Ran the following code in Colab:
uploaded = files.upload()
Clicked "Choose Files" and selected the csv I want to upload.
But the file is not being uploaded. It worked once before but not again. All videos I watch about how to upload csv's locally, once the file is selected, Colab uploads the file immediately.
Colab is not doing that in my case. It's just sitting stagnant like this:
stagnant colab
This is a Colab bug --
https://github.com/googlecolab/colabtools/issues/437
The team reports they are working on a service change to correct the problem today. (21 Feb, 2019)
Well even i had the same probem
you can also go for other option
1. In left pane of google colab there is a tab called Files Click on that.
2. click on the upload files.
Thats it!!!! Pretty Simple Enough!!!!
for more details :https://www.youtube.com/watch?v=0rygVrmHidg
Upload the file from the local machine using the following command:
from google.colab import files
import pandas as pd
uploaded = files.upload()
for fn in uploaded.keys():
print('User uploaded file "{name}" with length {length} bytes'.format(
name=fn, length=len(uploaded[fn])))
After that read the csv/text file using the pandas:
dataFrame= pd.read_csv('filename.csv')
I have same problem. I use this method. Upload the file from the google drive using the following command:
from google.colab import drive
drive.mount('/content/drive')
data = pd.read_csv('/content/drive/Myfiles/datafiles/mydata.csv', delimiter=",")
Related
I am creating a selenium script to automatically log in to a webpage, and then import a .xls file. However I am stuck in the part when the webpage prompts me to select a file from my computer. How do I code to send the keys with the file path and press "enter"? Thanks in advance!
To upload a file with Selenium you can send the file's path to input element with type file on the web page.
If, for example your file path is C:\your_file.xls your code will be something like this:
file_path = 'C:\your_file.xls'
upload_input = driver.find_element_by_xpath('//input[#type="file"]')
upload_input.send_keys(file_path)
I'm trying to run a deep learning model in jupyter notebook and its taking forever and also karnel dies during training . So i'm trying to run it on Google Colab . I've learned some basics that are available on the internet but its not helping me at all . The model gets it dataset from a module ,
this link https://github.com/awslabs/handwritten-text-recognition-for-apache-mxnet/blob/master/ocr/utils/iam_dataset.py has the module that extract and preprocess dataset for trining from local computer. I've uploaded the dataset in Gdrive now i want to change the path so that this module finds that 'dataset' folder . I've been stuck on it for 5 days and now i'm clueless .
I will suggest you not to load the dataset from GDrive to colab directly. It increases the dataset loading time.
Google Colab provides some local storage for your work(around 70 GB) that is shown on the upper-right corner below the RAM bar. Bring your dataset to that storage. This is how you can do it:-
import zipfile
from google.colab import drive
zip_ref = zipfile.ZipFile("/content/drive/My Drive/dataset.zip", 'r')
zip_ref.extractall("/content/")
zip_ref.close()
Please note that your entire dataset should be zipped.
It will be more than 20 times faster than the method you are trying...
Format of zipfile.ZipFile() function above:-
zip_ref = zipfile.ZipFile("/content/drive/Zip file location in GDrive", 'r')
If you click the folder icon in the left side in colab interface you should see your dataset there.
You can then access your dataset using the filepath='/content/dataset'
I know to read in the csv is:
pd.read_csv("s3://data-science/misc/survey.csv")
But I am trying to export results into there using:
filex.to_csv("s3://data-science/misc/filex.csv")
and this does not work - how can this be done?
If you are looking for get the CSV beside the path where you will save it, then try using just the name of the new file and it will be saved in the actual path (from where you excecute the script:
df1.to_csv('df1.csv', sep=', encoding='utf-8')
and I recommend paying attention to the arg's
I am training a model in Google Colab and storing it in json format. I want to upload this trained model to my drive in the colab itself.
I am currently doing:
model_json = model.to_json()
with open("trainedModel.json", "w") as json_file:
json_file.write(model_json)
model.save_weights("trainedModel.h5")
print("Saved model to disk")
print("This file ran till end.\nNow uploading to drive:")
uploaded = drive.CreateFile({'parents':[{u'id':'#id_no'}],'title': 'trainedModel.json'})
uploaded.SetContentFile('trainedModel.json')
uploaded.Upload()
uploaded = drive.CreateFile({'parents':[{u'id': '#id_no''}],'title': 'trainedModel.h5'})
uploaded.SetContentFile('trainedModel.h5')
uploaded.Upload()
But this gives me:
FileNotFoundError: [Errno 2] No such file or directory: 'client_secrets.json'
I'd recommend using the file browser browser or Drive FUSE instead. Both are radically simpler than using the Drive API directly.
File browser upload:
Drive FUSE:
from google.colab import drive
drive.mount('/content/gdrive')
(Details)
This was happening because the authorization code given to the notebook that grants it permission expires after a few minutes/hours.
This problem got resolved by requesting the authorization code again. That is inserting
auth.authenticate_user()
gauth = GoogleAuth()
gauth.credentials = GoogleCredentials.get_application_default()
drive = GoogleDrive(gauth)
after saving the model file and before uploading it to the drive.
I have a ipython file that I want to execute on colab. When I first ran it, the local files were imported but now it gives me an error.Following are the code snippet and error
FileNotFoundError Traceback (most recent call last)
<ipython-input-1-9132fbd19d75> in <module>()
1 import pickle
----> 2 pickle_in =
open(r"C:/Users/manas/PycharmProjects/allProjects/X.pickle","rb")
3 X = pickle.load(pickle_in)
4
5 pickle_in =
open(r"C:/Users/manas/PycharmProjects/allProjects/y.pickle","rb")
FileNotFoundError: [Errno 2] No such file or directory:
'C:/Users/manas/PycharmProjects/allProjects/X.pickle'
import pickle
pickle_in =
open(r"C:/Users/manas/PycharmProjects/allProjects/X.pickle","rb")
X = pickle.load(pickle_in)
pickle_in =
open(r"C:/Users/manas/PycharmProjects/allProjects/y.pickle","rb")
Y = pickle.load(pickle_in)
You can upload your files on colab if you're not going to be doing this often. Else it can get quite annoying.
from google.colab import files
files.upload()
Using the above snippet you can upload and use whatever you'd like.
However, if you're pickles are of a larger size, I'd advice you to just upload them on your Drive. Accessing them from your Drive is far easier and less troublesome. To access files on your Drive, all you have to do is mount it in colab's file directory.
from google.colab import drive
drive.mount("/content/drive")
This will generate a link, click on it and sign in using Google OAuth, paste the key in the colab cell and you're connected.
Check out the list of available files in the side panel on the left side and copy the path of the file you want to access. Read it as you would, with any other file.