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我想将大量的xml文件转换成清晰的csv文件，我已经将squawka.com刮掉了。我发现了一个脚本，据说这样做，但它总是提出这样的错误：Python IndexError with pandas and multiprocessing
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "squawka\utils.py", line 227, in export_all_stats
df = pd.concat(pool.imap(partial_loader, xml_paths), axis=0, ignore_index=True)
File "C:\Python27\lib\site-packages\pandas\tools\merge.py", line 812, in concat
copy=copy)
File "C:\Python27\lib\site-packages\pandas\tools\merge.py", line 842, in __init__
objs = list(objs)
File "C:\Python27\lib\multiprocessing\pool.py", line 668, in next
raise value
IndexError: list index out of range
我想从这个脚本中使用函数export_all_stats：
import gc
import glob
import logging
import multiprocessing
import numpy as np
import os
import pandas as pd
import re
import warnings
from dateutil import parser
from functools import partial
from lxml import etree
COMPETITIONS = {
4: 'World Cup',
5: 'Champions League',
6: 'Europa League',
8: 'English Barclays Premier League',
9: 'Dutch Eredivisie',
10: 'Football League Championship',
21: 'Italian Serie A',
22: 'German Bundesliga',
23: 'Spanish La Liga',
24: 'French Ligue 1',
98: 'US Major League Soccer',
114: 'Turkish Super Lig',
129: 'Russian Premier League',
199: 'Mexican Liga MX - Apertura',
214: 'Australian A-League',
363: 'Brazilian Serie A',
385: 'Mexican Liga MX - Clausura',
}
TIME_SLICE_EVENTS = [
'action_areas',
'all_passes',
'balls_out',
'blocked_events',
'cards',
'clearances',
'corners',
'crosses',
'extra_heat_maps',
'fouls',
'goal_keeping',
'goals_attempts',
'headed_duals',
'interceptions',
'keepersweeper',
'offside',
'oneonones',
'setpieces',
'tackles',
'takeons',
]
ALL_STATISTICS = sorted(TIME_SLICE_EVENTS + ['players', 'teams'])
logger = logging.getLogger()
handler = logging.StreamHandler()
formatter = logging.Formatter('%(asctime)s %(name)-12s %(levelname)-8s %(message)s')
handler.setFormatter(formatter)
logger.addHandler(handler)
logger.setLevel(logging.DEBUG)
class SquawkaReport:
"""Squawka match report object.
:param path: Path to XML-file to generate match report from.
"""
def __init__(self, path):
self.__time_slice_events = TIME_SLICE_EVENTS
self.path = path
self.xml = self.read_xml(path)
# See: https://stackoverflow.com/questions/10967551/how-do-i-dynamically-create-properties-in-python
def __getattr__(self, name):
if name in self.__time_slice_events:
return self._parse_timeslice(name)
else:
msg = "'{0}' object has no attribute '{1}'"
raise AttributeError(msg.format(type(self).__name__, name))
@staticmethod
def read_xml(path):
"""Read XML file.
:param path: Path to XML-file.
:return: XML tree.
"""
with open(path, 'r') as f:
data = f.read()
xml = etree.fromstring(data)
return xml
def _parse_timeslice(self, filter_type):
xpath = '/squawka/data_panel/filters/{filter_type}/time_slice/event'
return self._get_elements(xpath.format(filter_type=filter_type))
def _get_elements(self, xpath):
elements = self.xml.xpath(xpath)
if elements:
return self._parse_elements(elements)
else:
return None
def _parse_elements(self, elements):
parsed = [dict({c.tag: c.text for c in
e.getchildren()}.items() + e.attrib.items())
for e in elements]
return parsed
@property
def competition(self):
return re.findall("/(.*)_\d*.xml", self.path)[0]
@property
def filters(self):
filters_element = self.xml.xpath('/squawka/data_panel/filters')
if filters_element:
return [ch.tag for ch in filters_element[0].getchildren()]
# Some match reports don't have data.
else:
return None
@property
def kickoff(self):
date = self.xml.xpath("/squawka/data_panel/game/kickoff/text()")[0]
return parser.parse(date).strftime('%Y-%m-%d %H:%M:%S %z')
@property
def match_id(self):
return int(re.findall("/.*_(\d+).xml", self.path)[0])
@property
def name(self):
return self.xml.xpath("/squawka/data_panel/game/name/text()")[0]
@property
def players(self):
# TODO: Remove non-player elements
xpath = '/squawka/data_panel/players/player'
return self._get_elements(xpath)
@property
def teams(self):
xpath = '/squawka/data_panel/game/team'
return self._get_elements(xpath)
@property
def venue(self):
return self.xml.xpath("/squawka/data_panel/game/venue/text()")[0]
@property
def match_info(self):
info = ({
'competition': self.competition,
'kickoff': self.kickoff,
'match_id': self.match_id,
'name': self.name,
'venue': self.venue,
})
for team in self.teams:
for k in ['id', 'short_name']:
info['_'.join((team['state'], k))] = team[k]
return info
def stats_from_file(path, statistic, convert=True):
"""Load data for a statistic from file.
:param path: Path to file.
:param statistic: Statistic to load (e.g. 'goals_attempts', 'cards').
:param convert: Process and clean the data (boolean)
:return pd.DataFrame with data
"""
report = SquawkaReport(path)
return stats_from_report(report, statistic, convert)
def stats_from_report(report, statistic, convert=True):
"""Load data for a statistic from a SquawkaReport object.
:param report: SquawkaReport object
:param statistic: Statistic to load (e.g. 'goals_attempts', 'cards').
:param convert: Process and clean the data (boolean)
:return pd.DataFrame with data
"""
stats = pd.DataFrame(getattr(report, statistic))
stats['competition'] = report.competition
stats['kickoff'] = report.kickoff
stats['match_id'] = report.match_id
if convert:
return convert_export(stats)
else:
return stats
def export_all_stats(xml_dir, out_dir, statistics=ALL_STATISTICS, convert=True, n_jobs=None,
sequential=('all_passes', 'extra_heat_maps')):
"""Export all statistics from all XML-files in a folder to CSV.
:param xml_dir: Path to folder containing XML-files
:param out_dir: Path to folder to save output to
:param statistics: Statistics to export
:param convert: Process and clean the data (boolean)
:param n_jobs: Number of processes to use
:param sequential: Iterable with statistics to process sequentially (for memory-intensive stats)
"""
xml_paths = glob.glob(os.path.join(xml_dir, '*.xml'))
if n_jobs is None:
n_jobs = multiprocessing.cpu_count() - 1
if not os.path.exists(out_dir):
os.makedirs(out_dir)
pool = multiprocessing.Pool(n_jobs)
for statistic in statistics:
if statistic in sequential:
df = pd.concat((_load_xml(p, statistic) for p in xml_paths), axis=0, ignore_index=True)
else:
partial_loader = partial(_load_xml, statistic=statistic)
df = pd.concat(pool.imap(partial_loader, xml_paths), axis=0, ignore_index=True)
if convert:
df = convert_export(df)
save_path = os.path.join(out_dir, '{}.csv'.format(statistic))
df.to_csv(save_path, index=False, encoding='utf8')
logger.debug("Exported %s to %s", statistic, save_path)
def _load_xml(path, statistic):
"""Load XML files ignoring etree.XMLSyntaxErrors.
:param path: Path to file.
:param statistic: Statistic to load (e.g. 'goals_attempts', 'cards').
:return: XML tree (or None on etree.XMLSyntaxError).
"""
try:
return stats_from_file(path, statistic)
except etree.XMLSyntaxError:
msg = "XML error loading {}, skipping it...".format(path)
warnings.warn(msg, RuntimeWarning)
def convert_export(df):
"""Convert a statistics export.
:param df: pd.DataFrame with statistics (see e.g. stats_from_file())
:return: processed pd.DataFrame
"""
def parse_indicator(s, indicator):
return s.notnull() & (s == indicator) # Nulls are interpreted as False
convert_cols = {
'id': 'int',
'match_id': 'int',
'mins': 'int',
'minsec': 'int',
'secs': 'int',
'team_id': 'int'
}
coordinate_cols = [
'end',
'loc',
'middle',
'start',
]
indicator_cols = {
'is_own': 'yes',
'headed': 'true', # Note: ignores all falses
'shot': 'true', # Note: ignores all falses
}
# Convert strings to ints.
for col in df.columns.intersection(convert_cols):
df[col] = df[col].replace('', -1)
df.loc[df[col].isnull(), col] = -1
df[col] = df[col].astype(convert_cols[col])
# Convert indicator cols.
for col in df.columns.intersection(indicator_cols):
df[col] = parse_indicator(df[col], indicator_cols[col])
# Convert coordinate cols.
for col in df.columns.intersection(coordinate_cols):
df[[col + '_x', col + '_y']] = split_coordinates(df[col])
df.drop(col, axis=1, inplace=True)
return df
def split_coordinates(s):
"""Split Series containing strings with coordinates into a DataFrame.
:param s: pd.Series
:return: pd.DataFrame with columns 'x' and 'y'
"""
if s.notnull().all():
concatenated = s
else:
concatenated = s.copy()
concatenated.loc[concatenated.isnull()] = ','
split = pd.DataFrame(concatenated.str.split(',').tolist(), columns=['x', 'y'], dtype=float)
return split.replace('', np.nan)
我很新的这一点，所以我不知道发生了什么问题。我试图谷歌它，但还没有找到答案。有人可以帮帮我吗？