Exemple #1
0
def delete_no_checkpoints(parent):
    if os.path.isdir(parent):
        document = []
        for p in os.listdir(parent):
            try:
                document.append(p)
            except:
                print("not document~")
            d = os.path.join(parent, p)
            # print(d)
            if (os.path.isdir(d) == True):
                delete_no_checkpoints(d)
        print("----")

        print("document:", document)

        if (len(document) > 0):
            old_path_name = parent.split("\\")[-1]
            print("old_path_name:", old_path_name)
            # change = input("是否需要删除(y/n)?")
            # if (change == 'y'):
            try:
                # 判断后缀是否在集合里,如果没有后缀,那么就是文件夹了
                if 'pth' not in document and 'pt' not in document and 'checkpoint' not in document and 'progress.txt' in document:
                    for doc in document:
                        os.remove(os.path.join(old_path_name, doc))
                    shutil.retree(old_path_name)
                    print("old_path_name:", old_path_name)
                    print("删除成功!")
            except Exception as e:
                print("delete e:", e)
Exemple #2
0
def rmr(**kwargs):
    if os.path.isdir(kwargs['params']):
        shutil.retree(kwargs['params'])  # if it's a path
    elif os.path.isfile(kwargs['params']):
        os.remove(kwargs['params'])  #if it's a file
    else:
        print("not avalable to remove")
Exemple #3
0
		'MPICH2':'http://www.mcs.anl.gov/research/projects/mpich2/downloads/tarballs/mpich2-current.tar.gz',
		'FFTW3':'ftp://ftp.fftw.org/pub/fftw/fftw-3.3.2.tar.gz',
		'LAPACK':'http://www.netlib.org/lapack/lapack-3.4.1.tgz',
		'CBLAS':'http://www.netlib.org/clapack/cblas.tgz',
		'WCSLIB':'ftp://ftp.atnf.csiro.au/pub/software/wcslib/wcslib.tar.bz2',
		'NETCDF':'http://www.unidata.ucar.edu/downloads/netcdf/ftp/netcdf-4.2.1.1.tar.gz'
		}

print URL
SUB_DIR = {}
TAR_DIR = MAIN_DIR+'/tarballs'
for k,v in URL.items():
	urllib.urlretrieve(v,TAR_DIR)
	tar = tarfile.open(v.split('/')[-1])
	if tar.member[0].isdir():
		tar.extractall(path=MAIN_DIR)
		SUB_DIR.update({k,MAIN_DIR+'/'+tar.members[0].name})
	else:
		SUB_DIR.update({k,MAIN_DIR+k})
		os.makedirs(SUB_DIR)
		tar.extractall(path=SUB_DIR)
	shutil.retree(tar.name)
	tar.close()
print SUB_DIR	
	


#os.system('git clone [email protected]:/MWA_Tools')
#os.system('git clone [email protected]:/RTS')
#os.system('git clone [email protected]:/CASA_Cals')
def build_and_run(code, lang):
    result = {'build': None, 'run': None, 'error': None}

    source_file_parent_dir_name = uuid.uuid4()

    source_file_host_dir = "%s/%s" % (TEMP_BUILD_DIR,
                                      source_file_parent_dir_name)

    source_file_guest_dir = "/test/%s" % (source_file_parent_dir_name)

    make_dir(source_file_host_dir)

    with open("%s/%s" % (source_file_host_dir, SOURCE_FILE_NAMES[lang]),
              'w') as source_file:
        source_file.write(code)

    try:
        client.containers.run(image=IMAGE_NAME,
                              command="%s %s" %
                              (BUILD_COMMANDS[lang], SOURCE_FILE_NAMES[lang]),
                              volumes={
                                  source_file_host_dir: {
                                      'bind': source_file_guest_dir,
                                      'mode': 'rw'
                                  }
                              },
                              working_dir=source_file_guest_dir)

        print("source built")

        result['build'] = 'ok'

    except ContainerError as e:
        result['build'] = str(e.stderr, 'utf-8')
        shutil.rmtree(source_file_host_dir)

        return result

    try:
        log = client.containers.run(
            image=IMAGE_NAME,
            command="%s %s" % (EXECUTE_COMMANDS[lang], BINARY_NAMES[lang]),
            volumes={
                source_file_host_dir: {
                    'bind': source_file_guest_dir,
                    'mode': 'rw'
                }
            },
            working_dir=source_file_guest_dir)

        log = str(log, 'utf-8')

        print(log)

        result['run'] = log

    except ContainerError as e:
        result['run'] = str(e.stderr, 'utf-8')
        shutil.retree(source_file_host_dir)

        return result

    shutil.rmtree(source_file_host_dir)

    return result
Exemple #5
0
# 函数实现:os.mkdirs(name,mode = 0o777)    推荐
import os
os.mkdirs(r'D:\demo\mr\demo\Navigator97')

# 删除目录
# 语法:os.rmdir(path(相对路径或者绝对路径))    删除空目录
import os
if not os.path.exists(r'D:\demo\mr\demo\Navigator97'):
    os.rmdir(r'D:\demo\mr\demo\Navigator97')  # 删除目录
    print("目录删除成功")
else:
    print("目录不存在!")
# 删除不为空的目录:需要使用Python内置的shutil模块
# 语法:shutil.rmtree(path)
import shutil
shutil.retree(r'D:\demo')  # 删除不为空的目录

# 遍历目录
# 语法:os.walk(top[, topdown(确定遍历顺序,True自上而下遍历,False相反)][,onerror指定错误处理方式,默认为忽略][,followlinks(True指定在支持的系统上访问由符号链接(软链接)指向的目录)])
# 返回值:元组生成器对象(diepath字符串,dirnames列表,filenames列表)
import os
path = os.walk(r'H:\Python Program')
for p in path:
    print(p, '\n')
# 实例:遍历指定目录
import os
path = r'C:/Python'
print('【', path, "】目录下包含的文件和目录:")
for root, dirs, files in os.walk(path, topdown=True):  # 遍历指定目录
    for name in dirs:
        print(os.path.join(root, name))  # 输出遍历到的目录
Exemple #6
0
import os
import sys
import shutil
path=os.path.dirname(os.path.abspath(__file__))
for models in ['srgcn','gcn']:
    modelpath=os.path.join(path,model)
    for dirname in next(os.walk(modelpath))[1]:
        if 'label' in dirname:
            shutil.retree(os.path.join(modelpath,dirname))
Exemple #7
0
def  clean_work_dir(solution_id):
	dir_name = os.path.join(config.work_dir, str(solution_id))
	shutil.retree(dir_name)
Exemple #8
0
import tensorflow as tf
import numpy as np
import os
import shutil

decode = False
resume_training = True

save_dir = '_' + __file__[__file__.rfind('/') + 1:__file__.rfind('.')]

if (not decode) and (not resume_training):
    if os.path.exists(save_dir):
        shutil.retree(save_dir)
    os.makedirs(save_dir)

graph = tf.Graph()
with graph.as_default():
    with tf.variable_scope('variable'):
        w = tf.get_variable(name='w',
                            initializer=tf.constant([0]),
                            dtype=tf.int32)
        rand_inc = tf.random_uniform(minval=1,
                                     maxval=3,
                                     dtype=tf.int32,
                                     shape=[1])
        update_w = tf.assign_add(w, rand_inc)
    saver = tf.train.Saver(tf.trainable_variables(), max_to_keep=30)

    if decode:
        with tf.Session(graph=graph) as sess:
            ckpt = tf.train.get_checkpoint_state(save_dir)