Pandas read_xml () strategie di test del metodo

Attualmente, gli strumenti I / O di Panda non mantengono un read_xml()metodo e la controparte to_xml(). Tuttavia, read_jsondimostra che le strutture ad albero possono essere implementate per l'importazione di dataframe e read_htmlper i formati di markup.

Se la squadra panda fa considerare tale read_xmlmetodo per una futura versione panda, che cosa sarebbe implementazione che perseguire: l'analisi con built-in xml.etree.ElementTreecon i suoi iterfind()o iterparse()funzioni o il modulo di terze parti, lxmlcon la sua XPath 1.0 e XSLT 1.0 metodi?

Di seguito sono riportati i miei test eseguiti per quattro tipi di metodo su un input XML semplice, piatto e incentrato sugli elementi. Tutti sono impostati per l'analisi generalizzata per qualsiasi figlio di root di secondo livello e ogni metodo dovrebbe produrre esattamente lo stesso dataframe panda. Tutti tranne le ultime chiamate pd.Dataframe()nell'elenco dei dizionari. Il metodo XSLT trasforma XML in CSV per il cast StringIO()in pd.read_csv().

Domanda (in più parti)

• PRESTAZIONI: come spieghi il più lento iterparsespesso consigliato per file più grandi poiché il file viene analizzato in modo iterativo? È in parte dovuto ai ifcontrolli logici?

• MEMORIA: la memoria della CPU è correlata ai tempi nelle chiamate I / O? XSLT e XPath 1.0 tendono a non scalare bene con documenti XML di dimensioni maggiori poiché l'intero file deve essere letto in memoria per essere analizzato.

• STRATEGIA: l'elenco dei dizionari è una strategia ottimale per la Dataframe()chiamata? Guarda queste interessanti risposte: versione del generatore e una versione definita dall'utente iterwalk . Entrambi gli elenchi di upcast su dataframe.

Dati di input (gli attuali migliori utenti di Stack Overflow per anno di cui sono inclusi i nostri amici panda)

<?xml version="1.0" encoding="utf-8"?>
<stackoverflow>
  <topusers>
    <user>Gordon Linoff</user>
    <link>http://www.stackoverflow.com//users/1144035/gordon-linoff</link>
    <location>New York, United States</location>
    <year_rep>5,985</year_rep>
    <total_rep>499,408</total_rep>
    <tag1>sql</tag1>
    <tag2>sql-server</tag2>
    <tag3>mysql</tag3>
  </topusers>
  <topusers>
    <user>Günter Zöchbauer</user>
    <link>http://www.stackoverflow.com//users/217408/g%c3%bcnter-z%c3%b6chbauer</link>
    <location>Linz, Austria</location>
    <year_rep>5,835</year_rep>
    <total_rep>154,439</total_rep>
    <tag1>angular2</tag1>
    <tag2>typescript</tag2>
    <tag3>javascript</tag3>
  </topusers>
  <topusers>
    <user>jezrael</user>
    <link>http://www.stackoverflow.com//users/2901002/jezrael</link>
    <location>Bratislava, Slovakia</location>
    <year_rep>5,740</year_rep>
    <total_rep>83,237</total_rep>
    <tag1>pandas</tag1>
    <tag2>python</tag2>
    <tag3>dataframe</tag3>
  </topusers>
  <topusers>
    <user>VonC</user>
    <link>http://www.stackoverflow.com//users/6309/vonc</link>
    <location>France</location>
    <year_rep>5,577</year_rep>
    <total_rep>651,397</total_rep>
    <tag1>git</tag1>
    <tag2>github</tag2>
    <tag3>docker</tag3>
  </topusers>
  <topusers>
    <user>Martijn Pieters</user>
    <link>http://www.stackoverflow.com//users/100297/martijn-pieters</link>
    <location>Cambridge, United Kingdom</location>
    <year_rep>5,337</year_rep>
    <total_rep>525,176</total_rep>
    <tag1>python</tag1>
    <tag2>python-3.x</tag2>
    <tag3>python-2.7</tag3>
  </topusers>
  <topusers>
    <user>T.J. Crowder</user>
    <link>http://www.stackoverflow.com//users/157247/t-j-crowder</link>
    <location>United Kingdom</location>
    <year_rep>5,258</year_rep>
    <total_rep>508,310</total_rep>
    <tag1>javascript</tag1>
    <tag2>jquery</tag2>
    <tag3>java</tag3>
  </topusers>
  <topusers>
    <user>akrun</user>
    <link>http://www.stackoverflow.com//users/3732271/akrun</link>
    <location></location>
    <year_rep>5,188</year_rep>
    <total_rep>229,553</total_rep>
    <tag1>r</tag1>
    <tag2>dplyr</tag2>
    <tag3>dataframe</tag3>
  </topusers>
  <topusers>
    <user>Wiktor Stribi?ew</user>
    <link>http://www.stackoverflow.com//users/3832970/wiktor-stribi%c5%bcew</link>
    <location>Warsaw, Poland</location>
    <year_rep>4,948</year_rep>
    <total_rep>158,134</total_rep>
    <tag1>regex</tag1>
    <tag2>javascript</tag2>
    <tag3>c#</tag3>
  </topusers>
  <topusers>
    <user>Darin Dimitrov</user>
    <link>http://www.stackoverflow.com//users/29407/darin-dimitrov</link>
    <location>Sofia, Bulgaria</location>
    <year_rep>4,936</year_rep>
    <total_rep>709,683</total_rep>
    <tag1>c#</tag1>
    <tag2>asp.net-mvc</tag2>
    <tag3>asp.net-mvc-3</tag3>
  </topusers>
  <topusers>
    <user>Eric Duminil</user>
    <link>http://www.stackoverflow.com//users/6419007/eric-duminil</link>
    <location></location>
    <year_rep>4,854</year_rep>
    <total_rep>12,557</total_rep>
    <tag1>ruby</tag1>
    <tag2>ruby-on-rails</tag2>
    <tag3>arrays</tag3>
  </topusers>
  <topusers>
    <user>alecxe</user>
    <link>http://www.stackoverflow.com//users/771848/alecxe</link>
    <location>New York, United States</location>
    <year_rep>4,723</year_rep>
    <total_rep>233,368</total_rep>
    <tag1>python</tag1>
    <tag2>selenium</tag2>
    <tag3>protractor</tag3>
  </topusers>
  <topusers>
    <user>Jean-François Fabre</user>
    <link>http://www.stackoverflow.com//users/6451573/jean-fran%c3%a7ois-fabre</link>
    <location>Toulouse, France</location>
    <year_rep>4,526</year_rep>
    <total_rep>30,027</total_rep>
    <tag1>python</tag1>
    <tag2>python-3.x</tag2>
    <tag3>python-2.7</tag3>
  </topusers>
  <topusers>
    <user>piRSquared</user>
    <link>http://www.stackoverflow.com//users/2336654/pirsquared</link>
    <location>Bellevue, WA, United States</location>
    <year_rep>4,482</year_rep>
    <total_rep>41,183</total_rep>
    <tag1>pandas</tag1>
    <tag2>python</tag2>
    <tag3>dataframe</tag3>
  </topusers>
  <topusers>
    <user>CommonsWare</user>
    <link>http://www.stackoverflow.com//users/115145/commonsware</link>
    <location>Who Wants to Know?</location>
    <year_rep>4,475</year_rep>
    <total_rep>616,135</total_rep>
    <tag1>android</tag1>
    <tag2>java</tag2>
    <tag3>android-intent</tag3>
  </topusers>
  <topusers>
    <user>Quentin</user>
    <link>http://www.stackoverflow.com//users/19068/quentin</link>
    <location>United Kingdom</location>
    <year_rep>4,464</year_rep>
    <total_rep>509,365</total_rep>
    <tag1>javascript</tag1>
    <tag2>html</tag2>
    <tag3>css</tag3>
  </topusers>
  <topusers>
    <user>Jon Skeet</user>
    <link>http://www.stackoverflow.com//users/22656/jon-skeet</link>
    <location>Reading, United Kingdom</location>
    <year_rep>4,348</year_rep>
    <total_rep>921,690</total_rep>
    <tag1>c#</tag1>
    <tag2>java</tag2>
    <tag3>.net</tag3>
  </topusers>
  <topusers>
    <user>Felix Kling</user>
    <link>http://www.stackoverflow.com//users/218196/felix-kling</link>
    <location>Sunnyvale, CA</location>
    <year_rep>4,324</year_rep>
    <total_rep>411,535</total_rep>
    <tag1>javascript</tag1>
    <tag2>jquery</tag2>
    <tag3>asynchronous</tag3>
  </topusers>
  <topusers>
    <user>matt</user>
    <link>http://www.stackoverflow.com//users/341994/matt</link>
    <location></location>
    <year_rep>4,313</year_rep>
    <total_rep>220,515</total_rep>
    <tag1>swift</tag1>
    <tag2>ios</tag2>
    <tag3>xcode</tag3>
  </topusers>
  <topusers>
    <user>Psidom</user>
    <link>http://www.stackoverflow.com//users/4983450/psidom</link>
    <location>Atlanta, GA, United States</location>
    <year_rep>4,236</year_rep>
    <total_rep>36,950</total_rep>
    <tag1>python</tag1>
    <tag2>pandas</tag2>
    <tag3>r</tag3>
  </topusers>
  <topusers>
    <user>Martin R</user>
    <link>http://www.stackoverflow.com//users/1187415/martin-r</link>
    <location>Germany</location>
    <year_rep>4,195</year_rep>
    <total_rep>269,380</total_rep>
    <tag1>swift</tag1>
    <tag2>ios</tag2>
    <tag3>swift3</tag3>
  </topusers>
  <topusers>
    <user>Barmar</user>
    <link>http://www.stackoverflow.com//users/1491895/barmar</link>
    <location>Arlington, MA</location>
    <year_rep>4,179</year_rep>
    <total_rep>289,989</total_rep>
    <tag1>javascript</tag1>
    <tag2>php</tag2>
    <tag3>jquery</tag3>
  </topusers>
  <topusers>
    <user>Alexey Mezenin</user>
    <link>http://www.stackoverflow.com//users/1227923/alexey-mezenin</link>
    <location>??????</location>
    <year_rep>4,142</year_rep>
    <total_rep>31,602</total_rep>
    <tag1>laravel</tag1>
    <tag2>php</tag2>
    <tag3>laravel-5.3</tag3>
  </topusers>
  <topusers>
    <user>BalusC</user>
    <link>http://www.stackoverflow.com//users/157882/balusc</link>
    <location>Amsterdam, Netherlands</location>
    <year_rep>4,046</year_rep>
    <total_rep>703,046</total_rep>
    <tag1>java</tag1>
    <tag2>jsf</tag2>
    <tag3>servlets</tag3>
  </topusers>
  <topusers>
    <user>GurV</user>
    <link>http://www.stackoverflow.com//users/6348498/gurv</link>
    <location></location>
    <year_rep>4,016</year_rep>
    <total_rep>7,932</total_rep>
    <tag1>sql</tag1>
    <tag2>mysql</tag2>
    <tag3>sql-server</tag3>
  </topusers>
  <topusers>
    <user>Nina Scholz</user>
    <link>http://www.stackoverflow.com//users/1447675/nina-scholz</link>
    <location>Berlin, Deutschland</location>
    <year_rep>3,950</year_rep>
    <total_rep>61,135</total_rep>
    <tag1>javascript</tag1>
    <tag2>arrays</tag2>
    <tag3>object</tag3>
  </topusers>
  <topusers>
    <user>JB Nizet</user>
    <link>http://www.stackoverflow.com//users/571407/jb-nizet</link>
    <location>Saint-Etienne, France</location>
    <year_rep>3,923</year_rep>
    <total_rep>418,780</total_rep>
    <tag1>java</tag1>
    <tag2>hibernate</tag2>
    <tag3>java-8</tag3>
  </topusers>
  <topusers>
    <user>Frank van Puffelen</user>
    <link>http://www.stackoverflow.com//users/209103/frank-van-puffelen</link>
    <location>San Francisco, CA</location>
    <year_rep>3,920</year_rep>
    <total_rep>86,520</total_rep>
    <tag1>firebase</tag1>
    <tag2>firebase-database</tag2>
    <tag3>android</tag3>
  </topusers>
  <topusers>
    <user>dasblinkenlight</user>
    <link>http://www.stackoverflow.com//users/335858/dasblinkenlight</link>
    <location>United States</location>
    <year_rep>3,886</year_rep>
    <total_rep>475,813</total_rep>
    <tag1>c#</tag1>
    <tag2>java</tag2>
    <tag3>c++</tag3>
  </topusers>
  <topusers>
    <user>Tim Biegeleisen</user>
    <link>http://www.stackoverflow.com//users/1863229/tim-biegeleisen</link>
    <location>Singapore</location>
    <year_rep>3,814</year_rep>
    <total_rep>77,211</total_rep>
    <tag1>sql</tag1>
    <tag2>mysql</tag2>
    <tag3>java</tag3>
  </topusers>
  <topusers>
    <user>Greg Hewgill</user>
    <link>http://www.stackoverflow.com//users/893/greg-hewgill</link>
    <location>Christchurch, New Zealand</location>
    <year_rep>3,796</year_rep>
    <total_rep>529,137</total_rep>
    <tag1>git</tag1>
    <tag2>python</tag2>
    <tag3>git-pull</tag3>
  </topusers>
  <topusers>
    <user>unutbu</user>
    <link>http://www.stackoverflow.com//users/190597/unutbu</link>
    <location></location>
    <year_rep>3,735</year_rep>
    <total_rep>401,595</total_rep>
    <tag1>python</tag1>
    <tag2>pandas</tag2>
    <tag3>numpy</tag3>
  </topusers>
  <topusers>
    <user>Hans Passant</user>
    <link>http://www.stackoverflow.com//users/17034/hans-passant</link>
    <location>Madison, WI</location>
    <year_rep>3,688</year_rep>
    <total_rep>672,118</total_rep>
    <tag1>c#</tag1>
    <tag2>.net</tag2>
    <tag3>winforms</tag3>
  </topusers>
  <topusers>
    <user>Jonathan Leffler</user>
    <link>http://www.stackoverflow.com//users/15168/jonathan-leffler</link>
    <location>California, USA</location>
    <year_rep>3,649</year_rep>
    <total_rep>455,157</total_rep>
    <tag1>c</tag1>
    <tag2>bash</tag2>
    <tag3>unix</tag3>
  </topusers>
  <topusers>
    <user>paxdiablo</user>
    <link>http://www.stackoverflow.com//users/14860/paxdiablo</link>
    <location></location>
    <year_rep>3,636</year_rep>
    <total_rep>507,043</total_rep>
    <tag1>c</tag1>
    <tag2>c++</tag2>
    <tag3>bash</tag3>
  </topusers>
  <topusers>
    <user>Pranav C Balan</user>
    <link>http://www.stackoverflow.com//users/3037257/pranav-c-balan</link>
    <location>Ramanthali, Kannur, Kerala, India</location>
    <year_rep>3,604</year_rep>
    <total_rep>64,476</total_rep>
    <tag1>javascript</tag1>
    <tag2>jquery</tag2>
    <tag3>html</tag3>
  </topusers>
  <topusers>
    <user>Suragch</user>
    <link>http://www.stackoverflow.com//users/3681880/suragch</link>
    <location>Hohhot, China</location>
    <year_rep>3,580</year_rep>
    <total_rep>71,032</total_rep>
    <tag1>swift</tag1>
    <tag2>ios</tag2>
    <tag3>android</tag3>
  </topusers>
</stackoverflow>

Metodi Python

import xml.etree.ElementTree as et
import pandas as pd
from io import StringIO
from lxml import etree as lxet

def read_xml_iterfind():
    tree = et.parse('Input.xml')

    data = []
    inner = {}
    for el in tree.iterfind('./*'):
        for i in el.iterfind('*'):
            inner[i.tag] = i.text
        data.append(inner)
        inner = {}

    df = pd.DataFrame(data)

def read_xml_iterparse():
    data = []
    inner = {}
    i = 1
    for (ev, el) in et.iterparse(path):
        if i <= 2:
           first_tag = el.tag

        if el.tag == first_tag and len(inner) != 0:
            data.append(inner)            
            inner = {}

        if el.text is not None and len(el.text.strip()) > 0:
            inner[el.tag] = el.text
    i += 1

    df = pd.DataFrame(data)    

def read_xml_lxml_xpath():     
    tree = lxet.parse('Input.xml')

    data = []
    inner = {}
    for el in tree.xpath('/*/*'):
        for i in el:
            inner[i.tag] = i.text
        data.append(inner)
        inner = {}

    df = pd.DataFrame(data)

def read_xml_lxml_xsl():     
    xml = lxet.parse('Input.xml')

    xslstr = '''
    <xsl:transform xmlns:xsl="http://www.w3.org/1999/XSL/Transform" version="1.0">
        <xsl:output version="1.0" encoding="UTF-8" indent="yes"  method="text"/>
        <xsl:strip-space elements="*"/>

        <!-- HEADERS -->
        <xsl:template match = "/*">
            <xsl:for-each select="*[1]/*">
              <xsl:value-of select="local-name()" />
                <xsl:choose>
                   <xsl:when test="position() != last()">
                      <xsl:text>,</xsl:text>
                   </xsl:when>
                   <xsl:otherwise>
                      <xsl:text>&#xa;</xsl:text>
                   </xsl:otherwise>                              
                </xsl:choose>   
            </xsl:for-each>
            <xsl:apply-templates/>
        </xsl:template>

        <!-- DATA ROWS (COMMA-SEPARATED) -->
        <xsl:template match="/*/*" priority="2">    
            <xsl:for-each select="*">
              <xsl:if test="position() = 1">
                   <xsl:text>&quot;</xsl:text>
              </xsl:if>
              <xsl:value-of select="." />
                <xsl:choose>
                   <xsl:when test="position() != last()">
                      <xsl:text>&quot;,&quot;</xsl:text>
                   </xsl:when>
                   <xsl:otherwise>
                      <xsl:text>&quot;&#xa;</xsl:text>
                   </xsl:otherwise>                              
                </xsl:choose>
            </xsl:for-each>
        </xsl:template>

    </xsl:transform>
    '''
    xsl = lxet.fromstring(xslstr)

    transform = lxet.XSLT(xsl)
    newdom = transform(xml)

    df = pd.read_csv(StringIO(str(newdom)))

Tempistiche (con XML e XML correnti con 25 volte i figli (ad esempio, 900 record utente StackOverflow)

# SHORTER FILE
python -mtimeit -s'import readxml_test_runs as test' 'test.read_xml_iterfind()'
100 loops, best of 3: 3.87 msec per loop

python -mtimeit -s'import readxml_test_runs as test' 'test.read_xml_iterparse()'
100 loops, best of 3: 5.5 msec per loop

python -mtimeit -s'import readxml_test_runs as test' 'test.read_xml_lxml_xpath()'
100 loops, best of 3: 3.86 msec per loop

python -mtimeit -s'import readxml_test_runs as test' 'test.read_xml_lxml_xsl()'
100 loops, best of 3: 5.68 msec per loop

# LARGER FILE
python -mtimeit -n'100' -s'import readxml_test_runs as test' 'test.read_xml_iterfind()'
100 loops, best of 3: 36 msec per loop

python -mtimeit -n'100' -s'import readxml_test_runs as test' 'test.read_xml_iterparse()'
100 loops, best of 3: 78.9 msec per loop

python -mtimeit -n'100' -s'import readxml_test_runs as test' 'test.read_xml_lxml_xpath()'
100 loops, best of 3: 32.7 msec per loop

python -mtimeit -n'100' -s'import readxml_test_runs as test' 'test.read_xml_lxml_xsl()'
100 loops, best of 3: 51.4 msec per loop

PRESTAZIONI: come spieghi l'iterparse più lento spesso consigliato per file più grandi poiché il file viene analizzato in modo iterativo? È in parte dovuto ai controlli logici if?

Presumo che più codice python lo renderebbe più lento, poiché il codice python viene valutato ogni volta. Hai provato un compilatore JIT come pypy?

Se rimuovo ie uso first_tagsolo, sembra essere un po 'più veloce, quindi sì, è in parte dovuto ai controlli logici if:

def read_xml_iterparse2(path):
    data = []
    inner = {}
    first_tag = None
    for (ev, el) in et.iterparse(path):
        if not first_tag:
           first_tag = el.tag

        if el.tag == first_tag and len(inner) != 0:
            data.append(inner)            
            inner = {}

        if el.text is not None and len(el.text.strip()) > 0:
            inner[el.tag] = el.text

    df = pd.DataFrame(data)    

%timeit read_xml_iterparse(path)
# 10 loops, best of 5: 33 ms per loop
%timeit read_xml_iterparse2(path)
# 10 loops, best of 5: 23 ms per loop

Non ero sicuro di aver compreso lo scopo dell'ultimo ifcontrollo, ma non sono nemmeno sicuro del motivo per cui vorresti perdere gli elementi di soli spazi bianchi. La rimozione dell'ultimo ifriduce costantemente un po 'di tempo:

def read_xml_iterparse3(path):
    data = []
    inner = {}
    first_tag = None
    for (ev, el) in et.iterparse(path):
        if not first_tag:
           first_tag = el.tag

        if el.tag == first_tag and len(inner) != 0:
            data.append(inner)            
            inner = {}

        inner[el.tag] = el.text

    df = pd.DataFrame(data)    

%timeit read_xml_iterparse(path)
# 10 loops, best of 5: 34.4 ms per loop
%timeit read_xml_iterparse2(path)
# 10 loops, best of 5: 24.5 ms per loop
%timeit read_xml_iterparse3(path)
# 10 loops, best of 5: 20.9 ms per loop

Ora, con o senza questi miglioramenti delle prestazioni, la tua versione iterparse sembra produrre un dataframe extra-large. Qui sembra essere una versione funzionante e veloce:

def read_xml_iterparse5(path):
    data = []
    inner = {}
    for (ev, el) in et.iterparse(path):
        # /ending parents trigger a new row, and in our case .text is \n followed by spaces.  it would be more reliable to pass 'topusers' to our read_xml_iterparse5 as the .tag to check
        if el.text and el.text[0] == '\n':
            # ignore /stackoverflow
            if inner:
                data.append(inner)
                inner = {}
        else:
            inner[el.tag] = el.text

    return pd.DataFrame(data)    

print(read_xml_iterfind(path).shape)
# (900, 8)
print(read_xml_iterparse(path).shape)
# (7050, 8)
print(read_xml_lxml_xpath(path).shape)
# (900, 8)
print(read_xml_lxml_xsl(path).shape)
# (900, 8)
print(read_xml_iterparse5(path).shape)
# (900, 8)
%timeit read_xml_iterparse5(path)
# 10 loops, best of 5: 20.6 ms per loop

MEMORIA: la memoria della CPU è correlata ai tempi nelle chiamate I / O? XSLT e XPath 1.0 tendono a non scalare bene con documenti XML di dimensioni maggiori poiché l'intero file deve essere letto in memoria per essere analizzato.

Non sono del tutto sicuro di cosa intendi per "chiamate I / O" ma se il tuo documento è abbastanza piccolo da stare nella cache, allora tutto sarà molto più veloce in quanto non rimuoverà molti altri elementi dalla cache.

STRATEGIA: l'elenco dei dizionari è una strategia ottimale per la chiamata a Dataframe ()? Guarda queste interessanti risposte: versione del generatore e una versione definita dall'utente iterwalk. Entrambi gli elenchi di upcast su dataframe.

Gli elenchi utilizzano meno memoria, quindi a seconda di quante colonne hai, potrebbe fare una notevole differenza. Naturalmente, questo richiede quindi che i tag XML siano in un ordine coerente, come sembrano essere. La DataFrame()chiamata dovrebbe anche fare meno lavoro, poiché non deve cercare le chiavi nel dict su ogni riga, per capire quale colonna se per quale valore.