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archi | showcases 3 Android app architectures | Architecture library

 by   ivacf Java Version: Current License: Apache-2.0

 by   ivacf Java Version: Current License: Apache-2.0

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kandi X-RAY | archi Summary

archi is a Java library typically used in Architecture applications. archi has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can download it from GitHub.
This repository showcases and compares different architectural patterns that can be used to build Android apps. The exact same sample app is built three times using the following approaches:.
Support
Support
Quality
Quality
Security
Security
License
License
Reuse
Reuse

kandi-support Support

  • archi has a medium active ecosystem.
  • It has 3375 star(s) with 524 fork(s). There are 148 watchers for this library.
  • It had no major release in the last 12 months.
  • There are 9 open issues and 13 have been closed. On average issues are closed in 15 days. There are 2 open pull requests and 0 closed requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of archi is current.
archi Support
Best in #Architecture
Average in #Architecture
archi Support
Best in #Architecture
Average in #Architecture

quality kandi Quality

  • archi has 0 bugs and 0 code smells.
archi Quality
Best in #Architecture
Average in #Architecture
archi Quality
Best in #Architecture
Average in #Architecture

securitySecurity

  • archi has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • archi code analysis shows 0 unresolved vulnerabilities.
  • There are 0 security hotspots that need review.
archi Security
Best in #Architecture
Average in #Architecture
archi Security
Best in #Architecture
Average in #Architecture

license License

  • archi is licensed under the Apache-2.0 License. This license is Permissive.
  • Permissive licenses have the least restrictions, and you can use them in most projects.
archi License
Best in #Architecture
Average in #Architecture
archi License
Best in #Architecture
Average in #Architecture

buildReuse

  • archi releases are not available. You will need to build from source code and install.
  • Build file is available. You can build the component from source.
  • Installation instructions are not available. Examples and code snippets are available.
  • archi saves you 1548 person hours of effort in developing the same functionality from scratch.
  • It has 3446 lines of code, 214 functions and 62 files.
  • It has medium code complexity. Code complexity directly impacts maintainability of the code.
archi Reuse
Best in #Architecture
Average in #Architecture
archi Reuse
Best in #Architecture
Average in #Architecture
Top functions reviewed by kandi - BETA

kandi has reviewed archi and discovered the below as its top functions. This is intended to give you an instant insight into archi implemented functionality, and help decide if they suit your requirements.

  • load github repositories
  • Loads repositories for a given username .
  • Load the full user information .
  • Creates the repository .
  • Compares this object for equality .
  • Load user .
  • Creates a hash code for this node .
  • Show repositories .
  • Called when the view is created .
  • Gets the github service .

archi Key Features

Standard Android: traditional approach with layouts, Activities/Fragments and Model.

MVP: Model View Presenter.

MVVM: Model View ViewModel with data binding.

License

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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.

EKS Ingress with Single ALB, multiple namespaces, and External DNS

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apiVersion: v1
kind: Service
metadata:
  name: sentinel-srv
  annotations:
    external-dns.alpha.kubernetes.io/hostname: operatorv2.dev.sentinel.mysite.io
  namespace: operatorv2-dev
  labels:
    run: jsflow-sentinel
spec:
  ports:
    - port: 80
      targetPort: 80
      name: ps1
      protocol: TCP
  selector:
    app: sentinel-app
  type: NodePort
apiVersion: networking.k8s.io/v1beta1
kind: Ingress
metadata:
  annotations:
    alb.ingress.kubernetes.io/healthcheck-interval-seconds: "15"
    alb.ingress.kubernetes.io/healthcheck-path: /
    alb.ingress.kubernetes.io/healthcheck-port: traffic-port
    alb.ingress.kubernetes.io/healthcheck-protocol: HTTP
    alb.ingress.kubernetes.io/healthcheck-timeout-seconds: "5"
    alb.ingress.kubernetes.io/healthy-threshold-count: "2"
    alb.ingress.kubernetes.io/listen-ports: '[{"HTTP": 80} ]'
    alb.ingress.kubernetes.io/scheme: internet-facing
    alb.ingress.kubernetes.io/success-codes: "200"
    alb.ingress.kubernetes.io/tags: createdBy=aws-controller
    alb.ingress.kubernetes.io/target-type: ip
    alb.ingress.kubernetes.io/unhealthy-threshold-count: "2"
    external-dns.alpha.kubernetes.io/hostname: operatorv2.sentinel.mysite.io
    kubernetes.io/ingress.class: alb
    alb.ingress.kubernetes.io/group.name: sentinel-group
  name: dev-operatorv2-sentinel-ingress-controller
  namespace: operatorv2-dev
spec:
  rules:
    - host: operatorv2.dev.sentinel.mysite.io
      http:
        paths:
          - path: /*
            backend:
              servicePort: 80
              serviceName: sentinel-srv
-----------------------
apiVersion: v1
kind: Service
metadata:
  name: sentinel-srv
  annotations:
    external-dns.alpha.kubernetes.io/hostname: operatorv2.dev.sentinel.mysite.io
  namespace: operatorv2-dev
  labels:
    run: jsflow-sentinel
spec:
  ports:
    - port: 80
      targetPort: 80
      name: ps1
      protocol: TCP
  selector:
    app: sentinel-app
  type: NodePort
apiVersion: networking.k8s.io/v1beta1
kind: Ingress
metadata:
  annotations:
    alb.ingress.kubernetes.io/healthcheck-interval-seconds: "15"
    alb.ingress.kubernetes.io/healthcheck-path: /
    alb.ingress.kubernetes.io/healthcheck-port: traffic-port
    alb.ingress.kubernetes.io/healthcheck-protocol: HTTP
    alb.ingress.kubernetes.io/healthcheck-timeout-seconds: "5"
    alb.ingress.kubernetes.io/healthy-threshold-count: "2"
    alb.ingress.kubernetes.io/listen-ports: '[{"HTTP": 80} ]'
    alb.ingress.kubernetes.io/scheme: internet-facing
    alb.ingress.kubernetes.io/success-codes: "200"
    alb.ingress.kubernetes.io/tags: createdBy=aws-controller
    alb.ingress.kubernetes.io/target-type: ip
    alb.ingress.kubernetes.io/unhealthy-threshold-count: "2"
    external-dns.alpha.kubernetes.io/hostname: operatorv2.sentinel.mysite.io
    kubernetes.io/ingress.class: alb
    alb.ingress.kubernetes.io/group.name: sentinel-group
  name: dev-operatorv2-sentinel-ingress-controller
  namespace: operatorv2-dev
spec:
  rules:
    - host: operatorv2.dev.sentinel.mysite.io
      http:
        paths:
          - path: /*
            backend:
              servicePort: 80
              serviceName: sentinel-srv

Powershell: Arrays index acess and check if previous is substring to next

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function ConvertTo-ElementItems
{

    param
    (
        [object[]] $Relations
    )

    $jobTypes = @( "TechnologyInteraction", "TechnologyEvent" );
    $subTypes = @( "TechnologyService" );

    $previousItem = $null;

    foreach( $item in $Relations )
    {

        if( $item.Type -in $jobTypes )
        {
            # start of a new job, but don't output anything
        }
        elseif( $item.Type -notin $subTypes  )
        {
            # not a subjob type that we recognise
            throw "unrecognised subjob type '$($item.Type)' for subjob '$($item.ID)'";
        }
        elseif( $null -eq $previousItem )
        {
            # we've got a subjob, but there was no previous job or subjob
            throw "no preceding item for subjob '$($item.ID)'";
        }
        elseif( $previousItem.Type -in $jobTypes )
        {
            # this is the first subjob after the parent job
            new-object PSCustomObject -Property ([ordered] @{
                "ID"            = "New ID"
                "Type"          = "RealizationRelationship"
                "Name"          = "";
                "Documentation" = ""
                "Source"        = $previousItem.ID
                "Target"        = $item.ID
            });
        }
        else
        {
            # the preceding item was a subjob as well
            new-object PSCustomObject -Property ([ordered] @{
                "ID"            = "New ID"
                "Type"          = "TriggeringRelationship"
                "Name"          = ""
                "Documentation" = ""
                "Source"        = $previousItem.ID
                "Target"        = $item.ID
            });
        }

        $previousItem = $item;

    }
  
}
$ErrorActionPreference = "Stop";
Set-StrictMode -Version "Latest";

$inputCsv = @"
ID,"Type","Name","Documentation"
eb214110-2b6a-48b2-ba5a-7c13dc3bba39,"TechnologyInteraction","ACGN100Q","Begin Of JobStream"
a46681e7-19a8-4fc5-b747-09679c15ff26,"TechnologyService","ACGN-100Q-000T","Transfert UDM (xACGN000)"
85761a09-1145-4037-a527-66a743def45f,"TechnologyService","ACGN-100Q-010T","move fichier REF to work"
27b126fb-c708-427d-b0a6-ce4747114ac4,"TechnologyService","ACGN-100Q-020T","w_read_account"
bb0c5e42-5fad-4bd9-8ee9-f41d0b824e82,"TechnologyService","ACGN-100Q-030T","w_read_referential"
0b8b76e3-62fa-4527-9f05-2eb4dbaa8e97,"TechnologyService","ACGN-100Q-040T","w_load_CompanyGroup"
1f487986-3cac-4af8-bda2-6400a1c71f48,"TechnologyService","ACGN-100Q-050T","w_load_Company"
"@

$expectedCsv = @"
"ID","Type","Name","Documentation","Source","Target"
"New ID","RealizationRelationship","","","eb214110-2b6a-48b2-ba5a-7c13dc3bba39","a46681e7-19a8-4fc5-b747-09679c15ff26"
"New ID","TriggeringRelationship","","","a46681e7-19a8-4fc5-b747-09679c15ff26","85761a09-1145-4037-a527-66a743def45f"
"New ID","TriggeringRelationship","","","85761a09-1145-4037-a527-66a743def45f","27b126fb-c708-427d-b0a6-ce4747114ac4"
"New ID","TriggeringRelationship","","","27b126fb-c708-427d-b0a6-ce4747114ac4","bb0c5e42-5fad-4bd9-8ee9-f41d0b824e82"
"New ID","TriggeringRelationship","","","bb0c5e42-5fad-4bd9-8ee9-f41d0b824e82","0b8b76e3-62fa-4527-9f05-2eb4dbaa8e97"
"New ID","TriggeringRelationship","","","0b8b76e3-62fa-4527-9f05-2eb4dbaa8e97","1f487986-3cac-4af8-bda2-6400a1c71f48"
"@;

$relations = $inputCsv | ConvertFrom-Csv;
$elements = ConvertTo-ElementItems -Relations $relations;
$outputCsv = ($elements | ConvertTo-Csv -NoTypeInformation) -join "`n";

if( $outputCsv -ne $expectedCsv )
{
    throw "output csv doesn't match expected csv";
} else {
    write-host "output csv matches expected csv";
}
-----------------------
function ConvertTo-ElementItems
{

    param
    (
        [object[]] $Relations
    )

    $jobTypes = @( "TechnologyInteraction", "TechnologyEvent" );
    $subTypes = @( "TechnologyService" );

    $previousItem = $null;

    foreach( $item in $Relations )
    {

        if( $item.Type -in $jobTypes )
        {
            # start of a new job, but don't output anything
        }
        elseif( $item.Type -notin $subTypes  )
        {
            # not a subjob type that we recognise
            throw "unrecognised subjob type '$($item.Type)' for subjob '$($item.ID)'";
        }
        elseif( $null -eq $previousItem )
        {
            # we've got a subjob, but there was no previous job or subjob
            throw "no preceding item for subjob '$($item.ID)'";
        }
        elseif( $previousItem.Type -in $jobTypes )
        {
            # this is the first subjob after the parent job
            new-object PSCustomObject -Property ([ordered] @{
                "ID"            = "New ID"
                "Type"          = "RealizationRelationship"
                "Name"          = "";
                "Documentation" = ""
                "Source"        = $previousItem.ID
                "Target"        = $item.ID
            });
        }
        else
        {
            # the preceding item was a subjob as well
            new-object PSCustomObject -Property ([ordered] @{
                "ID"            = "New ID"
                "Type"          = "TriggeringRelationship"
                "Name"          = ""
                "Documentation" = ""
                "Source"        = $previousItem.ID
                "Target"        = $item.ID
            });
        }

        $previousItem = $item;

    }
  
}
$ErrorActionPreference = "Stop";
Set-StrictMode -Version "Latest";

$inputCsv = @"
ID,"Type","Name","Documentation"
eb214110-2b6a-48b2-ba5a-7c13dc3bba39,"TechnologyInteraction","ACGN100Q","Begin Of JobStream"
a46681e7-19a8-4fc5-b747-09679c15ff26,"TechnologyService","ACGN-100Q-000T","Transfert UDM (xACGN000)"
85761a09-1145-4037-a527-66a743def45f,"TechnologyService","ACGN-100Q-010T","move fichier REF to work"
27b126fb-c708-427d-b0a6-ce4747114ac4,"TechnologyService","ACGN-100Q-020T","w_read_account"
bb0c5e42-5fad-4bd9-8ee9-f41d0b824e82,"TechnologyService","ACGN-100Q-030T","w_read_referential"
0b8b76e3-62fa-4527-9f05-2eb4dbaa8e97,"TechnologyService","ACGN-100Q-040T","w_load_CompanyGroup"
1f487986-3cac-4af8-bda2-6400a1c71f48,"TechnologyService","ACGN-100Q-050T","w_load_Company"
"@

$expectedCsv = @"
"ID","Type","Name","Documentation","Source","Target"
"New ID","RealizationRelationship","","","eb214110-2b6a-48b2-ba5a-7c13dc3bba39","a46681e7-19a8-4fc5-b747-09679c15ff26"
"New ID","TriggeringRelationship","","","a46681e7-19a8-4fc5-b747-09679c15ff26","85761a09-1145-4037-a527-66a743def45f"
"New ID","TriggeringRelationship","","","85761a09-1145-4037-a527-66a743def45f","27b126fb-c708-427d-b0a6-ce4747114ac4"
"New ID","TriggeringRelationship","","","27b126fb-c708-427d-b0a6-ce4747114ac4","bb0c5e42-5fad-4bd9-8ee9-f41d0b824e82"
"New ID","TriggeringRelationship","","","bb0c5e42-5fad-4bd9-8ee9-f41d0b824e82","0b8b76e3-62fa-4527-9f05-2eb4dbaa8e97"
"New ID","TriggeringRelationship","","","0b8b76e3-62fa-4527-9f05-2eb4dbaa8e97","1f487986-3cac-4af8-bda2-6400a1c71f48"
"@;

$relations = $inputCsv | ConvertFrom-Csv;
$elements = ConvertTo-ElementItems -Relations $relations;
$outputCsv = ($elements | ConvertTo-Csv -NoTypeInformation) -join "`n";

if( $outputCsv -ne $expectedCsv )
{
    throw "output csv doesn't match expected csv";
} else {
    write-host "output csv matches expected csv";
}

Validation Accuracy capped at certain value and graph shows rapid growths and falls

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rlronp=tf.keras.callbacks.ReduceLROnPlateau(monitor="val_loss", factor=0.5, 
                                             patience=2, verbose=1)
es=tf.keras.callbacks.EarlyStopping(monitor="val_loss", patience=4, verbose=1,
                                  restore_best_weights=True)
callbacks=[rlronp, es]
model.add(layers.Dropout(rate=.4, seed=123))

Dense(256, kernel_regularizer = regularizers.l2(l = 0.016),activity_regularizer=regularizers.l1(0.006),
                bias_regularizer=regularizers.l1(0.006) ,activation='relu')
-----------------------
rlronp=tf.keras.callbacks.ReduceLROnPlateau(monitor="val_loss", factor=0.5, 
                                             patience=2, verbose=1)
es=tf.keras.callbacks.EarlyStopping(monitor="val_loss", patience=4, verbose=1,
                                  restore_best_weights=True)
callbacks=[rlronp, es]
model.add(layers.Dropout(rate=.4, seed=123))

Dense(256, kernel_regularizer = regularizers.l2(l = 0.016),activity_regularizer=regularizers.l1(0.006),
                bias_regularizer=regularizers.l1(0.006) ,activation='relu')
-----------------------
rlronp=tf.keras.callbacks.ReduceLROnPlateau(monitor="val_loss", factor=0.5, 
                                             patience=2, verbose=1)
es=tf.keras.callbacks.EarlyStopping(monitor="val_loss", patience=4, verbose=1,
                                  restore_best_weights=True)
callbacks=[rlronp, es]
model.add(layers.Dropout(rate=.4, seed=123))

Dense(256, kernel_regularizer = regularizers.l2(l = 0.016),activity_regularizer=regularizers.l1(0.006),
                bias_regularizer=regularizers.l1(0.006) ,activation='relu')
-----------------------
rlronp=tf.keras.callbacks.ReduceLROnPlateau(monitor="val_loss", factor=0.5, 
                                             patience=2, verbose=1)
es=tf.keras.callbacks.EarlyStopping(monitor="val_loss", patience=4, verbose=1,
                                  restore_best_weights=True)
callbacks=[rlronp, es]
model.add(layers.Dropout(rate=.4, seed=123))

Dense(256, kernel_regularizer = regularizers.l2(l = 0.016),activity_regularizer=regularizers.l1(0.006),
                bias_regularizer=regularizers.l1(0.006) ,activation='relu')
-----------------------
l = len(dataset)
x_train = dataset[:math.floor(l * 0.75)]
y_train = labels[:math.floor(l * 0.75)]


x_val = dataset[math.floor(l * 0.75):]
y_val = labels[math.floor(l * 0.75):]


mean = x_train.mean(axis = 0)
x_train -= mean
std = x_train.std(axis = 0)
x_train /= std

x_val -= mean
x_val /= std

Install libmysqlclient-dev along with npm in dockers

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RUN apt-get update \
    && apt-get install -y tzdata \
    && apt-get install -y libfontconfig1 \
    && apt-get install -y libxrender1 \
    && apt-get install -y nodejs \
    && apt-get install -y npm \
    && apt-get install -y yarn \
    && apt-get install -y mysql-client \
    && apt-get install -y libmysqlclient-dev \
    && apt-get install -y shared-mime-info \
    && apt-get clean \
    && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* \
    && npm install -g npm@4.1.1 \
    npm install -g yarn

How to handle implicit namespaces modifying XML in python xml.etree.ElementTree

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from lxml import etree

XSL= ‘’’
<xsl:stylesheet version=”1.0" xmlns:xsl=”http://www.w3.org/1999/XSL/Transform" 
   xmlns:people="http://people.example.com">

  <xsl:template match=”@*|node()”>
    <xsl:copy>
      <xsl:apply-templates select="@*|node()"/>
    <xsl:copy> 
  </xsl:template>

  <xsl:template match=”people:name/text()”>
    <xsl:text>Sir </xsl:text>
    <xsl:value-of select=”.” />
  </xsl:template>

</xsl:stylesheet>
‘’’
# load input
dom = etree.parse(‘/path/to/my.xml’)
# load XSLT
transform = etree.XSLT(etree.fromstring(XSL))
# apply XSLT on loaded dom
str(transform(dom))
-----------------------
 <?xml version="1.0" encoding="UTF-8"?>
 <xsl:stylesheet version="1.0" xmlns:xsl="http://www.w3.org/1999/XSL/Transform" xmlns:std="http://people.example.com">

     <!-- Identity template -->
     <xsl:template match="node()|@*">
         <xsl:copy>
             <xsl:apply-templates select="node()|@*" />
         </xsl:copy>
     </xsl:template>

     <xsl:template match="std:name">
       <xsl:copy>
         <xsl:value-of select="concat('Sir ',.)"/>
       </xsl:copy>
     </xsl:template>

 </xsl:stylesheet>
 import lxml.etree as ET

 xml_filename = "input.xml"
 xsl_filename = "trans.xslt"
 out_filename = "output.xml"

 dom = ET.parse(xml_filename)
 xslt = ET.parse(xsl_filename)
 transform = ET.XSLT(xslt)
 newdom = transform(dom)
 newdom.write(out_filename, encoding='utf-8', xml_declaration=True)
<?xml version='1.0' encoding='UTF-8'?>
<actors xmlns:fictional="http://characters.example.com" xmlns="http://people.example.com">
    <actor>
        <name>Sir John Cleese</name>
        <fictional:character>Lancelot</fictional:character>
        <fictional:character>Archie Leach</fictional:character>
    </actor>
    <actor>
        <name>Sir Eric Idle</name>
        <fictional:character>Sir Robin</fictional:character>
        <fictional:character>Gunther</fictional:character>
        <fictional:character>Commander Clement</fictional:character>
    </actor>
</actors>
-----------------------
 <?xml version="1.0" encoding="UTF-8"?>
 <xsl:stylesheet version="1.0" xmlns:xsl="http://www.w3.org/1999/XSL/Transform" xmlns:std="http://people.example.com">

     <!-- Identity template -->
     <xsl:template match="node()|@*">
         <xsl:copy>
             <xsl:apply-templates select="node()|@*" />
         </xsl:copy>
     </xsl:template>

     <xsl:template match="std:name">
       <xsl:copy>
         <xsl:value-of select="concat('Sir ',.)"/>
       </xsl:copy>
     </xsl:template>

 </xsl:stylesheet>
 import lxml.etree as ET

 xml_filename = "input.xml"
 xsl_filename = "trans.xslt"
 out_filename = "output.xml"

 dom = ET.parse(xml_filename)
 xslt = ET.parse(xsl_filename)
 transform = ET.XSLT(xslt)
 newdom = transform(dom)
 newdom.write(out_filename, encoding='utf-8', xml_declaration=True)
<?xml version='1.0' encoding='UTF-8'?>
<actors xmlns:fictional="http://characters.example.com" xmlns="http://people.example.com">
    <actor>
        <name>Sir John Cleese</name>
        <fictional:character>Lancelot</fictional:character>
        <fictional:character>Archie Leach</fictional:character>
    </actor>
    <actor>
        <name>Sir Eric Idle</name>
        <fictional:character>Sir Robin</fictional:character>
        <fictional:character>Gunther</fictional:character>
        <fictional:character>Commander Clement</fictional:character>
    </actor>
</actors>
-----------------------
 <?xml version="1.0" encoding="UTF-8"?>
 <xsl:stylesheet version="1.0" xmlns:xsl="http://www.w3.org/1999/XSL/Transform" xmlns:std="http://people.example.com">

     <!-- Identity template -->
     <xsl:template match="node()|@*">
         <xsl:copy>
             <xsl:apply-templates select="node()|@*" />
         </xsl:copy>
     </xsl:template>

     <xsl:template match="std:name">
       <xsl:copy>
         <xsl:value-of select="concat('Sir ',.)"/>
       </xsl:copy>
     </xsl:template>

 </xsl:stylesheet>
 import lxml.etree as ET

 xml_filename = "input.xml"
 xsl_filename = "trans.xslt"
 out_filename = "output.xml"

 dom = ET.parse(xml_filename)
 xslt = ET.parse(xsl_filename)
 transform = ET.XSLT(xslt)
 newdom = transform(dom)
 newdom.write(out_filename, encoding='utf-8', xml_declaration=True)
<?xml version='1.0' encoding='UTF-8'?>
<actors xmlns:fictional="http://characters.example.com" xmlns="http://people.example.com">
    <actor>
        <name>Sir John Cleese</name>
        <fictional:character>Lancelot</fictional:character>
        <fictional:character>Archie Leach</fictional:character>
    </actor>
    <actor>
        <name>Sir Eric Idle</name>
        <fictional:character>Sir Robin</fictional:character>
        <fictional:character>Gunther</fictional:character>
        <fictional:character>Commander Clement</fictional:character>
    </actor>
</actors>
-----------------------
from lxml import etree
 
tree = etree.parse("data1.xml")
 
for name in tree.findall(".//{*}name"):
    name.text = "Sir " + name.text

Merge with inner join

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MERGE INTO   TBL1 concent
        USING  (SELECT  inter.rfc as inter_rfc
                        arch.name_contr, arch.rfc,arch.taxpayer_situation, 
                        arch.oficio_global,arch.presumed_publication,arch.definitive_publication
        FROM TBL2 arch
        INNER JOIN  TBL3 inter 
              ON inter.rfc = arch.rfc ) v_using
        ON (concent.rfc = v_using.rfc) WHEN MATCHED THEN UPDATE SET concent.name_contr = v_using.name_contr, concent.taxpayer_situation = v_using.taxpayer_situation,...

Using XPath in ElementTree to find Nested Elements

copy iconCopydownload iconDownload
actors = root.findall('.//{*}actor')
for actor in actors:
    name = actor.find('./{*}name')
    location = actor.find('./{*}Location//{*}name')
    print(name.text, location.text)
John Cleese Ohio
Eric Idle Colorado
-----------------------
actors = root.findall('.//{*}actor')
for actor in actors:
    name = actor.find('./{*}name')
    location = actor.find('./{*}Location//{*}name')
    print(name.text, location.text)
John Cleese Ohio
Eric Idle Colorado

How to duplicate rows from a DataFrame based on a column in Python?

copy iconCopydownload iconDownload
s1 = df['Kids'].value_counts()
s2 = df.groupby('Kids')['Count'].first()   

df = df.append(s2.loc[s2.index.repeat(s2 - s1)].reset_index(), ignore_index=True)
>>> s1

Joe           2
Sofia         1
Betty         1
Claire Ann    1
Phil          1
Luke          1
Archie        1
Name: Kids, dtype: int64
>>> s2

Kids
Archie        1.0
Betty         2.0
Claire Ann    1.0
Joe           3.0
Luke          1.0
Phil          1.0
Sofia         1.0
Name: Count, dtype: float64
>>> s2 - s1

Archie        0.0
Betty         1.0
Claire Ann    0.0
Joe           1.0
Luke          0.0
Phil          0.0
Sofia         0.0
dtype: float64
>>> s2.loc[s2.index.repeat(s2 - s1)]

Kids
Betty    2.0
Joe      3.0
Name: Count, dtype: float64
>>> df

         Kids       City Preferred Transport  Count
0       Sofia     Boston                 Bus    1.0
1  Claire Ann        NaN                 NaN    1.0
2         Joe    Detroit               Train    3.0
3       Betty        NaN                 Car    2.0
4      Archie  Bruxelles                 NaN    1.0
5         Joe        NaN            Airplane    3.0
6        Phil     Berlin                Ship    1.0
7        Luke        NaN            Airplane    1.0
8       Betty        NaN                 NaN    2.0
9         Joe        NaN                 NaN    3.0
-----------------------
s1 = df['Kids'].value_counts()
s2 = df.groupby('Kids')['Count'].first()   

df = df.append(s2.loc[s2.index.repeat(s2 - s1)].reset_index(), ignore_index=True)
>>> s1

Joe           2
Sofia         1
Betty         1
Claire Ann    1
Phil          1
Luke          1
Archie        1
Name: Kids, dtype: int64
>>> s2

Kids
Archie        1.0
Betty         2.0
Claire Ann    1.0
Joe           3.0
Luke          1.0
Phil          1.0
Sofia         1.0
Name: Count, dtype: float64
>>> s2 - s1

Archie        0.0
Betty         1.0
Claire Ann    0.0
Joe           1.0
Luke          0.0
Phil          0.0
Sofia         0.0
dtype: float64
>>> s2.loc[s2.index.repeat(s2 - s1)]

Kids
Betty    2.0
Joe      3.0
Name: Count, dtype: float64
>>> df

         Kids       City Preferred Transport  Count
0       Sofia     Boston                 Bus    1.0
1  Claire Ann        NaN                 NaN    1.0
2         Joe    Detroit               Train    3.0
3       Betty        NaN                 Car    2.0
4      Archie  Bruxelles                 NaN    1.0
5         Joe        NaN            Airplane    3.0
6        Phil     Berlin                Ship    1.0
7        Luke        NaN            Airplane    1.0
8       Betty        NaN                 NaN    2.0
9         Joe        NaN                 NaN    3.0
-----------------------
s1 = df['Kids'].value_counts()
s2 = df.groupby('Kids')['Count'].first()   

df = df.append(s2.loc[s2.index.repeat(s2 - s1)].reset_index(), ignore_index=True)
>>> s1

Joe           2
Sofia         1
Betty         1
Claire Ann    1
Phil          1
Luke          1
Archie        1
Name: Kids, dtype: int64
>>> s2

Kids
Archie        1.0
Betty         2.0
Claire Ann    1.0
Joe           3.0
Luke          1.0
Phil          1.0
Sofia         1.0
Name: Count, dtype: float64
>>> s2 - s1

Archie        0.0
Betty         1.0
Claire Ann    0.0
Joe           1.0
Luke          0.0
Phil          0.0
Sofia         0.0
dtype: float64
>>> s2.loc[s2.index.repeat(s2 - s1)]

Kids
Betty    2.0
Joe      3.0
Name: Count, dtype: float64
>>> df

         Kids       City Preferred Transport  Count
0       Sofia     Boston                 Bus    1.0
1  Claire Ann        NaN                 NaN    1.0
2         Joe    Detroit               Train    3.0
3       Betty        NaN                 Car    2.0
4      Archie  Bruxelles                 NaN    1.0
5         Joe        NaN            Airplane    3.0
6        Phil     Berlin                Ship    1.0
7        Luke        NaN            Airplane    1.0
8       Betty        NaN                 NaN    2.0
9         Joe        NaN                 NaN    3.0
-----------------------
s1 = df['Kids'].value_counts()
s2 = df.groupby('Kids')['Count'].first()   

df = df.append(s2.loc[s2.index.repeat(s2 - s1)].reset_index(), ignore_index=True)
>>> s1

Joe           2
Sofia         1
Betty         1
Claire Ann    1
Phil          1
Luke          1
Archie        1
Name: Kids, dtype: int64
>>> s2

Kids
Archie        1.0
Betty         2.0
Claire Ann    1.0
Joe           3.0
Luke          1.0
Phil          1.0
Sofia         1.0
Name: Count, dtype: float64
>>> s2 - s1

Archie        0.0
Betty         1.0
Claire Ann    0.0
Joe           1.0
Luke          0.0
Phil          0.0
Sofia         0.0
dtype: float64
>>> s2.loc[s2.index.repeat(s2 - s1)]

Kids
Betty    2.0
Joe      3.0
Name: Count, dtype: float64
>>> df

         Kids       City Preferred Transport  Count
0       Sofia     Boston                 Bus    1.0
1  Claire Ann        NaN                 NaN    1.0
2         Joe    Detroit               Train    3.0
3       Betty        NaN                 Car    2.0
4      Archie  Bruxelles                 NaN    1.0
5         Joe        NaN            Airplane    3.0
6        Phil     Berlin                Ship    1.0
7        Luke        NaN            Airplane    1.0
8       Betty        NaN                 NaN    2.0
9         Joe        NaN                 NaN    3.0
-----------------------
s1 = df['Kids'].value_counts()
s2 = df.groupby('Kids')['Count'].first()   

df = df.append(s2.loc[s2.index.repeat(s2 - s1)].reset_index(), ignore_index=True)
>>> s1

Joe           2
Sofia         1
Betty         1
Claire Ann    1
Phil          1
Luke          1
Archie        1
Name: Kids, dtype: int64
>>> s2

Kids
Archie        1.0
Betty         2.0
Claire Ann    1.0
Joe           3.0
Luke          1.0
Phil          1.0
Sofia         1.0
Name: Count, dtype: float64
>>> s2 - s1

Archie        0.0
Betty         1.0
Claire Ann    0.0
Joe           1.0
Luke          0.0
Phil          0.0
Sofia         0.0
dtype: float64
>>> s2.loc[s2.index.repeat(s2 - s1)]

Kids
Betty    2.0
Joe      3.0
Name: Count, dtype: float64
>>> df

         Kids       City Preferred Transport  Count
0       Sofia     Boston                 Bus    1.0
1  Claire Ann        NaN                 NaN    1.0
2         Joe    Detroit               Train    3.0
3       Betty        NaN                 Car    2.0
4      Archie  Bruxelles                 NaN    1.0
5         Joe        NaN            Airplane    3.0
6        Phil     Berlin                Ship    1.0
7        Luke        NaN            Airplane    1.0
8       Betty        NaN                 NaN    2.0
9         Joe        NaN                 NaN    3.0
-----------------------
s1 = df['Kids'].value_counts()
s2 = df.groupby('Kids')['Count'].first()   

df = df.append(s2.loc[s2.index.repeat(s2 - s1)].reset_index(), ignore_index=True)
>>> s1

Joe           2
Sofia         1
Betty         1
Claire Ann    1
Phil          1
Luke          1
Archie        1
Name: Kids, dtype: int64
>>> s2

Kids
Archie        1.0
Betty         2.0
Claire Ann    1.0
Joe           3.0
Luke          1.0
Phil          1.0
Sofia         1.0
Name: Count, dtype: float64
>>> s2 - s1

Archie        0.0
Betty         1.0
Claire Ann    0.0
Joe           1.0
Luke          0.0
Phil          0.0
Sofia         0.0
dtype: float64
>>> s2.loc[s2.index.repeat(s2 - s1)]

Kids
Betty    2.0
Joe      3.0
Name: Count, dtype: float64
>>> df

         Kids       City Preferred Transport  Count
0       Sofia     Boston                 Bus    1.0
1  Claire Ann        NaN                 NaN    1.0
2         Joe    Detroit               Train    3.0
3       Betty        NaN                 Car    2.0
4      Archie  Bruxelles                 NaN    1.0
5         Joe        NaN            Airplane    3.0
6        Phil     Berlin                Ship    1.0
7        Luke        NaN            Airplane    1.0
8       Betty        NaN                 NaN    2.0
9         Joe        NaN                 NaN    3.0

How to delimit letters and numbers from a string in an array in Python?

copy iconCopydownload iconDownload
import re
kid_count_list = ['Sofia 1', 'Claire Ann 1', 'Joe 3', 'Betty 2', 'Archie 1', 'Phil 1', 'Luke 1']
rx = re.compile(r'\s+(?=\d+$)')
l = [rx.split(x) for x in kid_count_list]
names, counts = zip(*l)
print(list(names))  # => ['Sofia', 'Claire Ann', 'Joe', 'Betty', 'Archie', 'Phil', 'Luke']
print(list(counts)) # => ['1', '1', '3', '2', '1', '1', '1']
import re
import pandas as pd
import numpy as np

kid_count_list = ['Sofia 1', 'Claire Ann 1', 'Joe 3', 'Betty 2', 'Archie 1', 'Phil 1', 'Luke 1']
cols = [re.split(r'\s+(?=\d+$)', x) for x in kid_count_list]
df = pd.DataFrame(cols, columns=['names', 'counts'])
## >>> df
##         names counts
## 0       Sofia      1
## 1  Claire Ann      1
## 2         Joe      3
## 3       Betty      2
## 4      Archie      1
## 5        Phil      1
## 6        Luke      1
kid_count_list = ['Sofia 1', 'Claire Ann 1', 'Joe 3', 'Betty 2', 'Archie 1', 'Phil 1', 'Luke 1']
df = pd.DataFrame({'data':kid_count_list})
df[['names', 'counts']] = df.pop('data').str.rsplit(r' ', n=1, expand=True)
-----------------------
import re
kid_count_list = ['Sofia 1', 'Claire Ann 1', 'Joe 3', 'Betty 2', 'Archie 1', 'Phil 1', 'Luke 1']
rx = re.compile(r'\s+(?=\d+$)')
l = [rx.split(x) for x in kid_count_list]
names, counts = zip(*l)
print(list(names))  # => ['Sofia', 'Claire Ann', 'Joe', 'Betty', 'Archie', 'Phil', 'Luke']
print(list(counts)) # => ['1', '1', '3', '2', '1', '1', '1']
import re
import pandas as pd
import numpy as np

kid_count_list = ['Sofia 1', 'Claire Ann 1', 'Joe 3', 'Betty 2', 'Archie 1', 'Phil 1', 'Luke 1']
cols = [re.split(r'\s+(?=\d+$)', x) for x in kid_count_list]
df = pd.DataFrame(cols, columns=['names', 'counts'])
## >>> df
##         names counts
## 0       Sofia      1
## 1  Claire Ann      1
## 2         Joe      3
## 3       Betty      2
## 4      Archie      1
## 5        Phil      1
## 6        Luke      1
kid_count_list = ['Sofia 1', 'Claire Ann 1', 'Joe 3', 'Betty 2', 'Archie 1', 'Phil 1', 'Luke 1']
df = pd.DataFrame({'data':kid_count_list})
df[['names', 'counts']] = df.pop('data').str.rsplit(r' ', n=1, expand=True)
-----------------------
import re
kid_count_list = ['Sofia 1', 'Claire Ann 1', 'Joe 3', 'Betty 2', 'Archie 1', 'Phil 1', 'Luke 1']
rx = re.compile(r'\s+(?=\d+$)')
l = [rx.split(x) for x in kid_count_list]
names, counts = zip(*l)
print(list(names))  # => ['Sofia', 'Claire Ann', 'Joe', 'Betty', 'Archie', 'Phil', 'Luke']
print(list(counts)) # => ['1', '1', '3', '2', '1', '1', '1']
import re
import pandas as pd
import numpy as np

kid_count_list = ['Sofia 1', 'Claire Ann 1', 'Joe 3', 'Betty 2', 'Archie 1', 'Phil 1', 'Luke 1']
cols = [re.split(r'\s+(?=\d+$)', x) for x in kid_count_list]
df = pd.DataFrame(cols, columns=['names', 'counts'])
## >>> df
##         names counts
## 0       Sofia      1
## 1  Claire Ann      1
## 2         Joe      3
## 3       Betty      2
## 4      Archie      1
## 5        Phil      1
## 6        Luke      1
kid_count_list = ['Sofia 1', 'Claire Ann 1', 'Joe 3', 'Betty 2', 'Archie 1', 'Phil 1', 'Luke 1']
df = pd.DataFrame({'data':kid_count_list})
df[['names', 'counts']] = df.pop('data').str.rsplit(r' ', n=1, expand=True)
-----------------------
names, counts = zip(*[re.fullmatch(r"(\D+)\s(\d+)", s).groups() for s in kid_count_list])
('Sofia', 'Claire Ann', 'Joe', 'Betty', 'Archie', 'Phil', 'Luke')
('1', '1', '3', '2', '1', '1', '1')
names = list(names)
counts = list(map(int, counts))  # convert the counts to int, too
>>> names
['Sofia', 'Claire Ann', 'Joe', 'Betty', 'Archie', 'Phil', 'Luke']

>>> counts
[1, 1, 3, 2, 1, 1, 1]
[('Sofia', '1'), ('Claire Ann', '1'), ('Joe', '3'), ('Betty', '2'), ('Archie', '1'), ('Phil', '1'), ('Luke', '1')]
-----------------------
names, counts = zip(*[re.fullmatch(r"(\D+)\s(\d+)", s).groups() for s in kid_count_list])
('Sofia', 'Claire Ann', 'Joe', 'Betty', 'Archie', 'Phil', 'Luke')
('1', '1', '3', '2', '1', '1', '1')
names = list(names)
counts = list(map(int, counts))  # convert the counts to int, too
>>> names
['Sofia', 'Claire Ann', 'Joe', 'Betty', 'Archie', 'Phil', 'Luke']

>>> counts
[1, 1, 3, 2, 1, 1, 1]
[('Sofia', '1'), ('Claire Ann', '1'), ('Joe', '3'), ('Betty', '2'), ('Archie', '1'), ('Phil', '1'), ('Luke', '1')]
-----------------------
names, counts = zip(*[re.fullmatch(r"(\D+)\s(\d+)", s).groups() for s in kid_count_list])
('Sofia', 'Claire Ann', 'Joe', 'Betty', 'Archie', 'Phil', 'Luke')
('1', '1', '3', '2', '1', '1', '1')
names = list(names)
counts = list(map(int, counts))  # convert the counts to int, too
>>> names
['Sofia', 'Claire Ann', 'Joe', 'Betty', 'Archie', 'Phil', 'Luke']

>>> counts
[1, 1, 3, 2, 1, 1, 1]
[('Sofia', '1'), ('Claire Ann', '1'), ('Joe', '3'), ('Betty', '2'), ('Archie', '1'), ('Phil', '1'), ('Luke', '1')]
-----------------------
names, counts = zip(*[re.fullmatch(r"(\D+)\s(\d+)", s).groups() for s in kid_count_list])
('Sofia', 'Claire Ann', 'Joe', 'Betty', 'Archie', 'Phil', 'Luke')
('1', '1', '3', '2', '1', '1', '1')
names = list(names)
counts = list(map(int, counts))  # convert the counts to int, too
>>> names
['Sofia', 'Claire Ann', 'Joe', 'Betty', 'Archie', 'Phil', 'Luke']

>>> counts
[1, 1, 3, 2, 1, 1, 1]
[('Sofia', '1'), ('Claire Ann', '1'), ('Joe', '3'), ('Betty', '2'), ('Archie', '1'), ('Phil', '1'), ('Luke', '1')]
-----------------------
names, counts = zip(*[re.fullmatch(r"(\D+)\s(\d+)", s).groups() for s in kid_count_list])
('Sofia', 'Claire Ann', 'Joe', 'Betty', 'Archie', 'Phil', 'Luke')
('1', '1', '3', '2', '1', '1', '1')
names = list(names)
counts = list(map(int, counts))  # convert the counts to int, too
>>> names
['Sofia', 'Claire Ann', 'Joe', 'Betty', 'Archie', 'Phil', 'Luke']

>>> counts
[1, 1, 3, 2, 1, 1, 1]
[('Sofia', '1'), ('Claire Ann', '1'), ('Joe', '3'), ('Betty', '2'), ('Archie', '1'), ('Phil', '1'), ('Luke', '1')]
-----------------------
names, counts = zip(*[re.fullmatch(r"(\D+)\s(\d+)", s).groups() for s in kid_count_list])
('Sofia', 'Claire Ann', 'Joe', 'Betty', 'Archie', 'Phil', 'Luke')
('1', '1', '3', '2', '1', '1', '1')
names = list(names)
counts = list(map(int, counts))  # convert the counts to int, too
>>> names
['Sofia', 'Claire Ann', 'Joe', 'Betty', 'Archie', 'Phil', 'Luke']

>>> counts
[1, 1, 3, 2, 1, 1, 1]
[('Sofia', '1'), ('Claire Ann', '1'), ('Joe', '3'), ('Betty', '2'), ('Archie', '1'), ('Phil', '1'), ('Luke', '1')]
-----------------------
import re

kid_count_list = ['Sofia 1', 'Claire Ann 1', 'Joe 3', 'Betty 2', 'Archie 1', 'Phil 1', 'Luke 1']
names, counts = [], []

split_list = [re.split(r'\s+(?=\d+$)', item) for item in kid_count_list]

for item in split_list:
   names.append(item[0])
   counts.append(int(item[1]))
print(names)
print(counts)
['Sofia', 'Claire Ann', 'Joe', 'Betty', 'Archie', 'Phil', 'Luke']
[1, 1, 3, 2, 1, 1, 1]
-----------------------
import re

kid_count_list = ['Sofia 1', 'Claire Ann 1', 'Joe 3', 'Betty 2', 'Archie 1', 'Phil 1', 'Luke 1']
names, counts = [], []

split_list = [re.split(r'\s+(?=\d+$)', item) for item in kid_count_list]

for item in split_list:
   names.append(item[0])
   counts.append(int(item[1]))
print(names)
print(counts)
['Sofia', 'Claire Ann', 'Joe', 'Betty', 'Archie', 'Phil', 'Luke']
[1, 1, 3, 2, 1, 1, 1]

Linux Bash Script Awk Field Separator

copy iconCopydownload iconDownload
Mike Harrington:(510) 548-1278:250:100:175
Mike Harrington            $1
(510) 548-1278             $2
250                        $3
100                        $4
175                        $5
-----------------------
Mike Harrington:(510) 548-1278:250:100:175
Mike Harrington            $1
(510) 548-1278             $2
250                        $3
100                        $4
175                        $5

Community Discussions

Trending Discussions on archi
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  • Merge with inner join
  • Using XPath in ElementTree to find Nested Elements
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Trending Discussions on archi

QUESTION

HTML Unescape is not unescaping special characters

Asked 2022-Feb-02 at 01:39

My program does not unescape the HTML special characters for quotes and I can't figure out why. It still displays the special characters in the Terminal.

For example: 'In the comic book &quot;Archie&quot;

import requests
import html

API_URL = "https://opentdb.com/api.php"

parameters = {
    "amount": 10,
    "type": "boolean"
}

response = requests.get(API_URL, params=parameters)
data = html.unescape(response.json())
unescaped_data = data["results"]
print(f"UNESCAPED DATA: {unescaped_data}") # THIS IS NOT WORKING

ANSWER

Answered 2022-Feb-02 at 01:38

When I changed response.json() to response.text it works

data = html.unescape(response.text)

Source https://stackoverflow.com/questions/70949101

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

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Install archi

You can download it from GitHub.
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Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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