.encode('utf-8') if sys.version_info[0] == 2 else viter56)
oprot.writeMapEnd()
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
all_structs.append(RegisterUserWithId_args)
RegisterUserWithId_args.thrift_spec = (
None, # 0
(1, TType.I64, 'req_id', None, None, ), # 1
(2, TType.STRING, 'first_name', 'UTF8', None, ), # 2
(3, TType.STRING, 'last_name', 'UTF8', None, ), # 3
(4, TType.STRING, 'username', 'UTF8', None, ), # 4
(5, TType.STRING, 'password', 'UTF8', None, ), # 5
(6, TType.I64, 'user_id', None, None, ), # 6
(7, TType.MAP, 'carrier', (TType.STRING, 'UTF8', TType.STRING, 'UTF8', False), None, ), # 7
)
class RegisterUserWithId_result(object):
"""
Attributes:
- se
"""
def __init__(self, se=None,):
self.se = se
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.STRUCT:
self.se = ServiceException()
self.se.read(iprot)
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('RegisterUserWithId_result')
if self.se is not None:
oprot.writeFieldBegin('se', TType.STRUCT, 1)
self.se.write(oprot)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
all_structs.append(RegisterUserWithId_result)
RegisterUserWithId_result.thrift_spec = (
None, # 0
(1, TType.STRUCT, 'se', [ServiceException, None], None, ), # 1
)
class Login_args(object):
"""
Attributes:
- req_id
- username
- password
- carrier
"""
def __init__(self, req_id=None, username=None, password=None, carrier=None,):
self.req_id = req_id
self.username = username
self.password = password
self.carrier = carrier
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.I64:
self.req_id = iprot.readI64()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.STRING:
self.username = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 3:
if ftype == TType.STRING:
self.password = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 4:
if ftype == TType.MAP:
self.carrier = {}
(_ktype58, _vtype59, _size57) = iprot.readMapBegin()
for _i61 in range(_size57):
_key62 = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
_val63 = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
self.carrier[_key62] = _val63
iprot.readMapEnd()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('Login_args')
if self.req_id is not None:
oprot.writeFieldBegin('req_id', TType.I64, 1)
oprot.writeI64(self.req_id)
oprot.writeFieldEnd()
if self.username is not None:
oprot.writeFieldBegin('username', TType.STRING, 2)
oprot.writeString(self.username.encode('utf-8') if sys.version_info[0] == 2 else self.username)
oprot.writeFieldEnd()
if self.password is not None:
oprot.writeFieldBegin('password', TType.STRING, 3)
oprot.writeString(self.password.encode('utf-8') if sys.version_info[0] == 2 else self.password)
oprot.writeFieldEnd()
if self.carrier is not None:
oprot.writeFieldBegin('carrier', TType.MAP, 4)
oprot.writeMapBegin(TType.STRING, TType.STRING, len(self.carrier))
for kiter64, viter65 in self.carrier.items():
oprot.writeString(kiter64.encode('utf-8') if sys.version_info[0] == 2 else kiter64)
oprot.writeString(viter65.encode('utf-8') if sys.version_info[0] == 2 else viter65)
oprot.writeMapEnd()
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
all_structs.append(Login_args)
Login_args.thrift_spec = (
None, # 0
(1, TType.I64, 'req_id', None, None, ), # 1
(2, TType.STRING, 'username', 'UTF8', None, ), # 2
(3, TType.STRING, 'password', 'UTF8', None, ), # 3
(4, TType.MAP, 'carrier', (TType.STRING, 'UTF8', TType.STRING, 'UTF8', False), None, ), # 4
)
class Login_result(object):
"""
Attributes:
- success
- se
"""
def __init__(self, success=None, se=None,):
self.success = success
self.se = se
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 0:
if ftype == TType.STRING:
self.success = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 1:
if ftype == TType.STRUCT:
self.se = ServiceException()
self.se.read(iprot)
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('Login_result')
if self.success is not None:
oprot.writeFieldBegin('success', TType.STRING, 0)
oprot.writeString(self.success.encode('utf-8') if sys.version_info[0] == 2 else self.success)
oprot.writeFieldEnd()
if self.se is not None:
oprot.writeFieldBegin('se', TType.STRUCT, 1)
self.se.write(oprot)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
all_structs.append(Login_result)
Login_result.thrift_spec = (
(0, TType.STRING, 'success', 'UTF8', None, ), # 0
(1, TType.STRUCT, 'se', [ServiceException, None], None, ), # 1
)
class ComposeCreatorWithUserId_args(object):
"""
Attributes:
- req_id
- user_id
- username
- carrier
"""
def __init__(self, req_id=None, user_id=None, username=None, carrier=None,):
self.req_id = req_id
self.user_id = user_id
self.username = username
self.carrier = carrier
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.I64:
self.req_id = iprot.readI64()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.I64:
self.user_id = iprot.readI64()
else:
iprot.skip(ftype)
elif fid == 3:
if ftype == TType.STRING:
self.username = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 4:
if ftype == TType.MAP:
self.carrier = {}
(_ktype67, _vtype68, _size66) = iprot.readMapBegin()
for _i70 in range(_size66):
_key71 = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
_val72 = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
self.carrier[_key71] = _val72
iprot.readMapEnd()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('ComposeCreatorWithUserId_args')
if self.req_id is not None:
oprot.writeFieldBegin('req_id', TType.I64, 1)
oprot.writeI64(self.req_id)
oprot.writeFieldEnd()
if self.user_id is not None:
oprot.writeFieldBegin('user_id', TType.I64, 2)
oprot.writeI64(self.user_id)
oprot.writeFieldEnd()
if self.username is not None:
oprot.writeFieldBegin('username', TType.STRING, 3)
oprot.writeString(self.username.encode('utf-8') if sys.version_info[0] == 2 else self.username)
oprot.writeFieldEnd()
if self.carrier is not None:
oprot.writeFieldBegin('carrier', TType.MAP, 4)
oprot.writeMapBegin(TType.STRING, TType.STRING, len(self.carrier))
for kiter73, viter74 in self.carrier.items():
oprot.writeString(kiter73.encode('utf-8') if sys.version_info[0] == 2 else kiter73)
oprot.writeString(viter74.encode('utf-8') if sys.version_info[0] == 2 else viter74)
oprot.writeMapEnd()
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
all_structs.append(ComposeCreatorWithUserId_args)
ComposeCreatorWithUserId_args.thrift_spec = (
None, # 0
(1, TType.I64, 'req_id', None, None, ), # 1
(2, TType.I64, 'user_id', None, None, ), # 2
(3, TType.STRING, 'username', 'UTF8', None, ), # 3
(4, TType.MAP, 'carrier', (TType.STRING, 'UTF8', TType.STRING, 'UTF8', False), None, ), # 4
)
class ComposeCreatorWithUserId_result(object):
"""
Attributes:
- success
- se
"""
def __init__(self, success=None, se=None,):
self.success = success
self.se = se
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 0:
if ftype == TType.STRUCT:
self.success = Creator()
self.success.read(iprot)
else:
iprot.skip(ftype)
elif fid == 1:
if ftype == TType.STRUCT:
self.se = ServiceException()
self.se.read(iprot)
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('ComposeCreatorWithUserId_result')
if self.success is not None:
oprot.writeFieldBegin('success', TType.STRUCT, 0)
self.success.write(oprot)
oprot.writeFieldEnd()
if self.se is not None:
oprot.writeFieldBegin('se', TType.STRUCT, 1)
self.se.write(oprot)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
all_structs.append(ComposeCreatorWithUserId_result)
ComposeCreatorWithUserId_result.thrift_spec = (
(0, TType.STRUCT, 'success', [Creator, None], None, ), # 0
(1, TType.STRUCT, 'se', [ServiceException, None], None, ), # 1
)
class ComposeCreatorWithUsername_args(object):
"""
Attributes:
- req_id
- username
- carrier
"""
def __init__(self, req_id=None, username=None, carrier=None,):
self.req_id = req_id
self.username = username
self.carrier = carrier
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.I64:
self.req_id = iprot.readI64()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.STRING:
self.username = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 3:
if ftype == TType.MAP:
self.carrier = {}
(_ktype76, _vtype77, _size75) = iprot.readMapBegin()
for _i79 in range(_size75):
_key80 = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
_val81 = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
self.carrier[_key80] = _val81
iprot.readMapEnd()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('ComposeCreatorWithUsername_args')
if self.req_id is not None:
oprot.writeFieldBegin('req_id', TType.I64, 1)
oprot.writeI64(self.req_id)
oprot.writeFieldEnd()
if self.username is not None:
oprot.writeFieldBegin('username', TType.STRING, 2)
oprot.writeString(self.username.encode('utf-8') if sys.version_info[0] == 2 else self.username)
oprot.writeFieldEnd()
if self.carrier is not None:
oprot.writeFieldBegin('carrier', TType.MAP, 3)
oprot.writeMapBegin(TType.STRING, TType.STRING, len(self.carrier))
for kiter82, viter83 in self.carrier.items():
oprot.writeString(kiter82.encode('utf-8') if sys.version_info[0] == 2 else kiter82)
oprot.writeString(viter83.encode('utf-8') if sys.version_info[0] == 2 else viter83)
oprot.writeMapEnd()
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
all_structs.append(ComposeCreatorWithUsername_args)
ComposeCreatorWithUsername_args.thrift_spec = (
None, # 0
(1, TType.I64, 'req_id', None, None, ), # 1
(2, TType.STRING, 'username', 'UTF8', None, ), # 2
(3, TType.MAP, 'carrier', (TType.STRING, 'UTF8', TType.STRING, 'UTF8', False), None, ), # 3
)
class ComposeCreatorWithUsername_result(object):
"""
Attributes:
- success
- se
"""
def __init__(self, success=None, se=None,):
self.success = success
self.se = se
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 0:
if ftype == TType.STRUCT:
self.success = Creator()
self.success.read(iprot)
else:
iprot.skip(ftype)
elif fid == 1:
if ftype == TType.STRUCT:
self.se = ServiceException()
self.se.read(iprot)
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('ComposeCreatorWithUsername_result')
if self.success is not None:
oprot.writeFieldBegin('success', TType.STRUCT, 0)
self.success.write(oprot)
oprot.writeFieldEnd()
if self.se is not None:
oprot.writeFieldBegin('se', TType.STRUCT, 1)
self.se.write(oprot)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
all_structs.append(ComposeCreatorWithUsername_result)
ComposeCreatorWithUsername_result.thrift_spec = (
(0, TType.STRUCT, 'success', [Creator, None], None, ), # 0
(1, TType.STRUCT, 'se', [ServiceException, None], None, ), # 1
)
class GetUserId_args(object):
"""
Attributes:
- req_id
- username
- carrier
"""
def __init__(self, req_id=None, username=None, carrier=None,):
self.req_id = req_id
self.username = username
self.carrier = carrier
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 1:
if ftype == TType.I64:
self.req_id = iprot.readI64()
else:
iprot.skip(ftype)
elif fid == 2:
if ftype == TType.STRING:
self.username = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
else:
iprot.skip(ftype)
elif fid == 3:
if ftype == TType.MAP:
self.carrier = {}
(_ktype85, _vtype86, _size84) = iprot.readMapBegin()
for _i88 in range(_size84):
_key89 = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
_val90 = iprot.readString().decode('utf-8') if sys.version_info[0] == 2 else iprot.readString()
self.carrier[_key89] = _val90
iprot.readMapEnd()
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('GetUserId_args')
if self.req_id is not None:
oprot.writeFieldBegin('req_id', TType.I64, 1)
oprot.writeI64(self.req_id)
oprot.writeFieldEnd()
if self.username is not None:
oprot.writeFieldBegin('username', TType.STRING, 2)
oprot.writeString(self.username.encode('utf-8') if sys.version_info[0] == 2 else self.username)
oprot.writeFieldEnd()
if self.carrier is not None:
oprot.writeFieldBegin('carrier', TType.MAP, 3)
oprot.writeMapBegin(TType.STRING, TType.STRING, len(self.carrier))
for kiter91, viter92 in self.carrier.items():
oprot.writeString(kiter91.encode('utf-8') if sys.version_info[0] == 2 else kiter91)
oprot.writeString(viter92.encode('utf-8') if sys.version_info[0] == 2 else viter92)
oprot.writeMapEnd()
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
all_structs.append(GetUserId_args)
GetUserId_args.thrift_spec = (
None, # 0
(1, TType.I64, 'req_id', None, None, ), # 1
(2, TType.STRING, 'username', 'UTF8', None, ), # 2
(3, TType.MAP, 'carrier', (TType.STRING, 'UTF8', TType.STRING, 'UTF8', False), None, ), # 3
)
class GetUserId_result(object):
"""
Attributes:
- success
- se
"""
def __init__(self, success=None, se=None,):
self.success = success
self.se = se
def read(self, iprot):
if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None:
iprot._fast_decode(self, iprot, [self.__class__, self.thrift_spec])
return
iprot.readStructBegin()
while True:
(fname, ftype, fid) = iprot.readFieldBegin()
if ftype == TType.STOP:
break
if fid == 0:
if ftype == TType.I64:
self.success = iprot.readI64()
else:
iprot.skip(ftype)
elif fid == 1:
if ftype == TType.STRUCT:
self.se = ServiceException()
self.se.read(iprot)
else:
iprot.skip(ftype)
else:
iprot.skip(ftype)
iprot.readFieldEnd()
iprot.readStructEnd()
def write(self, oprot):
if oprot._fast_encode is not None and self.thrift_spec is not None:
oprot.trans.write(oprot._fast_encode(self, [self.__class__, self.thrift_spec]))
return
oprot.writeStructBegin('GetUserId_result')
if self.success is not None:
oprot.writeFieldBegin('success', TType.I64, 0)
oprot.writeI64(self.success)
oprot.writeFieldEnd()
if self.se is not None:
oprot.writeFieldBegin('se', TType.STRUCT, 1)
self.se.write(oprot)
oprot.writeFieldEnd()
oprot.writeFieldStop()
oprot.writeStructEnd()
def validate(self):
return
def __repr__(self):
L = ['%s=%r' % (key, value)
for key, value in self.__dict__.items()]
return '%s(%s)' % (self.__class__.__name__, ', '.join(L))
def __eq__(self, other):
return isinstance(other, self.__class__) and self.__dict__ == other.__dict__
def __ne__(self, other):
return not (self == other)
all_structs.append(GetUserId_result)
GetUserId_result.thrift_spec = (
(0, TType.I64, 'success', None, None, ), # 0
(1, TType.STRUCT, 'se', [ServiceException, None], None, ), # 1
)
fix_spec(all_structs)
del all_structs
| 36.775672 | 148 | 0.581368 | 6,431 | 60,165 | 5.238688 | 0.036542 | 0.016029 | 0.025646 | 0.013891 | 0.881092 | 0.866637 | 0.847225 | 0.834402 | 0.829475 | 0.825913 | 0 | 0.014831 | 0.313039 | 60,165 | 1,635 | 149 | 36.798165 | 0.800295 | 0.025713 | 0 | 0.826563 | 1 | 0 | 0.038067 | 0.006469 | 0 | 0 | 0 | 0 | 0 | 1 | 0.091406 | false | 0.035156 | 0.00625 | 0.028125 | 0.175 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
525656edf5262b1bb430a084e763a49e90eafe72 | 8,392 | py | Python | design_bench/oracles/feature_extractors/feature_extractor.py | brandontrabucco/design_bench | 824516ec59396aded3ca55ec7c1c313626ecaceb | [
"MIT"
] | 27 | 2020-06-30T00:57:12.000Z | 2022-03-25T16:24:11.000Z | design_bench/oracles/feature_extractors/feature_extractor.py | brandontrabucco/design_bench | 824516ec59396aded3ca55ec7c1c313626ecaceb | [
"MIT"
] | 7 | 2021-02-16T06:25:02.000Z | 2022-03-31T17:21:17.000Z | design_bench/oracles/feature_extractors/feature_extractor.py | brandontrabucco/design_bench | 824516ec59396aded3ca55ec7c1c313626ecaceb | [
"MIT"
] | 5 | 2021-07-19T12:16:32.000Z | 2022-03-01T16:56:16.000Z | import abc
class FeatureExtractor(abc.ABC):
"""An abstract class for managing transformations applied to model-based
optimization datasets when constructing the oracle; for example, if the
oracle is intended to learn from molecule fingerprints
max_x { y = f(x) }
Public Methods:
dataset_to_oracle_x(np.ndarray) -> np.ndarray
Helper function for converting from designs contained in the
dataset format into a format the oracle is expecting to process,
such as from integers to logits of a categorical distribution
dataset_to_oracle_y(np.ndarray) -> np.ndarray
Helper function for converting from predictions contained in the
dataset format into a format the oracle is expecting to process,
such as from normalized to denormalized predictions
oracle_to_dataset_x(np.ndarray) -> np.ndarray
Helper function for converting from designs in the format of the
oracle into the design format the dataset contains, such as
from categorical logits to integers
oracle_to_dataset_y(np.ndarray) -> np.ndarray
Helper function for converting from predictions in the
format of the oracle into a format the dataset contains,
such as from normalized to denormalized predictions
"""
name = "feature_extractor"
@abc.abstractmethod
def dataset_to_oracle_x(self, x_batch, dataset):
"""Helper function for converting from designs contained in the
dataset format into a format the oracle is expecting to process,
such as from integers to logits of a categorical distribution
Arguments:
x_batch: np.ndarray
a batch of design values 'x' that will be given as input to the
oracle model in order to obtain a prediction value 'y' for
each 'x' which is then returned
dataset: DatasetBuilder
an instance of a subclass of the DatasetBuilder class representing
the source of the batch, must be provided
Returns:
x_batch: np.ndarray
a batch of design values 'x' that have been converted from the
format of designs contained in the dataset to the format
expected by the oracle score function
"""
raise NotImplementedError("cannot run base class")
@abc.abstractmethod
def dataset_to_oracle_y(self, y_batch, dataset):
"""Helper function for converting from predictions contained in the
dataset format into a format the oracle is expecting to process,
such as from normalized to denormalized predictions
Arguments:
y_batch: np.ndarray
a batch of prediction values 'y' that are from the dataset and
will be processed into a format expected by the oracle score
function, which is useful when training the oracle
dataset: DatasetBuilder
an instance of a subclass of the DatasetBuilder class representing
the source of the batch, must be provided
Returns:
y_batch: np.ndarray
a batch of prediction values 'y' that have been converted from
the format of predictions contained in the dataset to the
format expected by the oracle score function
"""
raise NotImplementedError("cannot run base class")
@abc.abstractmethod
def oracle_to_dataset_x(self, x_batch, dataset):
"""Helper function for converting from designs in the format of the
oracle into the design format the dataset contains, such as
from categorical logits to integers
Arguments:
x_batch: np.ndarray
a batch of design values 'x' that have been converted from
the format of designs contained in the dataset to the
format expected by the oracle score function
dataset: DatasetBuilder
an instance of a subclass of the DatasetBuilder class representing
the source of the batch, must be provided
Returns:
x_batch: np.ndarray
a batch of design values 'x' that have been converted from
the format of the oracle to the format of designs
contained in the dataset
"""
raise NotImplementedError("cannot run base class")
@abc.abstractmethod
def oracle_to_dataset_y(self, y_batch, dataset):
"""Helper function for converting from predictions in the format
of the oracle into a format the dataset contains, such as
from normalized to denormalized predictions
Arguments:
y_batch: np.ndarray
a batch of prediction values 'y' that have been converted from
the format of predictions contained in the dataset to the
format expected by the oracle score function
dataset: DatasetBuilder
an instance of a subclass of the DatasetBuilder class representing
the source of the batch, must be provided
Returns:
y_batch: np.ndarray
a batch of prediction values 'y' that have been converted from
the format of the oracle to the format of predictions
contained in the dataset
"""
raise NotImplementedError("cannot run base class")
@abc.abstractmethod
def input_shape(self, dataset):
"""Helper function for converting from predictions in the format
of the oracle into a format the dataset contains, such as
from normalized to denormalized predictions
Arguments:
dataset: DatasetBuilder
an instance of a subclass of the DatasetBuilder class representing
the source of the batch, must be provided
Returns:
input_shape: List[int]
the shape of input tensors that were sampled from the dataset and
are transformed into features using subclasses of this class
"""
raise NotImplementedError("cannot run base class")
@abc.abstractmethod
def input_dtype(self, dataset):
"""Helper function that returns the data type of the features returned
by running the feature extractor from dataset to oracle
Arguments:
dataset: DatasetBuilder
an instance of a subclass of the DatasetBuilder class representing
the source of the batch, must be provided
Returns:
input_dtype: List[int]
the type of input tensors that were sampled from the dataset and
are transformed into features using subclasses of this class
"""
raise NotImplementedError("cannot run base class")
@abc.abstractmethod
def is_discrete(self, dataset):
"""Helper function that specifies whether the transformation applied
by the feature extractor returns a discrete or continuous set of
features, which is required for building predictive models
Arguments:
dataset: DatasetBuilder
an instance of a subclass of the DatasetBuilder class representing
the source of the batch, must be provided
Returns:
is_discrete: bool
a boolean that indicates whether the dataset has been transformed
into a discrete or continuous representation
"""
raise NotImplementedError("cannot run base class")
@abc.abstractmethod
def num_classes(self, dataset):
"""Helper function for determining the number of classes in the discrete
representation intended for the oracle, if it is discrete, otherwise
this function may not be implemented and will raise an error
Arguments:
dataset: DatasetBuilder
an instance of a subclass of the DatasetBuilder class representing
the source of the batch, must be provided
Returns:
num_classes: int
the number of classes in the discrete representation for the model
based optimization dataset used for training the oracle
"""
raise NotImplementedError("cannot run base class")
| 36.329004 | 81 | 0.654075 | 1,039 | 8,392 | 5.238691 | 0.141482 | 0.022047 | 0.026272 | 0.038582 | 0.806357 | 0.789822 | 0.772919 | 0.765938 | 0.746096 | 0.734705 | 0 | 0 | 0.314109 | 8,392 | 230 | 82 | 36.486957 | 0.945622 | 0.711034 | 0 | 0.592593 | 0 | 0 | 0.155332 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.296296 | false | 0 | 0.037037 | 0 | 0.407407 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
5e4df04ad40401ba698b908ddf0ce77a96fe8c0f | 26,783 | py | Python | GradientDescentMethods.py | bbdamodaran/RFF_PCA | 33b7af8ca15c850fb6df44ea66c8656ff2132d2f | [
"MIT"
] | null | null | null | GradientDescentMethods.py | bbdamodaran/RFF_PCA | 33b7af8ca15c850fb6df44ea66c8656ff2132d2f | [
"MIT"
] | null | null | null | GradientDescentMethods.py | bbdamodaran/RFF_PCA | 33b7af8ca15c850fb6df44ea66c8656ff2132d2f | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
"""
Created on Thu Jun 30 14:22:25 2016
@author: damodara
minimization by
Gradient descent method
"""
def Gradientdescent(SubsetData, W2,wnn,alphaN, RegW,gamma, K=None, update_b=True, philippe_update=False):
import numpy as np
from grad import gradcoswx1coswx2, Lossfunction2,gradcoswx1coswx2WithOutLoop
import time
import copy
err2=2
tol =1e-10
WTMP = wnn
woldnn = wnn
gradnorm=[]
loss =[]
intloss=[]
display = False
it=0
max_iter = 150
Ncheck =50
beta = np.zeros((max_iter,1))
sigma_inv2 = 2*gamma
intloss = np.zeros((max_iter,1))
loss = np.zeros((max_iter,1))
while(it<max_iter):
# randomNoise = np.random.normal(0, 1,1)
randomNoise = 0.0
r,s = np.shape(W2)
if (s==1):
# intloss.append(Lossfunction2(SubsetData,wnn,gamma,K))
intloss[it] =Lossfunction2(SubsetData,wnn,gamma,K)
else:
# intloss.append(Lossfunction2(SubsetData,W2,gamma,K, wnn))
intloss[it] =Lossfunction2(SubsetData,W2,gamma,K, wnn)
if update_b:
lw = len(wnn)
intloss[it] = intloss[it]+RegW*np.sum(np.square(wnn[0:lw-1]))
else:
intloss[it] = intloss[it]+RegW*np.sum(np.square(wnn))
if display:
print('Initial Loss =', intloss[it])
if (it==0):
old_loss = intloss[0]
if (it == Ncheck):
old_loss = intloss[0]
min_index = np.argmin(loss[0:Ncheck])
alphaN = beta[np.abs(min_index-1)]
if display:
print('min_index', min_index)
print('alp', alphaN)
print('min_loss', loss[min_index])
if (it<Ncheck):
old_loss =0.0
#np.random.shuffle(SubsetData)
GNew = gradcoswx1coswx2WithOutLoop(SubsetData,W2,wnn,gamma, K)
GNew1 = GNew+randomNoise
GNew = (RegW * wnn)+GNew1
if update_b:
GNew[-1] = GNew1[-1].copy()
#gradnorm.append(np.linalg.norm(GNew))
# alpha = alphaN*np.sqrt(100/(100+ita))
if it>=Ncheck:
alpha = alphaN/(1+(alphaN*RegW*it))
else:
alpha = alphaN
wnew = wnn - (alpha)*(GNew)
if philippe_update:
if update_b:
wnew[0:len(wnew)-1] = wnew[0:len(wnew)-1]*(sigma_inv2/np.std(wnew[0:len(wnew)-1]))
wnew[len(wnew)-1] = wnew[len(wnew)-1]/(2*np.pi)
else:
wnew = wnew*(sigma_inv2/np.std(wnew))
WTMP = np.concatenate((WTMP, wnn), axis =1)
iternorm2 = np.linalg.norm(wnn)
if display:
print('Learning rate is=', alpha)
r,s = np.shape(W2)
if (s==1):
# loss.append(Lossfunction2(SubsetData,wnew,gamma,K))
loss[it]=Lossfunction2(SubsetData,wnew,gamma,K)
else:
# loss.append(Lossfunction2(SubsetData,W2,gamma,K, wnew))
loss[it]= Lossfunction2(SubsetData,W2,gamma,K, wnew)
if update_b:
lw = len(wnew)
loss[it] = loss[it]+RegW*np.sum(np.square(wnew[0:lw-1]))
else:
loss[it] = loss[it]+RegW*np.sum(np.square(wnew))
new_loss =loss[it]
if display:
print('Loss is' , new_loss)
time.sleep(0.7)
print('Old Loss is', old_loss)
if new_loss<old_loss:
wnn = np.copy(wnew)
old_loss = np.copy(new_loss)
if display:
print('update')
else:
alphaN = alphaN*0.7
beta[it]= np.copy(alphaN)
err2=np.linalg.norm(woldnn-wnn)
# print('The error2 is', err2)
if (err2<=tol) and (it>=75):
if display:
print('done')
break
if (it>250):
# print('break')
break
woldnn=np.copy(wnn)
it=it+1
if display:
print('over')
print('==========================')
return wnn, loss
def NaturalGradientdescent(SubsetData, W2,wnn, alphaN, RegW,sigma, K=None):
import numpy as np
from grad import gradcoswx1coswx2, Lossfunction2
err2=2
tol =1e-5
WTMP = wnn
woldnn = wnn
gradnorm=[]
loss =[]
it=0
while(err2>tol):
#np.random.shuffle(SubsetData)
r,s = np.shape(W2)
if (s==1):
loss.append(Lossfunction2(SubsetData,wnn,sigma,K))
else:
loss.append(Lossfunction2(SubsetData,W2,sigma,K, wnn))
print('Loss is', loss[it])
GNew = gradcoswx1coswx2(SubsetData,W2,wnn,sigma, K)
FM = np.dot(GNew, GNew.T)+0.001
alpha = alphaN /(1+(alphaN*RegW*it))
wnn = wnn- (alpha)* (np.dot(np.linalg.inv(FM), GNew))
WTMP = np.concatenate((WTMP, wnn), axis =1)
iternorm2 = np.linalg.norm(wnn)
err2=np.linalg.norm(woldnn-wnn)
# print('The error2 is', err2)
if (err2<=tol):
# print('done')
break
elif (it>250):
# print('break')
break
woldnn=wnn
it=it+1
return wnn, loss
def BoldDrive(SubsetData, W2,wnn, alphaN, RegW,sigma, K=None):
import numpy as np
from grad import gradcoswx1coswx2, Lossfunction2
err2=2
tol =1e-5
WTMP = wnn
woldnn = wnn
gradnorm=[]
loss =[]
it=0
while(err2>tol):
#np.random.shuffle(SubsetData)
r,s = np.shape(W2)
if (s==1):
loss.append(Lossfunction2(SubsetData,wnn,sigma,K))
else:
loss.append(Lossfunction2(SubsetData,W2,sigma,K, wnn))
print('Loss is', loss[it])
GNew = gradcoswx1coswx2(SubsetData,W2,wnn,sigma, K)
gradnorm.append(np.linalg.norm(GNew))
# alpha = alphaN*np.sqrt(100/(100+ita))
alpha = alphaN /(1+(alphaN*RegW*it))
wnn = wnn - (alpha)*(RegW*wnn+GNew)
WTMP = np.concatenate((WTMP, wnn), axis =1)
iternorm2 = np.linalg.norm(wnn)
err2=np.linalg.norm(woldnn-wnn)
# print('The error2 is', err2)
if (err2<=tol):
# print('done')
break
elif (it>250):
# print('break')
break
woldnn=wnn
it=it+1
return wnn, loss
def Adam(SubsetData,W2, wnn, alpha, RegW, sigma, K=None):
import numpy as np
from grad import gradcoswx1coswx2, Lossfunction2
import copy
if K is None:
from sklearn.metrics import pairwise
K=pairwise.rbf_kernel(SubsetData,gamma=sigma**2/2)
Nfeat = np.shape(W2)[0]
err2=2
tol =1e-5
WTMP = copy.copy(wnn)
woldnn = copy.copy(wnn)
gradnorm=[]
loss =[]
it=0
m = np.zeros((Nfeat,1))
v = np.zeros((Nfeat,1))
b1 = 0.9
b2 = 0.999
eps = 1e-8
alpha=0.1
while(err2>tol):
#np.random.shuffle(SubsetData)
it = it+1
# print('iteration', it)
GNew = gradcoswx1coswx2(SubsetData,W2,wnn,sigma, K)
m = b1*m + (1-b1)*GNew
v = b2*v + (1-b2)*(GNew**2)
alphaN = alpha*(np.sqrt((1-b2**it)/(1-b1**it)))
# alpha = alphaN /(1+(alphaN*RegW*it))
wnn = wnn - (alphaN)* (RegW*wnn+ (m/(np.sqrt(v)+eps)))
# wnn = wnn - (alpha)*(0.1*wnn+GNew)
# wnn = wnn - (alpha)*(0.0*wnn+NG)
WTMP = np.concatenate((WTMP, wnn), axis =1)
iternorm2 = np.linalg.norm(wnn)
r,s = np.shape(W2)
if (s==1):
loss.append(Lossfunction2(SubsetData,wnn,sigma,K))
else:
loss.append(Lossfunction2(SubsetData,W2,sigma,K, wnn))
print('Loss is', loss[it-1])
err2=np.linalg.norm(woldnn-wnn)
# print('The error2 is', err2)
if (err2<=tol):
# print('done')
break
elif (it>250):
# print('break')
break
woldnn=wnn
return wnn, loss
def Adagrad(SubsetData,W2, wnn, alpha, RegW, sigma, K=None):
import numpy as np
from grad import gradcoswx1coswx2, Lossfunction2
import copy
if K is None:
from sklearn.metrics import pairwise
K=pairwise.rbf_kernel(SubsetData,gamma=sigma**2/2)
Nfeat = np.shape(W2)[0]
err2=2
tol =1e-5
WTMP = copy.copy(wnn)
woldnn = copy.copy(wnn)
gradnorm=[]
loss =[]
it=0
CumGrad = np.zeros((Nfeat,1))
eps = 1e-5
alpha=0.1
while(err2>tol):
#np.random.shuffle(SubsetData)
it = it+1
# print('iteration', it)
GNew = gradcoswx1coswx2(SubsetData,W2,wnn,sigma, K)
gradnorm.append(np.linalg.norm(GNew))
CumGrad = CumGrad + GNew**2
alphaN = alpha/ (eps+np.sqrt(CumGrad))
wnn = wnn - (alphaN)* (RegW*wnn+GNew )
WTMP = np.concatenate((WTMP, wnn), axis =1)
iternorm2 = np.linalg.norm(wnn)
r,s = np.shape(W2)
if (s==1):
loss.append(Lossfunction2(SubsetData,wnn,sigma,K))
else:
loss.append(Lossfunction2(SubsetData,W2,sigma,K, wnn))
print('Loss is', loss[it-1])
err2=np.linalg.norm(woldnn-wnn)
# print('The error2 is', err2)
if (err2<=tol):
# print('done')
break
elif (it>250):
# print('break')
break
woldnn=wnn
# minloss = np.argmin()
return wnn, gradnorm, loss
def Rprop(SubsetData, W2,wnn, alphaN, RegW, sigma, K=None):
import numpy as np
from grad import gradcoswx1coswx2, Lossfunction2
from math import copysign
import copy
if K is None:
from sklearn.metrics import pairwise
K=pairwise.rbf_kernel(SubsetData,gamma=sigma**2/2)
err2=2
tol =1e-5
WTMP = wnn
woldnn = wnn
gradnorm=[]
loss =[]
it=0
deltaold = 0.01
delta = deltaold
deltaMin = np.tile(0.0, (np.size(wnn),1))
deltaMax = np.tile(0.9, (np.size(wnn),1))
nplus = 1.2
nminus = 0.5
GOld = 0.0
deltaW = 0.0
alphaN = 0.1
while(err2>tol):
#np.random.shuffle(SubsetData)
if (it==51):
index = np.argmin(loss)
wnn = WTMP[:, index]
wnn = wnn[:, np.newaxis]
deltaold = alpha
print('Index', index)
#
r, s = np.shape(W2)
if (s==1):
loss.append(Lossfunction2(SubsetData,wnn,sigma,K))
else:
loss.append(Lossfunction2(SubsetData,W2,sigma,K, wnn))
print('Loss is ', loss[it])
GNew = gradcoswx1coswx2(SubsetData,W2,wnn,sigma, K)
if (it<51):
gradnorm.append(np.linalg.norm(GNew))
alpha = alphaN /(1+(alphaN*RegW*it))
wnn = wnn - (alpha)*(RegW*wnn+GNew)
#
WTMP = np.concatenate((WTMP, wnn), axis =1)
### print('The error2 is', err2)
else:
sigGrad = GNew*GOld
deltaPlus = np.minimum(deltaold*nplus, deltaMax)*(sigGrad>0)
deltaminus = np.maximum(deltaold*nminus, deltaMin)*(sigGrad<0)
deltaequal = deltaold*(sigGrad==0)
delta = deltaPlus+deltaminus+deltaequal
signG = np.sign(sigGrad)
deltaW = -(signG)*delta*(sigGrad>=0) - deltaW*(sigGrad<0)
#wnn = wnn + (0.1*wnn+deltaW)
wnn = wnn +deltaW
iternorm2 = np.linalg.norm(wnn)
if (it>0):
err2=np.linalg.norm(woldnn-wnn)
if (err2<=tol):
# print('done')
break
elif (it>250):
# print('break')
break
woldnn= copy.copy(wnn)
deltaold = copy.copy(delta)
GOld = copy.copy(GNew)
it=it+1
print('Iteration', it)
return wnn, loss
def IPprop(SubsetData, W2,wnn,alphaN, RegW, sigma, K=None):
import numpy as np
from grad import gradcoswx1coswx2, Lossfunction2
from math import copysign
import copy
if K is None:
from sklearn.metrics import pairwise
K=pairwise.rbf_kernel(SubsetData,gamma=sigma**2/2)
err2=2
tol =1e-5
WTMP = wnn
woldnn = 0
gradnorm=[]
loss =[]
it=0
deltaold = 0.01
delta = deltaold
deltaMin = np.tile(0.0, (np.size(wnn),1))
deltaMax = np.tile(1.0, (np.size(wnn),1))
nplus = 1.1
nminus = 0.25
GOld = 0.0
deltaW = 0.0
old_E = 500
while(err2>tol):
#np.random.shuffle(SubsetData)
if (it==51):
index = np.argmin(loss)
wnn = WTMP[:, index]
wnn = wnn[:, np.newaxis]
deltaold = 0.01
old_E = 10000
print('Index', index)
r,s= np.shape(W2)
if (s==1):
loss.append(Lossfunction2(SubsetData,wnn,sigma,K))
else:
loss.append(Lossfunction2(SubsetData,W2,sigma,K, wnn))
E = loss[it]
GNew = gradcoswx1coswx2(SubsetData,W2,wnn,sigma, K)
GNew = (RegW * wnn)+GNew
if (it<51):
gradnorm.append(np.linalg.norm(GNew))
alpha = alphaN /(1+(alphaN*RegW*it))
wnn = wnn - (alpha)*(GNew)
#
WTMP = np.concatenate((WTMP, wnn), axis =1)
#### print('The error2 is', err2)
else:
sigGrad = GNew*GOld
deltaPlus = np.minimum(deltaold*nplus, deltaMax)*(sigGrad>0)
deltaminus = np.maximum(deltaold*nminus, deltaMin)*(sigGrad<0)
deltaequal = deltaold*(sigGrad==0)
delta = deltaPlus+deltaminus+deltaequal
signG = np.sign(sigGrad)+ (it==0)
deltaW = -(signG)*delta*(sigGrad>=0) - deltaW*((sigGrad<0)*(E>old_E))
#GNew = GNew*(sigGrad>0)
#wnn = wnn + (0.1*wnn+deltaW)
wnn = wnn +deltaW
iternorm2 = np.linalg.norm(wnn)
print('Loss is ', loss[it])
if (it>0):
err2=np.linalg.norm(woldnn-wnn)
if (err2<=tol):
# print('done')
break
elif (it>250):
# print('break')
break
woldnn= copy.copy(wnn)
deltaold = copy.copy(delta)
GOld = copy.copy(GNew)
old_E = copy.copy(E)
it=it+1
print('Iteration', it)
return wnn, loss
def AdaptiveRateBatchCheck(SubsetData, W2,wnn,alphaN, RegW, sigma, K=None):
import numpy as np
from grad import gradcoswx1coswx2, Lossfunction2
from math import copysign
import copy
if K is None:
from sklearn.metrics import pairwise
K=pairwise.rbf_kernel(SubsetData,gamma=sigma**2/2)
err2=2
tol =1e-5
niter = 251
WTMP = wnn
woldnn = 0
gradnorm=[]
loss =np.zeros((niter,1))
it=0
deltaold = 0.01
delta = deltaold
deltaMin = np.tile(0.0, (np.size(wnn),1))
deltaMax = np.tile(1.0, (np.size(wnn),1))
nplus = 1.1
nminus = 0.25
GOld = 0.0
deltaW = 0.0
E_old = 500
E = 0
alpha=np.zeros((niter,1))
Ncheck = 20
end_ncheck = 0
n_check = 0
while(err2>tol):
#np.random.shuffle(SubsetData)
r,s= np.shape(W2)
if (s==1):
loss[it] = (Lossfunction2(SubsetData,wnn,sigma,K))
else:
loss[it] = (Lossfunction2(SubsetData,W2,sigma,K, wnn))
print('Loss is ', loss[it])
if ((np.mod(it, Ncheck)==0) & (it>0)):
print ('Error check', it)
E = loss[it]
st_ncheck = end_ncheck
n_check = n_check+1
end_ncheck = Ncheck*n_check
if (E>E_old):
print('Error greater', it)
index = np.argmin(loss[st_ncheck:end_ncheck-1])
index = index+st_ncheck
print('Index', index)
E = loss[index]
wnn = WTMP[:, index]
wnn = wnn[:, np.newaxis]
alphaN = alpha[index]
print ('alphaN ' , alphaN)
else:
alphaN = alpha[it-1]
GNew = gradcoswx1coswx2(SubsetData,W2,wnn,sigma, K)
GNew = (RegW * wnn)+GNew
alpha[it]= (alphaN /(1+(alphaN*RegW*it)))
wnn = wnn - (alpha[it])*(GNew)
#
# if (it==0):
# WTMP = wnn
# else:
WTMP = np.concatenate((WTMP, wnn), axis =1)
iternorm2 = np.linalg.norm(wnn)
if (it>0):
err2=np.linalg.norm(woldnn-wnn)
if (err2<=tol):
# print('done')
break
elif (it>=niter-1):
# print('break')
break
woldnn= copy.copy(wnn)
E_old = copy.copy(E)
it=it+1
print('Iteration', it)
minindex = np.argmin(loss)
wnn = WTMP[:, minindex]
wnn = wnn[:, np.newaxis]
return wnn, loss
def AdaptiveLearningRateErrorCheck(SubsetData, W2,wnn,alphaN, RegW, gamma,
K=None, philippe_update = False):
import numpy as np
from grad import Lossfunction2,gradcoswx1coswx2WithOutLoop
from math import copysign
import copy
import time
if K is None:
from sklearn.metrics import pairwise
K=pairwise.rbf_kernel(SubsetData,gamma=gamma)
err2=2
tol =1e-5
niter = 1001
WTMP = wnn
woldnn = 0
gradnorm=[]
loss =np.zeros((niter,1))
it=0
SubsetDataN = SubsetData.copy()
sigma_inv2 = 2*gamma
E_old = 500
E = 0
alpha=np.zeros((niter,1))
Ncheck = 100
end_ncheck = 0
n_check = 0
while(err2>tol):
#np.random.shuffle(SubsetData)
if (it==Ncheck):
# print ('Error check', it)
index = np.argmin(loss[0:Ncheck])
# print('Index', index)
wnn = WTMP[:, index]
wnn = wnn[:, np.newaxis]
alphaN = alpha[index]
E = loss[index]
# print('Error', E)
newit = index
r,s= np.shape(W2)
if (s==1):
loss[it] = (Lossfunction2(SubsetData,wnn,gamma,K))
else:
loss[it] = (Lossfunction2(SubsetData,W2,gamma,K, wnn))
loss[it]= loss[it]+RegW*(np.sum(np.square(wnn[0:len(wnn)-1])))
# print('Loss is ', loss[it])
# time.sleep(0.5)
# IRegW =1
# #nv = 0.0
# # Noise addition to the Gradient
# RegW = IRegW/(1+it)*0.55
# randomNoise = np.random.normal(0, nv,1)
randomNoise = 0.0
if (it<=Ncheck):
#GNew = gradcoswx1coswx2(SubsetData,W2,wnn,sigma, K)
GNew = gradcoswx1coswx2WithOutLoop(SubsetData,W2,wnn,gamma, K)
GNew1 = GNew+randomNoise
GNew = (RegW * wnn)+GNew1
GNew[-1] = GNew1[-1].copy()
alpha[it]= (alphaN /(1+(alphaN*RegW*it)))
wnew = wnn - (alpha[it]*GNew)
if philippe_update:
wnew = wnew*(sigma_inv2/np.std(wnew))
elif (it>(Ncheck)):
E = loss[it]
newit =newit+1
if (E>E_old):
alphaN = alphaN/5.0
wnn = woldnn.copy()
#GNew = gradcoswx1coswx2(SubsetData,W2,wnn,sigma, K)
GNew = gradcoswx1coswx2WithOutLoop(SubsetData,W2,wnn,gamma, K)
GNew1 = GNew+randomNoise
GNew = (RegW * wnn)+GNew1
GNew[-1] = GNew1[-1].copy()
beta = (alphaN)# /(1+(alphaN*RegW*newit)))
wnew = wnn - (beta*GNew)
if philippe_update:
wnew = wnew*(sigma_inv2/np.std(wnew))
else:
#GNew = gradcoswx1coswx2(SubsetData,W2,wnn,sigma, K)
GNew = gradcoswx1coswx2WithOutLoop(SubsetData,W2,wnn,gamma, K)
GNew1 = GNew+randomNoise
GNew = (RegW * wnn)+GNew1
GNew[-1] = GNew1[-1].copy()
alphaN = alphaN/2.0
#beta = (alphaN /(1+(alphaN*RegW*newit)))
beta = alphaN
wnew = wnn - (beta*GNew)
if philippe_update:
wnew = wnew*(sigma_inv2/np.std(wnew))
# SubsetData = SubsetDataN + np.random.normal(0,0.01,(1,1))
# if (it==0):
# WTMP = wnew
# else:
WTMP = np.concatenate((WTMP, wnew), axis =1)
iternorm2 = np.linalg.norm(wnew)
if (it>0):
err2=np.linalg.norm(woldnn-wnew)
if (err2<=tol):
# print('done')
break
elif (it>=niter-1):
# print('break')
break
woldnn= copy.copy(wnn)
wnn = copy.copy(wnew)
E_old = copy.copy(E)
it=it+1
# print('Iteration', it)
# print('Iterations', it)
if (it==1):
minindex = np.argmin(loss[0])
else:
minindex = np.argmin(loss[0:it-1])
wnn = WTMP[:, minindex]
wnn = wnn[:, np.newaxis]
return wnn, loss
def philippe_AdaptiveLearningRateErrorCheck(SubsetData, W2,wnn,alphaN, RegW, sigma, K=None):
'''
weight update as mentioned by philippe
new_w = sigma/std(new_w)
'''
import numpy as np
from grad import gradcoswx1coswx2, Lossfunction2,gradcoswx1coswx2WithOutLoop
from math import copysign
import copy
import time
if K is None:
from sklearn.metrics import pairwise
K=pairwise.rbf_kernel(SubsetData,gamma=sigma**2/2)
err2=2
tol =1e-10
niter = 201
WTMP = wnn
woldnn = 0
gradnorm=[]
loss =np.zeros((niter,1))
it=0
SubsetDataN = SubsetData.copy()
gamma=sigma**2/2
b_update = True
E_old = 500
E = 0
alpha=np.zeros((niter,1))
Ncheck = 100
end_ncheck = 0
n_check = 0
while(it<niter):
#np.random.shuffle(SubsetData)
if (it==Ncheck):
print ('Error check', it)
index = np.argmin(loss[0:Ncheck])
print('Index', index)
wnn = WTMP[:, index]
wnn = wnn[:, np.newaxis]
alphaN = alpha[index]
# alphaN = 1.0
E = loss[index]
old_loss =E
print('Error', E)
newit = index
r,s= np.shape(W2)
if (s==1):
loss[it] = (Lossfunction2(SubsetData,wnn,sigma,K))
else:
loss[it] = (Lossfunction2(SubsetData,W2,sigma,K, wnn))
loss[it] = loss[it]+RegW*np.sum(np.square(wnn))
#print('Loss is ', loss[it])
# IRegW =1
# #nv = 0.0
# # Noise addition to the Gradient
# RegW = IRegW/(1+it)*0.55
# randomNoise = np.random.normal(0, nv,1)
randomNoise = 0.0
if (it<=Ncheck):
#GNew = gradcoswx1coswx2(SubsetData,W2,wnn,sigma, K)
GNew = gradcoswx1coswx2WithOutLoop(SubsetData,W2,wnn,sigma, K)
GNew1 = GNew+randomNoise
GNew = (RegW * wnn)+GNew1
if b_update:
GNew[-1] = GNew1[-1].copy()
alpha[it]= (alphaN /(1+(alphaN*RegW*it)))
wnew = wnn - (alpha[it]*GNew)
# philippe update
wnew = wnew*(np.sqrt(2*gamma)/np.std(wnew))
wnn = copy.copy(wnew)
elif (it>(Ncheck)):
GNew = gradcoswx1coswx2WithOutLoop(SubsetData,W2,wnn,sigma, K)
GNew1 = GNew+randomNoise
GNew = (RegW * wnn)+GNew1
if b_update:
GNew[-1] = GNew1[-1].copy()
beta = (alphaN) /(1+(alphaN*RegW*newit))
wnew = wnn - (beta*GNew)
# philippe update
wnew = wnew*(np.sqrt(2*gamma)/np.std(wnew))
print('Learning rate =', beta)
if (s==1):
nloss = (Lossfunction2(SubsetData,wnew,sigma,K))
else:
nloss = (Lossfunction2(SubsetData,W2,sigma,K, wnew))
new_loss = nloss+RegW*np.sum(np.square(wnew))
print('New Loss =', new_loss)
print('Old Loss =', old_loss)
time.sleep(0.7)
newit =newit+1
if (new_loss<old_loss):
wnn = np.copy(wnew)
old_loss = np.copy(new_loss)
print('update')
else:
alphaN = alphaN*0.7
# SubsetData = SubsetDataN + np.random.normal(0,0.01,(1,1))
# if (it==0):
# WTMP = wnew
# else:
WTMP = np.concatenate((WTMP, wnew), axis =1)
iternorm2 = np.linalg.norm(wnew)
if (it>0):
err2=np.linalg.norm(woldnn-wnew)
# if (err2<=tol):
## print('done')
# break
if (it>=niter-1):
# print('break')
break
woldnn= copy.copy(wnn)
it=it+1
# print('Iteration', it)
# print('Iterations', it)
if (it==1):
minindex = np.argmin(loss[0])
else:
minindex = np.argmin(loss[0:it-1])
wnn = WTMP[:, minindex]
wnn = wnn[:, np.newaxis]
return wnn, loss | 30.331823 | 106 | 0.480454 | 3,075 | 26,783 | 4.156748 | 0.066341 | 0.038492 | 0.031685 | 0.036145 | 0.855343 | 0.821311 | 0.793616 | 0.767094 | 0.747536 | 0.743311 | 0 | 0.042555 | 0.391965 | 26,783 | 883 | 107 | 30.331823 | 0.74234 | 0.124295 | 0 | 0.805901 | 0 | 0 | 0.013192 | 0.001159 | 0 | 0 | 0 | 0 | 0 | 1 | 0.015528 | false | 0 | 0.06677 | 0 | 0.097826 | 0.052795 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
5eae55fb2cbba8af025fdebb44832ac555b80ae9 | 106 | py | Python | tests/services/blockchain_follower/store_notification.py | dpays/dsocial-notifications | 32b1cdcd58d622407fd50206053c5b9735a56ba9 | [
"MIT"
] | 10 | 2017-10-22T20:07:40.000Z | 2018-08-01T21:48:49.000Z | tests/services/blockchain_follower/store_notification.py | dpays/dsocial-notifications | 32b1cdcd58d622407fd50206053c5b9735a56ba9 | [
"MIT"
] | 81 | 2017-08-19T15:38:32.000Z | 2020-05-12T09:56:14.000Z | tests/services/blockchain_follower/store_notification.py | dpays/dsocial-notifications | 32b1cdcd58d622407fd50206053c5b9735a56ba9 | [
"MIT"
] | 9 | 2017-09-19T07:12:20.000Z | 2021-05-25T17:09:27.000Z | # coding=utf-8
import yo.services.blockchain_follower.service
def test_store_notifications():
pass
| 13.25 | 46 | 0.783019 | 14 | 106 | 5.714286 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.01087 | 0.132075 | 106 | 7 | 47 | 15.142857 | 0.858696 | 0.113208 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | true | 0.333333 | 0.333333 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 7 |
5eaebc17ddabdc9f58a45b8cd042c376c1da5ecf | 3,341 | py | Python | src/save_var.py | bdrummond1/um_post_proc | 2dc1dcaa164772e09e77cd3f3e7d927f2237228a | [
"MIT"
] | 1 | 2020-04-23T17:06:40.000Z | 2020-04-23T17:06:40.000Z | src/save_var.py | bdrummond1/um_post_proc | 2dc1dcaa164772e09e77cd3f3e7d927f2237228a | [
"MIT"
] | null | null | null | src/save_var.py | bdrummond1/um_post_proc | 2dc1dcaa164772e09e77cd3f3e7d927f2237228a | [
"MIT"
] | null | null | null | import netCDF4 as nc
from constant_umpp import *
import os
import sys
def save_var_3d(save_dir,fname,x,y,z,f):
# Check if directory exists
if os.path.exists(save_dir+'saved_vars') == False:
# Create saved_vars directory
os.makedirs(save_dir+'saved_vars')
# Open file
fout = nc.Dataset(save_dir+'saved_vars/'+fname,'w')
# Create dimensions
nx = x.size
ny = y.size
nz = z.size
fout.createDimension('x',nx)
fout.createDimension('y',ny)
fout.createDimension('z',nz)
# Create variable
varout = fout.createVariable('variable','f8',('z','y','x'))
xout = fout.createVariable('x','f8',('x'))
yout = fout.createVariable('y','f8',('y'))
zout = fout.createVariable('z','f8',('z'))
# Copy variable
varout[:,:,:] = f
xout[:] = x
yout[:] = y
zout[:] = z
fout.close()
def save_var_2d(save_dir,fname,x,y,f):
# Check if directory exists
if os.path.exists(save_dir+'saved_vars') == False:
# Create saved_vars directory
os.makedirs(save_dir+'saved_vars')
# Open file
fout = nc.Dataset(save_dir+'saved_vars/'+fname,'w')
# Create dimensions
nx = x.size
ny = y.size
fout.createDimension('x',nx)
fout.createDimension('y',ny)
# Create variable
varout = fout.createVariable('variable','f8',('y','x'))
xout = fout.createVariable('x','f8',('x'))
yout = fout.createVariable('y','f8',('y'))
# Copy variable
varout[:,:] = f
xout[:] = x
yout[:] = y
fout.close()
if verbose:
print 'Saved variable at : ',fname
# Save constructed variable to netcdf file
def save_var_1d(save_dir,fname,x,f):
# Check if directory exists
if os.path.exists(save_dir+'saved_vars') == False:
# Create saved_vars directory
os.makedirs(save_dir+'saved_vars')
# Open file
fout = nc.Dataset(save_dir+'saved_vars/'+fname,'w')
# Create Dimensions
nx = x.size
fout.createDimension('x',nx)
# Create variable
varout = fout.createVariable('variable','f8',('x'))
xout = fout.createVariable('x','f8',('x'))
# Copy variables
varout[:] = f
xout[:] = x
fout.close()
if verbose:
print 'Saved variable at : ', fname+'_saved_var'
def read_saved_var_3d(save_dir,fname):
# Open file
fin = nc.Dataset(save_dir+'saved_vars/'+fname,'r')
# Read dimensions
dims = fin.variables['variable'].dimensions
x = fin.variables[dims[0]][:]
y = fin.variables[dims[1]][:]
z = fin.variables[dims[2]][:]
# Read variable
f = fin.variables['variable'][:,:]
print 'Read saved variable from file: ',fname+'_saved_var'
return x, y, z, f
def read_saved_var_2d(save_dir,fname):
# Open file
fin = nc.Dataset(save_dir+'saved_vars/'+fname,'r')
# Read dimensions
dims = fin.variables['variable'].dimensions
x = fin.variables[dims[0]][:]
y = fin.variables[dims[1]][:]
# Read variable
f = fin.variables['variable'][:,:]
print 'Read saved variable from file: ',fname+'_saved_var'
return x, y, f
# Read saved variable 1D
def read_saved_var_1d(save_dir,fname):
# Open file
fin = nc.Dataset(save_dir+'saved_vars/'+fname,'r')
# Read dimensions
dims = fin.variables['variable'].dimensions
x = fin.variables[dims[0]][:]
# Read variable
f = fin.variables['variable'][:]
print 'Read saved variable from file: ',fname+'_saved_var'
return x, f
| 22.422819 | 61 | 0.639629 | 476 | 3,341 | 4.369748 | 0.138655 | 0.060577 | 0.069231 | 0.092308 | 0.860577 | 0.816346 | 0.816346 | 0.734135 | 0.70625 | 0.620673 | 0 | 0.008519 | 0.191859 | 3,341 | 148 | 62 | 22.574324 | 0.761852 | 0.155642 | 0 | 0.649351 | 0 | 0 | 0.150179 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0.051948 | null | null | 0.064935 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
5eb9af4a323bab115f39e84c403392d5963ef13d | 12,621 | py | Python | reduction/cifar10/factorized-layers/models.py | gishikawa3/my-nnabla-examples | 44af0c16cf3e730011a54cd104483d5f956c8f15 | [
"Apache-2.0"
] | 1 | 2018-10-22T15:37:33.000Z | 2018-10-22T15:37:33.000Z | reduction/cifar10/factorized-layers/models.py | gishikawa3/my-nnabla-examples | 44af0c16cf3e730011a54cd104483d5f956c8f15 | [
"Apache-2.0"
] | null | null | null | reduction/cifar10/factorized-layers/models.py | gishikawa3/my-nnabla-examples | 44af0c16cf3e730011a54cd104483d5f956c8f15 | [
"Apache-2.0"
] | null | null | null | # Copyright (c) 2017 Sony Corporation. 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.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License 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.
from six.moves import range
import os
import nnabla as nn
import nnabla.logger as logger
import nnabla.functions as F
import nnabla.parametric_functions as PF
import nnabla.solvers as S
import nnabla.utils.save as save
from nnabla.parameter import get_parameter, get_parameter_or_create, set_parameter
import numpy as np
def categorical_error(pred, label):
"""
Compute categorical error given score vectors and labels as
numpy.ndarray.
"""
pred_label = pred.argmax(1)
return (pred_label != label.flat).mean()
def cifar10_resnet23_prediction(image, maps=64,
test=False):
"""
Construct Resnet23 as reference.
"""
# Residual Unit
def res_unit(x, scope_name, dn=False):
C = x.shape[1]
with nn.parameter_scope(scope_name):
# Conv -> BN -> Relu
with nn.parameter_scope("conv1"):
h = PF.convolution(x, C // 2, kernel=(1, 1), pad=(0, 0),
with_bias=False)
h = PF.batch_normalization(h, batch_stat=not test)
h = F.relu(h)
# Conv -> BN -> Relu
with nn.parameter_scope("conv2"):
h = PF.convolution(h, C // 2, kernel=(3, 3), pad=(1, 1),
with_bias=False)
h = PF.batch_normalization(h, batch_stat=not test)
h = F.relu(h)
# Conv -> BN
with nn.parameter_scope("conv3"):
h = PF.convolution(h, C, kernel=(1, 1), pad=(0, 0),
with_bias=False)
h = PF.batch_normalization(h, batch_stat=not test)
# Residual -> Relu
h = F.relu(h + x)
# Maxpooling
if dn:
h = F.max_pooling(h, kernel=(2, 2), stride=(2, 2))
return h
ncls = 10
# Conv -> BN -> Relu
with nn.parameter_scope("conv1"):
# Preprocess
image /= 255.0
if not test:
image = F.image_augmentation(image, contrast=1.0,
angle=0.25,
flip_lr=True)
image.need_grad = False
h = PF.convolution(image, maps, kernel=(3, 3), pad=(1, 1),
with_bias=False)
h = PF.batch_normalization(h, batch_stat=not test)
h = F.relu(h)
h = res_unit(h, "conv2", False) # -> 32x32
h = res_unit(h, "conv3", True) # -> 16x16
h = res_unit(h, "conv4", False) # -> 16x16
h = res_unit(h, "conv5", True) # -> 8x8
h = res_unit(h, "conv6", False) # -> 8x8
h = res_unit(h, "conv7", True) # -> 4x4
h = res_unit(h, "conv8", False) # -> 4x4
h = F.average_pooling(h, kernel=(4, 4)) # -> 1x1
pred = PF.affine(h, ncls)
return pred
def cifar10_cpd3_factorized_resnet23_prediction(image, maps=64,
test=False, compression_ratio=0.0):
"""
Construct Resnet23 with factorized affine and convolution
"""
# SVD affine
def svd_affine(x, n_outputs, cr):
W = get_parameter('affine/W')
if W is None:
UV = None
else:
UV = W.d
b = get_parameter('affine/b')
# compute rank (size of intermediate activations)
# to obtained desired reduction
inshape = np.prod(x.shape[1:])
outshape = np.prod(n_outputs)
rank = int(np.floor((1-cr)*inshape*outshape/(inshape+outshape)))
# Initialize bias to existing b in affine if exists
if b is not None:
b_new = get_parameter_or_create(
'svd_affine/b', b.d.shape, need_grad=b.need_grad)
b_new.d = b.d.copy()
logger.info("SVD affine created: input_shape = {}; output_shape = {}; compression = {}; rank = {};".format(
inshape, outshape, cr, rank))
# create svd_affine initialized from W in current context if it exists
return PF.svd_affine(x, n_outputs, rank, uv_init=UV)
# CP convolution
def cpd3_convolution(x, n_outputs, kernel, pad, with_bias, cr):
W = get_parameter('conv/W')
if W is None:
OIK = None
else:
OIK = W.d
b = get_parameter('conv/b')
# compute rank (size of intermediate activations)
# to obtained desired reduction
inmaps = x.shape[1]
outmaps = n_outputs
Ksize = np.prod(kernel)
rank = int(np.floor((1-cr)*inmaps*outmaps *
Ksize/(inmaps+outmaps+Ksize)))
# Initialize bias to existing b in affine if exists
if b is not None:
b_new = get_parameter_or_create(
'cpd3_conv/b', b.d.shape, need_grad=b.need_grad)
b_new.d = b.d.copy()
logger.info("CP convolution created: inmaps = {}; outmaps = {}; compression = {}; rank = {};".format(
inmaps, outmaps, cr, rank))
# create cpd3_convolution initialized from W in current context if it exists
return PF.cpd3_convolution(x, n_outputs, kernel=kernel, r=rank, pad=pad, with_bias=with_bias, oik_init=OIK)
# Residual Unit
def res_unit(x, scope_name, dn=False):
C = x.shape[1]
with nn.parameter_scope(scope_name):
# Conv -> BN -> Relu
with nn.parameter_scope("conv1"):
h = PF.convolution(x, C // 2, kernel=(1, 1), pad=(0, 0),
with_bias=False)
h = PF.batch_normalization(h, batch_stat=not test)
h = F.relu(h)
# Conv -> BN -> Relu
with nn.parameter_scope("conv2"):
h = cpd3_convolution(h, C // 2, kernel=(3, 3), pad=(1, 1),
with_bias=False, cr=compression_ratio)
h = PF.batch_normalization(h, batch_stat=not test)
h = F.relu(h)
# Conv -> BN
with nn.parameter_scope("conv3"):
h = PF.convolution(h, C, kernel=(1, 1), pad=(0, 0),
with_bias=False)
h = PF.batch_normalization(h, batch_stat=not test)
# Residual -> Relu
h = F.relu(h + x)
# Maxpooling
if dn:
h = F.max_pooling(h, kernel=(2, 2), stride=(2, 2))
return h
ncls = 10
# Conv -> BN -> Relu
with nn.parameter_scope("conv1"):
# Preprocess
image /= 255.0
if not test:
image = F.image_augmentation(image, contrast=1.0,
angle=0.25,
flip_lr=True)
image.need_grad = False
h = cpd3_convolution(image, maps, kernel=(3, 3), pad=(1, 1),
with_bias=False, cr=compression_ratio)
h = PF.batch_normalization(h, batch_stat=not test)
h = F.relu(h)
h = res_unit(h, "conv2", False) # -> 32x32
h = res_unit(h, "conv3", True) # -> 16x16
h = res_unit(h, "conv4", False) # -> 16x16
h = res_unit(h, "conv5", True) # -> 8x8
h = res_unit(h, "conv6", False) # -> 8x8
h = res_unit(h, "conv7", True) # -> 4x4
h = res_unit(h, "conv8", False) # -> 4x4
h = F.average_pooling(h, kernel=(4, 4)) # -> 1x1
pred = svd_affine(h, ncls, compression_ratio)
return pred
def cifar10_svd_factorized_resnet23_prediction(image, maps=64,
test=False, compression_ratio=0.0):
"""
Construct Resnet23 with factorized affine and convolution
"""
# SVD affine
def svd_affine(x, n_outputs, cr):
W = get_parameter('affine/W')
if W is None:
UV = None
else:
UV = W.d
b = get_parameter('affine/b')
# compute rank (size of intermediate activations)
# to obtained desired reduction
inshape = np.prod(x.shape[1:])
outshape = np.prod(n_outputs)
rank = int(np.floor((1-cr)*inshape*outshape/(inshape+outshape)))
# Initialize bias to existing b in affine if exists
if b is not None:
b_new = get_parameter_or_create(
'svd_affine/b', b.d.shape, need_grad=b.need_grad)
b_new.d = b.d.copy()
logger.info("SVD affine created: input_shape = {}; output_shape = {}; compression = {}; rank = {};".format(
inshape, outshape, cr, rank))
# create svd_affine initialized from W in current context if it exists
return PF.svd_affine(x, n_outputs, rank, uv_init=UV)
# SVD convolution
def svd_convolution(x, n_outputs, kernel, pad, with_bias, cr):
W = get_parameter('conv/W')
if W is None:
UV = None
else:
UV = W.d
b = get_parameter('conv/b')
# compute rank (size of intermediate activations)
# to obtained desired reduction
inmaps = x.shape[1]
outmaps = n_outputs
Ksize = np.prod(kernel)
rank = int(np.floor((1-cr)*inmaps*outmaps *
Ksize/(inmaps*Ksize+inmaps*outmaps)))
# Initialize bias to existing b in affine if exists
if b is not None:
b_new = get_parameter_or_create(
'svd_conv/b', b.d.shape, need_grad=b.need_grad)
b_new.d = b.d.copy()
logger.info("SVD convolution created: inmaps = {}; outmaps = {}; compression = {}; rank = {};".format(
inmaps, outmaps, cr, rank))
# create svd_convolution initialized from W in current context if it exists
return PF.svd_convolution(x, n_outputs, kernel=kernel, r=rank, pad=pad, with_bias=with_bias, uv_init=UV)
# Residual Unit
def res_unit(x, scope_name, dn=False):
C = x.shape[1]
with nn.parameter_scope(scope_name):
# Conv -> BN -> Relu
with nn.parameter_scope("conv1"):
h = PF.convolution(x, C // 2, kernel=(1, 1), pad=(0, 0),
with_bias=False)
h = PF.batch_normalization(h, batch_stat=not test)
h = F.relu(h)
# Conv -> BN -> Relu
with nn.parameter_scope("conv2"):
h = svd_convolution(h, C // 2, kernel=(3, 3), pad=(1, 1),
with_bias=False, cr=compression_ratio)
h = PF.batch_normalization(h, batch_stat=not test)
h = F.relu(h)
# Conv -> BN
with nn.parameter_scope("conv3"):
h = PF.convolution(h, C, kernel=(1, 1), pad=(0, 0),
with_bias=False)
h = PF.batch_normalization(h, batch_stat=not test)
# Residual -> Relu
h = F.relu(h + x)
# Maxpooling
if dn:
h = F.max_pooling(h, kernel=(2, 2), stride=(2, 2))
return h
ncls = 10
# Conv -> BN -> Relu
with nn.parameter_scope("conv1"):
# Preprocess
image /= 255.0
if not test:
image = F.image_augmentation(image, contrast=1.0,
angle=0.25,
flip_lr=True)
image.need_grad = False
h = svd_convolution(image, maps, kernel=(3, 3), pad=(1, 1),
with_bias=False, cr=compression_ratio)
h = PF.batch_normalization(h, batch_stat=not test)
h = F.relu(h)
h = res_unit(h, "conv2", False) # -> 32x32
h = res_unit(h, "conv3", True) # -> 16x16
h = res_unit(h, "conv4", False) # -> 16x16
h = res_unit(h, "conv5", True) # -> 8x8
h = res_unit(h, "conv6", False) # -> 8x8
h = res_unit(h, "conv7", True) # -> 4x4
h = res_unit(h, "conv8", False) # -> 4x4
h = F.average_pooling(h, kernel=(4, 4)) # -> 1x1
pred = svd_affine(h, ncls, compression_ratio)
return pred
| 37.230088 | 115 | 0.53514 | 1,635 | 12,621 | 4.004281 | 0.13211 | 0.025661 | 0.025661 | 0.028868 | 0.835344 | 0.835039 | 0.833359 | 0.827555 | 0.827555 | 0.827555 | 0 | 0.031486 | 0.348229 | 12,621 | 338 | 116 | 37.340237 | 0.764406 | 0.174788 | 0 | 0.836364 | 0 | 0 | 0.057936 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.05 | false | 0 | 0.045455 | 0 | 0.145455 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
0db39d51f35c527c2e819b21d9297351c97cd8d7 | 7,580 | py | Python | rlpyt/ul/models/dmlab_conv2d.py | Slienteagle-wyb/rlpyt | fee14b1c28481f6751a7a1a6ce9b8cbac1e001f0 | [
"MIT"
] | null | null | null | rlpyt/ul/models/dmlab_conv2d.py | Slienteagle-wyb/rlpyt | fee14b1c28481f6751a7a1a6ce9b8cbac1e001f0 | [
"MIT"
] | null | null | null | rlpyt/ul/models/dmlab_conv2d.py | Slienteagle-wyb/rlpyt | fee14b1c28481f6751a7a1a6ce9b8cbac1e001f0 | [
"MIT"
] | null | null | null | import torch
import torch.nn.functional as F
from rlpyt.models.utils import conv2d_output_shape
from rlpyt.ul.models.utils import init_normalization
class DmlabConv2dModelBn(torch.nn.Module):
def __init__(
self,
in_channels,
use_fourth_layer=True,
skip_connections=True,
use_maxpool=False,
norm_type='bn',
):
super().__init__()
self.conv1 = torch.nn.Conv2d(
in_channels=in_channels,
out_channels=32,
kernel_size=8,
stride=1 if use_maxpool else 4,
padding=2 if use_maxpool else 0,
)
self.bn1 = init_normalization(channels=32, type_id=norm_type, one_d=False)
self.maxpool1 = torch.nn.MaxPool2d(kernel_size=4, stride=4) if use_maxpool else None
self.conv2 = torch.nn.Conv2d(
in_channels=32,
out_channels=64,
kernel_size=4,
stride=1 if use_maxpool else 2,
padding=1 if use_maxpool else 0,
)
self.bn2 = init_normalization(channels=64, type_id=norm_type, one_d=False)
self.maxpool2 = torch.nn.MaxPool2d(kernel_size=2, stride=2) if use_maxpool else None
self.conv3 = torch.nn.Conv2d(
in_channels=64,
out_channels=64,
kernel_size=3,
stride=1,
padding=1,
)
self.bn3 = init_normalization(channels=64, type_id=norm_type, one_d=False)
if use_fourth_layer:
self.conv4 = torch.nn.Conv2d(
in_channels=64,
out_channels=64,
kernel_size=3,
stride=1,
padding=1,
)
self.bn4 = init_normalization(channels=64, type_id=norm_type, one_d=False)
else:
self.conv4 = None
# if skip_connections:
# if self.conv4 is not None and channels4 != c3:
# self.skip4 = torch.nn.Conv2d(
# in_channels=c3,
# out_channels=channels4,
# kernel_size=1,
# stride=1,
# padding=0,
# )
# else:
# self.skip4 = None
self.skip_connections = skip_connections
def forward(self, x):
h1 = self.bn1(self.conv1(x))
conv1 = F.relu(h1)
if self.maxpool1 is not None:
conv1 = self.maxpool1(conv1)
h2 = self.bn2(self.conv2(conv1))
conv2 = F.relu(h2)
if self.maxpool2 is not None:
conv2 = self.maxpool2(conv2)
conv3_pre = self.bn3(self.conv3(conv2))
if self.skip_connections:
conv3_pre = conv3_pre + conv2
conv3 = F.relu(conv3_pre)
if self.conv4 is None:
return conv3
conv4_pre = self.bn4(self.conv4(conv3))
if self.skip_connections:
# if self.skip4 is not None:
# conv3_pre = self.skip4(conv3_pre)
conv4_pre = conv4_pre + conv3_pre
conv4 = F.relu(conv4_pre)
return conv4
def output_shape(self, h, w, c=None):
"""Helper function ot return the output shape for a given input shape,
without actually performing a forward pass through the model."""
for child in self.children():
try:
h, w = conv2d_output_shape(h, w, child.kernel_size, child.stride, child.padding)
except AttributeError:
pass # Not a conv or maxpool layer.
try:
c = child.out_channels
except AttributeError:
pass # Not a conv layer.
return c, h, w
def output_size(self, h, w, c=None):
"""Helper function ot return the output size for a given input shape,
without actually performing a forward pass through the model."""
c, h, w = self.output_shape(h=h, w=w, c=c)
return c * h * w
class DmlabConv2dModel(torch.nn.Module):
# A more hard-coded version, easier to work with.
def __init__(
self,
in_channels,
use_fourth_layer=True,
skip_connections=True,
use_maxpool=False,
):
super().__init__()
self.conv1 = torch.nn.Conv2d(
in_channels=in_channels,
out_channels=32,
kernel_size=8,
stride=1 if use_maxpool else 4,
padding=2 if use_maxpool else 0,
)
self.maxpool1 = torch.nn.MaxPool2d(kernel_size=4, stride=4) if use_maxpool else None
self.conv2 = torch.nn.Conv2d(
in_channels=32,
out_channels=64,
kernel_size=4,
stride=1 if use_maxpool else 2,
padding=1 if use_maxpool else 0,
)
self.maxpool2 = torch.nn.MaxPool2d(kernel_size=2, stride=2) if use_maxpool else None
self.conv3 = torch.nn.Conv2d(
in_channels=64,
out_channels=64,
kernel_size=3,
stride=1,
padding=1,
)
if use_fourth_layer:
self.conv4 = torch.nn.Conv2d(
in_channels=64,
out_channels=64,
kernel_size=3,
stride=1,
padding=1,
)
else:
self.conv4 = None
# if skip_connections:
# if self.conv4 is not None and channels4 != c3:
# self.skip4 = torch.nn.Conv2d(
# in_channels=c3,
# out_channels=channels4,
# kernel_size=1,
# stride=1,
# padding=0,
# )
# else:
# self.skip4 = None
self.skip_connections = skip_connections
def forward(self, x):
conv1 = F.relu(self.conv1(x))
if self.maxpool1 is not None:
conv1 = self.maxpool1(conv1)
conv2 = F.relu(self.conv2(conv1))
if self.maxpool2 is not None:
conv2 = self.maxpool2(conv2)
conv3_pre = self.conv3(conv2)
if self.skip_connections:
conv3_pre = conv3_pre + conv2
conv3 = F.relu(conv3_pre)
if self.conv4 is None:
return conv3
conv4_pre = self.conv4(conv3)
if self.skip_connections:
# if self.skip4 is not None:
# conv3_pre = self.skip4(conv3_pre)
conv4_pre = conv4_pre + conv3_pre
conv4 = F.relu(conv4_pre)
return conv4
def output_shape(self, h, w, c=None):
"""Helper function ot return the output shape for a given input shape,
without actually performing a forward pass through the model."""
for child in self.children():
try:
h, w = conv2d_output_shape(h, w, child.kernel_size, child.stride, child.padding)
except AttributeError:
pass # Not a conv or maxpool layer.
try:
c = child.out_channels
except AttributeError:
pass # Not a conv layer.
return c, h, w
def output_size(self, h, w, c=None):
"""Helper function ot return the output size for a given input shape,
without actually performing a forward pass through the model."""
c, h, w = self.output_shape(h=h, w=w, c=c)
return c * h * w
if __name__ == '__main__':
model = DmlabConv2dModelBn(
in_channels=3
)
x = torch.rand(1, 3, 84, 84)
conv4 = model(x)
print(conv4.size()) | 34.770642 | 96 | 0.543536 | 935 | 7,580 | 4.242781 | 0.124064 | 0.029997 | 0.036299 | 0.048399 | 0.878498 | 0.878498 | 0.878498 | 0.878498 | 0.8727 | 0.8727 | 0 | 0.0468 | 0.371372 | 7,580 | 218 | 97 | 34.770642 | 0.785729 | 0.181266 | 0 | 0.785714 | 0 | 0 | 0.001633 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.047619 | false | 0.02381 | 0.02381 | 0 | 0.130952 | 0.005952 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
21a1da127de7450f570d9238684f7990e841c23c | 92 | py | Python | Chapter03/core/models/__init__.py | ariwells2001/Python-Programming-Blueprints | 23981ab304e65bcc24560393c75fd5ee85c96ce5 | [
"MIT"
] | 72 | 2017-12-19T09:19:40.000Z | 2021-11-08T13:13:34.000Z | Chapter03/core/models/__init__.py | ariwells2001/Python-Programming-Blueprints | 23981ab304e65bcc24560393c75fd5ee85c96ce5 | [
"MIT"
] | 20 | 2018-03-21T01:15:27.000Z | 2021-09-08T00:59:40.000Z | Chapter03/core/models/__init__.py | ariwells2001/Python-Programming-Blueprints | 23981ab304e65bcc24560393c75fd5ee85c96ce5 | [
"MIT"
] | 53 | 2017-12-19T09:19:42.000Z | 2022-03-06T02:21:10.000Z | from .models import Config
from .models import RequestToken
from .models import RequestAuth
| 23 | 32 | 0.836957 | 12 | 92 | 6.416667 | 0.5 | 0.38961 | 0.623377 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.130435 | 92 | 3 | 33 | 30.666667 | 0.9625 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
21a38ef9bac3fed80c67bfc66ee9bd461909cf31 | 242 | py | Python | tests/test_statistics.py | soccermetrics/marcotti | eda2f19bd6cbc6f9c7482e8fe31b2233b33aacfd | [
"MIT"
] | 30 | 2015-11-23T07:51:54.000Z | 2020-06-29T16:11:55.000Z | tests/test_statistics.py | soccermetrics/marcotti | eda2f19bd6cbc6f9c7482e8fe31b2233b33aacfd | [
"MIT"
] | 1 | 2016-06-26T18:44:47.000Z | 2016-06-29T03:02:40.000Z | tests/test_statistics.py | soccermetrics/marcotti | eda2f19bd6cbc6f9c7482e8fe31b2233b33aacfd | [
"MIT"
] | 8 | 2016-01-13T12:23:16.000Z | 2021-10-11T07:39:33.000Z | # coding=utf-8
import pytest
from sqlalchemy.exc import DataError
import marcotti.models.club as mc
import marcotti.models.common.personnel as mcp
import marcotti.models.common.statistics as mcs
import marcotti.models.common.enums as enums
| 24.2 | 47 | 0.830579 | 37 | 242 | 5.432432 | 0.540541 | 0.278607 | 0.39801 | 0.38806 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00463 | 0.107438 | 242 | 9 | 48 | 26.888889 | 0.925926 | 0.049587 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
21a52d12088a78fbdde0193ae1f584707be0118b | 124 | py | Python | matilda/fundamental_analysis/fundamental_factor_scores/__init__.py | AlainDaccache/Quantropy | 6cfa06ed2b764471382ebf94d40af867f10433bb | [
"MIT"
] | 45 | 2021-01-28T04:12:21.000Z | 2022-02-24T13:15:50.000Z | matilda/fundamental_analysis/fundamental_factor_scores/__init__.py | AlainDaccache/Quantropy | 6cfa06ed2b764471382ebf94d40af867f10433bb | [
"MIT"
] | 32 | 2021-03-02T18:45:16.000Z | 2022-03-12T00:53:10.000Z | matilda/fundamental_analysis/fundamental_factor_scores/__init__.py | AlainDaccache/Quantropy | 6cfa06ed2b764471382ebf94d40af867f10433bb | [
"MIT"
] | 10 | 2020-12-25T15:02:40.000Z | 2021-12-30T11:40:15.000Z | from matilda.fundamental_analysis.financial_statements import *
from matilda.fundamental_analysis.accounting_ratios import * | 62 | 63 | 0.895161 | 14 | 124 | 7.642857 | 0.642857 | 0.205607 | 0.411215 | 0.560748 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.056452 | 124 | 2 | 64 | 62 | 0.91453 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 8 |
21d39e33a98fb4d48063fb3e2a6b5a7c463c9737 | 81 | py | Python | src/commands/scripts/creds/__init__.py | brandontkessler/workspace | ea2f30635563f2b9e9fc5e6fae490d77b6d84aea | [
"MIT"
] | null | null | null | src/commands/scripts/creds/__init__.py | brandontkessler/workspace | ea2f30635563f2b9e9fc5e6fae490d77b6d84aea | [
"MIT"
] | null | null | null | src/commands/scripts/creds/__init__.py | brandontkessler/workspace | ea2f30635563f2b9e9fc5e6fae490d77b6d84aea | [
"MIT"
] | null | null | null | from .code_creds import setup_bcreds
from .aws_creds_setup import aws_creds_setup | 40.5 | 44 | 0.888889 | 14 | 81 | 4.714286 | 0.5 | 0.242424 | 0.393939 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.08642 | 81 | 2 | 44 | 40.5 | 0.891892 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
21dba776509016c7f1a2f89cf8b92172d6ceeea6 | 153 | py | Python | making_pizzas.py | AmitSuresh/learning-python | f1ea5b9f3659f21504b1b0e452c03239b03cde85 | [
"MIT"
] | null | null | null | making_pizzas.py | AmitSuresh/learning-python | f1ea5b9f3659f21504b1b0e452c03239b03cde85 | [
"MIT"
] | null | null | null | making_pizzas.py | AmitSuresh/learning-python | f1ea5b9f3659f21504b1b0e452c03239b03cde85 | [
"MIT"
] | null | null | null | import pizza_fn2 #importing specific functions
pizza_fn2.make_pizza(16, 'pepperoni')
pizza_fn2.make_pizza(12, 'mushroom', 'peppers'), 'extra cheese' | 51 | 63 | 0.771242 | 21 | 153 | 5.380952 | 0.666667 | 0.212389 | 0.212389 | 0.300885 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.051095 | 0.104575 | 153 | 3 | 63 | 51 | 0.773723 | 0.183007 | 0 | 0 | 0 | 0 | 0.292683 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.333333 | 0 | 0.333333 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 7 |
21ddad3521341aba96656875e109e2f892222293 | 4,513 | py | Python | project/c++/mri/src/PI-slim-napa/db/mysql_migrate.py | jia57196/code41 | df611f84592afd453ccb2d22a7ad999ddb68d028 | [
"Apache-2.0"
] | null | null | null | project/c++/mri/src/PI-slim-napa/db/mysql_migrate.py | jia57196/code41 | df611f84592afd453ccb2d22a7ad999ddb68d028 | [
"Apache-2.0"
] | null | null | null | project/c++/mri/src/PI-slim-napa/db/mysql_migrate.py | jia57196/code41 | df611f84592afd453ccb2d22a7ad999ddb68d028 | [
"Apache-2.0"
] | null | null | null | from warnings import filterwarnings
import MySQLdb
import MySQLdb.cursors
# Suppress Warnings. We have all the exceptions covered.
filterwarnings('ignore', category = MySQLdb.Warning)
#start sql helper functions
def open_db(options, dictcursor=None):
if options.unit_test == True:
db_name=options.testdbname
else:
db_name=options.dbname
if not dictcursor:
return MySQLdb.connect(options.dbhostname, options.dbusername, options.dbpassword, db_name)
return MySQLdb.connect(options.dbhostname, options.dbusername, options.dbpassword, db_name, cursorclass=dictcursor)
def db_execute(options, sql, catch_error=False, print_error=False):
db = open_db(options)
cursor = db.cursor()
try:
# Execute the SQL command
cursor.execute(sql)
db.commit()
return cursor.lastrowid # last affected row id
except Exception as e:
db.rollback()
if catch_error:
if print_error: print 'db_execute caught exception: %s'%str(e)
else:
raise # Raise the exception
finally:
# close the cursor and commit the transaction
cursor.close()
db.close()
def db_fetch_next_row(options, sql):
# Open database connection
db = open_db(options)
# prepare a cursor object using cursor() method
cursor = db.cursor()
row = None
try:
# Execute the SQL command
cursor.execute(sql)
# Fetch all the rows in a list of lists.
row = cursor.fetchone()
except Exception: # Try to shutdown gracefully
pass
#logger.error('fetch next row Caught Exception: %s.\t\t' % (str(e),))
# disconnect from server
db.close()
if row is not None:
return row
else:
return (None,)
def db_fetch_remaining_rows(options, sql):
# Open database connection
db = open_db(options)
# prepare a cursor object using cursor() method
cursor = db.cursor()
rows = None
try:
# Execute the SQL command
cursor.execute(sql)
# Fetch all the rows in a list of lists.
rows = cursor.fetchall()
except Exception:
pass
#logger.error('fetch remaining rows Caught Exception: %s.\t\t' % (str(e),))
# disconnect from server
db.close()
if rows is not None:
return rows
else:
return (None,)
def db_fetch_next_row_dict(options, sql):
# Open database connection
db = open_db(options, MySQLdb.cursors.DictCursor)
# prepare a cursor object using cursor() method
cursor = db.cursor()
row = None
try:
# Execute the SQL command
cursor.execute(sql)
# Fetch all the rows in a list of lists.
row = cursor.fetchone()
except Exception:
pass
#logger.error('fetch next row dict Caught Exception: %s.\t\t' % (str(e),))
# disconnect from server
db.close()
if row is not None:
return row
else:
return (None,)
def db_fetch_remaining_rows_dict(options, sql):
# Open database connection
db = open_db(options, MySQLdb.cursors.DictCursor)
# prepare a cursor object using cursor() method
cursor = db.cursor()
rows = None
try:
# Execute the SQL command
cursor.execute(sql)
# Fetch all the rows in a list of lists.
rows = cursor.fetchall()
except Exception:
pass
#logger.error('fetch remaining rows dict Caught Exception: %s.\t\t' % (str(e),))
# disconnect from server
db.close()
if rows is not None:
return rows
else:
return (None,)
def db_fetch_col_by_string(options, sql, index):
# Open database connection
db = open_db(options, MySQLdb.cursors.DictCursor)
# prepare a cursor object using cursor() method
cursor = db.cursor()
try:
# Execute the SQL command
cursor.execute(sql)
# Fetch all the rows in a list of lists.
row = cursor.fetchone()
except Exception:
pass
#logger.error('fetch col by string Caught Exception: %s.\t\t' % (str(e),))
# disconnect from server
db.close()
#check for key membership
try:
if row.has_key(index):
return row[index]
except Exception:
pass
#logger.error('fetch col by string Caught Exception: %s.\t\t' % (str(e),))
return 0
| 30.086667 | 120 | 0.610459 | 564 | 4,513 | 4.819149 | 0.18617 | 0.015453 | 0.033481 | 0.033113 | 0.740618 | 0.731788 | 0.719279 | 0.719279 | 0.719279 | 0.719279 | 0 | 0.000317 | 0.301795 | 4,513 | 149 | 121 | 30.288591 | 0.862266 | 0.324618 | 0 | 0.707071 | 0 | 0 | 0.012955 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0.080808 | 0.030303 | null | null | 0.020202 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 8 |
df4b67eaf2bd430f1903bb4c51e7fb6b8d3e1eb7 | 4,868 | py | Python | fython/fml/add_interpolant.py | nicolasessisbreton/fython | 988f5a94cee8b16b0000501a22239195c73424a1 | [
"Apache-2.0"
] | 41 | 2016-01-21T05:14:45.000Z | 2021-11-24T20:37:21.000Z | fython/fml/add_interpolant.py | nicolasessisbreton/fython | 988f5a94cee8b16b0000501a22239195c73424a1 | [
"Apache-2.0"
] | 5 | 2016-01-21T05:36:37.000Z | 2016-08-22T19:26:51.000Z | fython/fml/add_interpolant.py | nicolasessisbreton/fython | 988f5a94cee8b16b0000501a22239195c73424a1 | [
"Apache-2.0"
] | 3 | 2016-01-23T04:03:44.000Z | 2016-08-21T15:58:38.000Z | from fython.config import *
def add_interpolant(lexer, fmt, arg):
if fmt == '':
lexer += 'g0'
lexer -= arg
elif fmt == 'v':
lexer += 'a'
lexer *= 'trim({:s}(size({:s})))'.format(fytbk.int_to_char_tag, arg)
lexer /= '(g0,:,'
lexer *= 'achar(34)'
lexer /= ', '
lexer *= 'achar(34)'
lexer += ')'
lexer += 'a'
lexer -= "'['"
lexer -= arg
lexer -= "']'"
elif fmt == 'vc':
lexer *= 'trim({:s}(size({:s})))'.format(fytbk.int_to_char_tag, arg)
lexer /= '(g0,:,'
lexer *= 'achar(34)'
lexer /= ', '
lexer *= 'achar(34)'
lexer += ')'
lexer -= arg
elif fmt == 'va':
lexer += 'a'
lexer *= 'trim({:s}(size({:s})))'.format(fytbk.int_to_char_tag, arg)
lexer /= '(g0,:,'
lexer *= 'achar(34)'
lexer /= ', '
lexer *= 'achar(34)'
lexer += ')'
lexer += 'a'
lexer -= "'array(['"
lexer -= arg
lexer -= "'])'"
elif fmt == 'jn':
lexer += 'a'
lexer += 'a'
lexer += 'a'
lexer += 'a'
lexer /= '('
lexer *= 'achar(39)'
lexer *= 'achar(34)'
lexer *= 'achar(39)'
lexer /= ',g0,'
lexer *= 'achar(39)'
lexer *= 'achar(34)'
lexer *= 'achar(39)'
lexer += ')'
lexer -= 'achar(34)'
lexer -= '"{:s}"'.format(arg)
lexer -= 'achar(34)'
lexer -= '":"'
lexer -= arg
elif fmt == 'j':
lexer += 'a'
lexer += 'a'
lexer += 'a'
lexer += 'a'
lexer += 'a'
lexer /= '('
lexer *= 'achar(39)'
lexer *= 'achar(34)'
lexer *= 'achar(39)'
lexer /= ',g0,'
lexer *= 'achar(39)'
lexer *= 'achar(34)'
lexer *= 'achar(39)'
lexer += ')'
lexer -= '","'
lexer -= 'achar(34)'
lexer -= '"{:s}"'.format(arg)
lexer -= 'achar(34)'
lexer -= '":"'
lexer -= arg
elif fmt == 'jv':
lexer += 'a'
lexer += 'a'
lexer += 'a'
lexer += 'a'
lexer += 'a'
lexer *= 'trim({:s}(size({:s})))'.format(fytbk.int_to_char_tag, arg)
lexer /= '(('
lexer *= 'achar(39)'
lexer *= 'achar(34)'
lexer *= 'achar(39)'
lexer /= ',g0,'
lexer *= 'achar(39)'
lexer *= 'achar(34)'
lexer *= 'achar(39)'
lexer /= '),'
lexer *= 'achar(34)'
lexer /= ', '
lexer *= 'achar(34)'
lexer += ')'
lexer += 'tl2,a'
lexer -= '","'
lexer -= 'achar(34)'
lexer -= '"{:s}"'.format(arg)
lexer -= 'achar(34)'
lexer -= '": ["'
lexer -= arg
lexer -= '"]"'
elif fmt == 'jvn':
lexer += 'a'
lexer += 'a'
lexer += 'a'
lexer += 'a'
lexer *= 'trim({:s}(size({:s})))'.format(fytbk.int_to_char_tag, arg)
lexer /= '(('
lexer *= 'achar(39)'
lexer *= 'achar(34)'
lexer *= 'achar(39)'
lexer /= ',g0,'
lexer *= 'achar(39)'
lexer *= 'achar(34)'
lexer *= 'achar(39)'
lexer /= '),'
lexer *= 'achar(34)'
lexer /= ', '
lexer *= 'achar(34)'
lexer += ')'
lexer += 'tl2,a'
lexer -= 'achar(34)'
lexer -= '"{:s}"'.format(arg)
lexer -= 'achar(34)'
lexer -= '": ["'
lexer -= arg
lexer -= '"]"'
elif fmt.startswith('jn_'):
lexer += 'a'
lexer += 'a'
lexer += 'a'
lexer += 'a'
lexer /= '('
lexer *= 'achar(39)'
lexer *= 'achar(34)'
lexer *= 'achar(39)'
lexer /= ',g0,'
lexer *= 'achar(39)'
lexer *= 'achar(34)'
lexer *= 'achar(39)'
lexer += ')'
lexer -= 'achar(34)'
lexer -= '"{:s}"'.format(fmt[3:])
lexer -= 'achar(34)'
lexer -= '":"'
lexer -= arg
elif fmt.startswith('j_'):
lexer += 'a'
lexer += 'a'
lexer += 'a'
lexer += 'a'
lexer += 'a'
lexer /= '('
lexer *= 'achar(39)'
lexer *= 'achar(34)'
lexer *= 'achar(39)'
lexer /= ',g0,'
lexer *= 'achar(39)'
lexer *= 'achar(34)'
lexer *= 'achar(39)'
lexer += ')'
lexer -= '","'
lexer -= 'achar(34)'
lexer -= '"{:s}"'.format(fmt[2:])
lexer -= 'achar(34)'
lexer -= '":"'
lexer -= arg
elif fmt.startswith('jv_'):
lexer += 'a'
lexer += 'a'
lexer += 'a'
lexer += 'a'
lexer += 'a'
lexer *= 'trim({:s}(size({:s})))'.format(fytbk.int_to_char_tag, arg)
lexer /= '(('
lexer *= 'achar(39)'
lexer *= 'achar(34)'
lexer *= 'achar(39)'
lexer /= ',g0,'
lexer *= 'achar(39)'
lexer *= 'achar(34)'
lexer *= 'achar(39)'
lexer /= '),'
lexer *= 'achar(34)'
lexer /= ', '
lexer *= 'achar(34)'
lexer += ')'
lexer += 'tl2,a'
lexer -= '","'
lexer -= 'achar(34)'
lexer -= '"{:s}"'.format(fmt[3:])
lexer -= 'achar(34)'
lexer -= '": ["'
lexer -= arg
lexer -= '"]"'
elif fmt.startswith('jvn_'):
lexer += 'a'
lexer += 'a'
lexer += 'a'
lexer += 'a'
lexer *= 'trim({:s}(size({:s})))'.format(fytbk.int_to_char_tag, arg)
lexer /= '(('
lexer *= 'achar(39)'
lexer *= 'achar(34)'
lexer *= 'achar(39)'
lexer /= ',g0,'
lexer *= 'achar(39)'
lexer *= 'achar(34)'
lexer *= 'achar(39)'
lexer /= '),'
lexer *= 'achar(34)'
lexer /= ', '
lexer *= 'achar(34)'
lexer += ')'
lexer += 'tl2,a'
lexer -= 'achar(34)'
lexer -= '"{:s}"'.format(fmt[4:])
lexer -= 'achar(34)'
lexer -= '": ["'
lexer -= arg
lexer -= '"]"'
else:
lexer += fmt
lexer -= arg | 17.9631 | 70 | 0.471857 | 599 | 4,868 | 3.791319 | 0.066778 | 0.343461 | 0.243065 | 0.344342 | 0.952004 | 0.943197 | 0.93439 | 0.919859 | 0.914135 | 0.888155 | 0 | 0.047826 | 0.244043 | 4,868 | 271 | 71 | 17.9631 | 0.569293 | 0 | 0 | 0.899123 | 0 | 0 | 0.238447 | 0.031629 | 0 | 0 | 0 | 0 | 0 | 1 | 0.004386 | false | 0 | 0.004386 | 0 | 0.008772 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 10 |
df5967f43e728e1c19e8913baee5ba2f158f6ed4 | 40,430 | py | Python | benchmarks/import_cost/functions_100_with_10_contracts.py | kklein/icontract | 718ef1733cc2cce6d3c8f59a5a37de96f8be6664 | [
"MIT"
] | 244 | 2018-08-15T22:58:58.000Z | 2022-03-12T16:10:39.000Z | benchmarks/import_cost/functions_100_with_10_contracts.py | kklein/icontract | 718ef1733cc2cce6d3c8f59a5a37de96f8be6664 | [
"MIT"
] | 157 | 2018-08-29T21:36:47.000Z | 2022-02-14T19:30:24.000Z | benchmarks/import_cost/functions_100_with_10_contracts.py | kklein/icontract | 718ef1733cc2cce6d3c8f59a5a37de96f8be6664 | [
"MIT"
] | 23 | 2019-04-24T11:09:10.000Z | 2022-02-14T15:56:26.000Z | #!/usr/bin/env python3
import icontract
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func0(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func1(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func2(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func3(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func4(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func5(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func6(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func7(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func8(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func9(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func10(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func11(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func12(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func13(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func14(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func15(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func16(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func17(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func18(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func19(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func20(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func21(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func22(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func23(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func24(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func25(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func26(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func27(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func28(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func29(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func30(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func31(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func32(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func33(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func34(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func35(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func36(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func37(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func38(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func39(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func40(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func41(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func42(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func43(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func44(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func45(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func46(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func47(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func48(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func49(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func50(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func51(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func52(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func53(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func54(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func55(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func56(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func57(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func58(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func59(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func60(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func61(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func62(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func63(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func64(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func65(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func66(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func67(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func68(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func69(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func70(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func71(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func72(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func73(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func74(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func75(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func76(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func77(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func78(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func79(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func80(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func81(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func82(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func83(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func84(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func85(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func86(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func87(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func88(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func89(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func90(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func91(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func92(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func93(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func94(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func95(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func96(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func97(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func98(x: int) -> None:
pass
@icontract.require(lambda x: x > 0)
@icontract.require(lambda x: x > 1)
@icontract.require(lambda x: x > 2)
@icontract.require(lambda x: x > 3)
@icontract.require(lambda x: x > 4)
@icontract.require(lambda x: x > 5)
@icontract.require(lambda x: x > 6)
@icontract.require(lambda x: x > 7)
@icontract.require(lambda x: x > 8)
@icontract.require(lambda x: x > 9)
def some_func99(x: int) -> None:
pass
| 28.816821 | 35 | 0.683181 | 6,706 | 40,430 | 4.103937 | 0.018491 | 0.581374 | 0.79939 | 0.835725 | 0.976999 | 0.976999 | 0.976999 | 0.976999 | 0.976999 | 0.976999 | 0 | 0.034798 | 0.15345 | 40,430 | 1,402 | 36 | 28.837375 | 0.769298 | 0.000519 | 0 | 0.915903 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.083264 | false | 0.083264 | 0.000833 | 0 | 0.084097 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 11 |
df69e535f13ac311198bd4a7f6a41913c01cffe4 | 8,786 | py | Python | code/Autoencoder.py | SSANGMAN/Anomaly_Detection | 0607efbbb85e9b52f34e514c73395e5c446c771e | [
"MIT"
] | 3 | 2020-01-08T08:20:02.000Z | 2020-12-09T13:07:27.000Z | code/Autoencoder.py | SSANGMAN/Anomaly_Detection | 0607efbbb85e9b52f34e514c73395e5c446c771e | [
"MIT"
] | null | null | null | code/Autoencoder.py | SSANGMAN/Anomaly_Detection | 0607efbbb85e9b52f34e514c73395e5c446c771e | [
"MIT"
] | 1 | 2020-12-09T13:07:29.000Z | 2020-12-09T13:07:29.000Z | import numpy as np
from sklearn import metrics
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, GaussianNoise
from keras.callbacks import EarlyStopping
import gc
import warnings
warnings.filterwarnings('ignore')
class SimpleUncompleteAutoencoder:
def __init__(self, df):
self.df = df
self.input_dim = self.df.shape[1]
def Modeling(self, train, dense_dim, batchsize = None, validation_size = None):
if batchsize == None:
raise AssertionError("Batchsize must be defined.")
self.train = train
self.dense_dim = dense_dim
model = Sequential()
model.add(Dense(self.dense_dim, input_dim = self.input_dim, activation = 'relu'))
model.add(Dense(self.input_dim))
model.compile(loss = 'mean_squared_error', optimizer = 'adam')
print(model.summary())
self.model = model
self.model.fit(train, train, batch_size = batchsize, validation_split = validation_size,
verbose = 1, epochs = 50, callbacks = [EarlyStopping(monitor = 'val_loss', patience = 3)])
gc.collect()
def Prediction(self, test_data, data_type = None):
self.test_data = test_data
if data_type == None:
raise AssertionError('Data type must be defined.')
elif data_type == 'Insample':
pred = self.model.predict(self.test_data)
score = np.sqrt(metrics.mean_squared_error(pred, self.test_data))
print("Insample Normal Score (RMSE) : {}".format(score))
return pred
elif data_type == 'OutOfSample':
pred = self.model.predict(self.test_data)
score = np.sqrt(metrics.mean_squared_error(pred, self.test_data))
print('Out of Sample Normal Score (RMSE) : {}'.format(score))
return pred
elif data_type == 'Attack':
pred = self.model.predict(self.test_data)
score = np.sqrt(metrics.mean_squared_error(pred, self.test_data))
print('Attack Underway Score (RMSE) : {}'.format(score))
return pred
class SimpleStackedAutoencoder:
def __init__(self, df):
self.df = df
self.input_dim = self.df.shape[1]
def Modeling(self, train, hidden_dim = None, coding_dim = None, batchsize = None, validation_size = None):
if hidden_dim == None:
raise AssertionError("Hidden Layer Dimension must be defined.")
if coding_dim == None:
raise AssertionError("Coding Layer Dimension must be defined.")
if batchsize == None:
raise AssertionError("Batchsize must be defined.")
self.train = train
self.hidden_dim = hidden_dim
self.coding_dim = coding_dim
model = Sequential()
model.add(Dense(self.hidden_dim, input_dim = self.input_dim, activation = 'relu'))
model.add(Dense(self.coding_dim, activation = 'relu'))
model.add(Dense(self.hidden_dim, activation = 'relu'))
model.add(Dense(self.input_dim))
model.compile(loss = 'mean_squared_error', optimizer = 'adam')
print(model.summary())
self.model = model
self.model.fit(train, train, batch_size = batchsize, validation_split = validation_size,
verbose = 1, epochs = 50, callbacks = [EarlyStopping(monitor = 'val_loss', patience = 3)])
gc.collect()
def Prediction(self, test_data, data_type):
self.test_data = test_data
if data_type == None:
raise AssertionError('Data Type must be defined.')
elif data_type == 'Insample':
pred = self.model.predict(self.test_data)
score = np.sqrt(metrics.mean_squared_error(pred, self.test_data))
print("Insample Normal Score (RMSE) : {}".format(score))
return pred
elif data_type == 'OutOfSample':
pred = self.model.predict(self.test_data)
score = np.sqrt(metrics.mean_squared_error(pred, self.test_data))
print("Out of Sample Normal Score (RMSE) : {}".format(score))
return pred
elif data_type =='Attack':
pred = self.model.predict(self.test_data)
score = np.sqrt(metrics.mean_squared_error(pred, self.test_data))
print("Attack Underway Score (RMSE) : {}".format(score))
return pred
class SimpleDenosingAutoencoder:
def __init__(self, df):
self.df = df
self.input_dim = self.df.shape[1]
def Modeling(self, train, hidden_dim = None, coding_dim = None, batchsize = None, validation_size = None, denosing_type = None, std = None):
if hidden_dim == None:
raise AssertionError("Hidden Layer Dimension must be defined.")
if coding_dim == None:
raise AssertionError("Coding Layer Dimension must be defined.")
if batchsize == None:
raise AssertionError("Batchsize must be defined.")
if denosing_type == None:
raise AssertionError("Denosing Type must be Defined. ('Gaussian' or 'Dropout')")
if denosing_type != None:
if denosing_type == "Dropout":
self.train = train
self.hidden_dim = hidden_dim
self.coding_dim = coding_dim
model = Sequential()
model.add(Dense(self.hidden_dim, input_dim = self.input_dim, activation = 'relu'))
model.add(Dropout(0.2))
model.add(Dense(self.coding_dim, activation = 'relu'))
model.add(Dense(self.hidden_dim, activation = 'relu'))
model.add(Dense(self.input_dim))
model.compile(loss = 'mean_squared_error', optimizer = 'adam')
print(model.summary())
self.model = model
self.model.fit(train, train, batch_size = batchsize, validation_split = validation_size,
verbose = 1, epochs = 50, callbacks = [EarlyStopping(monitor = 'val_loss', patience = 3)])
gc.collect()
elif denosing_type == 'Gaussian':
if std == None:
raise AssertionError('Gaussian Noise std must be defined.')
self.train = train
self.hidden_dim = hidden_dim
self.coding_dim = coding_dim
model = Sequential()
model.add(Dense(self.hidden_dim, input_dim = self.input_dim, activation = 'relu'))
model.add(GaussianNoise(std))
model.add(Dense(self.coding_dim, activation = 'relu'))
model.add(Dense(self.hidden_dim, activation = 'relu'))
model.add(Dense(self.input_dim))
model.compile(loss = 'mean_squared_error', optimizer = 'adam')
print(model.summary())
self.model = model
self.model.fit(train, train, batch_size = batchsize, validation_split = validation_size,
verbose = 1, epochs = 50, callbacks = [EarlyStopping(monitor = 'val_loss', patience = 3)])
gc.collect()
def Prediction(self, test_data, data_type):
self.test_data = test_data
if data_type == None:
raise AssertionError('Data Type must be defined.')
elif data_type == 'Insample':
pred = self.model.predict(self.test_data)
score = np.sqrt(metrics.mean_squared_error(pred, self.test_data))
print("Insample Normal Score (RMSE) : {}".format(score))
return pred
elif data_type == 'OutOfSample':
pred = self.model.predict(self.test_data)
score = np.sqrt(metrics.mean_squared_error(pred, self.test_data))
print("Out of Sample Normal Score (RMSE) : {}".format(score))
return pred
elif data_type =='Attack':
pred = self.model.predict(self.test_data)
score = np.sqrt(metrics.mean_squared_error(pred, self.test_data))
print("Attack Underway Score (RMSE) : {}".format(score))
return pred | 39.936364 | 144 | 0.559527 | 939 | 8,786 | 5.073482 | 0.106496 | 0.04534 | 0.060453 | 0.049958 | 0.881612 | 0.881612 | 0.875105 | 0.867758 | 0.867758 | 0.867758 | 0 | 0.003629 | 0.341452 | 8,786 | 220 | 145 | 39.936364 | 0.819737 | 0 | 0 | 0.814103 | 0 | 0 | 0.110504 | 0 | 0 | 0 | 0 | 0 | 0.076923 | 1 | 0.057692 | false | 0 | 0.044872 | 0 | 0.179487 | 0.083333 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
df75755e75f6a0f90615de8d6d0c99d3c805c2d8 | 49,756 | py | Python | mff/models/combined.py | alvarovm/mff | cd1b22b606dfd64d91dc94fece72ad6a707212af | [
"Apache-2.0"
] | 14 | 2019-03-22T18:57:34.000Z | 2021-12-15T11:37:17.000Z | mff/models/combined.py | alvarovm/mff | cd1b22b606dfd64d91dc94fece72ad6a707212af | [
"Apache-2.0"
] | 4 | 2019-06-18T14:55:46.000Z | 2019-11-26T19:34:59.000Z | mff/models/combined.py | alvarovm/mff | cd1b22b606dfd64d91dc94fece72ad6a707212af | [
"Apache-2.0"
] | 3 | 2019-08-05T14:42:20.000Z | 2022-03-16T18:48:54.000Z | # -*- coding: utf-8 -*-
import json
import logging
import warnings
from itertools import combinations_with_replacement
from pathlib import Path
import numpy as np
from mff import gp, interpolation, kernels, utility, models
from .base import Model
logger = logging.getLogger(__name__)
class NpEncoder(json.JSONEncoder):
def default(self, obj):
if isinstance(obj, np.integer):
return int(obj)
elif isinstance(obj, np.floating):
return float(obj)
elif isinstance(obj, np.ndarray):
return obj.tolist()
else:
return super(NpEncoder, self).default(obj)
class CombinedSingleSpeciesModel(Model):
""" 2- and 3-body single species model class
Class managing the Gaussian processes and their mapped counterparts
Args:
element (int): The atomic number of the element considered
r_cut (foat): The cutoff radius used to carve the atomic environments
sigma_2b (foat): Lengthscale parameter of the 2-body Gaussian process
sigma_3b (foat): Lengthscale parameter of the 2-body Gaussian process
theta_2b (float): decay ratio of the cutoff function in the 2-body Gaussian Process
theta_3b (float): decay ratio of the cutoff function in the 3-body Gaussian Process
noise (float): noise value associated with the training output data
Attributes:
gp_2b (method): The 2-body single species Gaussian Process
gp_3b (method): The 3-body single species Gaussian Process
grid_2b (method): The 2-body single species tabulated potential
grid_3b (method): The 3-body single species tabulated potential
grid_start (float): Minimum atomic distance for which the grids are defined (cannot be 0.0)
grid_num (int): number of points per side used to create the 2- and 3-body grid. The 3-body
grid is 3-dimensional, therefore its total number of grid points will be grid_num^3
"""
def __init__(self, element, r_cut, sigma_2b, sigma_3b, theta_2b, theta_3b, noise, rep_sig=1, **kwargs):
super().__init__()
self.element = element
self.r_cut = r_cut
self.rep_sig = rep_sig
kernel_2b = kernels.TwoBodySingleSpeciesKernel(
theta=[sigma_2b, theta_2b, r_cut])
self.gp_2b = gp.GaussianProcess(
kernel=kernel_2b, noise=noise, **kwargs)
kernel_3b = kernels.ThreeBodySingleSpeciesKernel(
theta=[sigma_3b, theta_3b, r_cut])
self.gp_3b = gp.GaussianProcess(
kernel=kernel_3b, noise=noise, **kwargs)
self.grid_2b, self.grid_3b, self.grid_start, self.grid_num = None, None, None, None
def fit(self, confs, forces, ncores=1):
""" Fit the GP to a set of training forces using a 2- and
3-body single species force-force kernel functions. The 2-body Gaussian
process is first fitted, then the 3-body GP is fitted to the difference
between the training forces and the 2-body predictions of force on the
training configurations
Args:
confs (list): List of M x 5 arrays containing coordinates and
atomic numbers of atoms within a cutoff from the central one
forces (array) : Array containing the vector forces on
the central atoms of the training configurations
ncores (int): number of CPUs to use for the gram matrix evaluation
"""
hypotetical_model_name = ("models/MODEL_ker_TwoBodySingleSpecies_ntr_%i.json" %(len(forces)))
try:
model_2b = models.TwoBodySingleSpeciesModel.from_json(hypotetical_model_name)
self.rep_sig = model_2b.rep_sig
self.gp_2b = model_2b.gp
if self.rep_sig:
self.rep_forces = utility.get_repulsive_forces(confs, self.rep_sig)
forces -= self.rep_forces
print("Loaded 2-body model to bootstart training")
except:
if self.rep_sig:
self.rep_sig = utility.find_repulstion_sigma(confs)
self.rep_forces = utility.get_repulsive_forces(confs, self.rep_sig)
forces -= self.rep_forces
self.gp_2b.fit(confs, forces, ncores=ncores)
two_body_forces = self.gp_2b.predict(confs, ncores=ncores)
self.gp_3b.fit(confs, forces - two_body_forces, ncores=ncores)
def fit_energy(self, glob_confs, energies, ncores=1):
""" Fit the GP to a set of training energies using a 2- and
3-body single species energy-energy kernel functions. The 2-body Gaussian
process is first fitted, then the 3-body GP is fitted to the difference
between the training energies and the 2-body predictions of energies on the
training configurations.
Args:
glob_confs (list of lists): List of configurations arranged so that
grouped configurations belong to the same snapshot
energies (array) : Array containing the total energy of each snapshot
ncores (int): number of CPUs to use for the gram matrix evaluation
"""
hypotetical_model_name = "models/MODEL_ker_TwoBodySingleSpecies_ntr_%i.json" %(len(energies))
try:
model_2b = models.TwoBodySingleSpeciesModel.from_json(hypotetical_model_name)
self.rep_sig = model_2b.rep_sig
self.gp_2b = model_2b.gp
if self.rep_sig:
self.rep_energies = utility.get_repulsive_energies(
glob_confs, self.rep_sig)
energies -= self.rep_energies
print("Loaded 2-body model to bootstart training")
except:
if self.rep_sig:
self.rep_sig = utility.find_repulstion_sigma(glob_confs)
self.rep_energies = utility.get_repulsive_energies(
glob_confs, self.rep_sig)
energies -= self.rep_energies
self.gp_2b.fit_energy(glob_confs, energies, ncores=ncores)
two_body_energies = self.gp_2b.predict_energy(
glob_confs, ncores=ncores)
self.gp_3b.fit_energy(glob_confs, energies -
two_body_energies, ncores=ncores)
def fit_force_and_energy(self, confs, forces, glob_confs, energies, ncores=1):
""" Fit the GP to a set of training energies using a 2- and
3-body single species force-force, energy-energy, and energy-forces kernel
functions. The 2-body Gaussian process is first fitted, then the 3-body GP
is fitted to the difference between the training energies (and forces) and
the 2-body predictions of energies (and forces) on the training configurations.
Args:
confs (list): List of M x 5 arrays containing coordinates and
atomic numbers of atoms within a cutoff from the central one
forces (array) : Array containing the vector forces on
the central atoms of the training configurations
glob_confs (list of lists): List of configurations arranged so that
grouped configurations belong to the same snapshot
energies (array) : Array containing the total energy of each snapshot
ncores (int): number of CPUs to use for the gram matrix evaluation
"""
hypotetical_model_name = "models/MODEL_ker_TwoBodySingleSpecies_ntr_%i.json" %(len(energies)+len(forces))
try:
model_2b = models.TwoBodySingleSpeciesModel.from_json(hypotetical_model_name)
self.rep_sig = model_2b.rep_sig
self.gp_2b = model_2b.gp
if self.rep_sig:
self.rep_energies = utility.get_repulsive_energies(
glob_confs, self.rep_sig)
energies -= self.rep_energies
self.rep_forces = utility.get_repulsive_forces(confs, self.rep_sig)
forces -= self.rep_forces
print("Loaded 2-body model to bootstart training")
except:
if self.rep_sig:
self.rep_sig = utility.find_repulstion_sigma(confs)
self.rep_energies = utility.get_repulsive_energies(
glob_confs, self.rep_sig)
energies -= self.rep_energies
self.rep_forces = utility.get_repulsive_forces(confs, self.rep_sig)
forces -= self.rep_forces
self.gp_2b.fit_force_and_energy(
confs, forces, glob_confs, energies, ncores=ncores)
two_body_forces = self.gp_2b.predict(confs, ncores=ncores)
two_body_energies = self.gp_2b.predict_energy(
glob_confs, ncores=ncores)
self.gp_3b.fit_force_and_energy(
confs, forces - two_body_forces, glob_confs, energies - two_body_energies, ncores=ncores)
def predict(self, confs, return_std=False, ncores=1):
""" Predict the forces acting on the central atoms of confs using the
2- and 3-body GPs. The total force is the sum of the two predictions.
Args:
confs (list): List of M x 5 arrays containing coordinates and
atomic numbers of atoms within a cutoff from the central one
return_std (bool): if True, returns the standard deviation
associated to predictions according to the GP framework
Returns:
forces (array): array of force vectors predicted by the GPs
forces_errors (array): errors associated to the force predictions,
returned only if return_std is True
"""
if return_std:
if self.rep_sig:
rep_forces = utility.get_repulsive_forces(confs, self.rep_sig)
force_2b, std_2b = self.gp_2b.predict(confs, return_std)
force_2b += rep_forces
else:
force_2b, std_2b = self.gp_2b.predict(
confs, return_std, ncores=ncores)
force_3b, std_3b = self.gp_2b.predict(
confs, return_std, ncores=ncores)
return force_2b + force_3b, std_2b + std_3b
else:
if self.rep_sig:
rep_forces = utility.get_repulsive_forces(confs, self.rep_sig)
return self.gp_2b.predict(confs, return_std, ncores=ncores) + rep_forces + \
self.gp_3b.predict(confs, return_std, ncores=ncores)
else:
return self.gp_2b.predict(confs, return_std, ncores=ncores) + \
self.gp_3b.predict(confs, return_std, ncores=ncores)
def predict_energy(self, glob_confs, return_std=False, ncores=1):
""" Predict the local energies of the central atoms of confs using the
2- and 3-body GPs. The total force is the sum of the two predictions.
Args:
glob_confs (list of lists): List of configurations arranged so that
grouped configurations belong to the same snapshot
return_std (bool): if True, returns the standard deviation
associated to predictions according to the GP framework
Returns:
energies (array) : Array containing the total energy of each snapshot
energies_errors (array): errors associated to the energies predictions,
returned only if return_std is True
"""
if return_std:
if self.rep_sig:
rep_energies = utility.get_repulsive_energies(
glob_confs, self.rep_sig)
force_2b, std_2b = self.gp_2b.predict_energy(
glob_confs, return_std, ncores=ncores)
energy_2b += rep_energies
else:
energy_2b, std_2b = self.gp_2b.predict_energy(
glob_confs, return_std, ncores=ncoress)
energy_3b, std_3b = self.gp_2b.predict_energy(
glob_confs, return_std, ncores=ncores)
return energy_2b + energy_3b, std_2b + std_3b
else:
if self.rep_sig:
rep_energies = utility.get_repulsive_energies(
glob_confs, self.rep_sig)
return self.gp_2b.predict_energy(glob_confs, return_std) + rep_energies +\
self.gp_3b.predict_energy(
glob_confs, return_std, ncores=ncores)
else:
return self.gp_2b.predict_energy(glob_confs, return_std, ncores=ncores) + \
self.gp_3b.predict_energy(
glob_confs, return_std, ncores=ncores)
def build_grid(self, start, num_2b, num_3b, ncores=1):
""" Build the mapped 2- and 3-body potentials.
Calculates the energy predicted by the GP for two and three atoms at all possible combination
of num distances ranging from start to r_cut. The energy for the 3-body mapped grid is
calculated only for ``valid`` triplets of atoms, i.e. sets of three distances which
form a triangle (this is checked via the triangle inequality).
The grid building exploits all the permutation invariances to reduce the number of energy
calculations needed to fill the grid.
The computed 2-body energies are stored in an array of values, and a 1D spline interpolation is created.
The computed 3-body energies are stored in a 3D cube of values, and a 3D spline interpolation is
created.
The total force or local energy can then be calculated for any atom by summing the pairwise and
triplet contributions of every valid couple and triplet of atoms of which one is always the central one.
The prediction is done by the ``calculator`` module, which is built to work within
the ase python package.
Args:
start (float): smallest interatomic distance for which the energy is predicted
by the GP and stored inn the 3-body mapped potential
num_2b (int):number of points to use in the grid of the 2-body mapped potential
num_3b (int): number of points to use to generate the list of distances used to
generate the triplets of atoms for the 2-body mapped potential
ncores (int): number of CPUs to use to calculate the energy predictions
"""
dists_2b = np.linspace(start, self.r_cut, num_2b)
confs = np.zeros((num_2b, 1, 5))
confs[:, 0, 0] = dists_2b
confs[:, 0, 3], confs[:, 0, 4] = self.element, self.element
grid_data = self.gp_2b.predict_energy(
confs, ncores=ncores, mapping=True)
if self.rep_sig:
grid_data += utility.get_repulsive_energies(
confs, self.rep_sig, mapping=True)
grid_2b = interpolation.Spline1D(dists_2b, grid_data)
# Mapping 3 body part
dists_3b = np.linspace(start, self.r_cut, num_3b)
inds, r_ij_x, r_ki_x, r_ki_y = self.generate_triplets(dists_3b)
confs = np.zeros((len(r_ij_x), 2, 5))
confs[:, 0, 0] = r_ij_x # Element on the x axis
confs[:, 1, 0] = r_ki_x # Reshape into confs shape: this is x2
confs[:, 1, 1] = r_ki_y # Reshape into confs shape: this is y2
# Permutations of elements
confs[:, :, 3] = self.element # Central element is always element 1
# Element on the x axis is always element 2
confs[:, 0, 4] = self.element
# Element on the xy plane is always element 3
confs[:, 1, 4] = self.element
grid_3b = np.zeros((num_3b, num_3b, num_3b))
grid_3b[inds] = self.gp_3b.predict_energy(
confs, ncores=ncores, mapping=True).flatten()
for ind_i in range(num_3b):
for ind_j in range(ind_i + 1):
for ind_k in range(ind_j + 1):
grid_3b[ind_i, ind_k, ind_j] = grid_3b[ind_i, ind_j, ind_k]
grid_3b[ind_j, ind_i, ind_k] = grid_3b[ind_i, ind_j, ind_k]
grid_3b[ind_j, ind_k, ind_i] = grid_3b[ind_i, ind_j, ind_k]
grid_3b[ind_k, ind_i, ind_j] = grid_3b[ind_i, ind_j, ind_k]
grid_3b[ind_k, ind_j, ind_i] = grid_3b[ind_i, ind_j, ind_k]
grid_3b = interpolation.Spline3D(dists_3b, dists_3b, dists_3b, grid_3b)
self.grid_2b = grid_2b
self.grid_3b = grid_3b
self.grid_num_2b = num_2b
self.grid_num_3b = num_3b
self.grid_start = start
def save(self, path):
""" Save the model.
This creates a .json file containing the parameters of the model and the
paths to the GP objects and the mapped potentials, which are saved as
separate .gpy and .gpz files, respectively.
Args:
path (str): path to the file
"""
if not isinstance(path, Path):
path = Path(path)
### SAVE THE 2B MODEL ###
params = {
'model': self.__class__.__name__,
'element': self.element,
'r_cut': self.r_cut,
'rep_sig': self.rep_sig,
'fitted': self.gp_2b.fitted,
'gp_2b': {
'kernel': self.gp_2b.kernel.kernel_name,
'n_train': self.gp_2b.n_train,
'sigma': self.gp_2b.kernel.theta[0],
'theta': self.gp_2b.kernel.theta[1],
'noise': self.gp_2b.noise
},
'gp_3b': {
'kernel': self.gp_3b.kernel.kernel_name,
'n_train': self.gp_3b.n_train,
'sigma': self.gp_3b.kernel.theta[0],
'theta': self.gp_3b.kernel.theta[1],
'noise': self.gp_3b.noise
},
'grid_2b': {
'r_min': self.grid_start,
'r_num': self.grid_num_2b,
'filename': {}
} if self.grid_2b else {},
'grid_3b': {
'r_min': self.grid_start,
'r_num': self.grid_num_3b,
'filename': {}
} if self.grid_3b else {}
}
gp_filename_2b = "GP_ker_{p[gp_2b][kernel]}_ntr_{p[gp_2b][n_train]}.npy".format(
p=params)
params['gp_2b']['filename'] = gp_filename_2b
self.gp_2b.save(path / gp_filename_2b)
if self.grid_2b:
grid_filename_2b = "GRID_ker_{p[gp_2b][kernel]}_ntr_{p[gp_2b][n_train]}.npz".format(
p=params)
print("Saved 2-body grid under name %s" % (grid_filename_2b))
params['grid_2b']['filename'] = grid_filename_2b
self.grid_2b.save(path / grid_filename_2b)
### SAVE THE 3B MODEL ###
gp_filename_3b = "GP_ker_{p[gp_3b][kernel]}_ntr_{p[gp_3b][n_train]}.npy".format(
p=params)
params['gp_3b']['filename'] = gp_filename_3b
self.gp_3b.save(path / gp_filename_3b)
if self.grid_3b:
grid_filename_3b = "GRID_ker_{p[gp_3b][kernel]}_ntr_{p[gp_3b][n_train]}.npz".format(
p=params)
print("Saved 3-body grid under name %s" % (grid_filename_3b))
params['grid_3b']['filename'] = grid_filename_3b
self.grid_3b.save(path / grid_filename_3b)
with open(path / "MODEL_combined_ntr_{p[gp_2b][n_train]}.json".format(p=params), 'w') as fp:
json.dump(params, fp, indent=4, cls=NpEncoder)
print("Saved model with name: MODEL_combined_ntr_{p[gp_2b][n_train]}.json".format(p=params))
@classmethod
def from_json(cls, path):
""" Load the model.
Loads the model, the associated GPs and the mapped potentials, if available.
Args:
path (str): path to the .json model file
Return:
model (obj): the model object
"""
if not isinstance(path, Path):
path = Path(path)
directory, prefix = path.parent, path.stem
with open(path) as fp:
params = json.load(fp)
model = cls(params['element'],
params['r_cut'],
params['gp_2b']['sigma'],
params['gp_3b']['sigma'],
params['gp_2b']['theta'],
params['gp_3b']['theta'],
params['gp_2b']['noise'],
params['rep_sig'])
gp_filename_2b = params['gp_2b']['filename']
gp_filename_3b = params['gp_3b']['filename']
try:
model.gp_2b.load(directory / gp_filename_2b)
except:
warnings.warn("The 2-body GP file is missing")
pass
try:
model.gp_3b.load(directory / gp_filename_3b)
except:
warnings.warn("The 3-body GP file is missing")
pass
if params['grid_2b']:
grid_filename_2b = params['grid_2b']['filename']
model.grid_2b = interpolation.Spline1D.load(
directory / grid_filename_2b)
grid_filename_3b = params['grid_3b']['filename']
model.grid_3b = interpolation.Spline3D.load(
directory / grid_filename_3b)
model.grid_start = params['grid_2b']['r_min']
model.grid_num_2b = params['grid_2b']['r_num']
model.grid_num_3b = params['grid_3b']['r_num']
return model
def save_gp(self, filename_2b, filename_3b):
""" Saves the GP objects, now obsolete
"""
warnings.warn('use save and load function', DeprecationWarning)
self.gp_2b.save(filename_2b)
self.gp_3b.save(filename_3b)
def load_gp(self, filename_2b, filename_3b):
""" Loads the GP objects, now obsolete
"""
warnings.warn('use save and load function', DeprecationWarning)
self.gp_2b.load(filename_2b)
self.gp_3b.load(filename_3b)
@staticmethod
def generate_triplets(dists):
""" Generate a list of all valid triplets using perutational invariance.
Calculates the energy predicted by the GP for three atoms at all possible combination
of num distances ranging from start to r_cut. The energy is calculated only for ``valid``
triplets of atoms, i.e. sets of three distances which form a triangle (this is checked via
the triangle inequality). The grid building exploits all the permutation invariances to
reduce the number of energy calculations needed to fill the grid.
The computed energies are stored in a 3D cube of values, and a 3D spline interpolation is
created, which can be used to predict the energy and, through its analytic derivative,
the force associated to any triplet of atoms.
The total force or local energy can then be calculated for any atom by summing the
triplet contributions of every valid triplet of atoms of which one is always the central one.
The prediction is done by the ``calculator`` module which is built to work within
the ase python package.
Args:
dists (array): array of floats containing all of the distances which can be used to
build triplets of atoms. This array is created by calling np.linspace(start, r_cut, num)
Returns:
inds (array): array of booleans indicating which triplets (three distance values) need to be
evaluated to fill the 3D grid of energy values.
r_ij_x (array): array containing the x coordinate of the second atom j w.r.t. the central atom i
r_ki_x (array): array containing the x coordinate of the third atom k w.r.t. the central atom i
r_ki_y (array): array containing the y coordinate of the third atom k w.r.t. the central atom i
"""
d_ij, d_jk, d_ki = np.meshgrid(
dists, dists, dists, indexing='ij', sparse=False, copy=True)
# Valid triangles according to triangle inequality
inds = np.logical_and(
d_ij <= d_jk + d_ki, np.logical_and(d_jk <= d_ki + d_ij, d_ki <= d_ij + d_jk))
# Utilizing permutation invariance
inds = np.logical_and(np.logical_and(d_ij >= d_jk, d_jk >= d_ki), inds)
# Element on the x axis
r_ij_x = d_ij[inds]
# Element on the xy plane
r_ki_x = (d_ij[inds] ** 2 - d_jk[inds] ** 2 +
d_ki[inds] ** 2) / (2 * d_ij[inds])
# using abs to avoid numerical error near to 0
r_ki_y = np.sqrt(np.abs(d_ki[inds] ** 2 - r_ki_x ** 2))
return inds, r_ij_x, r_ki_x, r_ki_y
class CombinedManySpeciesModel(Model):
""" 2- and 3-body many species model class
Class managing the Gaussian processes and their mapped counterparts
Args:
elements (list): List containing the atomic numbers in increasing order
r_cut (foat): The cutoff radius used to carve the atomic environments
sigma_2b (foat): Lengthscale parameter of the 2-body Gaussian process
sigma_3b (foat): Lengthscale parameter of the 2-body Gaussian process
theta_2b (float): decay ratio of the cutoff function in the 2-body Gaussian Process
theta_3b (float): decay ratio of the cutoff function in the 3-body Gaussian Process
noise (float): noise value associated with the training output data
Attributes:
gp_2b (method): The 2-body single species Gaussian Process
gp_3b (method): The 3-body single species Gaussian Process
grid_2b (list): Contains the three 2-body two species tabulated potentials, accounting for
interactions between two atoms of types 0-0, 0-1, and 1-1.
grid_2b (list): Contains the three 3-body two species tabulated potentials, accounting for
interactions between three atoms of types 0-0-0, 0-0-1, 0-1-1, and 1-1-1.
grid_start (float): Minimum atomic distance for which the grids are defined (cannot be 0.0)
grid_num_2b (int):number of points to use in the grid of the 2-body mapped potential
grid_num_3b (int): number of points to use to generate the list of distances used to
generate the triplets of atoms for the 2-body mapped potential
"""
def __init__(self, elements, r_cut, sigma_2b, sigma_3b, theta_2b, theta_3b, noise, rep_sig=1, **kwargs):
super().__init__()
self.elements = list(np.sort(elements))
self.r_cut = r_cut
self.rep_sig = rep_sig
kernel_2b = kernels.TwoBodyManySpeciesKernel(
theta=[sigma_2b, theta_2b, r_cut])
self.gp_2b = gp.GaussianProcess(
kernel=kernel_2b, noise=noise, **kwargs)
kernel_3b = kernels.ThreeBodyManySpeciesKernel(
theta=[sigma_3b, theta_3b, r_cut])
self.gp_3b = gp.GaussianProcess(
kernel=kernel_3b, noise=noise, **kwargs)
self.grid_2b, self.grid_3b, self.grid_start, self.grid_num_2b, self.grid_num_3b = {
}, {}, None, None, None
def fit(self, confs, forces, ncores=1):
""" Fit the GP to a set of training forces using a 2- and
3-body single species force-force kernel functions. The 2-body Gaussian
process is first fitted, then the 3-body GP is fitted to the difference
between the training forces and the 2-body predictions of force on the
training configurations
Args:
confs (list): List of M x 5 arrays containing coordinates and
atomic numbers of atoms within a cutoff from the central one
forces (array) : Array containing the vector forces on
the central atoms of the training configurations
ncores (int): number of CPUs to use for the gram matrix evaluation
"""
hypotetical_model_name = "models/MODEL_ker_TwoBodyManySpecies_ntr_%i.json" %(len(forces))
try:
model_2b = models.TwoBodyManySpeciesModel.from_json(hypotetical_model_name)
self.rep_sig = model_2b.rep_sig
self.gp_2b = model_2b.gp
if self.rep_sig:
self.rep_sig = utility.find_repulstion_sigma(confs)
self.rep_forces = utility.get_repulsive_forces(confs, self.rep_sig)
forces -= self.rep_forces
print("Loaded 2-body model to bootstart training")
except:
if self.rep_sig:
self.rep_sig = utility.find_repulstion_sigma(confs)
self.rep_forces = utility.get_repulsive_forces(confs, self.rep_sig)
forces -= self.rep_forces
self.gp_2b.fit(confs, forces, ncores=ncores)
ntr = len(confs)
two_body_forces = self.gp_2b.predict(confs, ncores=ncores)
self.gp_3b.fit(confs, forces - two_body_forces, ncores=ncores)
def fit_energy(self, glob_confs, energies, ncores=1):
""" Fit the GP to a set of training energies using a 2- and
3-body single species energy-energy kernel functions. The 2-body Gaussian
process is first fitted, then the 3-body GP is fitted to the difference
between the training energies and the 2-body predictions of energies on the
training configurations.
Args:
glob_confs (list of lists): List of configurations arranged so that
grouped configurations belong to the same snapshot
energies (array) : Array containing the total energy of each snapshot
ncores (int): number of CPUs to use for the gram matrix evaluation
"""
hypotetical_model_name = "models/MODEL_ker_TwoBodyManySpecies_ntr_%i.json" %(len(energies))
try:
model_2b = models.TwoBodyManySpeciesModel.from_json(hypotetical_model_name)
self.rep_sig = model_2b.rep_sig
self.gp_2b = model_2b.gp
if self.rep_sig:
self.rep_energies = utility.get_repulsive_energies(
glob_confs, self.rep_sig)
energies -= self.rep_energies
print("Loaded 2-body model to bootstart training")
except:
if self.rep_sig:
self.rep_sig = utility.find_repulstion_sigma(glob_confs)
self.rep_energies = utility.get_repulsive_energies(
glob_confs, self.rep_sig)
energies -= self.rep_energies
self.gp_2b.fit_energy(glob_confs, energies, ncores=1)
ntr = len(glob_confs)
two_body_energies = self.gp_2b.predict_energy(
glob_confs, ncores=ncores)
self.gp_3b.fit_energy(glob_confs, energies -
two_body_energies, ncores=ncores)
def fit_force_and_energy(self, confs, forces, glob_confs, energies, ncores=1):
""" Fit the GP to a set of training energies using a 2- and
3-body single species force-force, energy-energy, and energy-forces kernel
functions. The 2-body Gaussian process is first fitted, then the 3-body GP
is fitted to the difference between the training energies (and forces) and
the 2-body predictions of energies (and forces) on the training configurations.
Args:
confs (list): List of M x 5 arrays containing coordinates and
atomic numbers of atoms within a cutoff from the central one
forces (array) : Array containing the vector forces on
the central atoms of the training configurations
glob_confs (list of lists): List of configurations arranged so that
grouped configurations belong to the same snapshot
energies (array) : Array containing the total energy of each snapshot
ncores (int): number of CPUs to use for the gram matrix evaluation
"""
hypotetical_model_name = "models/MODEL_ker_TwoBodyManySpecies_ntr_%i.json" %(len(forces) + len(energies))
try:
model_2b = models.TwoBodyManySpeciesModel.from_json(hypotetical_model_name)
self.rep_sig = model_2b.rep_sig
self.gp_2b = model_2b.gp
if self.rep_sig:
self.rep_energies = utility.get_repulsive_energies(
glob_confs, self.rep_sig)
energies -= self.rep_energies
self.rep_forces = utility.get_repulsive_forces(confs, self.rep_sig)
forces -= self.rep_forces
print("Loaded 2-body model to bootstart training")
except:
if self.rep_sig:
self.rep_sig = utility.find_repulstion_sigma(confs)
self.rep_energies = utility.get_repulsive_energies(
glob_confs, self.rep_sig)
energies -= self.rep_energies
self.rep_forces = utility.get_repulsive_forces(confs, self.rep_sig)
forces -= self.rep_forces
self.gp_2b.fit_force_and_energy(
confs, forces, glob_confs, energies, ncores=ncores)
two_body_forces = self.gp_2b.predict(confs, ncores=ncores)
two_body_energies = self.gp_2b.predict_energy(
glob_confs, ncores=ncores)
self.gp_3b.fit_force_and_energy(
confs, forces - two_body_forces, glob_confs, energies - two_body_energies, ncores=ncores)
def predict(self, confs, return_std=False, ncores=1):
""" Predict the forces acting on the central atoms of confs using the
2- and 3-body GPs. The total force is the sum of the two predictions.
Args:
confs (list): List of M x 5 arrays containing coordinates and
atomic numbers of atoms within a cutoff from the central one
return_std (bool): if True, returns the standard deviation
associated to predictions according to the GP framework
Returns:
forces (array): array of force vectors predicted by the GPs
forces_errors (array): errors associated to the force predictions,
returned only if return_std is True
"""
if return_std:
if self.rep_sig:
rep_forces = utility.get_repulsive_forces(confs, self.rep_sig)
force_2b, std_2b = self.gp_2b.predict(
confs, return_std, ncores=ncores)
force_2b += rep_forces
else:
force_2b, std_2b = self.gp_2b.predict(
confs, return_std, ncores=ncores)
force_3b, std_3b = self.gp_2b.predict(
confs, return_std, ncores=ncores)
return force_2b + force_3b, std_2b + std_3b
else:
if self.rep_sig:
rep_forces = utility.get_repulsive_forces(confs, self.rep_sig)
return self.gp_2b.predict(confs, return_std, ncores=ncores) + rep_forces + \
self.gp_3b.predict(confs, return_std, ncores=ncores)
else:
return self.gp_2b.predict(confs, return_std, ncores=ncores) + \
self.gp_3b.predict(confs, return_std, ncores=ncores)
def predict_energy(self, glob_confs, return_std=False, ncores=1):
""" Predict the local energies of the central atoms of confs using the
2- and 3-body GPs. The total force is the sum of the two predictions.
Args:
glob_confs (list of lists): List of configurations arranged so that
grouped configurations belong to the same snapshot
return_std (bool): if True, returns the standard deviation
associated to predictions according to the GP framework
Returns:
energies (array) : Array containing the total energy of each snapshot
energies_errors (array): errors associated to the energies predictions,
returned only if return_std is True
"""
if return_std:
if self.rep_sig:
rep_energies = utility.get_repulsive_energies(
glob_confs, self.rep_sig)
force_2b, std_2b = self.gp_2b.predict_energy(
glob_confs, return_std, ncores=ncores)
energy_2b += rep_energies
else:
energy_2b, std_2b = self.gp_2b.predict_energy(
glob_confs, return_std, ncores=ncores)
energy_3b, std_3b = self.gp_2b.predict_energy(
glob_confs, return_std, ncores=ncores)
return energy_2b + energy_3b, std_2b + std_3b
else:
if self.rep_sig:
rep_energies = utility.get_repulsive_energies(
glob_confs, self.rep_sig)
return self.gp_2b.predict_energy(glob_confs, return_std, ncores=ncores) + rep_energies +\
self.gp_3b.predict_energy(
glob_confs, return_std, ncores=ncores)
else:
return self.gp_2b.predict_energy(glob_confs, return_std, ncores=ncores) + \
self.gp_3b.predict_energy(
glob_confs, return_std, ncores=ncores)
def build_grid(self, start, num_2b, num_3b, ncores=1):
"""Function used to create the three different 2-body energy grids for
atoms of elements 0-0, 0-1, and 1-1, and the four different 3-body energy grids for
atoms of elements 0-0-0, 0-0-1, 0-1-1, and 1-1-1. The function calls the
``build_grid_3b`` function for each of the 3-body grids to build.
Args:
start (float): smallest interatomic distance for which the energy is predicted
by the GP and stored inn the 3-body mapped potential
num (int): number of points to use in the grid of the 2-body mapped potentials
num_3b (int): number of points to use to generate the list of distances used to
generate the triplets of atoms for the 3-body mapped potentials
ncores (int): number of CPUs to use to calculate the energy predictions
"""
self.grid_start = start
self.grid_num_2b = num_2b
self.grid_num_3b = num_2b
perm_list_2b = list(combinations_with_replacement(self.elements, 2))
perm_list_3b = list(combinations_with_replacement(self.elements, 3))
dists_2b = np.linspace(start, self.r_cut, num_2b)
confs_2b = np.zeros((num_2b, 1, 5))
confs_2b[:, 0, 0] = dists_2b
for pair in perm_list_2b: # in this for loop, predicting then save for each individual one
confs_2b[:, 0, 3], confs_2b[:, 0,
4] = pair[0], pair[1]
mapped_energies = self.gp_2b.predict_energy(
list(confs_2b), ncores=ncores, mapping=True)
if self.rep_sig:
mapped_energies += utility.get_repulsive_energies(
confs_2b, self.rep_sig, mapping=True)
self.grid_2b[pair] = interpolation.Spline1D(dists_2b, mapped_energies)
dists_3b = np.linspace(start, self.r_cut, num_3b)
for trip in perm_list_3b:
self.grid_3b[trip] = self.build_grid_3b(
dists_3b, trip[0], trip[1], trip[2], ncores = ncores)
def build_grid_3b(self, dists, element_k, element_i, element_j, ncores=1):
""" Build a mapped 3-body potential.
Calculates the energy predicted by the GP for three atoms of elements element_i, element_j, element_k,
at all possible combinations of num distances ranging from start to r_cut.
The energy is calculated only for ``valid`` triplets of atoms, i.e. sets of three distances
which form a triangle (this is checked via the triangle inequality), found by calling the
``generate_triplets_with_permutation_invariance`` function.
The computed energies are stored in a 3D cube of values, and a 3D spline interpolation is
created, which can be used to predict the energy and, through its analytic derivative,
the force associated to any triplet of atoms.
The total force or local energy can then be calculated for any atom by summing the
triplet contributions of every valid triplet of atoms of which one is always the central one.
The prediction is done by the ``calculator`` module which is built to work within
the ase python package.
Args:
dists (array): array of floats containing all of the distances which can be used to
build triplets of atoms. This array is created by calling np.linspace(start, r_cut, num)
element_i (int): atomic number of the central atom i in a triplet
element_j (int): atomic number of the second atom j in a triplet
element_k (int): atomic number of the third atom k in a triplet
ncores (int): number of CPUs to use when computing the triplet local energies
Returns:
spline3D (obj): a 3D spline object that can be used to predict the energy and the force associated
to the central atom of a triplet.
"""
num = len(dists)
inds, r_ij_x, r_ki_x, r_ki_y = self.generate_triplets_all(dists)
confs = np.zeros((len(r_ij_x), 2, 5))
confs[:, 0, 0] = r_ij_x # Element on the x axis
confs[:, 1, 0] = r_ki_x # Reshape into confs shape: this is x2
confs[:, 1, 1] = r_ki_y # Reshape into confs shape: this is y2
# Permutations of elements
confs[:, :, 3] = element_i # Central element is always element 1
confs[:, 0, 4] = element_j # Element on the x axis is always element 2
# Element on the xy plane is always element 3
confs[:, 1, 4] = element_k
grid_3b = np.zeros((num, num, num))
grid_3b[inds] = self.gp_3b.predict_energy(
confs, ncores=ncores, mapping=True).flatten()
return interpolation.Spline3D(dists, dists, dists, grid_3b)
def save(self, path):
""" Save the model.
This creates a .json file containing the parameters of the model and the
paths to the GP objects and the mapped potentials, which are saved as
separate .gpy and .gpz files, respectively.
Args:
path (str): path to the file
"""
if not isinstance(path, Path):
path = Path(path)
### SAVE THE MODEL ###
params = {
'model': self.__class__.__name__,
'elements': self.elements,
'r_cut': self.r_cut,
'rep_sig': self.rep_sig,
'fitted': self.gp_2b.fitted,
'gp_2b': {
'kernel': self.gp_2b.kernel.kernel_name,
'n_train': self.gp_2b.n_train,
'sigma': self.gp_2b.kernel.theta[0],
'theta': self.gp_2b.kernel.theta[1],
'noise': self.gp_2b.noise
},
'gp_3b': {
'kernel': self.gp_3b.kernel.kernel_name,
'n_train': self.gp_3b.n_train,
'sigma': self.gp_3b.kernel.theta[0],
'theta': self.gp_3b.kernel.theta[1],
'noise': self.gp_3b.noise
},
'grid_2b': {
'r_min': self.grid_start,
'r_num': self.grid_num_2b,
'filename': {}
} if self.grid_2b else {},
'grid_3b': {
'r_min': self.grid_start,
'r_num': self.grid_num_3b,
'filename': {}
} if self.grid_3b else {}
}
gp_filename_2b = "GP_ker_{p[gp_2b][kernel]}_ntr_{p[gp_2b][n_train]}.npy".format(
p=params)
params['gp_2b']['filename'] = gp_filename_2b
self.gp_2b.save(path / gp_filename_2b)
for k, grid in self.grid_2b.items():
key = '_'.join(str(element) for element in k)
grid_filename_2b = "GRID_{}_ker_{p[gp_2b][kernel]}_ntr_{p[gp_2b][n_train]}.npz".format(
key, p=params)
print("Saved 2-body grid under name %s" % (grid_filename_2b))
params['grid_2b']['filename'][key] = grid_filename_2b
grid.save(path / grid_filename_2b)
### SAVE THE 3B MODEL ###
gp_filename_3b = "GP_ker_{p[gp_3b][kernel]}_ntr_{p[gp_3b][n_train]}.npy".format(
p=params)
params['gp_3b']['filename'] = gp_filename_3b
self.gp_3b.save(path / gp_filename_3b)
for k, grid in self.grid_3b.items():
key = '_'.join(str(element) for element in k)
grid_filename_3b = "GRID_{}_ker_{p[gp_3b][kernel]}_ntr_{p[gp_3b][n_train]}.npz".format(
key, p=params)
print("Saved 3-body grid under name %s" % (grid_filename_3b))
params['grid_3b']['filename'][key] = grid_filename_3b
grid.save(path / grid_filename_3b)
with open(path / "MODEL_combined_ntr_{p[gp_2b][n_train]}.json".format(p=params), 'w') as fp:
json.dump(params, fp, indent=4, cls=NpEncoder)
print("Saved model with name: MODEL_combined_ntr_{p[gp_2b][n_train]}.json".format(p=params))
@classmethod
def from_json(cls, path):
""" Load the model.
Loads the model, the associated GPs and the mapped potentials, if available.
Args:
path (str): path to the .json model file
Return:
model (obj): the model object
"""
if not isinstance(path, Path):
path = Path(path)
directory, prefix = path.parent, path.stem
with open(path) as fp:
params = json.load(fp)
model = cls(params['elements'],
params['r_cut'],
params['gp_2b']['sigma'],
params['gp_3b']['sigma'],
params['gp_2b']['theta'],
params['gp_3b']['theta'],
params['gp_2b']['noise'],
params['rep_sig'])
gp_filename_2b = params['gp_2b']['filename']
gp_filename_3b = params['gp_3b']['filename']
try:
model.gp_2b.load(directory / gp_filename_2b)
except:
warnings.warn("The 2-body GP file is missing")
pass
try:
model.gp_3b.load(directory / gp_filename_3b)
except:
warnings.warn("The 3-body GP file is missing")
pass
if params['grid_2b']:
for key, grid_filename_2b in params['grid_2b']['filename'].items():
k = tuple(int(ind) for ind in key.split('_'))
model.grid_2b[k] = interpolation.Spline1D.load(
directory / grid_filename_2b)
for key, grid_filename_3b in params['grid_3b']['filename'].items():
k = tuple(int(ind) for ind in key.split('_'))
model.grid_3b[k] = interpolation.Spline3D.load(
directory / grid_filename_3b)
model.grid_start = params['grid_2b']['r_min']
model.grid_num_2b = params['grid_2b']['r_num']
model.grid_num_3b = params['grid_3b']['r_num']
return model
def save_gp(self, filename_2b, filename_3b):
""" Saves the GP objects, now obsolete
"""
self.gp_2b.save(filename_2b)
self.gp_3b.save(filename_3b)
def load_gp(self, filename_2b, filename_3b):
""" Loads the GP objects, now obsolete
"""
self.gp_2b.load(filename_2b)
self.gp_3b.load(filename_3b)
@staticmethod
def generate_triplets_all(dists):
""" Generate a list of all valid triplets.
Calculates the energy predicted by the GP for three atoms at all possible combination
of num distances ranging from start to r_cut. The energy is calculated only for ``valid``
triplets of atoms, i.e. sets of three distances which form a triangle (this is checked via
the triangle inequality).
The computed energies are stored in a 3D cube of values, and a 3D spline interpolation is
created, which can be used to predict the energy and, through its analytic derivative,
the force associated to any triplet of atoms.
The total force or local energy can then be calculated for any atom by summing the
triplet contributions of every valid triplet of atoms of which one is always the central one.
The prediction is done by the ``calculator`` module which is built to work within
the ase python package.
Args:
dists (array): array of floats containing all of the distances which can be used to
build triplets of atoms. This array is created by calling np.linspace(start, r_cut, num)
Returns:
inds (array): array of booleans indicating which triplets (three distance values) need to be
evaluated to fill the 3D grid of energy values.
r_ij_x (array): array containing the x coordinate of the second atom j w.r.t. the central atom i
r_ki_x (array): array containing the x coordinate of the third atom k w.r.t. the central atom i
r_ki_y (array): array containing the y coordinate of the third atom k w.r.t. the central atom i
"""
d_ij, d_jk, d_ki = np.meshgrid(
dists, dists, dists, indexing='ij', sparse=False, copy=True)
# Valid triangles according to triangle inequality
inds = np.logical_and(
d_ij <= d_jk + d_ki, np.logical_and(d_jk <= d_ki + d_ij, d_ki <= d_ij + d_jk))
# Element on the x axis
r_ij_x = d_ij[inds]
# Element on the xy plane
r_ki_x = (d_ij[inds] ** 2 - d_jk[inds] ** 2 +
d_ki[inds] ** 2) / (2 * d_ij[inds])
# using abs to avoid numerical error near to 0
r_ki_y = np.sqrt(np.abs(d_ki[inds] ** 2 - r_ki_x ** 2))
return inds, r_ij_x, r_ki_x, r_ki_y
| 45.315118 | 113 | 0.615705 | 6,833 | 49,756 | 4.295624 | 0.060735 | 0.023133 | 0.022145 | 0.015331 | 0.915917 | 0.894931 | 0.880996 | 0.870196 | 0.862394 | 0.855512 | 0 | 0.020111 | 0.304446 | 49,756 | 1,097 | 114 | 45.356427 | 0.828017 | 0.369202 | 0 | 0.775685 | 0 | 0 | 0.076712 | 0.030836 | 0 | 0 | 0 | 0 | 0 | 1 | 0.044521 | false | 0.006849 | 0.013699 | 0 | 0.099315 | 0.020548 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
10ca0d1fb65f0cf9330392f01eb786d057450fd3 | 14,277 | py | Python | redox_net_code/lib/.ipynb_checkpoints/Reaction_Library_Mother-checkpoint.py | beangoben/gp_redox_rxn | dfd4c358858192bcff4b1c93da1b9d3e0d9b0299 | [
"MIT"
] | 8 | 2019-05-26T14:30:12.000Z | 2021-09-17T20:18:23.000Z | redox_net_code/lib/.ipynb_checkpoints/Reaction_Library_Mother-checkpoint.py | beangoben/gp_redox_rxn | dfd4c358858192bcff4b1c93da1b9d3e0d9b0299 | [
"MIT"
] | 1 | 2019-06-05T13:59:02.000Z | 2019-06-05T13:59:02.000Z | redox_net_code/lib/.ipynb_checkpoints/Reaction_Library_Mother-checkpoint.py | beangoben/gp_redox_rxn | dfd4c358858192bcff4b1c93da1b9d3e0d9b0299 | [
"MIT"
] | 3 | 2020-07-01T22:01:20.000Z | 2021-09-17T21:19:24.000Z | from rdkit import Chem
import json
from rdkit.Chem import AllChem,Draw,Descriptors
import copy
import pandas as pd
import re
import matplotlib.pyplot as plt
import lib.Reaction_Library as RL
### Reduction Functions:
def G1_function(metab_smiles):
reactant = Chem.MolFromSmiles(metab_smiles)
prod_list = []
prod = RL.G1_carb_acid.RunReactants([reactant])
if len(prod) > 0:
for x in prod:
smiles = Chem.MolToSmiles(x[0])
prod_list.append(smiles)
return prod_list
def G2_function(metab_smiles):
reactant = Chem.MolFromSmiles(metab_smiles)
prod_list = []
#Aldehyde reduction
prod_1 = RL.G2_ald.RunReactants([reactant])
if len(prod_1) > 0:
for x in prod_1:
smiles = Chem.MolToSmiles(x[0])
prod_list.append(smiles)
#Ketone reduction
prod_2 = RL.G2_ket.RunReactants([reactant])
if len(prod_2) > 0:
for x in prod_2:
smiles = Chem.MolToSmiles(x[0])
prod_list.append(smiles)
#6 carbon ring reactions...
#prod_3 = RL.G2_6c6r.RunReactants([reactant])
#if len(prod_3) > 0:
# for x in prod_3:
# smiles = Chem.MolToSmiles(x[0])
# prod_list.append(smiles)
#prod_4 = RL.G2_6c5r.RunReactants([reactant])
#if len(prod_4) > 0:
# for x in prod_4:
# smiles = Chem.MolToSmiles(x[0])
# prod_list.append(smiles)
#prod_5 = RL.G2_5c6r.RunReactants([reactant])
#if len(prod_5) > 0:
# for x in prod_5:
# smiles = Chem.MolToSmiles(x[0])
# prod_list.append(smiles)
#prod_6 = RL.G2_5c5r.RunReactants([reactant])
#if len(prod_6) > 0:
# for x in prod_6:
# smiles = Chem.MolToSmiles(x[0])
# prod_list.append(smiles)
return prod_list
def G3_function(metab_smiles):
reactant = Chem.MolFromSmiles(metab_smiles)
prod_list = []
#Aldehyde reduction
prod_1 = RL.G3_ald.RunReactants([reactant])
if len(prod_1) > 0:
for x in prod_1:
smiles = Chem.MolToSmiles(x[0])
prod_list.append(smiles)
#Ketone reduction
prod_2 = RL.G3_ket.RunReactants([reactant])
if len(prod_2) > 0:
for x in prod_2:
smiles = Chem.MolToSmiles(x[0])
prod_list.append(smiles)
return prod_list
def G4_function(metab_smiles):
reactant = Chem.MolFromSmiles(metab_smiles)
prod_list = []
# Hydroxyl in the end of a molecule
prod_1 = RL.G4_end_hydr.RunReactants([reactant])
if len(prod_1) > 0:
for x in prod_1:
smiles = Chem.MolToSmiles(x[0])
prod_list.append(smiles)
# Hydroxyl in the middle of a molecule.
prod_2 = RL.G4_mid_hydr.RunReactants([reactant])
if len(prod_2) > 0:
for x in prod_2:
smiles = Chem.MolToSmiles(x[0])
prod_list.append(smiles)
prod_3 = RL.G4_arom_hydr.RunReactants([reactant])
if len(prod_3) > 0:
for x in prod_3:
smiles = Chem.MolToSmiles(x[0])
prod_list.append(smiles)
return prod_list
### Oxidation Functions:
def G1_function_ox(metab_smiles):
reactant = Chem.MolFromSmiles(metab_smiles)
prod_list = []
prod = RL.G1_carb_acid_ox.RunReactants([reactant])
if len(prod) > 0:
for x in prod:
smiles = Chem.MolToSmiles(x[0])
prod_list.append(smiles)
return prod_list
def G2_function_ox(metab_smiles):
reactant = Chem.MolFromSmiles(metab_smiles)
prod_list = []
#Aldehyde reduction
prod_1 = RL.G2_ald_ox.RunReactants([reactant])
if len(prod_1) > 0:
for x in prod_1:
smiles = Chem.MolToSmiles(x[0])
prod_list.append(smiles)
#Ketone reduction
prod_2 = RL.G2_ket_ox.RunReactants([reactant])
if len(prod_2) > 0:
for x in prod_2:
smiles = Chem.MolToSmiles(x[0])
prod_list.append(smiles)
return prod_list
def G3_function_ox(metab_smiles):
reactant = Chem.MolFromSmiles(metab_smiles)
prod_list = []
#Aldehyde reduction
prod_1 = RL.G3_ald_ox.RunReactants([reactant])
if len(prod_1) > 0:
for x in prod_1:
smiles = Chem.MolToSmiles(x[0])
prod_list.append(smiles)
#Ketone reduction
prod_2 = RL.G3_ket_ox.RunReactants([reactant])
if len(prod_2) > 0:
for x in prod_2:
smiles = Chem.MolToSmiles(x[0])
prod_list.append(smiles)
return prod_list
def G4_function_ox(metab_smiles):
reactant = Chem.MolFromSmiles(metab_smiles)
prod_list = []
# Hydroxyl in the end of a molecule
prod_1 = RL.G4_end_hydr_ox.RunReactants([reactant])
if len(prod_1) > 0:
for x in prod_1:
smiles = Chem.MolToSmiles(x[0])
prod_list.append(smiles)
# Hydroxyl in the middle of a molecule.
prod_2 = RL.G4_mid_hydr_ox.RunReactants([reactant])
if len(prod_2) > 0:
for x in prod_2:
smiles = Chem.MolToSmiles(x[0])
prod_list.append(smiles)
prod_3 = RL.G4_arom_hydr_ox.RunReactants([reactant])
if len(prod_3) > 0:
for x in prod_3:
smiles = Chem.MolToSmiles(x[0])
prod_list.append(smiles)
return prod_list
# Old Reduce metabolite:
def reduce_metabolite_old(metabolite_smiles):
#empty rxn_list
rxn_list = [ ]
#single starting substrate
substrate_list = [ metabolite_smiles ]
# initialize this flag to 1
num_new_reactions = 1
while (num_new_reactions): #keep going as long as you have new reactions:
new_reactions = [ ] # this is the list of new reactions in the latest iteration
substrate_list_temp = []
#For every substrate in substrate list:
for sub in substrate_list:
# For every reaction_type: (looping through all G1 - G4 functions):
#G1. Apply reaction_type to substrate
G1_prods = G1_function(sub) #list of G1 products
#G2
G2_prods = G2_function(sub) #list of G2 products
#G3
#G3_prods = G3_function(sub) #list of G3 products
#G4
G4_prods = G4_function(sub) #list of G4 products
#All prods:
# GAll_prods = list(set(G1_prods + G2_prods + G3_prods + G4_prods)) #unique new products.
GAll_prods = list(set(G1_prods + G2_prods + G4_prods)) #unique new products.
substrate_list_temp += GAll_prods
#2. Store resulting (uniqe) reactions in new_reactions list
for prod in GAll_prods:
new_reactions.append( sub+'>>'+prod )
rxn_list += list(set(new_reactions))
#After reducing all current substrates, update substrate list.
substrate_list = list(set(substrate_list_temp))
if len(GAll_prods)==0:
num_new_reactions = 0
return list(set(rxn_list))
def reduce_metabolite(metabolite_smiles, Master_Sub_List = [], do_G3 = False):
rxn_list = [ ] #empty rxn_list
substrate_list = [ metabolite_smiles ] #single starting substrate
num_new_reactions = 1 # initialize this flag to 1
while (num_new_reactions): #keep going as long as you have new reactions:
new_reactions = [ ] # this is the list of new reactions in the latest iteration
substrate_list_temp = []
# Remove substrates that are already in the Master Substrate List:
substrate_list = list( set(substrate_list) - set(Master_Sub_List) )
Master_Sub_List += substrate_list # --> shouldn't you turn this into a set?
#For every substrate in substrate list:
for sub in substrate_list:
# For every reaction_type: (looping through all G1 - G4 functions):
#G1_prods = G1_function(sub) # list of G1 products
G2_prods = G2_function(sub) # list of G2 products
G3_prods = G3_function(sub) # list of G4 products
# if do_G3:
# G3_prods = G3_function(sub) # list of G3 products
# GAll_prods = list(set(G1_prods + G2_prods + G3_prods + G4_prods))
# else:
GAll_prods = list(set(G2_prods + G3_prods)) #unique new products.
substrate_list_temp += GAll_prods # this puts together the products of all substrates?
# Store resulting (uniqe) reactions in new_reactions list
for prod in GAll_prods:
new_reactions.append( sub+'>>'+prod )
rxn_list += list(set(new_reactions))
#After reducing all current substrates, update substrate list.
substrate_list = list(set(substrate_list_temp))
if len(substrate_list)==0:
num_new_reactions = 0
return list(set(rxn_list)), Master_Sub_List
def oxidize_metabolite_old(metabolite_smiles):
#empty rxn_list
rxn_list = [ ]
#single starting substrate
substrate_list = [ metabolite_smiles ]
# initialize this flag to 1
num_new_reactions = 1
while (num_new_reactions): #keep going as long as you have new reactions:
new_reactions = [ ] # this is the list of new reactions in the latest iteration
substrate_list_temp = []
#For every substrate in substrate list:
for sub in substrate_list:
# For every reaction_type: (looping through all G1 - G4 functions):
#G1. Apply reaction_type to substrate
G1_prods = G1_function_ox(sub) #list of G1 products
#G2
G2_prods = G2_function_ox(sub) #list of G2 products
#G3
# G3_prods = G3_function_ox(sub) #list of G3 products
#G4
G4_prods = G4_function_ox(sub) #list of G4 products
#All prods:
GAll_prods = list(set(G1_prods + G2_prods + G4_prods)) #unique new products.
substrate_list_temp += GAll_prods
#2. Store resulting (uniqe) reactions in new_reactions list
for prod in GAll_prods:
new_reactions.append( sub+'>>'+prod )
rxn_list += list(set(new_reactions))
#print 'GAll:' + str(GAll_prods)
#print 'new:' + str(new_reactions)
#for rxn in new_reactions:
# display(AllChem.ReactionFromSmarts(rxn))
#After reducing all current substrates, update substrate list.
substrate_list = list(set(substrate_list_temp))
#print substrate_list
if len(GAll_prods)==0:
num_new_reactions = 0
return list(set(rxn_list))
def oxidize_metabolite(metabolite_smiles, Master_Sub_List = None, rxn_network_file = None, rxn_limit = None):
# empty rxn_list
rxn_list = [ ]
# single starting substrate
substrate_list = [ metabolite_smiles ]
# initialize this flag to 1
num_new_reactions = 1
# num reaction status
len_status = 0
while (num_new_reactions): #keep going as long as you have new reactions:
new_reactions = [ ] # this is the list of new reactions in the latest iteration
substrate_list_temp = []
# Remove substrates that are already in the Master Substrate List:
# print 'Substrate List before filtering:', substrate_list
substrate_list = list(set(substrate_list) - set(Master_Sub_List))
# print 'Substrate List after filtering:', substrate_list
Master_Sub_List += substrate_list
# print 'Updated MasterSubList', Master_Sub_List, '\n'
#For every substrate in substrate list, perform all 4 types of oxidations:
for sub in substrate_list:
# For every reaction_type: (looping through all G1 - G4 functions):
#G1. Apply reaction_type to substrate
# G1_prods = G1_function_ox(sub) #list of G1 products
#G2
G2_prods = G2_function_ox(sub) #list of G2 products
#G3
G3_prods = G3_function_ox(sub) #list of G3 products
#G4
# G4_prods = G4_function_ox(sub) #list of G4 products
# These are all the products from all reactions acting on current substrate
GAll_prods = list(set(G2_prods + G3_prods)) #unique new products.
substrate_list_temp += GAll_prods
#2. Store resulting (uniqe) reactions in new_reactions list
for prod in GAll_prods:
new_reactions.append( sub+'>>'+prod )
# Update the list of reactions
rxn_list += new_reactions
# Get rid of duplicates -->
rxn_list = list(set(rxn_list))
#After reducing all current substrates, update substrate list.
substrate_list = list(set(substrate_list_temp))
#print substrate_list
if len(substrate_list)==0:
num_new_reactions = 0
# If you only want to run up to a certain number of reactions:
if rxn_limit:
if len(rxn_list) > rxn_limit:
return list(set(rxn_list)), Master_Sub_List
if len(rxn_list) > len_status:
# print 'number of reactions', len(rxn_list)
len_status = len(rxn_list) + 1000
return list(set(rxn_list)), Master_Sub_List
def visualize_reaction_old(metabolite_smiles):
rxn_list = reduce_metabolite_old(metabolite_smiles)
rxn_list.sort(key = len, reverse = True)
print("Starting metabolite: " + metabolite_smiles)
print("Number of reactions: " + str(len(rxn_list)))
for rxn in rxn_list:
print(rxn)
display(AllChem.ReactionFromSmarts(rxn))
def visualize_reaction_new(metabolite_smiles):
rxn_list = reduce_metabolite(metabolite_smiles)
rxn_list.sort(key = len, reverse = True)
print("Starting metabolite: " + metabolite_smiles)
print("Number of reactions: " + str(len(rxn_list)))
for rxn in rxn_list:
print(rxn)
display(AllChem.ReactionFromSmarts(rxn))
def visualize_reaction_ox_old(metabolite_smiles):
rxn_list = oxidize_metabolite_old(metabolite_smiles)
rxn_list.sort(key = len)
print("Starting metabolite: " + metabolite_smiles)
print("Number of reactions: " + str(len(rxn_list)))
for rxn in rxn_list:
print(rxn)
display(AllChem.ReactionFromSmarts(rxn))
| 34.992647 | 109 | 0.630595 | 1,895 | 14,277 | 4.525594 | 0.089182 | 0.072761 | 0.051306 | 0.058302 | 0.876283 | 0.849813 | 0.820079 | 0.817048 | 0.8132 | 0.79431 | 0 | 0.023856 | 0.283603 | 14,277 | 407 | 110 | 35.078624 | 0.814627 | 0.304406 | 0 | 0.759657 | 0 | 0 | 0.013687 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.064378 | false | 0 | 0.034335 | 0 | 0.154506 | 0.038627 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
10f12e1f8552b6679ab96e5fe7ff167e31068f3b | 7,132 | py | Python | tests/functional/basic_queries_tests.py | suhaibaffan/database | 1ff9d8b770d893ffa53d8fdd0f004518e91763c1 | [
"Apache-2.0"
] | 1 | 2021-09-20T05:09:34.000Z | 2021-09-20T05:09:34.000Z | tests/functional/basic_queries_tests.py | suhaibaffan/database | 1ff9d8b770d893ffa53d8fdd0f004518e91763c1 | [
"Apache-2.0"
] | null | null | null | tests/functional/basic_queries_tests.py | suhaibaffan/database | 1ff9d8b770d893ffa53d8fdd0f004518e91763c1 | [
"Apache-2.0"
] | null | null | null | # Copyright 2020 Alex Dukhno
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License 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 psycopg2 as pg
import pytest
@pytest.fixture(scope="session", autouse=True)
def create_cursor(request):
try:
conn = pg.connect(host="localhost", password="check_this_out", database="postgres")
cur = conn.cursor()
def close_all():
conn.close()
cur.close()
request.addfinalizer(close_all)
except Exception as e:
assert False, str(e)
return cur
def test_create_drop_schema(create_cursor):
cur = create_cursor
try:
cur.execute('create schema schema_name;')
finally:
cur.execute('drop schema schema_name;')
def test_create_drop_empty_table(create_cursor):
cur = create_cursor
try:
cur.execute('create schema schema_name;')
cur.execute('create table schema_name.empty_table();')
finally:
cur.execute('drop table schema_name.empty_table;')
cur.execute('drop schema schema_name;')
def test_insert_select(create_cursor):
cur = create_cursor
try:
cur.execute('create schema schema_name;')
cur.execute('create table schema_name.table_name(si_column smallint);')
cur.execute('insert into schema_name.table_name values (%d);' % 1)
cur.execute('select * from schema_name.table_name;')
r = cur.fetchone()
assert r == (1,)
finally:
cur.execute('drop table schema_name.table_name;')
cur.execute('drop schema schema_name;')
def test_insert_select_many(create_cursor):
cur = create_cursor
try:
cur.execute('create schema schema_name;')
cur.execute('create table schema_name.table_name(si_column smallint);')
cur.execute('insert into schema_name.table_name values (%d), (%d), (%d);' % (1, 2, 3))
cur.execute('select * from schema_name.table_name;')
r = cur.fetchmany(3)
assert r == [(1,), (2,), (3,)]
finally:
cur.execute('drop table schema_name.table_name;')
cur.execute('drop schema schema_name;')
def test_insert_select_update_all_select(create_cursor):
cur = create_cursor
try:
cur.execute('create schema schema_name;')
cur.execute('create table schema_name.table_name(si_column smallint);')
cur.execute('insert into schema_name.table_name values (%d), (%d), (%d);' % (1, 2, 3))
cur.execute('select * from schema_name.table_name;')
r = cur.fetchmany(3)
assert r == [(1,), (2,), (3,)]
cur.execute('update schema_name.table_name set si_column = %d;' % 4)
cur.execute('select * from schema_name.table_name;')
r = cur.fetchmany(3)
assert r == [(4,), (4,), (4,)]
finally:
cur.execute('drop table schema_name.table_name;')
cur.execute('drop schema schema_name;')
def test_insert_select_delete_all_select(create_cursor):
cur = create_cursor
try:
cur.execute('create schema schema_name;')
cur.execute('create table schema_name.table_name(si_column smallint);')
cur.execute('insert into schema_name.table_name values (%d), (%d), (%d);' % (1, 2, 3))
cur.execute('select * from schema_name.table_name;')
r = cur.fetchmany(3)
assert r == [(1,), (2,), (3,)]
cur.execute('delete from schema_name.table_name;')
cur.execute('select * from schema_name.table_name;')
r = cur.fetchmany(3)
assert r == []
finally:
cur.execute('drop table schema_name.table_name;')
cur.execute('drop schema schema_name;')
def test_insert_select_many_columns(create_cursor):
cur = create_cursor
try:
cur.execute('create schema schema_name;')
cur.execute('create table schema_name.table_name(si_column_1 smallint, si_column_2 smallint, si_column_3 smallint);')
for t in [(1, 2, 3), (4, 5, 6), (7, 8, 9)]:
cur.execute('insert into schema_name.table_name values (%s, %s, %s);' % t)
cur.execute('select * from schema_name.table_name;')
r = cur.fetchmany(3)
assert r == [(1, 2, 3,), (4, 5, 6,), (7, 8, 9,)]
finally:
cur.execute('drop table schema_name.table_name;')
cur.execute('drop schema schema_name;')
def test_insert_update_specified_column(create_cursor):
cur = create_cursor
try:
cur.execute('create schema schema_name;')
cur.execute('create table schema_name.table_name(si_column_1 smallint, si_column_2 smallint, si_column_3 smallint);')
for t in [(1, 2, 3), (4, 5, 6), (7, 8, 9)]:
cur.execute('insert into schema_name.table_name values (%s, %s, %s);' % t)
cur.execute('select * from schema_name.table_name;')
r = cur.fetchmany(3)
assert r == [(1, 2, 3,), (4, 5, 6,), (7, 8, 9,)]
cur.execute('update schema_name.table_name set si_column_2 = %d;' % 10)
cur.execute('select * from schema_name.table_name;')
r = cur.fetchmany(3)
assert r == [(1, 10, 3,), (4, 10, 6,), (7, 10, 9,)]
finally:
cur.execute('drop table schema_name.table_name;')
cur.execute('drop schema schema_name;')
def test_insert_select_reordered(create_cursor):
cur = create_cursor
try:
cur.execute('create schema schema_name;')
cur.execute('create table schema_name.table_name(si_column_1 smallint, si_column_2 smallint, si_column_3 smallint);')
for t in [(1, 2, 3), (4, 5, 6), (7, 8, 9)]:
cur.execute('insert into schema_name.table_name values (%s, %s, %s);' % t)
cur.execute('select si_column_3, si_column_1, si_column_2 from schema_name.table_name;')
r = cur.fetchmany(3)
assert r == [(3, 1, 2,), (6, 4, 5,), (9, 7, 8,)]
finally:
cur.execute('drop table schema_name.table_name;')
cur.execute('drop schema schema_name;')
def test_insert_select_same_column_many_times(create_cursor):
cur = create_cursor
try:
cur.execute('create schema schema_name;')
cur.execute('create table schema_name.table_name(si_column_1 smallint, si_column_2 smallint, si_column_3 smallint);')
for t in [(1, 2, 3), (4, 5, 6), (7, 8, 9)]:
cur.execute('insert into schema_name.table_name values (%s, %s, %s);' % t)
cur.execute('select si_column_3, si_column_1, si_column_2, si_column_1, si_column_3 from schema_name.table_name;')
r = cur.fetchmany(3)
assert r == [(3, 1, 2, 1, 3), (6, 4, 5, 4, 6,), (9, 7, 8, 7, 9,)]
finally:
cur.execute('drop table schema_name.table_name;')
cur.execute('drop schema schema_name;')
| 35.66 | 125 | 0.638671 | 1,025 | 7,132 | 4.238049 | 0.132683 | 0.138122 | 0.131215 | 0.166206 | 0.797422 | 0.787983 | 0.78361 | 0.775322 | 0.766805 | 0.766805 | 0 | 0.028251 | 0.225743 | 7,132 | 199 | 126 | 35.839196 | 0.758421 | 0.076837 | 0 | 0.728571 | 0 | 0 | 0.395738 | 0.151294 | 0 | 0 | 0 | 0 | 0.085714 | 1 | 0.085714 | false | 0.007143 | 0.014286 | 0 | 0.107143 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
804f1f6bf2b4d3e4254e40f96d8dc384dff4ffac | 95 | py | Python | tools/Vitis-AI-Quantizer/vai_q_pytorch/pytorch_binding/pytorch_nndct/pruning/__init__.py | Carles-Figuerola/Vitis-AI | fc043ea4aca1f9fe4e18962e6a6ae397812bb34b | [
"Apache-2.0"
] | 1 | 2021-04-01T06:38:48.000Z | 2021-04-01T06:38:48.000Z | tools/Vitis-AI-Quantizer/vai_q_pytorch/pytorch_binding/pytorch_nndct/pruning/__init__.py | cy333/Vitis-AI | 611b82cfc32ea2fe04491432bf8feed1f378c9de | [
"Apache-2.0"
] | null | null | null | tools/Vitis-AI-Quantizer/vai_q_pytorch/pytorch_binding/pytorch_nndct/pruning/__init__.py | cy333/Vitis-AI | 611b82cfc32ea2fe04491432bf8feed1f378c9de | [
"Apache-2.0"
] | null | null | null | from pytorch_nndct.pruning.core import InputSpec
from pytorch_nndct.pruning.core import Pruner
| 31.666667 | 48 | 0.873684 | 14 | 95 | 5.785714 | 0.571429 | 0.271605 | 0.395062 | 0.567901 | 0.814815 | 0.814815 | 0 | 0 | 0 | 0 | 0 | 0 | 0.084211 | 95 | 2 | 49 | 47.5 | 0.931034 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 9 |
337f488f4f8222c18e39047a33b38cab4dd65d8d | 12,000 | py | Python | models/mix_2dmodel.py | bzhai/Ubi-SleepNet | 27837827dec608d06659421d073872fb1f68453e | [
"MIT"
] | 3 | 2022-01-22T15:55:31.000Z | 2022-01-28T16:09:02.000Z | models/mix_2dmodel.py | bzhai/Ubi-SleepNet | 27837827dec608d06659421d073872fb1f68453e | [
"MIT"
] | null | null | null | models/mix_2dmodel.py | bzhai/Ubi-SleepNet | 27837827dec608d06659421d073872fb1f68453e | [
"MIT"
] | null | null | null | import torch.nn as nn
import torch
def num_flat_features(x):
size = x.size()[1:]
num_features = 1
for s in size:
num_features *= s
return num_features
class VggIMG(nn.Module):
"""
Treat inputs as a image using 3x1 kernel, e.g. mesa H=9, W=101
"""
def __init__(self, in_channels=9, num_classes=3, time_step_dim=25) -> None:
super(VggIMG, self).__init__()
self.channels = in_channels
self.features = nn.Sequential(
# #### block 1
nn.Conv2d(1, 512, kernel_size=(1, 3), padding=(0, 1)), # con_1
nn.ReLU(inplace=True),
nn.Conv2d(512, 512, kernel_size=(1, 3), padding=(0, 1)), # con_2
nn.ReLU(inplace=True),
nn.MaxPool2d(kernel_size=(1, 2), stride=(1, 2)), # max_pool
# #### block 2
nn.Conv2d(512, 128, kernel_size=(1, 3), padding=(0, 1)), # con_3
nn.ReLU(inplace=True),
nn.Conv2d(128, 128, kernel_size=(1, 3), padding=(0, 1)), # con_4
nn.ReLU(inplace=True),
nn.MaxPool2d(kernel_size=(1, 2), stride=(1, 2)), # max pool
# #### block 3 = con_3
nn.Conv2d(128, 512, kernel_size=(1, 3), padding=(0, 1)), # con_5
nn.ReLU(inplace=True),
nn.Conv2d(512, 512, kernel_size=(1, 3), padding=(0, 1)), # con_6
nn.ReLU(inplace=True),
nn.Conv2d(512, 512, kernel_size=(1, 3), padding=(0, 1)), # con_7
nn.ReLU(inplace=True),
)
self.classifier = nn.Sequential(
nn.Linear(time_step_dim * 512 * self.channels, 512),
nn.ReLU(inplace=True),
nn.Dropout(p=0.25),
nn.Linear(512, 128),
nn.ReLU(inplace=True),
nn.Dropout(p=0.25),
nn.Linear(128, 32),
nn.ReLU(inplace=True),
nn.Dropout(p=0.25),
nn.Linear(32, num_classes),
)
def forward(self, x: torch.Tensor) -> torch.Tensor:
x = self.features(x)
x = torch.flatten(x, 1)
x = self.classifier(x)
return x
class VggIMGRes(nn.Module):
"""
Treat inputs as a image using 3x1 kernel, e.g. mesa H=9, W=101
"""
def __init__(self, in_channels=9, num_classes=3, time_step_dim=25) -> None:
super(VggIMGRes, self).__init__()
self.conv_1 = nn.Conv2d(1, 512, kernel_size=(1, 3), padding=(0, 1)) # con_1
self.conv_2 = nn.Conv2d(512, 512, kernel_size=(1, 3), padding=(0, 1)) # con_2
self.conv_3 = nn.Conv2d(512, 128, kernel_size=(1, 3), padding=(0, 1)) # conv_3
self.conv_4 = nn.Conv2d(128, 128, kernel_size=(1, 3), padding=(0, 1)) # conv_4
self.conv_5 = nn.Conv2d(128, 512, kernel_size=(1, 3), padding=(0, 1)) # conv_5
self.conv_6 = nn.Conv2d(512, 512, kernel_size=(1, 3), padding=(0, 1)) # conv_6
self.conv_7 = nn.Conv2d(512, 512, kernel_size=(1, 3), padding=(0, 1)) # conv_7
self.relu = nn.ReLU(inplace=True)
self.max_pool = nn.MaxPool2d(kernel_size=(1, 2), stride=(1, 2))
self.channels = in_channels
self.classifier = nn.Sequential(
nn.Linear(time_step_dim * 512 * self.channels, 512),
nn.ReLU(inplace=True),
nn.Dropout(p=0.25),
nn.Linear(512, 128),
nn.ReLU(inplace=True),
nn.Dropout(p=0.25),
nn.Linear(128, 32),
nn.ReLU(inplace=True),
nn.Dropout(p=0.25),
nn.Linear(32, num_classes),
)
def forward(self, x: torch.Tensor) -> torch.Tensor:
x = self.conv_1(x)
x = self.relu(x)
residual_1 = x
output = self.conv_2(x)
output += residual_1
output = self.relu(output)
output = self.max_pool(output)
output_2 = self.conv_3(output)
residual_2 = output_2
output_2 = self.relu(output_2)
output_2 = self.conv_4(output_2)
output_2 += residual_2
output_2 = self.relu(output_2)
output_2 = self.max_pool(output_2)
output_3 = self.conv_5(output_2)
output_3 = self.relu(output_3)
residual_3 = output_3
output_3 = self.conv_6(output_3)
output_3 = self.relu(output_3)
output_3 = self.conv_7(output_3)
output_3 += residual_3
output_3 = self.relu(output_3)
output_3 = torch.flatten(output_3, 1)
output_3 = self.classifier(output_3)
return output_3
class VggIMGResSum(nn.Module):
"""
Treat inputs as a image using 3x1 kernel, e.g. mesa H=9, W=101
"""
def __init__(self, in_channels=9, num_classes=3, time_step_dim=25) -> None:
super(VggIMGResSum, self).__init__()
self.conv_1 = nn.Conv2d(1, 512, kernel_size=(1, 3), padding=(0, 1)) # con_1
self.conv_2 = nn.Conv2d(512, 512, kernel_size=(1, 3), padding=(0, 1)) # con_2
self.conv_3 = nn.Conv2d(512, 128, kernel_size=(1, 3), padding=(0, 1)) # conv_3
self.conv_4 = nn.Conv2d(128, 128, kernel_size=(1, 3), padding=(0, 1)) # conv_4
self.conv_5 = nn.Conv2d(128, 512, kernel_size=(1, 3), padding=(0, 1)) # conv_5
self.conv_6 = nn.Conv2d(512, 512, kernel_size=(1, 3), padding=(0, 1)) # conv_6
self.conv_7 = nn.Conv2d(512, 512, kernel_size=(1, 3), padding=(0, 1)) # conv_7
self.relu = nn.ReLU(inplace=True)
self.max_pool = nn.MaxPool2d(kernel_size=(1, 2), stride=(1, 2))
self.channels = in_channels
self.classifier = nn.Sequential(
nn.Linear(time_step_dim * 512, 512),
nn.ReLU(inplace=True),
nn.Dropout(p=0.25),
nn.Linear(512, 128),
nn.ReLU(inplace=True),
nn.Dropout(p=0.25),
nn.Linear(128, 32),
nn.ReLU(inplace=True),
nn.Dropout(p=0.25),
nn.Linear(32, num_classes),
)
def forward(self, x: torch.Tensor) -> torch.Tensor:
x = self.conv_1(x)
x = self.relu(x)
residual_1 = x
output = self.conv_2(x)
output += residual_1
output = self.relu(output)
output = self.max_pool(output)
output_2 = self.conv_3(output)
residual_2 = output_2
output_2 = self.relu(output_2)
output_2 = self.conv_4(output_2)
output_2 += residual_2
output_2 = self.relu(output_2)
output_2 = self.max_pool(output_2)
output_3 = self.conv_5(output_2)
output_3 = self.relu(output_3)
residual_3 = output_3
output_3 = self.conv_6(output_3)
output_3 = self.relu(output_3)
output_3 = self.conv_7(output_3)
output_3 += residual_3
output_3 = self.relu(output_3)
output_3 = output_3.sum(axis=2)
output_3 = torch.flatten(output_3, 1)
output_3 = self.classifier(output_3)
return output_3
class VggIMGSum(nn.Module):
"""
Treat inputs as a image using 3x1 kernel, e.g. mesa H=9, W=101
"""
def __init__(self, in_channels=9, num_classes=3, time_step_dim=25) -> None:
super(VggIMGSum, self).__init__()
self.channels = in_channels
self.features = nn.Sequential(
# #### block 1
nn.Conv2d(1, 512, kernel_size=(1, 3), padding=(0, 1)), # con_1
nn.ReLU(inplace=True),
nn.Conv2d(512, 512, kernel_size=(1, 3), padding=(0, 1)), # con_2
nn.ReLU(inplace=True),
nn.MaxPool2d(kernel_size=(1, 2), stride=(1, 2)), # max_pool
# #### block 2
nn.Conv2d(512, 128, kernel_size=(1, 3), padding=(0, 1)), # con_3
nn.ReLU(inplace=True),
nn.Conv2d(128, 128, kernel_size=(1, 3), padding=(0, 1)), # con_4
nn.ReLU(inplace=True),
nn.MaxPool2d(kernel_size=(1, 2), stride=(1, 2)), # max pool
# #### block 3 = con_3
nn.Conv2d(128, 512, kernel_size=(1, 3), padding=(0, 1)), # con_5
nn.ReLU(inplace=True),
nn.Conv2d(512, 512, kernel_size=(1, 3), padding=(0, 1)), # con_6
nn.ReLU(inplace=True),
nn.Conv2d(512, 512, kernel_size=(1, 3), padding=(0, 1)), # con_7
nn.ReLU(inplace=True),
)
self.classifier = nn.Sequential(
nn.Linear(time_step_dim * 512, 512),
nn.ReLU(inplace=True),
nn.Dropout(p=0.25),
nn.Linear(512, 128),
nn.ReLU(inplace=True),
nn.Dropout(p=0.25),
nn.Linear(128, 32),
nn.ReLU(inplace=True),
nn.Dropout(p=0.25),
nn.Linear(32, num_classes),
)
def forward(self, x: torch.Tensor) -> torch.Tensor:
x = self.features(x)
x = x.sum(axis=2)
x = torch.flatten(x, 1)
x = self.classifier(x)
return x
class VggIMGNOFC(nn.Module):
"""
Treat inputs as a image using 3x1 kernel, e.g. mesa H=9, W=101
"""
def __init__(self) -> None:
super(VggIMGNOFC, self).__init__()
self.features = nn.Sequential(
# #### block 1
nn.Conv2d(1, 512, kernel_size=(1, 3), padding=(0, 1)), # con_1
nn.ReLU(inplace=True),
nn.Conv2d(512, 512, kernel_size=(1, 3), padding=(0, 1)), # con_2
nn.ReLU(inplace=True),
nn.MaxPool2d(kernel_size=(1, 2), stride=(1, 2)), # max_pool
# #### block 2
nn.Conv2d(512, 128, kernel_size=(1, 3), padding=(0, 1)), # con_3
nn.ReLU(inplace=True),
nn.Conv2d(128, 128, kernel_size=(1, 3), padding=(0, 1)), # con_4
nn.ReLU(inplace=True),
nn.MaxPool2d(kernel_size=(1, 2), stride=(1, 2)), # max pool
# #### block 3 = con_3
nn.Conv2d(128, 512, kernel_size=(1, 3), padding=(0, 1)), # con_5
nn.ReLU(inplace=True),
nn.Conv2d(512, 512, kernel_size=(1, 3), padding=(0, 1)), # con_6
nn.ReLU(inplace=True),
nn.Conv2d(512, 512, kernel_size=(1, 3), padding=(0, 1)), # con_7
nn.ReLU(inplace=True),
)
def forward(self, x: torch.Tensor) -> torch.Tensor:
x = self.features(x)
return x
class VggIMGResNOFC(nn.Module):
"""
Treat inputs as a image using 3x1 kernel, e.g. mesa H=9, W=101
"""
def __init__(self, in_channels=9, num_classes=3, time_step_dim=25) -> None:
super(VggIMGResNOFC, self).__init__()
self.conv_1 = nn.Conv2d(1, 512, kernel_size=(1, 3), padding=(0, 1)) # con_1
self.conv_2 = nn.Conv2d(512, 512, kernel_size=(1, 3), padding=(0, 1)) # con_2
self.conv_3 = nn.Conv2d(512, 128, kernel_size=(1, 3), padding=(0, 1)) # conv_3
self.conv_4 = nn.Conv2d(128, 128, kernel_size=(1, 3), padding=(0, 1)) # conv_4
self.conv_5 = nn.Conv2d(128, 512, kernel_size=(1, 3), padding=(0, 1)) # conv_5
self.conv_6 = nn.Conv2d(512, 512, kernel_size=(1, 3), padding=(0, 1)) # conv_6
self.conv_7 = nn.Conv2d(512, 512, kernel_size=(1, 3), padding=(0, 1)) # conv_7
self.relu = nn.ReLU(inplace=True)
self.max_pool = nn.MaxPool2d(kernel_size=(1, 2), stride=(1, 2))
def forward(self, x: torch.Tensor) -> torch.Tensor:
x = self.conv_1(x)
x = self.relu(x)
residual_1 = x
output = self.conv_2(x)
output += residual_1
output = self.relu(output)
output = self.max_pool(output)
output_2 = self.conv_3(output)
residual_2 = output_2
output_2 = self.relu(output_2)
output_2 = self.conv_4(output_2)
output_2 += residual_2
output_2 = self.relu(output_2)
output_2 = self.max_pool(output_2)
output_3 = self.conv_5(output_2)
output_3 = self.relu(output_3)
residual_3 = output_3
output_3 = self.conv_6(output_3)
output_3 = self.relu(output_3)
output_3 = self.conv_7(output_3)
output_3 += residual_3
output_3 = self.relu(output_3)
return output_3
| 39.087948 | 87 | 0.555167 | 1,793 | 12,000 | 3.523146 | 0.045176 | 0.041159 | 0.088808 | 0.079785 | 0.95615 | 0.952984 | 0.952984 | 0.952984 | 0.952984 | 0.952984 | 0 | 0.103277 | 0.295583 | 12,000 | 306 | 88 | 39.215686 | 0.644032 | 0.067 | 0 | 0.88 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.052 | false | 0 | 0.008 | 0 | 0.112 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
3393c05f17122c315f018eb952815b894d1f5ade | 8,522 | py | Python | tests/redeem_deposit_test.py | mixbytes/lido-dot-ksm | d9cfa4bd113a14d18cf2e4c8cf2c9a08dde8e5ff | [
"MIT"
] | null | null | null | tests/redeem_deposit_test.py | mixbytes/lido-dot-ksm | d9cfa4bd113a14d18cf2e4c8cf2c9a08dde8e5ff | [
"MIT"
] | 5 | 2022-03-21T15:23:26.000Z | 2022-03-28T07:59:27.000Z | tests/redeem_deposit_test.py | mixbytes/lido-dot-ksm | d9cfa4bd113a14d18cf2e4c8cf2c9a08dde8e5ff | [
"MIT"
] | null | null | null | from brownie import chain
from helpers import RelayChain, distribute_initial_tokens
def test_redeem_right_after_deposit_equal(lido, oracle_master, vKSM, accounts):
distribute_initial_tokens(vKSM, lido, accounts)
relay = RelayChain(lido, vKSM, oracle_master, accounts, chain)
relay.new_ledger("0x10", "0x11")
relay.new_ledger("0x20", "0x21")
relay.new_ledger("0x30", "0x31")
deposit = 20 * 10**18
lido.deposit(deposit, {'from': accounts[0]})
relay.new_era()
assert relay.ledgers[0].free_balance > 0
assert relay.ledgers[1].free_balance > 0
assert relay.ledgers[2].free_balance > 0
assert relay.ledgers[0].active_balance == 0
assert relay.ledgers[1].active_balance == 0
assert relay.ledgers[2].active_balance == 0
for i in range(20):
relay.new_era()
# 0. Save ledger stakes before actions
led1_stake = lido.ledgerStake(relay.ledgers[0].ledger_address)
led2_stake = lido.ledgerStake(relay.ledgers[1].ledger_address)
led3_stake = lido.ledgerStake(relay.ledgers[2].ledger_address)
# 1. Deposit and redeem before new era
deposit_2 = 5 * 10**18
lido.deposit(deposit_2, {'from': accounts[1]})
lido.redeem(deposit_2, {'from': accounts[1]})
relay.new_era()
# 2. Check token distirbution after new era
led1_stake_upd = lido.ledgerStake(relay.ledgers[0].ledger_address)
led2_stake_upd = lido.ledgerStake(relay.ledgers[1].ledger_address)
led3_stake_upd = lido.ledgerStake(relay.ledgers[2].ledger_address)
assert led1_stake_upd == led1_stake
assert led2_stake_upd == led2_stake
assert led3_stake_upd == led3_stake
# 3. check unbonding balance
(waitingToUnbonding, readyToClaim) = lido.getUnbonded(accounts[1])
assert waitingToUnbonding == deposit_2
assert readyToClaim == 0
# 4. wait and check
relay.new_era()
(waitingToUnbonding, readyToClaim) = lido.getUnbonded(accounts[1])
assert waitingToUnbonding == 0
assert readyToClaim == deposit_2
balance_before_claim = vKSM.balanceOf(accounts[1])
lido.claimUnbonded({'from': accounts[1]})
assert vKSM.balanceOf(accounts[1]) == (deposit_2 + balance_before_claim)
def test_redeem_right_after_deposit_less(lido, oracle_master, vKSM, accounts):
distribute_initial_tokens(vKSM, lido, accounts)
relay = RelayChain(lido, vKSM, oracle_master, accounts, chain)
relay.new_ledger("0x10", "0x11")
deposit = 20 * 10**18
lido.deposit(deposit, {'from': accounts[0]})
relay.new_era()
relay.new_era()
# 0. Save ledger stakes before actions
led1_stake = lido.ledgerStake(relay.ledgers[0].ledger_address)
# 1. Deposit and redeem before new era
deposit_2 = 5 * 10**18
redeem = 4 * 10**18
lido.deposit(deposit_2, {'from': accounts[1]})
lido.redeem(redeem, {'from': accounts[1]})
relay.new_era()
# 2. Check token distirbution after new era
led1_stake_upd = lido.ledgerStake(relay.ledgers[0].ledger_address)
assert led1_stake_upd == (led1_stake + (deposit_2 - redeem))
# 3. check unbonding balance
(waitingToUnbonding, readyToClaim) = lido.getUnbonded(accounts[1])
assert waitingToUnbonding == redeem
assert readyToClaim == 0
# 4. wait and check
relay.new_era()
(waitingToUnbonding, readyToClaim) = lido.getUnbonded(accounts[1])
assert waitingToUnbonding == 0
assert readyToClaim == redeem
balance_before_claim = vKSM.balanceOf(accounts[1])
lido.claimUnbonded({'from': accounts[1]})
assert vKSM.balanceOf(accounts[1]) == (redeem + balance_before_claim)
def test_redeem_right_after_deposit_greater(lido, oracle_master, vKSM, accounts):
distribute_initial_tokens(vKSM, lido, accounts)
relay = RelayChain(lido, vKSM, oracle_master, accounts, chain)
relay.new_ledger("0x10", "0x11")
deposit = 20 * 10**18
lido.deposit(deposit, {'from': accounts[0]})
relay.new_era()
relay.new_era()
# 0. Save ledger stakes before actions
led1_stake = lido.ledgerStake(relay.ledgers[0].ledger_address)
# 1. Deposit and redeem before new era
deposit_2 = 5 * 10**18
redeem = 8 * 10**18
lido.deposit(deposit_2, {'from': accounts[0]})
lido.redeem(redeem, {'from': accounts[0]})
relay.new_era()
# 2. Check token distirbution after new era
led1_stake_upd = lido.ledgerStake(relay.ledgers[0].ledger_address)
assert led1_stake_upd == (led1_stake - (redeem - deposit_2))
# 3. check unbonding balance
(waitingToUnbonding, readyToClaim) = lido.getUnbonded(accounts[0])
assert waitingToUnbonding == redeem
assert readyToClaim == 0
# 5. wait for unbonding
for i in range(33):
relay.new_era()
balance_before_claim = vKSM.balanceOf(accounts[0])
lido.claimUnbonded({'from': accounts[0]})
assert vKSM.balanceOf(accounts[0]) == (redeem + balance_before_claim)
def test_deposit_after_redeem_in_new_era(lido, oracle_master, vKSM, accounts):
distribute_initial_tokens(vKSM, lido, accounts)
relay = RelayChain(lido, vKSM, oracle_master, accounts, chain)
relay.new_ledger("0x10", "0x11")
relay.new_ledger("0x20", "0x21")
deposit = 20 * 10**12
lido.deposit(deposit, {'from': accounts[0]})
relay.new_era()
relay.new_era()
redeem = 10 * 10**12
lido.redeem(redeem, {'from': accounts[0]})
relay.new_era()
assert relay.ledgers[0].active_balance == (deposit - redeem) / 2
assert relay.ledgers[1].active_balance == (deposit - redeem) / 2
lido.deposit(redeem, {'from': accounts[1]})
relay.new_era() # transfer excess to withdrawal
relay.new_era() # remove element from queue
(waitingToUnbonding, readyToClaim) = lido.getUnbonded(accounts[0])
assert waitingToUnbonding == 0
assert readyToClaim == redeem
balance_before_claim = vKSM.balanceOf(accounts[0])
lido.claimUnbonded({'from': accounts[0]})
assert vKSM.balanceOf(accounts[0]) == (redeem + balance_before_claim)
def test_deposit_after_redeem_in_new_era_less(lido, oracle_master, vKSM, Ledger, accounts):
distribute_initial_tokens(vKSM, lido, accounts)
relay = RelayChain(lido, vKSM, oracle_master, accounts, chain)
relay.new_ledger("0x10", "0x11")
deposit = 20 * 10**12
lido.deposit(deposit, {'from': accounts[0]})
relay.new_era()
relay.new_era()
assert Ledger.at(lido.findLedger(relay.ledgers[0].stash_account)).ledgerStake() == deposit
redeem = 5 * 10**12
lido.redeem(redeem, {'from': accounts[0]})
relay.new_era()
assert Ledger.at(lido.findLedger(relay.ledgers[0].stash_account)).ledgerStake() == deposit - redeem
deposit_2 = 15 * 10**12
lido.deposit(deposit_2, {'from': accounts[1]})
relay.new_era() # transfer excess to withdrawal
relay.new_era() # remove element from queue
assert Ledger.at(lido.findLedger(relay.ledgers[0].stash_account)).ledgerStake() == deposit + (deposit_2 - redeem)
(waitingToUnbonding, readyToClaim) = lido.getUnbonded(accounts[0])
assert waitingToUnbonding == 0
assert readyToClaim == redeem
balance_before_claim = vKSM.balanceOf(accounts[0])
lido.claimUnbonded({'from': accounts[0]})
assert vKSM.balanceOf(accounts[0]) == (redeem + balance_before_claim)
def test_deposit_after_redeem_in_new_era_greater(lido, oracle_master, vKSM, Ledger, accounts):
distribute_initial_tokens(vKSM, lido, accounts)
relay = RelayChain(lido, vKSM, oracle_master, accounts, chain)
relay.new_ledger("0x10", "0x11")
deposit = 20 * 10**12
lido.deposit(deposit, {'from': accounts[0]})
relay.new_era()
relay.new_era()
assert Ledger.at(lido.findLedger(relay.ledgers[0].stash_account)).ledgerStake() == deposit
redeem = 10 * 10**12
lido.redeem(redeem, {'from': accounts[0]})
relay.new_era()
assert Ledger.at(lido.findLedger(relay.ledgers[0].stash_account)).ledgerStake() == deposit - redeem
deposit_2 = 5 * 10**12
lido.deposit(deposit_2, {'from': accounts[1]})
relay.new_era()
assert Ledger.at(lido.findLedger(relay.ledgers[0].stash_account)).ledgerStake() == deposit + (deposit_2 - redeem)
(waitingToUnbonding, readyToClaim) = lido.getUnbonded(accounts[0])
assert waitingToUnbonding == redeem
assert readyToClaim == 0
for i in range(32):
relay.new_era()
balance_before_claim = vKSM.balanceOf(accounts[0])
lido.claimUnbonded({'from': accounts[0]})
assert vKSM.balanceOf(accounts[0]) == (redeem + balance_before_claim) | 30.765343 | 117 | 0.697489 | 1,094 | 8,522 | 5.256856 | 0.082267 | 0.050078 | 0.051643 | 0.031299 | 0.955834 | 0.940358 | 0.89654 | 0.884716 | 0.870283 | 0.824204 | 0 | 0.040729 | 0.176015 | 8,522 | 277 | 118 | 30.765343 | 0.778268 | 0.070171 | 0 | 0.743902 | 0 | 0 | 0.021252 | 0 | 0 | 0 | 0.009108 | 0 | 0.25 | 1 | 0.036585 | false | 0 | 0.012195 | 0 | 0.04878 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
33bfe3938c921779de89f8550adc636b7f2f43fb | 117 | py | Python | python/testData/refactoring/move/moveDoesntMergeFromImportsAccordingToCodeStyle/after/src/dst.py | jnthn/intellij-community | 8fa7c8a3ace62400c838e0d5926a7be106aa8557 | [
"Apache-2.0"
] | 2 | 2019-04-28T07:48:50.000Z | 2020-12-11T14:18:08.000Z | python/testData/refactoring/move/moveDoesntMergeFromImportsAccordingToCodeStyle/after/src/dst.py | Cyril-lamirand/intellij-community | 60ab6c61b82fc761dd68363eca7d9d69663cfa39 | [
"Apache-2.0"
] | 173 | 2018-07-05T13:59:39.000Z | 2018-08-09T01:12:03.000Z | python/testData/refactoring/move/moveDoesntMergeFromImportsAccordingToCodeStyle/after/src/dst.py | Cyril-lamirand/intellij-community | 60ab6c61b82fc761dd68363eca7d9d69663cfa39 | [
"Apache-2.0"
] | 2 | 2020-03-15T08:57:37.000Z | 2020-04-07T04:48:14.000Z | from lib import bar
from lib import baz, quux
from lib import foo
print(baz, quux)
def func():
print(foo, bar) | 13 | 25 | 0.700855 | 21 | 117 | 3.904762 | 0.47619 | 0.256098 | 0.47561 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.213675 | 117 | 9 | 26 | 13 | 0.891304 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.166667 | true | 0 | 0.5 | 0 | 0.666667 | 0.333333 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
33d79871557dc79e9faae381c037ca5743ff7435 | 239 | py | Python | examples/middleware.py | David-Wobrock/simpleflow | 09f59105b48ae79aef37b506bbde0cd1f2c360d1 | [
"MIT"
] | 69 | 2015-02-24T00:49:40.000Z | 2022-02-05T02:35:04.000Z | examples/middleware.py | David-Wobrock/simpleflow | 09f59105b48ae79aef37b506bbde0cd1f2c360d1 | [
"MIT"
] | 295 | 2015-02-06T11:02:00.000Z | 2022-03-21T11:01:34.000Z | examples/middleware.py | David-Wobrock/simpleflow | 09f59105b48ae79aef37b506bbde0cd1f2c360d1 | [
"MIT"
] | 27 | 2015-08-31T22:14:42.000Z | 2022-02-08T07:25:01.000Z | def my_pre_execution_middleware(context, **kwargs):
print("AAAH PRE EXECUTION MIDDLEWARE", context)
def my_post_execution_middleware(context, result, **kwargs):
print("AAAH POST EXECUTION MIDDLEWARE", "activity result:", result)
| 34.142857 | 71 | 0.76569 | 29 | 239 | 6.103448 | 0.413793 | 0.429379 | 0.440678 | 0.327684 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.121339 | 239 | 6 | 72 | 39.833333 | 0.842857 | 0 | 0 | 0 | 0 | 0 | 0.313808 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.5 | false | 0 | 0 | 0 | 0.5 | 0.5 | 1 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 7 |
1d313a592762c41ab237bf1484187ca6a0afff37 | 90 | py | Python | scripts/graph/rrn/__init__.py | dair-iitd/1oML_workdir | 37117de4abf1774548786e9534c90977d67091d8 | [
"Apache-2.0"
] | 3 | 2021-05-07T02:41:54.000Z | 2022-02-10T05:18:55.000Z | scripts/graph/rrn/__init__.py | dair-iitd/1oML_workdir | 37117de4abf1774548786e9534c90977d67091d8 | [
"Apache-2.0"
] | null | null | null | scripts/graph/rrn/__init__.py | dair-iitd/1oML_workdir | 37117de4abf1774548786e9534c90977d67091d8 | [
"Apache-2.0"
] | null | null | null | from .rrn import *
from .sudoku import *
from .sudoku_data import *
#import .sudoku_data
| 15 | 26 | 0.744444 | 13 | 90 | 5 | 0.384615 | 0.307692 | 0.492308 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.166667 | 90 | 5 | 27 | 18 | 0.866667 | 0.211111 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
1d410ce5953d7a05e5a377ee96b89775dc5c9f7e | 3,621 | py | Python | code_tools/src/bsd_3_clause_license.py | xykivo/percipio | a583b7887d5515d928ad4c47c425c4363462838c | [
"BSD-3-Clause"
] | 2 | 2016-04-14T09:11:01.000Z | 2016-05-05T17:52:33.000Z | code_tools/src/bsd_3_clause_license.py | xykivo/percipio | a583b7887d5515d928ad4c47c425c4363462838c | [
"BSD-3-Clause"
] | 4 | 2018-04-03T02:53:08.000Z | 2018-12-08T00:18:41.000Z | code_tools/src/bsd_3_clause_license.py | xykivo/percipio | a583b7887d5515d928ad4c47c425c4363462838c | [
"BSD-3-Clause"
] | null | null | null | #!/usr/bin/python3
# -*- coding: utf-8 -*-
# BSD 3-Clause License
#
# Copyright (c) 2021, Dror Smolarsky
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following disclaimer.
#
# 2. Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
#
# 3. Neither the name of the copyright holder nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
'''This file contains constants for the BSD 3 clause license.
The constants contain regular expression captures and escapes so they can be
used to compare to licenses in files using regular expression matching.
The constants are stored as a sequence of lines, where each line contains one
line form the license.
'''
BSD_LICENSE_3_CLAUSE = r'''BSD 3-Clause License
Copyright \(c\) (?P<year>[\d\-]+), (?P<copyright_owner>[\w\s]+)
All rights reserved\.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
1\. Redistributions of source code must retain the above copyright notice,
this list of conditions and the following disclaimer\.
2\. Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution\.
3\. Neither the name of the copyright holder nor the names of its
contributors may be used to endorse or promote products derived from
this software without specific prior written permission\.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
ARE DISCLAIMED\. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
CONSEQUENTIAL DAMAGES \(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
INTERRUPTION\) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
CONTRACT, STRICT LIABILITY, OR TORT \(INCLUDING NEGLIGENCE OR OTHERWISE\)
ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
POSSIBILITY OF SUCH DAMAGE\.
'''.split('\n')
| 48.28 | 79 | 0.765811 | 527 | 3,621 | 5.254269 | 0.316888 | 0.026002 | 0.024558 | 0.033225 | 0.876851 | 0.876851 | 0.857349 | 0.857349 | 0.857349 | 0.857349 | 0 | 0.005402 | 0.181994 | 3,621 | 74 | 80 | 48.932432 | 0.92944 | 0.515051 | 0 | 0 | 0 | 0 | 0.952555 | 0.017032 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
1d4bedc87cfc353189f577742fc5ac0a24898e5d | 35 | py | Python | Problems/Calculate it/main.py | TataSatyaPratheek/Tic-Tac-Toe | fa3da80f9ec9ffa3c8c9aaa34a5bb1e88553fecd | [
"MIT"
] | null | null | null | Problems/Calculate it/main.py | TataSatyaPratheek/Tic-Tac-Toe | fa3da80f9ec9ffa3c8c9aaa34a5bb1e88553fecd | [
"MIT"
] | null | null | null | Problems/Calculate it/main.py | TataSatyaPratheek/Tic-Tac-Toe | fa3da80f9ec9ffa3c8c9aaa34a5bb1e88553fecd | [
"MIT"
] | null | null | null | print((1234567890*987654321)+67890) | 35 | 35 | 0.828571 | 4 | 35 | 7.25 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.685714 | 0 | 35 | 1 | 35 | 35 | 0.142857 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 7 |
1d98de36b51912212cbeec045cba61df6188c6ac | 1,945 | py | Python | test_1D.py | jl2264/Flood44 | e2b83a6e7da86d200d9e63394e346211e27536c7 | [
"MIT"
] | null | null | null | test_1D.py | jl2264/Flood44 | e2b83a6e7da86d200d9e63394e346211e27536c7 | [
"MIT"
] | null | null | null | test_1D.py | jl2264/Flood44 | e2b83a6e7da86d200d9e63394e346211e27536c7 | [
"MIT"
] | 1 | 2022-02-06T23:00:09.000Z | 2022-02-06T23:00:09.000Z |
from floodsystem.geo import rivers_with_station
from floodsystem.station import MonitoringStation
def test_rivers_with_station_no_duplicate():
stations = []
s1 = MonitoringStation(
station_id=1,
measure_id=1,
label='label1',
coord=(float(52.2053), float(0.1218)),
typical_range='typical_range',
river='river1',
town='town')
s2 = MonitoringStation(
station_id=2,
measure_id=1,
label='label2',
coord=(float(2.2053), float(10.1218)),
typical_range='typical_range',
river='river2',
town='town')
s3 = MonitoringStation(
station_id=3,
measure_id=1,
label='label3',
coord=(float(52.2153), float(0.1318)),
typical_range='typical_range',
river='river3',
town='town')
stations.append(s1)
stations.append(s2)
stations.append(s3)
list_test_1D = rivers_with_station(stations)
assert len(list_test_1D) == 3 # all of the station rivers
def test_rivers_with_station_with_duplicate():
stations = []
s1 = MonitoringStation(
station_id=1,
measure_id=1,
label='label1',
coord=(float(52.2053), float(0.1218)),
typical_range='typical_range',
river='river1',
town='town')
s2 = MonitoringStation(
station_id=2,
measure_id=1,
label='label2',
coord=(float(2.2053), float(10.1218)),
typical_range='typical_range',
river='river2',
town='town')
s3 = MonitoringStation(
station_id=3,
measure_id=1,
label='label3',
coord=(float(52.2153), float(0.1318)),
typical_range='typical_range',
river='river1',
town='town')
stations.append(s1)
stations.append(s2)
stations.append(s3)
list_test_1D = rivers_with_station(stations)
assert len(list_test_1D) == 2 # all of the station rivers with one duplicate
assert list_test_1D[0] == s1.river
assert list_test_1D[1] == s2.river
assert s1.river == s3.river
| 22.616279 | 82 | 0.653985 | 254 | 1,945 | 4.80315 | 0.19685 | 0.118033 | 0.127869 | 0.07377 | 0.84918 | 0.77541 | 0.77541 | 0.77541 | 0.770492 | 0.770492 | 0 | 0.075718 | 0.212339 | 1,945 | 85 | 83 | 22.882353 | 0.720627 | 0.03599 | 0 | 0.850746 | 0 | 0 | 0.092998 | 0 | 0 | 0 | 0 | 0 | 0.074627 | 1 | 0.029851 | false | 0 | 0.029851 | 0 | 0.059701 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
1daa3aa15bbf2d249439189e5cd6e4758de130df | 45,169 | py | Python | SBaaS_thermodynamics/stage03_quantification_dG_r_query.py | dmccloskey/SBaaS_thermodynamics | 0eeed0191f952ea0226ab8bbc234a30638fb2f9f | [
"MIT"
] | null | null | null | SBaaS_thermodynamics/stage03_quantification_dG_r_query.py | dmccloskey/SBaaS_thermodynamics | 0eeed0191f952ea0226ab8bbc234a30638fb2f9f | [
"MIT"
] | null | null | null | SBaaS_thermodynamics/stage03_quantification_dG_r_query.py | dmccloskey/SBaaS_thermodynamics | 0eeed0191f952ea0226ab8bbc234a30638fb2f9f | [
"MIT"
] | null | null | null | #SBaaS models
from .stage03_quantification_dG_r_postgresql_models import *
#SBaaS base
from SBaaS_base.sbaas_base import sbaas_base
from SBaaS_base.sbaas_base_query_update import sbaas_base_query_update
from SBaaS_base.sbaas_base_query_drop import sbaas_base_query_drop
from SBaaS_base.sbaas_base_query_initialize import sbaas_base_query_initialize
from SBaaS_base.sbaas_base_query_insert import sbaas_base_query_insert
from SBaaS_base.sbaas_base_query_select import sbaas_base_query_select
from SBaaS_base.sbaas_base_query_delete import sbaas_base_query_delete
from SBaaS_base.sbaas_template_query import sbaas_template_query
#Resources
#from math import copysign
class stage03_quantification_dG_r_query(sbaas_template_query):
def initialize_supportedTables(self):
'''Set the supported tables dict for data_stage03_quantification_dG_r
'''
tables_supported = {
'data_stage03_quantification_dG0_r':data_stage03_quantification_dG0_r,
'data_stage03_quantification_dG_r':data_stage03_quantification_dG_r,
'data_stage03_quantification_tcc':data_stage03_quantification_tcc,
'data_stage03_quantification_dG_r_comparison':data_stage03_quantification_dG_r_comparison,
};
self.set_supportedTables(tables_supported);
## Query from data_stage03_quantification_dG0_r
# query rows from data_stage03_quantificaton_dG0_r
def get_rowsDict_experimentIDAndModelIDAndTimePointAndSampleNameAbbreviations_dataStage03QuantificationDG0r(self,experiment_id_I,
model_id_I,
time_point_I,
sample_name_abbreviation_I,
measured_dG_f_coverage_criteria_I=0.0):
'''Query rows that are used from the dG_r'''
try:
#data = self.session.query(data_stage03_quantification_dG0_r).filter(
# data_stage03_quantification_dG0_r.model_id.like(model_id_I),
# data_stage03_quantification_dG0_r.time_point.like(time_point_I),
# data_stage03_quantification_dG0_r.sample_name_abbreviation.like(sample_name_abbreviation_I),
# data_stage03_quantification_dG0_r.experiment_id.like(experiment_id_I),
# data_stage03_quantification_dG0_r.model_id.like(data_stage03_quantification_tcc.model_id),
# data_stage03_quantification_dG0_r.time_point.like(data_stage03_quantification_tcc.time_point),
# data_stage03_quantification_dG0_r.sample_name_abbreviation.like(data_stage03_quantification_tcc.sample_name_abbreviation),
# data_stage03_quantification_dG0_r.experiment_id.like(data_stage03_quantification_tcc.experiment_id),
# data_stage03_quantification_dG0_r.rxn_id.like(data_stage03_quantification_tcc.rxn_id),
# data_stage03_quantification_tcc.measured_dG_f_coverage>measured_dG_f_coverage_criteria_I,
# data_stage03_quantification_dG0_r.used_.is_(True)).all();
data = self.session.query(data_stage03_quantification_dG0_r).filter(
data_stage03_quantification_dG0_r.model_id.like(model_id_I),
data_stage03_quantification_dG0_r.time_point.like(time_point_I),
data_stage03_quantification_dG0_r.sample_name_abbreviation.like(sample_name_abbreviation_I),
data_stage03_quantification_dG0_r.experiment_id.like(experiment_id_I),
data_stage03_quantification_dG0_r.used_.is_(True)).all();
rows_O = {};
if data:
for d in data:
if d.rxn_id in rows_O:
print('duplicate rxn_id found!');
else:
rows_O[d.rxn_id]={
'Keq_lb':d.Keq_lb,
'Keq_ub':d.Keq_ub,
'dG_r':d.dG0_r,
'dG_r_var':d.dG0_r_var,
'dG_r_units':d.dG0_r_units,
'dG_r_lb':d.dG0_r_lb,
'dG_r_ub':d.dG0_r_ub};
return rows_O;
except SQLAlchemyError as e:
print(e);
# update rows of data_stage03_quantification_dG0_r
def update_dataStage03DG0r(self,data_I):
'''update rows of data_stage03_quantification_dG0_r'''
if data_I:
for d in data_I:
try:
data_update = self.session.query(data_stage03_quantification_dG0_r).filter(
data_stage03_quantification_dG0_r.experiment_id.like(d['experiment_id']),
data_stage03_quantification_dG0_r.model_id.like(d['model_id']),
data_stage03_quantification_dG0_r.rxn_id.like(d['rxn_id']),
data_stage03_quantification_dG_r.sample_name_abbreviation.like(d['sample_name_abbreviation']),
data_stage03_quantification_dG_r.time_point.like(d['time_point'])).update(
{
'Keq_lb':d['Keq_lb'],
'Keq_ub':d['Keq_ub'],
'dG0_r':d['dG0_r'],
'dG0_r_var':d['dG0_r_var'],
'dG0_r_units':d['dG0_r_units'],
'dG0_r_lb':d['dG0_r_lb'],
'dG0_r_ub':d['dG0_r_ub'],
'used_':d['used_'],
'comment_':d['comment_']},
synchronize_session=False);
except SQLAlchemyError as e:
print(e);
self.session.commit();
## Query from data_stage03_quantification_dG_r
# query rows from data_stage03_quantification_dG_r
def get_rows_experimentIDAndModelIDAndTimePointAndSampleNameAbbreviations_dataStage03QuantificationDGr(self,experiment_id_I,
model_id_I,
time_point_I,
sample_name_abbreviation_I,
measured_concentration_coverage_criteria_I=0.5,
measured_dG_f_coverage_criteria_I=0.99):
'''Query rows that are used from the dG_r'''
try:
data = self.session.query(data_stage03_quantification_dG_r).filter(
data_stage03_quantification_dG_r.model_id.like(model_id_I),
data_stage03_quantification_dG_r.time_point.like(time_point_I),
data_stage03_quantification_dG_r.sample_name_abbreviation.like(sample_name_abbreviation_I),
data_stage03_quantification_dG_r.experiment_id.like(experiment_id_I),
data_stage03_quantification_dG_r.model_id.like(data_stage03_quantification_tcc.model_id),
data_stage03_quantification_dG_r.time_point.like(data_stage03_quantification_tcc.time_point),
data_stage03_quantification_dG_r.sample_name_abbreviation.like(data_stage03_quantification_tcc.sample_name_abbreviation),
data_stage03_quantification_dG_r.experiment_id.like(data_stage03_quantification_tcc.experiment_id),
data_stage03_quantification_dG_r.rxn_id.like(data_stage03_quantification_tcc.rxn_id),
data_stage03_quantification_tcc.measured_concentration_coverage>measured_concentration_coverage_criteria_I,
data_stage03_quantification_tcc.measured_dG_f_coverage>measured_dG_f_coverage_criteria_I,
data_stage03_quantification_tcc.used_.is_(True),
data_stage03_quantification_dG_r.used_.is_(True)).all();
rows_O = [];
if data:
for d in data:
data_tmp = {'experiment_id':d.experiment_id,
'model_id':d.model_id,
'sample_name_abbreviation':d.sample_name_abbreviation,
'time_point':d.time_point,
'rxn_id':d.rxn_id,
'Keq_lb':d.Keq_lb,
'Keq_ub':d.Keq_ub,
'dG_r':d.dG_r,
'dG_r_var':d.dG_r_var,
'dG_r_units':d.dG_r_units,
'dG_r_lb':d.dG_r_lb,
'dG_r_ub':d.dG_r_ub,
'displacement_lb':d.displacement_lb,
'displacement_ub':d.displacement_ub,
'Q_lb':d.Q_lb,
'Q_ub':d.Q_ub,
'used_':d.used_,
'comment_':d.comment_};
rows_O.append(data_tmp);
return rows_O;
except SQLAlchemyError as e:
print(e);
def get_rowsDict_experimentIDAndModelIDAndTimePointAndSampleNameAbbreviations_dataStage03QuantificationDGr(self,experiment_id_I,
model_id_I,
time_point_I,
sample_name_abbreviation_I,
measured_concentration_coverage_criteria_I=0.0,
measured_dG_f_coverage_criteria_I=0.0):
'''Query rows that are used from the dG_r'''
try:
#data = self.session.query(data_stage03_quantification_dG_r).filter(
# data_stage03_quantification_dG_r.model_id.like(model_id_I),
# data_stage03_quantification_dG_r.time_point.like(time_point_I),
# data_stage03_quantification_dG_r.sample_name_abbreviation.like(sample_name_abbreviation_I),
# data_stage03_quantification_dG_r.experiment_id.like(experiment_id_I),
# data_stage03_quantification_dG_r.model_id.like(data_stage03_quantification_tcc.model_id),
# data_stage03_quantification_dG_r.time_point.like(data_stage03_quantification_tcc.time_point),
# data_stage03_quantification_dG_r.sample_name_abbreviation.like(data_stage03_quantification_tcc.sample_name_abbreviation),
# data_stage03_quantification_dG_r.experiment_id.like(data_stage03_quantification_tcc.experiment_id),
# data_stage03_quantification_dG_r.rxn_id.like(data_stage03_quantification_tcc.rxn_id),
# data_stage03_quantification_tcc.measured_concentration_coverage>measured_concentration_coverage_criteria_I,
# data_stage03_quantification_tcc.measured_dG_f_coverage>measured_dG_f_coverage_criteria_I,
# data_stage03_quantification_dG_r.used_.is_(True)).all();
data = self.session.query(data_stage03_quantification_dG_r).filter(
data_stage03_quantification_dG_r.model_id.like(model_id_I),
data_stage03_quantification_dG_r.time_point.like(time_point_I),
data_stage03_quantification_dG_r.sample_name_abbreviation.like(sample_name_abbreviation_I),
data_stage03_quantification_dG_r.experiment_id.like(experiment_id_I),
data_stage03_quantification_dG_r.used_.is_(True)).all();
rows_O = {};
if data:
for d in data:
if d.rxn_id in rows_O:
print('duplicate rxn_id found!');
else:
rows_O[d.rxn_id]={
'Keq_lb':d.Keq_lb,
'Keq_ub':d.Keq_ub,
'dG_r':d.dG_r,
'dG_r_var':d.dG_r_var,
'dG_r_units':d.dG_r_units,
'dG_r_lb':d.dG_r_lb,
'dG_r_ub':d.dG_r_ub};
return rows_O;
except SQLAlchemyError as e:
print(e);
def get_rowsEscherDGrLbUb_experimentIDAndModelIDAndTimePointAndSampleNameAbbreviations_dataStage03QuantificationDGr(self,experiment_id_I,
model_id_I,
time_point_I,
sample_name_abbreviation_I,
measured_concentration_coverage_criteria_I=0.5,
measured_dG_f_coverage_criteria_I=0.99):
'''Query rows that are used from the dG_r'''
try:
data = self.session.query(data_stage03_quantification_dG_r).filter(
data_stage03_quantification_dG_r.model_id.like(model_id_I),
data_stage03_quantification_dG_r.time_point.like(time_point_I),
data_stage03_quantification_dG_r.sample_name_abbreviation.like(sample_name_abbreviation_I),
data_stage03_quantification_dG_r.experiment_id.like(experiment_id_I),
data_stage03_quantification_dG_r.model_id.like(data_stage03_quantification_tcc.model_id),
data_stage03_quantification_dG_r.time_point.like(data_stage03_quantification_tcc.time_point),
data_stage03_quantification_dG_r.sample_name_abbreviation.like(data_stage03_quantification_tcc.sample_name_abbreviation),
data_stage03_quantification_dG_r.experiment_id.like(data_stage03_quantification_tcc.experiment_id),
data_stage03_quantification_dG_r.rxn_id.like(data_stage03_quantification_tcc.rxn_id),
data_stage03_quantification_tcc.measured_concentration_coverage>measured_concentration_coverage_criteria_I,
data_stage03_quantification_tcc.measured_dG_f_coverage>measured_dG_f_coverage_criteria_I,
data_stage03_quantification_tcc.used_.is_(True),
data_stage03_quantification_dG_r.used_.is_(True)).all();
rows_O = [None,None];
rows_O[0] = {};
rows_O[1] = {}
if data:
for d in data:
rows_O[0][d.rxn_id]=d.dG_r_lb;
rows_O[1][d.rxn_id]=d.dG_r_ub;
return rows_O;
except SQLAlchemyError as e:
print(e);
def get_rowsEscherDGr_experimentIDAndModelIDAndTimePointAndSampleNameAbbreviations_dataStage03QuantificationDGr(self,experiment_id_I,
model_id_I,
time_point_I,
sample_name_abbreviation_I,
measured_concentration_coverage_criteria_I=0.5,
measured_dG_f_coverage_criteria_I=0.99):
'''Query rows that are used from the dG_r'''
try:
data = self.session.query(data_stage03_quantification_dG_r).filter(
data_stage03_quantification_dG_r.model_id.like(model_id_I),
data_stage03_quantification_dG_r.time_point.like(time_point_I),
data_stage03_quantification_dG_r.sample_name_abbreviation.like(sample_name_abbreviation_I),
data_stage03_quantification_dG_r.experiment_id.like(experiment_id_I),
data_stage03_quantification_dG_r.model_id.like(data_stage03_quantification_tcc.model_id),
data_stage03_quantification_dG_r.time_point.like(data_stage03_quantification_tcc.time_point),
data_stage03_quantification_dG_r.sample_name_abbreviation.like(data_stage03_quantification_tcc.sample_name_abbreviation),
data_stage03_quantification_dG_r.experiment_id.like(data_stage03_quantification_tcc.experiment_id),
data_stage03_quantification_dG_r.rxn_id.like(data_stage03_quantification_tcc.rxn_id),
data_stage03_quantification_tcc.measured_concentration_coverage>measured_concentration_coverage_criteria_I,
data_stage03_quantification_tcc.measured_dG_f_coverage>measured_dG_f_coverage_criteria_I,
data_stage03_quantification_tcc.used_.is_(True),
data_stage03_quantification_dG_r.used_.is_(True)).all();
rows_O = {}
if data:
for d in data:
rows_O[d.rxn_id]=(d.dG_r_lb+d.dG_r_ub)/2;
return rows_O;
except SQLAlchemyError as e:
print(e);
# update rows of data_stage03_quantification_dG_r
def update_dataStage03DGr(self,data_I):
'''update rows of data_stage03_quantification_dG_r'''
if data_I:
for d in data_I:
try:
data_update = self.session.query(data_stage03_quantification_dG_r).filter(
data_stage03_quantification_dG_r.experiment_id.like(d['experiment_id']),
data_stage03_quantification_dG_r.model_id.like(d['model_id']),
data_stage03_quantification_dG_r.rxn_id.like(d['rxn_id']),
data_stage03_quantification_dG_r.sample_name_abbreviation.like(d['sample_name_abbreviation']),
data_stage03_quantification_dG_r.time_point.like(d['time_point'])).update(
{
'Keq_lb':d['Keq_lb'],
'Keq_ub':d['Keq_ub'],
'dG_r':d['dG_r'],
'dG_r_var':d['dG_r_var'],
'dG_r_units':d['dG_r_units'],
'dG_r_lb':d['dG_r_lb'],
'dG_r_ub':d['dG_r_ub'],
'displacement_lb':d['displacement_lb'],
'displacement_ub':d['displacement_ub'],
'Q_lb':d['Q_lb'],
'Q_ub':d['Q_ub'],
'used_':d['used_'],
'comment_':d['comment_']},
synchronize_session=False);
except SQLAlchemyError as e:
print(e);
self.session.commit();
## Query from data_stage03_quantification_tcc
# query rows from data_stage03_quantification_tcc
def get_infeasibleReactions_experimentIDAndModelIDAndTimePointAndSampleNameAbbreviations_dataStage03QuantificationTCC(self,experiment_id_I,
model_id_I,
time_point_I,
sample_name_abbreviation_I,
feasible_I=False):
'''Query rows that are used from the dG_r'''
try:
data = self.session.query(
data_stage03_quantification_tcc.rxn_id).filter(
data_stage03_quantification_dG_r.model_id.like(model_id_I),
data_stage03_quantification_dG_r.time_point.like(time_point_I),
data_stage03_quantification_dG_r.sample_name_abbreviation.like(sample_name_abbreviation_I),
data_stage03_quantification_dG_r.experiment_id.like(experiment_id_I),
data_stage03_quantification_tcc.feasible.is_(feasible_I),
data_stage03_quantification_tcc.used_.is_(True),
data_stage03_quantification_dG_r.used_.is_(True)).group_by(
data_stage03_quantification_tcc.rxn_id).order_by(
data_stage03_quantification_tcc.rxn_id.asc()).all();
rows_O = [];
if data:
for d in data:
data_tmp = {'experiment_id':d.data_stage03_quantification_dG_r.experiment_id,
'model_id':d.data_stage03_quantification_dG_r.model_id,
'sample_name_abbreviation':d.data_stage03_quantification_dG_r.sample_name_abbreviation,
'time_point':d.data_stage03_quantification_dG_r.time_point,
'rxn_id':d.data_stage03_quantification_dG_r.rxn_id,
'dG_r_units':d.data_stage03_quantification_dG_r.dG_r_units,
'dG_r_lb':d.data_stage03_quantification_dG_r.dG_r_lb,
'dG_r_ub':d.data_stage03_quantification_dG_r.dG_r_ub,
'displacement_lb':d.data_stage03_quantification_dG_r.displacement_lb,
'displacement_ub':d.data_stage03_quantification_dG_r.displacement_ub,
'feasible':d.feasible,
'used_':d.data_stage03_quantification_dG_r.used_,
'comment_':d.data_stage03_quantification_dG_r.comment_};
rows_O.append(data_tmp);
return rows_O;
except SQLAlchemyError as e:
print(e);
# query rows from data_stage03_quantification_tcc
def get_rows_experimentIDAndModelIDAndTimePointAndSampleNameAbbreviations_dataStage03QuantificationTCC(self,experiment_id_I,
model_id_I,
time_point_I,
sample_name_abbreviation_I,
measured_concentration_coverage_criteria_I=0.5,
measured_dG_f_coverage_criteria_I=0.99):
'''Query rows that are used from the dG_r'''
try:
data = self.session.query(data_stage03_quantification_dG_r,
data_stage03_quantification_tcc.measured_concentration_coverage,
data_stage03_quantification_tcc.measured_dG_f_coverage,
data_stage03_quantification_tcc.feasible).filter(
data_stage03_quantification_dG_r.model_id.like(model_id_I),
data_stage03_quantification_dG_r.time_point.like(time_point_I),
data_stage03_quantification_dG_r.sample_name_abbreviation.like(sample_name_abbreviation_I),
data_stage03_quantification_dG_r.experiment_id.like(experiment_id_I),
data_stage03_quantification_dG_r.model_id.like(data_stage03_quantification_tcc.model_id),
data_stage03_quantification_dG_r.time_point.like(data_stage03_quantification_tcc.time_point),
data_stage03_quantification_dG_r.sample_name_abbreviation.like(data_stage03_quantification_tcc.sample_name_abbreviation),
data_stage03_quantification_dG_r.experiment_id.like(data_stage03_quantification_tcc.experiment_id),
data_stage03_quantification_dG_r.rxn_id.like(data_stage03_quantification_tcc.rxn_id),
data_stage03_quantification_tcc.measured_concentration_coverage>measured_concentration_coverage_criteria_I,
data_stage03_quantification_tcc.measured_dG_f_coverage>measured_dG_f_coverage_criteria_I,
data_stage03_quantification_tcc.used_.is_(True),
data_stage03_quantification_dG_r.used_.is_(True)).all();
rows_O = [];
if data:
for d in data:
data_tmp = {'experiment_id':d.data_stage03_quantification_dG_r.experiment_id,
'model_id':d.data_stage03_quantification_dG_r.model_id,
'sample_name_abbreviation':d.data_stage03_quantification_dG_r.sample_name_abbreviation,
'time_point':d.data_stage03_quantification_dG_r.time_point,
'rxn_id':d.data_stage03_quantification_dG_r.rxn_id,
'dG_r':d.data_stage03_quantification_dG_r.dG_r,
'dG_r_units':d.data_stage03_quantification_dG_r.dG_r_units,
'dG_r_lb':d.data_stage03_quantification_dG_r.dG_r_lb,
'dG_r_ub':d.data_stage03_quantification_dG_r.dG_r_ub,
'displacement_lb':d.data_stage03_quantification_dG_r.displacement_lb,
'displacement_ub':d.data_stage03_quantification_dG_r.displacement_ub,
'feasible':d.feasible,
'used_':d.data_stage03_quantification_dG_r.used_,
'comment_':d.data_stage03_quantification_dG_r.comment_};
rows_O.append(data_tmp);
return rows_O;
except SQLAlchemyError as e:
print(e);
def get_row_experimentIDAndModelIDAndTimePointAndSampleNameAbbreviations_dataStage03QuantificationTCC(self,experiment_id_I,
model_id_I,
time_point_I,
sample_name_abbreviation_I,
rxn_id_I,
dG_r_lb_I,
dG_r_ub_I,
measured_concentration_coverage_criteria_I=0.5,
measured_dG_f_coverage_criteria_I=0.99):
'''Query rows that are used from the dG_r
Assumption: dG_r_lb < dG_r_ub'''
try:
data = self.session.query(data_stage03_quantification_dG_r,
data_stage03_quantification_tcc.measured_concentration_coverage,
data_stage03_quantification_tcc.measured_dG_f_coverage,
data_stage03_quantification_tcc.feasible).filter(
data_stage03_quantification_dG_r.rxn_id.like(rxn_id_I),
data_stage03_quantification_dG_r.model_id.like(model_id_I),
data_stage03_quantification_dG_r.time_point.like(time_point_I),
data_stage03_quantification_dG_r.sample_name_abbreviation.like(sample_name_abbreviation_I),
data_stage03_quantification_dG_r.experiment_id.like(experiment_id_I),
data_stage03_quantification_dG_r.model_id.like(data_stage03_quantification_tcc.model_id),
data_stage03_quantification_dG_r.time_point.like(data_stage03_quantification_tcc.time_point),
data_stage03_quantification_dG_r.sample_name_abbreviation.like(data_stage03_quantification_tcc.sample_name_abbreviation),
data_stage03_quantification_dG_r.experiment_id.like(data_stage03_quantification_tcc.experiment_id),
data_stage03_quantification_dG_r.rxn_id.like(data_stage03_quantification_tcc.rxn_id),
data_stage03_quantification_dG_r.used_.is_(True),
## constraint for statistical significance
#or_(data_stage03_quantification_dG_r.dG_r_ub < dG_r_lb_I,
# data_stage03_quantification_dG_r.dG_r_lb > dG_r_ub_I),
## constraint for biological significance
#or_(copysign(1.0,data_stage03_quantification_dG_r.dG_r_lb) != copysign(1.0,dG_r_lb_I),
# copysign(1.0,data_stage03_quantification_dG_r.dG_r_ub) != copysign(1.0,dG_r_ub_I)),
data_stage03_quantification_tcc.measured_concentration_coverage>measured_concentration_coverage_criteria_I,
data_stage03_quantification_tcc.measured_dG_f_coverage>measured_dG_f_coverage_criteria_I,
data_stage03_quantification_tcc.used_.is_(True)).all();
rows_O = {};
if data:
for d in data:
data_tmp = {'experiment_id':d.data_stage03_quantification_dG_r.experiment_id,
'model_id':d.data_stage03_quantification_dG_r.model_id,
'sample_name_abbreviation':d.data_stage03_quantification_dG_r.sample_name_abbreviation,
'time_point':d.data_stage03_quantification_dG_r.time_point,
'rxn_id':d.data_stage03_quantification_dG_r.rxn_id,
'dG_r_units':d.data_stage03_quantification_dG_r.dG_r_units,
'dG_r_lb':d.data_stage03_quantification_dG_r.dG_r_lb,
'dG_r_ub':d.data_stage03_quantification_dG_r.dG_r_ub,
'displacement_lb':d.data_stage03_quantification_dG_r.displacement_lb,
'displacement_ub':d.data_stage03_quantification_dG_r.displacement_ub,
'feasible':d.feasible,
'used_':d.data_stage03_quantification_dG_r.used_,
'comment_':d.data_stage03_quantification_dG_r.comment_};
rows_O.update(data_tmp);
return rows_O;
except SQLAlchemyError as e:
print(e);
except TypeError as e:
print(e);
def get_rowsDict_experimentIDAndModelIDAndTimePointAndSampleNameAbbreviations_dataStage03QuantificationTCC(self,experiment_id_I,
model_id_I,
time_point_I,
sample_name_abbreviation_I,
measured_concentration_coverage_criteria_I=0.5,
measured_dG_f_coverage_criteria_I=0.99):
'''Query rows that are used from the tcc'''
try:
data = self.session.query(data_stage03_quantification_tcc.rxn_id,
data_stage03_quantification_tcc.measured_concentration_coverage,
data_stage03_quantification_tcc.measured_dG_f_coverage,
data_stage03_quantification_tcc.feasible).filter(
data_stage03_quantification_tcc.model_id.like(model_id_I),
data_stage03_quantification_tcc.time_point.like(time_point_I),
data_stage03_quantification_tcc.sample_name_abbreviation.like(sample_name_abbreviation_I),
data_stage03_quantification_tcc.experiment_id.like(experiment_id_I),
data_stage03_quantification_tcc.measured_concentration_coverage>measured_concentration_coverage_criteria_I,
data_stage03_quantification_tcc.measured_dG_f_coverage>measured_dG_f_coverage_criteria_I,
data_stage03_quantification_tcc.used_.is_(True)).all();
measured_concentration_coverage_O = {};
measured_dG_f_coverage_O = {};
feasible_O = {};
if data:
for d in data:
if d.rxn_id in measured_concentration_coverage_O:
print('duplicate rxn_id found!');
else:
measured_concentration_coverage_O[d.rxn_id]=d.measured_concentration_coverage
measured_dG_f_coverage_O[d.rxn_id]=d.measured_dG_f_coverage
feasible_O[d.rxn_id]=d.feasible
return measured_concentration_coverage_O,measured_dG_f_coverage_O,feasible_O;
except SQLAlchemyError as e:
print(e);
# update rows of data_stage03_quantification_tcc
def update_dataStage03Tcc(self,data_I):
'''update rows of data_stage03_quantification_tcc'''
if data_I:
for d in data_I:
try:
data_update = self.session.query(data_stage03_quantification_tcc).filter(
data_stage03_quantification_tcc.experiment_id.like(d['experiment_id']),
data_stage03_quantification_tcc.model_id.like(d['model_id']),
data_stage03_quantification_tcc.rxn_id.like(d['rxn_id']),
data_stage03_quantification_dG_r.sample_name_abbreviation.like(d['sample_name_abbreviation']),
data_stage03_quantification_dG_r.time_point.like(d['time_point'])).update(
{
'feasible':d['feasible'],
'measured_concentration_coverage_criteria':d['measured_concentration_coverage_criteria'],
'measured_dG_f_coverage_criteria':d['measured_dG_f_coverage_criteria'],
'measured_concentration_coverage':d['measured_concentration_coverage'],
'measured_dG_f_coverage':d['measured_dG_f_coverage'],
'used_':d['used_'],
'comment_':d['comment_']},
synchronize_session=False);
except SQLAlchemyError as e:
print(e);
self.session.commit();
def add_dataStage03QuantificationDG0r(self, data_I):
'''add rows of data_stage03_quantification_dG0_r'''
if data_I:
for d in data_I:
try:
data_add = data_stage03_quantification_dG0_r(d
#d['experiment_id'],
#d['model_id'],
#d['sample_name_abbreviation'],
#d['time_point'],
#d['rxn_id'],
#d['Keq_lb'],
#d['Keq_ub'],
#d['dG0_r'],
#d['dG0_r_var'],
#d['dG0_r_units'],
#d['dG0_r_lb'],
#d['dG0_r_ub'],
#d['used_'],
#d['comment_']
);
self.session.add(data_add);
except SQLAlchemyError as e:
print(e);
self.session.commit();
def update_dataStage03QuantificationDG0r(self,data_I):
#Not yet tested
'''update rows of data_stage03_quantification_dG0_r'''
if data_I:
for d in data_I:
try:
data_update = self.session.query(data_stage03_quantification_dG0_r).filter(
standards.id.like(d['id'])).update(
{'experiment_id':d['experiment_id'],
'model_id':d['model_id'],
'sample_name_abbreviation':d['sample_name_abbreviation'],
'time_point':d['time_point'],
'rxn_id':d['rxn_id'],
'Keq_lb':d['Keq_lb'],
'Keq_ub':d['Keq_ub'],
'dG0_r':d['dG0_r'],
'dG0_r_var':d['dG0_r_var'],
'dG0_r_units':d['dG0_r_units'],
'dG0_r_lb':d['dG0_r_lb'],
'dG0_r_ub':d['dG0_r_ub'],
'used_':d['used_'],
'comment_':d['comment_']},
synchronize_session=False);
except SQLAlchemyError as e:
print(e);
self.session.commit();
def add_dataStage03QuantificationDGr(self, data_I):
'''add rows of data_stage03_quantification_dG_r'''
if data_I:
for d in data_I:
try:
data_add = data_stage03_quantification_dG_r(d
#d['experiment_id'],
#d['model_id'],
#d['sample_name_abbreviation'],
#d['time_point'],
#d['rxn_id'],
#d['Keq_lb'],
#d['Keq_ub'],
#d['dG_r'],
#d['dG_r_var'],
#d['dG_r_units'],
#d['dG_r_lb'],
#d['dG_r_ub'],
#d['displacement_lb'],
#d['displacement_ub'],
#d['Q_lb'],
#d['Q_ub'],
#d['used_'],
#d['comment_']
);
self.session.add(data_add);
except SQLAlchemyError as e:
print(e);
self.session.commit();
def update_dataStage03QuantificationDGr(self,data_I):
#Not yet tested
'''update rows of data_stage03_quantification_dG_r'''
if data_I:
for d in data_I:
try:
data_update = self.session.query(data_stage03_quantification_dG_r).filter(
standards.id.like(d['id'])).update(
{'experiment_id':d['experiment_id'],
'model_id':d['model_id'],
'sample_name_abbreviation':d['sample_name_abbreviation'],
'time_point':d['time_point'],
'rxn_id':d['rxn_id'],
'Keq_lb':d['Keq_lb'],
'Keq_ub':d['Keq_ub'],
'dG_r':d['dG_r'],
'dG_r_var':d['dG_r_var'],
'dG_r_units':d['dG_r_units'],
'dG_r_lb':d['dG_r_lb'],
'dG_r_ub':d['dG_r_ub'],
'displacement_lb':d['displacement_lb'],
'displacement_ub':d['displacement_ub'],
'Q_lb':d['Q_lb'],
'Q_ub':d['Q_ub'],
'used_':d['used_'],
'comment_':d['comment_']},
synchronize_session=False);
except SQLAlchemyError as e:
print(e);
self.session.commit();
def add_dataStage03QuantificationTcc(self, data_I):
'''add rows of data_stage03_quantification_tcc'''
if data_I:
for d in data_I:
try:
data_add = data_stage03_quantification_tcc(d
#d['experiment_id'],
#d['model_id'],
#d['sample_name_abbreviation'],
#d['time_point'],
#d['rxn_id'],
#d['feasible'],
#d['measured_concentration_coverage_criteria'],
#d['measured_dG_f_coverage_criteria'],
#d['measured_concentration_coverage'],
#d['measured_dG_f_coverage'],
#d['used_'],
#d['comment_']
);
self.session.add(data_add);
except SQLAlchemyError as e:
print(e);
self.session.commit();
def update_dataStage03QuantificationTcc(self,data_I):
#Not yet tested
'''update rows of data_stage03_quantification_tcc'''
if data_I:
for d in data_I:
try:
data_update = self.session.query(data_stage03_quantification_tcc).filter(
standards.id.like(d['id'])).update(
{'experiment_id':d['experiment_id'],
'model_id':d['model_id'],
'sample_name_abbreviation':d['sample_name_abbreviation'],
'time_point':d['time_point'],
'rxn_id':d['rxn_id'],
'feasible':d['feasible'],
'measured_concentration_coverage_criteria':d['measured_concentration_coverage_criteria'],
'measured_dG_f_coverage_criteria':d['measured_dG_f_coverage_criteria'],
'measured_concentration_coverage':d['measured_concentration_coverage'],
'measured_dG_f_coverage':d['measured_dG_f_coverage'],
'used_':d['used_'],
'comment_':d['comment_']},
synchronize_session=False);
except SQLAlchemyError as e:
print(e);
self.session.commit();
def reset_dataStage03_quantification_dG_r_all(self,experiment_id_I = None,simulation_id_I=None):
try:
if experiment_id_I:
reset = self.session.query(data_stage03_quantification_dG0_r).filter(data_stage03_quantification_dG0_r.experiment_id.like(experiment_id_I)).delete(synchronize_session=False);
reset = self.session.query(data_stage03_quantification_dG_r).filter(data_stage03_quantification_dG_r.experiment_id.like(experiment_id_I)).delete(synchronize_session=False);
reset = self.session.query(data_stage03_quantification_tcc).filter(data_stage03_quantification_tcc.experiment_id.like(experiment_id_I)).delete(synchronize_session=False);
self.session.commit();
except SQLAlchemyError as e:
print(e);
def reset_dataStage03_quantification_dG0_r(self,experiment_id_I = None,simulation_id_I=None):
try:
if experiment_id_I:
reset = self.session.query(data_stage03_quantification_dG0_r).filter(data_stage03_quantification_dG0_r.experiment_id.like(experiment_id_I)).delete(synchronize_session=False);
self.session.commit();
except SQLAlchemyError as e:
print(e);
def reset_dataStage03_quantification_dG_r(self,experiment_id_I = None,simulation_id_I=None):
try:
if experiment_id_I:
reset = self.session.query(data_stage03_quantification_dG_r).filter(data_stage03_quantification_dG_r.experiment_id.like(experiment_id_I)).delete(synchronize_session=False);
self.session.commit();
except SQLAlchemyError as e:
print(e);
def reset_dataStage03_quantification_tcc(self,experiment_id_I = None,simulation_id_I=None):
try:
if experiment_id_I:
reset = self.session.query(data_stage03_quantification_tcc).filter(data_stage03_quantification_tcc.experiment_id.like(experiment_id_I)).delete(synchronize_session=False);
self.session.commit();
except SQLAlchemyError as e:
print(e);
def reset_dataStage03_quantification_dG_r_comparison(self,analysis_id_I = None):
try:
if analysis_id_I:
reset = self.session.query(data_stage03_quantification_dG_r_comparison).filter(
data_stage03_quantification_dG_r_comparison.analysis_id.like(analysis_id_I)).delete(synchronize_session=False);
self.session.commit();
except SQLAlchemyError as e:
print(e);
| 65.844023 | 190 | 0.554119 | 4,636 | 45,169 | 4.875539 | 0.027826 | 0.258284 | 0.305269 | 0.159271 | 0.945007 | 0.935363 | 0.911782 | 0.90196 | 0.883644 | 0.864752 | 0 | 0.025625 | 0.375346 | 45,169 | 685 | 191 | 65.940146 | 0.775474 | 0.107419 | 0 | 0.788256 | 0 | 0 | 0.06658 | 0.023606 | 0 | 0 | 0 | 0 | 0 | 1 | 0.042705 | false | 0 | 0.016014 | 0 | 0.076512 | 0.048043 | 0 | 0 | 0 | null | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 9 |
d52b0d5eb3843c29566679026847ae177dc5fb82 | 307 | py | Python | platform/hwconf_data/efr32mg1p/modules/WDOG/__init__.py | lenloe1/v2.7 | 9ac9c4a7bb37987af382c80647f42d84db5f2e1d | [
"Zlib"
] | null | null | null | platform/hwconf_data/efr32mg1p/modules/WDOG/__init__.py | lenloe1/v2.7 | 9ac9c4a7bb37987af382c80647f42d84db5f2e1d | [
"Zlib"
] | 1 | 2020-08-25T02:36:22.000Z | 2020-08-25T02:36:22.000Z | platform/hwconf_data/efr32mg1p/modules/WDOG/__init__.py | lenloe1/v2.7 | 9ac9c4a7bb37987af382c80647f42d84db5f2e1d | [
"Zlib"
] | 1 | 2020-08-25T01:56:04.000Z | 2020-08-25T01:56:04.000Z | import efr32mg1p.halconfig.halconfig_types as halconfig_types
import efr32mg1p.halconfig.halconfig_dependency as halconfig_dependency
import efr32mg1p.PythonSnippet.ExporterModel as ExporterModel
import efr32mg1p.PythonSnippet.RuntimeModel as RuntimeModel
import efr32mg1p.PythonSnippet.Metadata as Metadata | 61.4 | 71 | 0.905537 | 34 | 307 | 8.058824 | 0.294118 | 0.273723 | 0.306569 | 0.240876 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.052083 | 0.061889 | 307 | 5 | 72 | 61.4 | 0.899306 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
d5a343d753defa3c4332c241341060bdd8d38479 | 6,575 | py | Python | tests/test_search.py | timmahrt/pysle | b81d0be0bf3a9994ad449f8802db0e6f5cb36265 | [
"MIT"
] | 30 | 2016-04-20T22:18:59.000Z | 2022-03-07T13:34:16.000Z | tests/test_search.py | timmahrt/pysle | b81d0be0bf3a9994ad449f8802db0e6f5cb36265 | [
"MIT"
] | 14 | 2016-10-20T09:00:50.000Z | 2022-01-03T13:50:28.000Z | tests/test_search.py | timmahrt/pysle | b81d0be0bf3a9994ad449f8802db0e6f5cb36265 | [
"MIT"
] | 6 | 2016-05-09T07:35:30.000Z | 2021-04-14T18:09:35.000Z | import unittest
from typing import List
from pysle import phonetics
from pysle import isletool
from pysle import praattools
from pysle.utilities import errors
class VirtualIsle(isletool.Isle):
def _load(self, _islePath):
return {
"another": [
"another(dt,nn,prp) # ə . n ˈʌ . ð ɚ #",
"another(dt,nn,prp) # ə . n ˈʌ ð . ə ɹ #",
],
"any": ["any(dt) # ˈɛ . n i #"],
"brown": ["brown(jj) # b ɹ ˈaʊ n #"],
"brown_cat": ["brown_cat() # b ɹ ˈaʊ n # k ˌæ t˺ #"],
"cat": ["cat(dt,nn,prp) # k ˌæ t˺ #"],
"nominee": ["nominee(nn) # n ˌɑ . m ə . n ˈi #"],
}
class TestSearch(unittest.TestCase):
def setUp(self):
self.isle = VirtualIsle()
def test_num_syllables(self):
results = [result for result in self.isle.search("VNV", numSyllables=None)]
self.assertEqual(4, len(results))
self.assertEqual("another", results[0]["word"])
self.assertEqual("another", results[1]["word"])
self.assertEqual("any", results[2]["word"])
self.assertEqual("nominee", results[3]["word"])
results = [result for result in self.isle.search("VNV", numSyllables=1)]
self.assertEqual(0, len(results))
results = [result for result in self.isle.search("VNV", numSyllables=2)]
self.assertEqual(1, len(results))
self.assertEqual("any", results[0]["word"])
results = [result for result in self.isle.search("VNV", numSyllables=3)]
self.assertEqual(3, len(results))
self.assertEqual("another", results[0]["word"])
self.assertEqual("another", results[1]["word"])
self.assertEqual("nominee", results[2]["word"])
def test_word_initial(self):
results = [result for result in self.isle.search("NV", wordInitial="ok")]
self.assertEqual(4, len(results))
self.assertEqual("another", results[0]["word"])
self.assertEqual("another", results[1]["word"])
self.assertEqual("any", results[2]["word"])
self.assertEqual("nominee", results[3]["word"])
results = [result for result in self.isle.search("NV", wordInitial="no")]
self.assertEqual(4, len(results))
self.assertEqual("another", results[0]["word"])
self.assertEqual("another", results[1]["word"])
self.assertEqual("any", results[2]["word"])
self.assertEqual("nominee", results[3]["word"]) # b/c the second 'n'
results = [result for result in self.isle.search("NV", wordInitial="only")]
self.assertEqual(1, len(results))
self.assertEqual("nominee", results[0]["word"])
def test_word_final(self):
results = [result for result in self.isle.search("ɹ", wordFinal="ok")]
self.assertEqual(3, len(results))
self.assertEqual("another", results[0]["word"])
self.assertEqual("brown", results[1]["word"])
self.assertEqual("brown_cat", results[2]["word"])
results = [result for result in self.isle.search("ɹ", wordFinal="no")]
self.assertEqual(2, len(results))
self.assertEqual("brown", results[0]["word"])
self.assertEqual("brown_cat", results[1]["word"])
results = [result for result in self.isle.search("ɹ", wordFinal="only")]
self.assertEqual(1, len(results))
self.assertEqual("another", results[0]["word"])
def test_span_syllable(self):
results = [result for result in self.isle.search("VD", spanSyllable="ok")]
self.assertEqual(4, len(results))
self.assertEqual("another", results[0]["word"])
self.assertEqual("another", results[1]["word"])
self.assertEqual("brown_cat", results[2]["word"])
self.assertEqual("cat", results[3]["word"])
results = [result for result in self.isle.search("VD", spanSyllable="no")]
self.assertEqual(3, len(results))
self.assertEqual("another", results[0]["word"])
self.assertEqual("brown_cat", results[1]["word"])
self.assertEqual("cat", results[2]["word"])
results = [result for result in self.isle.search("VD", spanSyllable="only")]
self.assertEqual(1, len(results))
self.assertEqual("another", results[0]["word"])
def test_stressed_syllable(self):
results = [result for result in self.isle.search("Ni", stressedSyllable="ok")]
self.assertEqual(2, len(results))
self.assertEqual("any", results[0]["word"])
self.assertEqual("nominee", results[1]["word"])
results = [result for result in self.isle.search("Ni", stressedSyllable="only")]
self.assertEqual(1, len(results))
self.assertEqual("nominee", results[0]["word"])
results = [result for result in self.isle.search("Ni", stressedSyllable="no")]
self.assertEqual(1, len(results))
self.assertEqual("any", results[0]["word"])
def test_multiword(self):
results = [result for result in self.isle.search("kV", multiword="ok")]
self.assertEqual(2, len(results))
self.assertEqual("brown_cat", results[0]["word"])
self.assertEqual("cat", results[1]["word"])
results = [result for result in self.isle.search("kV", multiword="only")]
self.assertEqual(1, len(results))
self.assertEqual("brown_cat", results[0]["word"])
results = [result for result in self.isle.search("kV", multiword="no")]
self.assertEqual(1, len(results))
self.assertEqual("cat", results[0]["word"])
def test_pos(self):
results = [result for result in self.isle.search("Vt", pos=None)]
self.assertEqual(2, len(results))
self.assertEqual(("brown_cat", ""), (results[0]["word"], results[0]["posList"]))
self.assertEqual(
("cat", "dt,nn,prp"), (results[1]["word"], results[1]["posList"])
)
results = [result for result in self.isle.search("Vt", pos="nn")]
self.assertEqual(1, len(results))
self.assertEqual(
("cat", "dt,nn,prp"), (results[0]["word"], results[0]["posList"])
)
def test_exact_match(self):
results = [result for result in self.isle.search("bɹaʊn", exactMatch=False)]
self.assertEqual(2, len(results))
self.assertEqual("brown", results[0]["word"])
self.assertEqual("brown_cat", results[1]["word"])
results = [result for result in self.isle.search("bɹaʊn", exactMatch=True)]
self.assertEqual(1, len(results))
self.assertEqual("brown", results[0]["word"])
| 40.838509 | 88 | 0.604867 | 809 | 6,575 | 4.886279 | 0.118665 | 0.258032 | 0.093094 | 0.128004 | 0.863395 | 0.833797 | 0.826714 | 0.815077 | 0.747281 | 0.741209 | 0 | 0.014419 | 0.219468 | 6,575 | 160 | 89 | 41.09375 | 0.755456 | 0.002738 | 0 | 0.472 | 0 | 0 | 0.127536 | 0 | 0 | 0 | 0 | 0 | 0.544 | 1 | 0.08 | false | 0 | 0.048 | 0.008 | 0.152 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
6371cf5a7236bcd5a3bb838f26e872e03c51d4a2 | 45 | py | Python | hydrogels/systems/__init__.py | debeshmandal/brownian | bc5b2e00a04d11319c85e749f9c056b75b450ff7 | [
"MIT"
] | 3 | 2020-05-13T01:07:30.000Z | 2021-02-12T13:37:23.000Z | hydrogels/systems/__init__.py | debeshmandal/brownian | bc5b2e00a04d11319c85e749f9c056b75b450ff7 | [
"MIT"
] | 24 | 2020-06-04T13:48:57.000Z | 2021-12-31T18:46:52.000Z | hydrogels/systems/__init__.py | debeshmandal/brownian | bc5b2e00a04d11319c85e749f9c056b75b450ff7 | [
"MIT"
] | 1 | 2020-07-23T17:15:23.000Z | 2020-07-23T17:15:23.000Z | from .degradation import EnzymaticDegradation | 45 | 45 | 0.911111 | 4 | 45 | 10.25 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.066667 | 45 | 1 | 45 | 45 | 0.97619 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 7 |
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