I am writing a test that needs to read a file. I wrote the following function:
upload_file = (file_name, input_class) ->
await browser.executeScript("window.document.getElementsByClassName('" +
input_class + "')[0].style.display = 'block'", [])
file_path = path.join(FILE_PATH, file_name)
await $('input.' + input_class).then((res) ->
return res.setValue(file_path)
)
However, the test fails to test the script
In the code that is executed after the file is uploaded to the site, I output the file that was read. All information is correct except file size which is 0
Please help me
Related
I would like to download a picture into a blob folder.
Before that I need to create the folder first.
Below codes are what I am doing.
The issue is the folder needs time to be created.
When it comes to with open(abs_file_name, "wb") as f:
it can not find the folder.
I am wondering whether there is an 'await' to get to know the completion of the folder creation, then do the write operation.
for index, row in data.iterrows():
url = row['Creatives']
file_name = url.split('/')[-1]
r = requests.get(url)
abs_file_name = lake_root + file_name
dbutils.fs.mkdirs(abs_file_name)
if r.status_code == 200:
with open(abs_file_name, "wb") as f:
f.write(r.content)
The final sub folder will not be created when using dbutils.fs.mkdirs() on blob storage.
It creates a file with the final sub folder name which would be considered as a directory, but it is not a directory. Look at the following demonstration:
dbutils.fs.mkdirs('/mnt/repro/s1/s2/s3.csv')
When I try to open this file, the error says that this is a directory.
This might be the issue with the code. So, try using the following code instead:
for index, row in data.iterrows():
url = row['Creatives']
file_name = url.split('/')[-1]
r = requests.get(url)
abs_file_name = lake_root + 'fail' #creates the fake directory (to counter the problem we are facing above)
dbutils.fs.mkdirs(abs_file_name)
if r.status_code == 200:
with open(lake_root + file_name, "wb") as f:
f.write(r.content)
I now: the automatic token refreshing is not a new topic.
This is the use case that generate my problem: let's say that we want extract data from Dropbox. Below you can find the code: for the first time works perfectly: in fact 1) the user goes to the generated link; 2) after allow the app coping and pasting the authorization code in the input box.
The problem arise when some hours after the user wants to do the same operation. How to avoid or by-pass the newly generation of authorization code and go straight to the operation?enter code here
As you can see in the code in a short period is possible reinject the auth code inside the code (commented in the code). But after 1 hour or more this is not loger possible.
Any help is welcome.
#!/usr/bin/env python3
import dropbox
from dropbox import DropboxOAuth2FlowNoRedirect
'''
Populate your app key in order to run this locally
'''
APP_KEY = ""
auth_flow = DropboxOAuth2FlowNoRedirect(APP_KEY, use_pkce=True, token_access_type='offline')
target='/DVR/DVR/'
authorize_url = auth_flow.start()
print("1. Go to: " + authorize_url)
print("2. Click \"Allow\" (you might have to log in first).")
print("3. Copy the authorization code.")
auth_code = input("Enter the authorization code here: ").strip()
#auth_code="3NIcPps_UxAAAAAAAAAEin1sp5jUjrErQ6787_RUbJU"
try:
oauth_result = auth_flow.finish(auth_code)
except Exception as e:
print('Error: %s' % (e,))
exit(1)
with dropbox.Dropbox(oauth2_refresh_token=oauth_result.refresh_token, app_key=APP_KEY) as dbx:
dbx.users_get_current_account()
print("Successfully set up client!")
for entry in dbx.files_list_folder(target).entries:
print(entry.name)
def dropbox_list_files(path):
try:
files = dbx.files_list_folder(path).entries
files_list = []
for file in files:
if isinstance(file, dropbox.files.FileMetadata):
metadata = {
'name': file.name,
'path_display': file.path_display,
'client_modified': file.client_modified,
'server_modified': file.server_modified
}
files_list.append(metadata)
df = pd.DataFrame.from_records(files_list)
return df.sort_values(by='server_modified', ascending=False)
except Exception as e:
print('Error getting list of files from Dropbox: ' + str(e))
#function to get the list of files in a folder
def create_links(target, csvfile):
filesList = []
print("creating links for folder " + target)
files = dbx.files_list_folder('/'+target)
filesList.extend(files.entries)
print(len(files.entries))
while(files.has_more == True) :
files = dbx.files_list_folder_continue(files.cursor)
filesList.extend(files.entries)
print(len(files.entries))
for file in filesList :
if (isinstance(file, dropbox.files.FileMetadata)) :
filename = file.name + ',' + file.path_display + ',' + str(file.size) + ','
link_data = dbx.sharing_create_shared_link(file.path_lower)
filename += link_data.url + '\n'
csvfile.write(filename)
print(file.name)
else :
create_links(target+'/'+file.name, csvfile)
#create links for all files in the folder belgeler
create_links(target, open('links.csv', 'w', encoding='utf-8'))
listing = dbx.files_list_folder(target)
#todo: add implementation for files_list_folder_continue
for entry in listing.entries:
if entry.name.endswith(".pdf"):
# note: this simple implementation only works for files in the root of the folder
res = dbx.sharing_get_shared_links(
target + entry.name)
#f.write(res.content)
print('\r', res)
I am trying to use the multipart file with the file as a variable, my feature looks like below
Feature: Test feature
Background:
* def JavaUtil = Java.type('com.intuit.karate.demo.util.JavaUtil')
* def file = JavaUtil.createBatchFile("1003");
# Scenario: test one
# * print " this is the first test: "
* url appUrl + '/api/partner/v1/bulk/'
* print 'file :', file
Given path 'jobs', jobId, 'batches'
And multipart file newBatchInfo = { read: file}
When method post
Then status 200
When the code executes the file has the right value but the multipart file does not accept the file variable which has the absolute path.
Is this the right usage? If there are some docs around this, can someone point me. Thanks.
This is my output
There is a file: prefix, which you can use in cases like this, where you generate a file. I recommend you generate files into target when using Maven for e.g.
Refer docs: https://github.com/intuit/karate#reading-files
Also note that you should use embedded expressions:
* def file = 'file:' + JavaUtil.createBatchFile("1003")
# ...
* And multipart file newBatchInfo = { read: '#(file)' }
My requirement is to iterate over a CSV Data Set Config in Apache JMeter with a varying starting index. Let us assume I have started a test plan in JMeter today and my CSV file has 8 variables. The first time my sampler will run from 1st row to 8th row. The next time I will start running my test plan I want sampler to pick values from 2nd index to 8th index. In this manner, I want to iterate over CSV file using CSV Data set config.
I am able to initialize a counter for every test run in Apache JMeter using setUp ThreadGroup and tearDown Thread group. I am able to extract the same using _P(count) in JMeter.
In setUp Thread group I have included JSR 223 Sampler and written a script like
def file = new File('number')
if (!file.exists() || !file.canRead()) {
number = '1'
}
else {
number = file.text
}
props.put('number', number as String)
In tearDown Thread Group the JSR223 Sampler has a script like
def number = props.get('number') as int
number++
new File('number').text = number
I want to loop over my CSV data set config file with the counter through properties file( which is getting incremented by 1 for every test run)
Please check the below plan:-
Input CSV example:-
If Controller has the below code:-
${__groovy(vars.get('Used').take(1)!='Y')}
In JSR223 post processor, I have the below code:-
def inputFile = new File("C:\\Path\\toFile\\Excel\\OutputCSV.csv")
def lines = inputFile.readLines()
boolean isWrite = false;
lines.each { String line ->
if(line.contains('Used'))
{
inputFile.write(line + '\n')
}
else
{
if(line.startsWith('Y'))
{
inputFile.append(line + '\n')
}
else if (!isWrite)
{
inputFile.append('Y' + line + '\n')
isWrite = true;
}
else
{
inputFile.append(line + '\n')
}
}
}
First Run output:-
Second Run output:-
As you can see, in first run sample 1 execute 4 time and in 2nd it is executed 3 times.
This is not the nicest or best code, just first try.
Please check if helps.
I want to combine two requests to the Google cloud text-to-speech API in a single mp3 output. The reason I need to combine two requests is that the output should contain two different languages.
Below code works fine for many language pair combinations, but unfortunately not for all. If I request e.g. a sentence in English and one in German and combine them everything works. If I request one in English and one in Japanes I can't combine the two files in a single output. The output only contains the first sentence and instead of the second sentence, it outputs silence.
I tried now multiple ways to combine the two outputs but the result stays the same. The code below should show the issue.
Please run the code first with:
python synthesize_bug.py --t1 'Hallo' --code1 de-De --t2 'August' --code2 de-De
This works perfectly.
python synthesize_bug.py --t1 'Hallo' --code1 de-De --t2 'こんにちは' --code2 ja-JP
This doesn't work. The single files are ok, but the combined files contain silence instead of the Japanese part.
Also, if used with two Japanes sentences everything works.
I already filed a bug report at Google with no response yet, but maybe it's just me who is doing something wrong here with encoding assumptions. Hope someone has an idea.
#!/usr/bin/env python
import argparse
# [START tts_synthesize_text_file]
def synthesize_text_file(text1, text2, code1, code2):
"""Synthesizes speech from the input file of text."""
from apiclient.discovery import build
import base64
service = build('texttospeech', 'v1beta1')
collection = service.text()
data1 = {}
data1['input'] = {}
data1['input']['ssml'] = '<speak><break time="2s"/></speak>'
data1['voice'] = {}
data1['voice']['ssmlGender'] = 'FEMALE'
data1['voice']['languageCode'] = code1
data1['audioConfig'] = {}
data1['audioConfig']['speakingRate'] = 0.8
data1['audioConfig']['audioEncoding'] = 'MP3'
request = collection.synthesize(body=data1)
response = request.execute()
audio_pause = base64.b64decode(response['audioContent'].decode('UTF-8'))
raw_pause = response['audioContent']
ssmlLine = '<speak>' + text1 + '</speak>'
data1 = {}
data1['input'] = {}
data1['input']['ssml'] = ssmlLine
data1['voice'] = {}
data1['voice']['ssmlGender'] = 'FEMALE'
data1['voice']['languageCode'] = code1
data1['audioConfig'] = {}
data1['audioConfig']['speakingRate'] = 0.8
data1['audioConfig']['audioEncoding'] = 'MP3'
request = collection.synthesize(body=data1)
response = request.execute()
# The response's audio_content is binary.
with open('output1.mp3', 'wb') as out:
out.write(base64.b64decode(response['audioContent'].decode('UTF-8')))
print('Audio content written to file "output1.mp3"')
audio_text1 = base64.b64decode(response['audioContent'].decode('UTF-8'))
raw_text1 = response['audioContent']
ssmlLine = '<speak>' + text2 + '</speak>'
data2 = {}
data2['input'] = {}
data2['input']['ssml'] = ssmlLine
data2['voice'] = {}
data2['voice']['ssmlGender'] = 'MALE'
data2['voice']['languageCode'] = code2 #'ko-KR'
data2['audioConfig'] = {}
data2['audioConfig']['speakingRate'] = 0.8
data2['audioConfig']['audioEncoding'] = 'MP3'
request = collection.synthesize(body=data2)
response = request.execute()
# The response's audio_content is binary.
with open('output2.mp3', 'wb') as out:
out.write(base64.b64decode(response['audioContent'].decode('UTF-8')))
print('Audio content written to file "output2.mp3"')
audio_text2 = base64.b64decode(response['audioContent'].decode('UTF-8'))
raw_text2 = response['audioContent']
result = audio_text1 + audio_pause + audio_text2
with open('result.mp3', 'wb') as out:
out.write(result)
print('Audio content written to file "result.mp3"')
raw_result = raw_text1 + raw_pause + raw_text2
with open('raw_result.mp3', 'wb') as out:
out.write(base64.b64decode(raw_result.decode('UTF-8')))
print('Audio content written to file "raw_result.mp3"')
# [END tts_synthesize_text_file]ls
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument('--t1')
parser.add_argument('--code1')
parser.add_argument('--t2')
parser.add_argument('--code2')
args = parser.parse_args()
synthesize_text_file(args.t1, args.t2, args.code1, args.code2)
You can find the answer here:
https://issuetracker.google.com/issues/120687867
Short answer: It's not clear why it is not working, but Google suggests a workaround to first write the files as .wav, combine and then re-encode the result to mp3.
I have managed to do this in NodeJS with just one function (idk how optimal is it, but at least it works). Maybe you could take inspiration from it
I have used memory-streams dependency from npm
var streams = require('memory-streams');
function mergeAudios(audios) {
var reader = new streams.ReadableStream();
var writer = new streams.WritableStream();
audios.forEach(element => {
if (element instanceof streams.ReadableStream) {
element.pipe(writer)
}
else {
writer.write(element)
}
});
reader.append(writer.toBuffer())
return reader
}
Input parameter is a list which contain ReadableStream or responce.audioContent from synthesizeSpeech operation. If it is readablestream, it uses pipe operation, if it is audiocontent, it uses write method. At the end all content is passed into an readabblestream.