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package main | |
import ( | |
"fmt" | |
"http://github.com/robfig/cron/v3" | |
"sync" | |
"time" | |
) | |
func one() { |
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from collections import Counter | |
name = "Aashish Chaubey" | |
vowels = "aeiou" | |
vowels_list = list(filter(lambda x: x in vowels, name.lower())) | |
print(f"Number of vowels in name is: {len(vowels_list)}") | |
print(dict(Counter(vowels_list))) |
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import math | |
l = 50 | |
def is_prime(num: int) -> bool: | |
lim = math.floor(math.sqrt(num)) | |
for i in range(2, lim+1): | |
if num % i == 0: | |
return False | |
return True |
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def taskOfPairing(freq): | |
count = 0 | |
marker = False | |
for i in freq: | |
if i != 0: | |
count += i // 2 | |
if i % 2 != 0 and marker: | |
count += 1 | |
marker = False | |
elif i % 2 != 0: |
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import pandas as pd | |
df = pd.DataFrame({'agent_id': [1, 1, 1, 1, 2, 2, 2, 2], | |
'date': ["2021-01-01", "2021-04-01", "2021-05-01", "2021-06-01", "2021-01-01", "2021-02-01", "2021-03-01", "2021-06-01"], | |
'txn_amount': [100, 200, 100, 200, 100, 200, 100, 200], | |
'txn_status': ["Failure", "Success", "Failure", "Success", "Failure", "Success", "Failure", "Success"]}) | |
df['date'] = pd.to_datetime(df['date'], format='%Y-%m-%d') | |
df1 = df.set_index('date') |
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import firebase_admin | |
from firebase_admin import credentials | |
from firebase_admin import auth | |
cred = credentials.Certificate('secreatFile.json') | |
default_app = firebase_admin.initialize_app(cred) | |
# Search a user by email, ig registered | |
user = auth.get_user_by_email('chaubey.aashish@gmail.com') |
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start_text = "RIFF" | |
import os | |
for i, filename in enumerate(os.listdir('./')): | |
with open(filename, 'rb') as imageFile: | |
if imageFile.read().startswith(b'RIFF'): | |
print(f"{i+1}: {filename} - found!") | |
else: | |
continue |
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import ibm_boto3 | |
from ibm_botocore.client import Config, ClientError | |
# Constants for IBM COS values | |
COS_ENDPOINT = # Current list avaiable at https://control.cloud-object-storage.cloud.ibm.com/v2/endpoints | |
COS_API_KEY_ID = # eg "W00YiRnLW4a3fTjMB-odB-2ySfTrFBIQQWanc--P3byk" | |
COS_AUTH_ENDPOINT = "https://iam.cloud.ibm.com/identity/token" | |
COS_RESOURCE_CRN = # eg "crn:v1:bluemix:public:cloud-object-storage:global:a/3bf0d9003abfb5d29761c3e97696b71c:d6f04d83-6c4f-4a62-a165-696756d63903::" | |
# Create resource |
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### Using the fuzzywuzzy package | |
fuzzywuzzy package in python implements the Lavenshtein distance between two string to calculate the similarity between the two. | |
Install 2 packages: | |
pip install fuzzywuzzy | |
pip install python-Levenshtein / conda install -c conda-forge python-levenshtein | |
`[I actually had an issue installing the package, so I used the conda installation for this this package]` | |
This package is required to suppress the warning for the default slow fuzzywuzzy package. |
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/** | |
* @author Aashish Chaubey | |
* @link https://github.com/aashish-chaubey | |
*/ | |
/** | |
* First Create a Promise my implementing it with a `new` keyword | |
* Do all the heavy weight operations in the promise | |
* Store the promise in a variable | |
*/ |
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