I have developer mode on my chromebook and I am looking for app source code to add VS Code, and Linux is not supported, but developer is.Linux Not Supported Image
I wrote a python script to ran as root to find the file but it just produced random output
import os
import re
for path, dirs, files in os.walk("/"):
for filename in files:
if re.match(r".*"+re.escape(".desktop"), filename):
print(os.path.join("/", path, filename))
else:
pass
How do I download kaggle datasets to colab or any other place from script or notebook?
! kaggle datasets download -d arslanali4343/world-cities-database-population-oct2022
The Easy way
Clone repo (small file)
!git clone https://github.com/tikendraw/funcyou.git
Import Function
from funcyou.dataset import download_kaggle_dataset
3.Note: Keep the kaggle.json token file in the current working directory.(where the notebook/script is)
Get command api for the dataset you want to download by clicking on the 3 dots next to download button and copy api command
call the function and paste api command as argument
download_kaggle_dataset(api_command='kaggle datasets download -d arslanali4343/world-cities-database-population-oct2022', unzip=True)
how to extract text from pdf and dumping the information into a database using python?
How do I install PyPDF2?
i tried doing it but it shows the following problem
I see you are in Windows, so this is how you install it in Windows! You first need to install properly the setup.py files.
cd C:\Users\User\Downloads\pyPDF2 to go into the directory where the setup.py
C:\python27\python.exe setup.py install I use Python2.7 here. Use C:\python33\python.exe setup.py install for python 3.3 and so on.
That's the fastest way to do it (check the source!!)
On regards of how to extract it, there are lots of tutorials. You should follow the official doc and trustworthy websites! Here is an example!
from PyPDF2 import PdfFileReader
def text_extractor(path):
with open(path, 'rb') as f:
pdf = PdfFileReader(f)
# get the first page
page = pdf.getPage(1)
print(page)
print('Page type: {}'.format(str(type(page))))
text = page.extractText()
print(text)
if __name__ == '__main__':
path = 'reportlab-sample.pdf'
text_extractor(path)
Is it possible to use any datasets available via the kaggle API in Google Colab? I see the Kaggle API is used in this Colab notebook, but it's a bit unclear to me what datasets it provides access to.
Step-by-step --
Create an API key in Kaggle.
To do this, go to kaggle.com/ and open your user settings page.
Next, scroll down to the API access section and click generate
to download an API key.
This will download a file called kaggle.json to your computer.
You'll use this file in Colab to access Kaggle datasets and
competitions.
Navigate to https://colab.research.google.com/.
Upload your kaggle.json file using the following snippet in
a code cell:
from google.colab import files
files.upload()
Install the kaggle API using !pip install -q kaggle
Move the kaggle.json file into ~/.kaggle, which is where the
API client expects your token to be located:
!mkdir -p ~/.kaggle
!cp kaggle.json ~/.kaggle/
Now you can access datasets using the client, e.g., !kaggle datasets list.
Here's a complete example notebook of the Colab portion of this process:
https://colab.research.google.com/drive/1DofKEdQYaXmDWBzuResXWWvxhLgDeVyl
This example shows uploading the kaggle.json file, the Kaggle API client, and using the Kaggle client to download a dataset.
You should be able to access any dataset on Kaggle via the API. In this example, only the datasets for competitions are being listed. You can see that datasets you can access with this command:
kaggle datasets list
You can also search for datasets by adding the -s tag and then the search term you're interested in. So this would give you a list of datasets about dogs:
kaggle datasets list -s dogs
You can find more information on the API and how to use it in the documentation here.
Hope that helps! :)
Detailed approach:
Go to my account in your profile
Scroll down, until you find an option Create new Api Token, this will download a file called kaggle.json
Go to Colab upload the file kaggle.json
pip install kaggle
create a new folder named kaggle, copy kaggle.json into the kaggle folder, and set read-write permissions only for you(user).
6.Go to Kaggle website.For example, you want to download any data, click on the three dots in the right hand side of the screen. Then click copy API command
Go to colab, paste the API command
8.When you do an !ls, you will see that our download is a zip file.
To unzip the file use the following command
Now, when you do !ls you'll find our csv file is extracted from the zip file.
To read the file perform a simple pd.read_csv, import pandas
12.As you see, we have successfully read our file into colab.
This downloads the kaggle dataset into google colab, where you can perform analysis and build amazing machine learning models or train neural networks.
Happy Analysis!!!
Combined the top response to this Github gist as Colab Implementation. You can directly copy the code and use it.
How to Import a Dataset from Kaggle in Colab
Method:
First a few things you have to do:
Sign up for Kaggle
Sign up for a competition you want to access data from (for example LANL-Earthquake-Prediction competition).
Download your credentials to access Kaggle API as kaggle.json
# Install kaggle packages
!pip install -q kaggle
!pip install -q kaggle-cli
# Colab's file access feature
from google.colab import files
# Upload `kaggle.json` file
uploaded = files.upload()
# Retrieve uploaded file
# print results
for fn in uploaded.keys():
print('User uploaded file "{name}" with length {length} bytes'.format(
name=fn, length=len(uploaded[fn])))
# Then copy kaggle.json into the folder where the API expects to find it.
!mkdir -p ~/.kaggle
!cp kaggle.json ~/.kaggle/
!chmod 600 ~/.kaggle/kaggle.json
!ls ~/.kaggle
Now check if it worked!
#list competitions
!kaggle competitions list -s LANL-Earthquake-Prediction
Have a look at this.
It uses official kaggle api behind scene, but automates the process so you dont have to re-download manually every time your VM is taken away. Also, another issue i faced with using Kaggle API directly on Colab was the hassle of transferring Kaggle API token via Google Drive. Above method automates that as well.
Disclaimer: I am one of the creators of Clouderizer.
First of all, run this command to find out where this colab file exists, how it executes.
!ls -d $PWD/*
It will show /content/data /content/gdrive /content/models
In other words, your current directory is root/content/. Your working directory(pwd) is /content/. so when you do !ls, it will show data gdrive models.
FYI, ! allows you to run linux commands inside colab.
Google Drive keeps cleaning up the /content folder. Therefore, every session you use colab, downloaded data sets, kaggle json file will be gone. That's why it's important to automate the process, so you can focus on writing code, not setting up the environment every time.
Run this in colab code block as an example with your own api key. open kaggle.json file. you will find them out.
# Info on how to get your api key (kaggle.json) here: https://github.com/Kaggle/kaggle-api#api-credentials
!pip install kaggle
{"username":"seunghunsunmoonlee","key":""}
import json
import zipfile
import os
with open('/content/.kaggle/kaggle.json', 'w') as file:
json.dump(api_token, file)
!chmod 600 /content/.kaggle/kaggle.json
!kaggle config path -p /content
!kaggle competitions download -c dog-breed-identification
os.chdir('/content/competitions/dog-breed-identification')
for file in os.listdir():
zip_ref = zipfile.ZipFile(file, 'r')
zip_ref.extractall()
zip_ref.close()
Then run !ls again. You will see all data you need.
Hope it helps!
To download the competitve data on google colab from kaggle.
I'm working on google colab and I've been through the same problem. but i did two tings .
First you have to register your mobile number along with your country code.
Second you have to click on last submission on the kaggle dataset page
Then download kaggle.json file from kaggle.upload kaggle.json on the google colab
After that on google colab run these code is given below.
!pip install -q kaggle
!mkdir -p ~/.kaggle
!cp kaggle.json ~/.kaggle/
!chmod 600 ~/.kaggle/kaggle.json
!kaggle competitions download -c web-traffic-time-series-forecasting
A quick guide to use Kaggle datasets inside Google Colab using Kaggle API
(1) Download the Kaggle API token.
Go to “Account”, go down the page, and find the “API” section.
Click the “Create New API Token” button.
The “kaggle.json” file will be downloaded.
(2) Mount the Google drive to the Colab notebook.
It means giving access to the files in your google drive to Colab notebook.
from google.colab import drive
drive.mount("/content/gdrive", force_remount=True)
(3) Upload the “kaggle.json” file into the folder in google drive where you want to download the Kaggle dataset.
(4) Install Kaggle API.
!pip install kaggle
(5) Change the current working directory to where you want to download the Kaggle dataset.
%cd /content/gdrive/MyDrive/DataSets/house_price_data/
(6) Run the following code to configure the path to “kaggle.json”.
import os
os.environ['KAGGLE_CONFIG_DIR'] = "/content/gdrive/MyDrive/DataSets/house_price_data/"
(7) Download the dataset.
!kaggle competitions download -c house-prices-advanced-regression-techniques
After the steps (1-6) above from Bob Smith's answer, to use dataset from a particular competition in colab,
you can use the command:
!kaggle competitions download -c elo-merchant-category-recommendation
Here, elo-merchant-category-recommendation is the name of the competition.
Most important part is before to download files:
In the Kaggle webpage, in the Competition section you must clicked on:
Late Submission or on Join Competition
and
ACCEPT RULE AND CONDITIONS ON KAGGLE COMPETITION WEBPAGE
if not, after copying api file, and after launched downloading the dataset, 403 error shows as result.
A hacky way:
Go to the dataset page after login
Open Chrome Developer Tools, then go to Network pane
Click Download button on Kaggle
When clicked you will see many requests in Network pane, find the request starting archive.zip
Right click on that request, then Copy -> Copy as cURL (bash). Now you copied the command
On Colab, paste the command and append an ! to the beginnning of the command then run it
This is definitely a less reliable way than the API, but still remains as an option.
I find the accepted answer to be very comprehensive, but would like to add that:
!kaggle competitions download -c dogs-vs-cats
or most other downloads still wont work. You will probably get the following error:
403 - Forbidden
which is not very verbose. It wants to say: "Please visit kaggle.com and accept the rules (e.g. for that competition). You cannot accept through the API! It is explicitly stated in the docs (see Public API documentation | Kaggle):
Just like participating in a Competition normally through the user interface, you must read and accept the rules in order to download data or make submissions. You cannot accept Competition rules via the API. You must do this by visiting the Kaggle website and accepting the rules there.
Yes, this could have been a comment, but I am missing enough reputation to comment.
import os
os.makedirs("/content/.kaggle/")
import json
token = {"username":"your_username_here","key":"your_kaggle_key_here"}
with open('/content/.kaggle/kaggle.json', 'a+') as file:
json.dump(token, file)
import shutil
os.makedirs("/.kaggle/")
src="/content/.kaggle/kaggle.json"
des="/.kaggle/kaggle.json"
shutil.copy(src,des)
os.makedirs("/root/.kaggle/")
!cp /content/.kaggle/kaggle.json ~/.kaggle/kaggle.json
!kaggle config set -n path -v /content
#https://towardsdatascience.com/setting-up-kaggle-in-google-colab-ebb281b61463
!kaggle datasets download -d xhlulu/siim-covid19-resized-to-512px-png
Works for me on Colab as of 29-05-21!
I try the following for lemmatization:
from nltk.stem.wordnet import WordNetLemmatizer
wnl = WordNetLemmatizer()
wnl.lemmatize("dogs")
and keep getting "BadZipFile: File is not a zip file" error. I am unable to find anything on it in the context of lemmatization. Can somebody help?
you will get rid of it after downloading wordnet & wordnet_ic
python -m nltk.downloader all
you need to download the zip-file
the zipfile.BadZipFile: File is not a zip file issue is due to an
incomplete installation of nltk. so uninstall previous versions and
follow these instructions.
First,close your IDE, then run your command prompt or anaconda prompt as an administrator
now, run the following commands:
pip install numpy
pip install nltk
after installing nltk,
type python on your command line to enter python mode
after opening python, let's import the nltk library
import nltk
now that you have imported it on your command prompt
run the following
nltk.download("wordnet")
nltk.download("omw-1.4")
now the zipfile.BadZipFile: File is not a zip file issue should be solved.