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What makes Python language an ideal choice for developing applications? It offers higher-level functions and higher-level data types than other programming languages. It also provides easy way to access and manipulate those data in an efficient way. Python is used regularly in mainstream software such as AI, data science, networking, gaming and more.

Popular New Releases in Python

youtube-dl 2021.12.17

TensorFlow Official Models 2.7.1

v4.18.0: Checkpoint sharding, vision models

youtube-dl

youtube-dl 2021.12.17

models

TensorFlow Official Models 2.7.1

thefuck

transformers

v4.18.0: Checkpoint sharding, vision models

flask

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4429 Libraries

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2

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604

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1263 Libraries

3038

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723 Libraries

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690 Libraries

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628 Libraries

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627 Libraries

23550

9

550 Libraries

33409

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512 Libraries

20636

Trending Kits in Python

course-recommendation-kit

Build AI Course Recommender

The use case of AI Course Recommender System is to provide personalized recommendation to the user based on their interest, course they can take and their current knowledge. This system will be able to recommend course based on user’s interest, current knowledge, analytical view of students’ performance in mathematics and recommends if a student can consider math subject for his/ her higher education. The recommended course will be based on the information of user’s profile, analysis of grades of students, visualization of patterns, prediction of grade in final test, and some rules that were set by their instructor. Using machine learning algorithms, we can train our model on a set of data and then predict the ratings for new items. This is all done in Python using numpy, pandas, matplotlib, scikit-learn and seaborn. kandi kit provides you with a fully deployable AI Course Recommender System. Source code included so that you can customize it for your requirement.

kandi

1-Click Install

object-tracking-system

Build Object Tracking System

<div><img src="https://kandi.dev/owassets/object-tracking-system-banner.png" alt="Object Tracking" style="height:auto;max-width:100%;"/> Real-time object tracking system is a technology used to track objects (from images, videos, and webcam) in real time. It can be used for security purposes or for commercial purposes. Tracking can be done for video formats and live streaming webcam. The real-time object tracking system has many applications, such as in retail stores, airports, stadiums and other places where security is important. The system can be used to monitor customer activity in stores, track inventory and detect shoplifting. It can also be used to increase safety in public places by monitoring the movements of pedestrians or vehicles. Please see below a sample solution kit to jumpstart your solution on Real-time object tracking system. To use this kit to build your own solution, scroll down to the Kit Deployment Instructions sections. Source code included so that you can customize it for your requirement. <button class="MuiButtonBase-root MuiButton-root MuiButton-contained editexp MuiButton-containedSecondary click_collections_oneclickfiledownload " onclick="location.href='https://github.com/kandikits/Yolov5_DeepSort_Pytorch/raw/master/kit_installer.zip'" type="button"> ⬇️ Download 1-Click Installer </button>

kandi

1-Click Install

text-summarizer

Build Text Summarizer in Python

<img src="https://kandi.dev/owassets/text-summarizer-banner.png" alt="Text Summarizer Banner" style="height:auto;max-width:100%;"/> NLP text summarizer, is a Python package that summarizes texts and extracts the most important sentences from a given text. Text summarizer is commonly used in news feeding websites to summarize long articles. Summarizer shortens long texts such that the summarized text preserves all the essential points of the actual text. It uses spaCy, nltk, and NumPy to do the job. This solution is also used to summarize texts (in Extractive and abstractive techniques), extract key sentences and find their TF-IDF values. You can use this package for your own projects; we are sure you'll find it useful! Extraction-based summarization involves selecting sentences from an original document and organizing them into a cohesive summary. In contrast to extraction-based summarization, abstraction-based summaries are created by using algorithms to produce abstracts that can be used as templates. spaCy is a library for Natural Language Processing (NLP). It provides functions for tokenization, part of speech tagging, and parsing. The library also includes pre-trained models for some languages. NLTK (Natural Language Toolkit) is another popular toolkit for NLP tasks. It is used in many research papers to solve different problems related to NLP. There are several popular open-source libraries available for developers: <button class="MuiButtonBase-root MuiButton-root MuiButton-contained editexp MuiButton-containedSecondary" onclick="location.href='https://github.com/kandikits/bert-extractive-summarizer/raw/master/kit_installer.zip'" type="button"> ⬇️ Download 1-Click Installer </button>

kandi

1-Click Install

food-wastage-recommender-system

food Wastage Recommender system

Data Summary : Resources that have been shared for the problem statement has info about food items and their description. Also we had order info from both donor and from consumer side orders on daily basis. We have done data cleaning and preprocessing as required. Recommendation system : In order to control the food wastage we have built Recommendation engine using "item-item based collaborative filtering" to recommend the items which expire early and are more in consumption. Data Analysis : We have developed a dashboard on tableau using cleaned datasets and these analysis can be used to match supply-demand of different types of food and to give an overview to the NGO, donors and consumers on how to reduce the food wastage. Use the open source, cloud APIs, or public libraries listed below in your application development based on your technology preferences, such as primary language. The below list also provides a view of the components' rating on different dimensions such as community support availability, security vulnerability, and overall quality, helping you make an informed choice for implementation and maintenance of your application. Please review the components carefully, having a no license alert or proprietary license, and use them appropriately in your applications. Please check the component page for the exact license of the component. You can also get information on the component's features, installation steps, top code snippets, and top community discussions on the component details page. The links to package managers are listed for download, where packages are readily available. Otherwise, build from the respective repositories for use in your application. You can also use the source code from the repositories in your applications based on the respective license types.

kandi

1-Click Install

ai-hulks-app-kit

Ai Hulks App Kit

SPEAKER COUNTING It enhances understanding through automatic speech recognition Beneficial for real - world applications like call-center transcription and meeting transcription analytics Speaker Diarization is a developing field of study, with new approaches being published on a frequent basis. The Problem Not many studies have been done for estimating a large number of speakers. Diarization becomes extremely difficult when the number of speakers is huge. Providing the number of speakers to the diarization system can be advantageous Complete solution Architecture - Machine Learning model - To predict the no. of speakers and the time stamps of the speaker. Web App - Frontend for the user to use the feature. Middleware Flask Api - To connect Frontend and ML Model. We have build a Web App that a user can use to communicate and leverage the advantages of the our Machine learning model. Since the model we build and the web app are build on different platforms, we used REST API as a middleware to connect frontend and model.

buildwithai2021

Team CE.net

This kit is helpful for audio analysis. Audio information plays a rather important role in the increasing digital content that is available today; resulting in a need for methodologies that automatically analyze such content. Speaker Identification is one of the vital field of research based upon Voice Signals. Its other notable fields are: Speech Recognition, Speech-to-Text Conversion, and vice versa, etc. Mel Frequency Cepstral Coefficient (MFCC) is considered a key factor in performing Speaker Identification. But, there are other features lists available as an alternate to MFCC; like- Linear Predictor Coefficient (LPC), Spectrum Sub-band Centroid (SSC), Rhythm, Turbulence, Line Spectral Frequency (LPF), ChromaFactor, etc. Gaussian Mixture Model (GMM) is the most popular model for training on our data. The training task can also be executed on other significant models; viz. Hidden Markov Model (HMM). Recently, most of the model training phase for a speaker identification project is executed using Deep learning; especially, Artificial Neural Networks (ANN). In this project, we are mainly focused on implementing MFCC and GMM in pair to achieve our target. We have considered MFCC with “tuned parameters” as the primary feature and delta- MFCC as secondary feature. And, we have implemented GMM with some tuned parameters to train our model. We have performed this project on two different kinds of Dataset; viz. “VoxForge” Dataset and a custom dataset which we have prepared by ourselves. We have obtained an outstanding result on both of these Datasets; viz. 100% accuracy on VoxForge Dataset and 95.29 % accuracy on self prepared Dataset. We demonstrate that speaker identification task can be performed using MFCC and GMM together with outstanding accuracy in Identification/ Diarization results.

buildwithai-theme1

BuildWithAI Challenge 1

The Pandemic has impacted education - classes have moved online, students have been isolated on screens and coping with this change. Despite the challenges, the digital school has the potential to transform education. How can we empower students and teachers in this new digital school paradigm. In this challenge, we are inviting AI-powered solutions for the digital school of tomorrow. <h3>DATASET: Feel free to use any dataset of your choice.</h3> There is no restriction and you can use any data set. <b>Please see the section - DATASETS below for sample datasets to help as a reference. </b> Here are sample areas you could choose to tackle in this challenge. Feel free to come up with your own ideas as well. 1. Higher Education and Career Recommendation 2. Mental Health Monitor and Virtual Companion 3. Adaptive Learning Curriculum 4. Class availability scheduling for social distancing 5. Compliance of COVID guidelines - masking, distancing, temperature Please see below for guidelines and reusable libraries to jumpstart your solution. This kit provides reference to open-source libraries which can be reused as core building blocks for creating a predictive solution. You may use any other open-source libraries also as relevant to your solution. Reusability is a key design principle and will be scored positively in your submission. These reference reusable libraries are spread over functions in Data Analysis and Mining, Data Visualization, Machine Learning, and other key areas to build AI solution. Below are the guidelines for creating your submission kit for this challenge. 1. See Product Tour > Creating a kit from the kandi header. This will guide you on creating your kit. 2. Your submission kit should contain the kit heading/ name, description of the solution, and other relevant information. 3. Create groups with logical names and add the libraries to the respective sections. 4. You solution can be built with any libraries other than the libraries provided here for reference. 5. The project source library for the solution built in the hackathon should be hosted in GitHub and listed in your kit under 'Kit Solution Source' section. 6. Any deployment instructions should be added under 'Kit Deployment Instructions' section of the kit. 7. Add any additional information, links under the kit description or group descriptions.

osint-solutions

Open Source Intelligence

Open Source Intelligence has played a pivotal role in key events like tracing Covid-19 origins, MH17 downing, the Boston Marathon bombing, and the Myanmar refugee crisis. Approximately 500 million tweets are published every day, totaling over 200 billion posts in a year. Facebook users upload 350 million photos per day. YouTube users add nearly 720,000 hours of new video every day. Almost all devices are online today in the connected world. <br/> <br/> While monitoring messages was exclusive to intelligence agencies, the tons of information available in the public realm today has made it possible for general and security enthusiasts to look for insights that might not have been possible earlier. The U.S. Department of State defines OSINT as "intelligence that is produced from publicly available information and is collected, exploited, and disseminated promptly to an appropriate audience to address a specific intelligence requirement." <br/> <br/> Designed correctly, OSINT can reduce risk across a variety of common risks such as weather conditions, disease outbreaks, corporate risk management, data privacy, reputation management, in addition to higher-order tasks like national security and cybersecurity. Do not construe this as legal advice, promotion, or authorization to indulge in any activity whatsoever.

sudoku-game-in-python

Sudoku game in Python

Everyone loves to play games, especially online games. Sudoku is one of the great and prominent online games that helps us to develop problem-solving skills. Sudoku is one of the logic-based, combinatorial number-placement puzzles. The benefits of playing sudoku are that it improves concentration, promotes a healthy mind. The ultimate goal of the sudoku game is to fill a 9×9 grid with numbers. Python is preferable for building sudoku games; the reason behind that is python is free and open-source, with vast library support. Before technology evolution, we could play sudoku in magazines, article books. Modern technology has brought the opportunity to digitally create and play sudoku, so let's get started with the bellow libraries without delay. This kit aids the development of the Sudoku game using python by following the below steps. 1. Select a development environment of your choice 2. knowledge of Graphical user interface 3. Idea of the key binding controller 4. Fill the grid with default numbers. 5. Assign a specific key for each operation and listen to it. 6. Implement sudoku solver 7. Conjoin the backtracking algorithm into it. 8. Apply a set of colors to visualize auto-solving.

object-tracking-system

Build Object Tracking System

<div><img src="https://kandi.dev/owassets/object-tracking-system-banner.png" alt="Object Tracking" style="height:auto;max-width:100%;"/> Real-time object tracking system is a technology used to track objects (from images, videos, and webcam) in real time. It can be used for security purposes or for commercial purposes. Tracking can be done for video formats and live streaming webcam. The real-time object tracking system has many applications, such as in retail stores, airports, stadiums and other places where security is important. The system can be used to monitor customer activity in stores, track inventory and detect shoplifting. It can also be used to increase safety in public places by monitoring the movements of pedestrians or vehicles. Please see below a sample solution kit to jumpstart your solution on Real-time object tracking system. To use this kit to build your own solution, scroll down to the Kit Deployment Instructions sections. Source code included so that you can customize it for your requirement. <button class="MuiButtonBase-root MuiButton-root MuiButton-contained editexp MuiButton-containedSecondary click_collections_oneclickfiledownload " onclick="location.href='https://github.com/kandikits/Yolov5_DeepSort_Pytorch/raw/master/kit_installer.zip'" type="button"> ⬇️ Download 1-Click Installer </button>

kandi

1-Click Install

text-summarizer

Build Text Summarizer in Python

<img src="https://kandi.dev/owassets/text-summarizer-banner.png" alt="Text Summarizer Banner" style="height:auto;max-width:100%;"/> NLP text summarizer, is a Python package that summarizes texts and extracts the most important sentences from a given text. Text summarizer is commonly used in news feeding websites to summarize long articles. Summarizer shortens long texts such that the summarized text preserves all the essential points of the actual text. It uses spaCy, nltk, and NumPy to do the job. This solution is also used to summarize texts (in Extractive and abstractive techniques), extract key sentences and find their TF-IDF values. You can use this package for your own projects; we are sure you'll find it useful! Extraction-based summarization involves selecting sentences from an original document and organizing them into a cohesive summary. In contrast to extraction-based summarization, abstraction-based summaries are created by using algorithms to produce abstracts that can be used as templates. spaCy is a library for Natural Language Processing (NLP). It provides functions for tokenization, part of speech tagging, and parsing. The library also includes pre-trained models for some languages. NLTK (Natural Language Toolkit) is another popular toolkit for NLP tasks. It is used in many research papers to solve different problems related to NLP. There are several popular open-source libraries available for developers: <button class="MuiButtonBase-root MuiButton-root MuiButton-contained editexp MuiButton-containedSecondary" onclick="location.href='https://github.com/kandikits/bert-extractive-summarizer/raw/master/kit_installer.zip'" type="button"> ⬇️ Download 1-Click Installer </button>

kandi

1-Click Install

food-wastage-recommender-system

food Wastage Recommender system

Data Summary : Resources that have been shared for the problem statement has info about food items and their description. Also we had order info from both donor and from consumer side orders on daily basis. We have done data cleaning and preprocessing as required. Recommendation system : In order to control the food wastage we have built Recommendation engine using "item-item based collaborative filtering" to recommend the items which expire early and are more in consumption. Data Analysis : We have developed a dashboard on tableau using cleaned datasets and these analysis can be used to match supply-demand of different types of food and to give an overview to the NGO, donors and consumers on how to reduce the food wastage. Use the open source, cloud APIs, or public libraries listed below in your application development based on your technology preferences, such as primary language. The below list also provides a view of the components' rating on different dimensions such as community support availability, security vulnerability, and overall quality, helping you make an informed choice for implementation and maintenance of your application. Please review the components carefully, having a no license alert or proprietary license, and use them appropriately in your applications. Please check the component page for the exact license of the component. You can also get information on the component's features, installation steps, top code snippets, and top community discussions on the component details page. The links to package managers are listed for download, where packages are readily available. Otherwise, build from the respective repositories for use in your application. You can also use the source code from the repositories in your applications based on the respective license types.

kandi

1-Click Install

buildwithai2021

Team CE.net

This kit is helpful for audio analysis. Audio information plays a rather important role in the increasing digital content that is available today; resulting in a need for methodologies that automatically analyze such content. Speaker Identification is one of the vital field of research based upon Voice Signals. Its other notable fields are: Speech Recognition, Speech-to-Text Conversion, and vice versa, etc. Mel Frequency Cepstral Coefficient (MFCC) is considered a key factor in performing Speaker Identification. But, there are other features lists available as an alternate to MFCC; like- Linear Predictor Coefficient (LPC), Spectrum Sub-band Centroid (SSC), Rhythm, Turbulence, Line Spectral Frequency (LPF), ChromaFactor, etc. Gaussian Mixture Model (GMM) is the most popular model for training on our data. The training task can also be executed on other significant models; viz. Hidden Markov Model (HMM). Recently, most of the model training phase for a speaker identification project is executed using Deep learning; especially, Artificial Neural Networks (ANN). In this project, we are mainly focused on implementing MFCC and GMM in pair to achieve our target. We have considered MFCC with “tuned parameters” as the primary feature and delta- MFCC as secondary feature. And, we have implemented GMM with some tuned parameters to train our model. We have performed this project on two different kinds of Dataset; viz. “VoxForge” Dataset and a custom dataset which we have prepared by ourselves. We have obtained an outstanding result on both of these Datasets; viz. 100% accuracy on VoxForge Dataset and 95.29 % accuracy on self prepared Dataset. We demonstrate that speaker identification task can be performed using MFCC and GMM together with outstanding accuracy in Identification/ Diarization results.

buildwithai-theme1

BuildWithAI Challenge 1

The Pandemic has impacted education - classes have moved online, students have been isolated on screens and coping with this change. Despite the challenges, the digital school has the potential to transform education. How can we empower students and teachers in this new digital school paradigm. In this challenge, we are inviting AI-powered solutions for the digital school of tomorrow. <h3>DATASET: Feel free to use any dataset of your choice.</h3> There is no restriction and you can use any data set. <b>Please see the section - DATASETS below for sample datasets to help as a reference. </b> Here are sample areas you could choose to tackle in this challenge. Feel free to come up with your own ideas as well. 1. Higher Education and Career Recommendation 2. Mental Health Monitor and Virtual Companion 3. Adaptive Learning Curriculum 4. Class availability scheduling for social distancing 5. Compliance of COVID guidelines - masking, distancing, temperature Please see below for guidelines and reusable libraries to jumpstart your solution. This kit provides reference to open-source libraries which can be reused as core building blocks for creating a predictive solution. You may use any other open-source libraries also as relevant to your solution. Reusability is a key design principle and will be scored positively in your submission. These reference reusable libraries are spread over functions in Data Analysis and Mining, Data Visualization, Machine Learning, and other key areas to build AI solution. Below are the guidelines for creating your submission kit for this challenge. 1. See Product Tour > Creating a kit from the kandi header. This will guide you on creating your kit. 2. Your submission kit should contain the kit heading/ name, description of the solution, and other relevant information. 3. Create groups with logical names and add the libraries to the respective sections. 4. You solution can be built with any libraries other than the libraries provided here for reference. 5. The project source library for the solution built in the hackathon should be hosted in GitHub and listed in your kit under 'Kit Solution Source' section. 6. Any deployment instructions should be added under 'Kit Deployment Instructions' section of the kit. 7. Add any additional information, links under the kit description or group descriptions.

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QUESTION

Python/Docker ImportError: cannot import name 'json' from itsdangerous

Asked 2022-Mar-31 at 12:49

I am trying to get a Flask and Docker application to work but when I try and run it using my docker-compose up command in my Visual Studio terminal, it gives me an ImportError called ImportError: cannot import name 'json' from itsdangerous. I have tried to look for possible solutions to this problem but as of right now there are not many on here or anywhere else. The only two solutions I could find are to change the current installation of MarkupSafe and itsdangerous to a higher version: https://serverfault.com/questions/1094062/from-itsdangerous-import-json-as-json-importerror-cannot-import-name-json-fr and another one on GitHub that tells me to essentially change the MarkUpSafe and itsdangerous installation again https://github.com/aws/aws-sam-cli/issues/3661, I have also tried to make a virtual environment named veganetworkscriptenv to install the packages but that has also failed as well. I am currently using Flask 2.0.0 and Docker 5.0.0 and the error occurs on line eight in vegamain.py.

Here is the full ImportError that I get when I try and run the program:

1veganetworkscript-backend-1  | Traceback (most recent call last):
2veganetworkscript-backend-1  |   File &quot;/app/vegamain.py&quot;, line 8, in &lt;module&gt;
3veganetworkscript-backend-1  |     from flask import Flask
4veganetworkscript-backend-1  |   File &quot;/usr/local/lib/python3.9/site-packages/flask/__init__.py&quot;, line 19, in &lt;module&gt;
5veganetworkscript-backend-1  |     from . import json
6veganetworkscript-backend-1  |   File &quot;/usr/local/lib/python3.9/site-packages/flask/json/__init__.py&quot;, line 15, in &lt;module&gt;
7veganetworkscript-backend-1  |     from itsdangerous import json as _json
8veganetworkscript-backend-1  | ImportError: cannot import name 'json' from 'itsdangerous' (/usr/local/lib/python3.9/site-packages/itsdangerous/__init__.py)
9veganetworkscript-backend-1 exited with code 1
10

Here are my requirements.txt, vegamain.py, Dockerfile, and docker-compose.yml files:

requirements.txt:

1veganetworkscript-backend-1  | Traceback (most recent call last):
2veganetworkscript-backend-1  |   File &quot;/app/vegamain.py&quot;, line 8, in &lt;module&gt;
3veganetworkscript-backend-1  |     from flask import Flask
4veganetworkscript-backend-1  |   File &quot;/usr/local/lib/python3.9/site-packages/flask/__init__.py&quot;, line 19, in &lt;module&gt;
5veganetworkscript-backend-1  |     from . import json
6veganetworkscript-backend-1  |   File &quot;/usr/local/lib/python3.9/site-packages/flask/json/__init__.py&quot;, line 15, in &lt;module&gt;
7veganetworkscript-backend-1  |     from itsdangerous import json as _json
8veganetworkscript-backend-1  | ImportError: cannot import name 'json' from 'itsdangerous' (/usr/local/lib/python3.9/site-packages/itsdangerous/__init__.py)
9veganetworkscript-backend-1 exited with code 1
10Flask==2.0.0
11Flask-SQLAlchemy==2.4.4
12SQLAlchemy==1.3.20
13Flask-Migrate==2.5.3
14Flask-Script==2.0.6
15Flask-Cors==3.0.9
16requests==2.25.0
17mysqlclient==2.0.1
18pika==1.1.0
19wolframalpha==4.3.0
20

vegamain.py:

1veganetworkscript-backend-1  | Traceback (most recent call last):
2veganetworkscript-backend-1  |   File &quot;/app/vegamain.py&quot;, line 8, in &lt;module&gt;
3veganetworkscript-backend-1  |     from flask import Flask
4veganetworkscript-backend-1  |   File &quot;/usr/local/lib/python3.9/site-packages/flask/__init__.py&quot;, line 19, in &lt;module&gt;
5veganetworkscript-backend-1  |     from . import json
6veganetworkscript-backend-1  |   File &quot;/usr/local/lib/python3.9/site-packages/flask/json/__init__.py&quot;, line 15, in &lt;module&gt;
7veganetworkscript-backend-1  |     from itsdangerous import json as _json
8veganetworkscript-backend-1  | ImportError: cannot import name 'json' from 'itsdangerous' (/usr/local/lib/python3.9/site-packages/itsdangerous/__init__.py)
9veganetworkscript-backend-1 exited with code 1
10Flask==2.0.0
11Flask-SQLAlchemy==2.4.4
12SQLAlchemy==1.3.20
13Flask-Migrate==2.5.3
14Flask-Script==2.0.6
15Flask-Cors==3.0.9
16requests==2.25.0
17mysqlclient==2.0.1
18pika==1.1.0
19wolframalpha==4.3.0
20# Veganetwork (C) TetraSystemSolutions 2022
21# all rights are reserved.  
22# 
23# Author: Trevor R. Blanchard Feb-19-2022-Jul-30-2022
24#
25
26# get our imports in order first
27from flask import Flask # &lt;-- error occurs here!!!
28
29# start the application through flask.
30app = Flask(__name__)
31
32# if set to true will return only a &quot;Hello World&quot; string.
33Debug = True
34
35# start a route to the index part of the app in flask.
36@app.route('/')
37def index():
38    if (Debug == True):
39        return 'Hello World!'
40    else:
41        pass
42
43# start the flask app here ---&gt;
44if __name__ == '__main__':
45    app.run(debug=True, host='0.0.0.0') 
46

Dockerfile:

1veganetworkscript-backend-1  | Traceback (most recent call last):
2veganetworkscript-backend-1  |   File &quot;/app/vegamain.py&quot;, line 8, in &lt;module&gt;
3veganetworkscript-backend-1  |     from flask import Flask
4veganetworkscript-backend-1  |   File &quot;/usr/local/lib/python3.9/site-packages/flask/__init__.py&quot;, line 19, in &lt;module&gt;
5veganetworkscript-backend-1  |     from . import json
6veganetworkscript-backend-1  |   File &quot;/usr/local/lib/python3.9/site-packages/flask/json/__init__.py&quot;, line 15, in &lt;module&gt;
7veganetworkscript-backend-1  |     from itsdangerous import json as _json
8veganetworkscript-backend-1  | ImportError: cannot import name 'json' from 'itsdangerous' (/usr/local/lib/python3.9/site-packages/itsdangerous/__init__.py)
9veganetworkscript-backend-1 exited with code 1
10Flask==2.0.0
11Flask-SQLAlchemy==2.4.4
12SQLAlchemy==1.3.20
13Flask-Migrate==2.5.3
14Flask-Script==2.0.6
15Flask-Cors==3.0.9
16requests==2.25.0
17mysqlclient==2.0.1
18pika==1.1.0
19wolframalpha==4.3.0
20# Veganetwork (C) TetraSystemSolutions 2022
21# all rights are reserved.  
22# 
23# Author: Trevor R. Blanchard Feb-19-2022-Jul-30-2022
24#
25
26# get our imports in order first
27from flask import Flask # &lt;-- error occurs here!!!
28
29# start the application through flask.
30app = Flask(__name__)
31
32# if set to true will return only a &quot;Hello World&quot; string.
33Debug = True
34
35# start a route to the index part of the app in flask.
36@app.route('/')
37def index():
38    if (Debug == True):
39        return 'Hello World!'
40    else:
41        pass
42
43# start the flask app here ---&gt;
44if __name__ == '__main__':
45    app.run(debug=True, host='0.0.0.0') 
46FROM python:3.9
47ENV PYTHONUNBUFFERED 1
48WORKDIR /app
49COPY requirements.txt /app/requirements.txt
50RUN pip install -r requirements.txt
51COPY . /app
52

docker-compose.yml:

1veganetworkscript-backend-1  | Traceback (most recent call last):
2veganetworkscript-backend-1  |   File &quot;/app/vegamain.py&quot;, line 8, in &lt;module&gt;
3veganetworkscript-backend-1  |     from flask import Flask
4veganetworkscript-backend-1  |   File &quot;/usr/local/lib/python3.9/site-packages/flask/__init__.py&quot;, line 19, in &lt;module&gt;
5veganetworkscript-backend-1  |     from . import json
6veganetworkscript-backend-1  |   File &quot;/usr/local/lib/python3.9/site-packages/flask/json/__init__.py&quot;, line 15, in &lt;module&gt;
7veganetworkscript-backend-1  |     from itsdangerous import json as _json
8veganetworkscript-backend-1  | ImportError: cannot import name 'json' from 'itsdangerous' (/usr/local/lib/python3.9/site-packages/itsdangerous/__init__.py)
9veganetworkscript-backend-1 exited with code 1
10Flask==2.0.0
11Flask-SQLAlchemy==2.4.4
12SQLAlchemy==1.3.20
13Flask-Migrate==2.5.3
14Flask-Script==2.0.6
15Flask-Cors==3.0.9
16requests==2.25.0
17mysqlclient==2.0.1
18pika==1.1.0
19wolframalpha==4.3.0
20# Veganetwork (C) TetraSystemSolutions 2022
21# all rights are reserved.  
22# 
23# Author: Trevor R. Blanchard Feb-19-2022-Jul-30-2022
24#
25
26# get our imports in order first
27from flask import Flask # &lt;-- error occurs here!!!
28
29# start the application through flask.
30app = Flask(__name__)
31
32# if set to true will return only a &quot;Hello World&quot; string.
33Debug = True
34
35# start a route to the index part of the app in flask.
36@app.route('/')
37def index():
38    if (Debug == True):
39        return 'Hello World!'
40    else:
41        pass
42
43# start the flask app here ---&gt;
44if __name__ == '__main__':
45    app.run(debug=True, host='0.0.0.0') 
46FROM python:3.9
47ENV PYTHONUNBUFFERED 1
48WORKDIR /app
49COPY requirements.txt /app/requirements.txt
50RUN pip install -r requirements.txt
51COPY . /app
52version: '3.8'
53services:
54  backend:
55    build:
56      context: .
57      dockerfile: Dockerfile
58    command: 'python vegamain.py'
59    ports:
60      - 8004:5000
61    volumes:
62      - .:/app
63    depends_on:
64      - db
65
66#  queue:
67#    build:
68#      context: .
69#      dockerfile: Dockerfile
70#    command: 'python -u consumer.py'
71#    depends_on:
72#      - db
73
74  db:
75    image: mysql:5.7.22
76    restart: always
77    environment:
78      MYSQL_DATABASE: admin
79      MYSQL_USER: root
80      MYSQL_PASSWORD: root
81      MYSQL_ROOT_PASSWORD: root
82    volumes:
83      - .dbdata:/var/lib/mysql
84    ports:
85      - 33069:3306
86

How exactly can I fix this code? thank you!

ANSWER

Answered 2022-Feb-20 at 12:31

I was facing the same issue while running docker containers with flask.

I downgraded Flask to 1.1.4 and markupsafe to 2.0.1 which solved my issue.

Check this for reference.

Source https://stackoverflow.com/questions/71189819

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QUESTION

Python/Docker ImportError: cannot import name 'json' from itsdangerous

Asked 2022-Mar-31 at 12:49

I am trying to get a Flask and Docker application to work but when I try and run it using my docker-compose up command in my Visual Studio terminal, it gives me an ImportError called ImportError: cannot import name 'json' from itsdangerous. I have tried to look for possible solutions to this problem but as of right now there are not many on here or anywhere else. The only two solutions I could find are to change the current installation of MarkupSafe and itsdangerous to a higher version: https://serverfault.com/questions/1094062/from-itsdangerous-import-json-as-json-importerror-cannot-import-name-json-fr and another one on GitHub that tells me to essentially change the MarkUpSafe and itsdangerous installation again https://github.com/aws/aws-sam-cli/issues/3661, I have also tried to make a virtual environment named veganetworkscriptenv to install the packages but that has also failed as well. I am currently using Flask 2.0.0 and Docker 5.0.0 and the error occurs on line eight in vegamain.py.

Here is the full ImportError that I get when I try and run the program:

1veganetworkscript-backend-1  | Traceback (most recent call last):
2veganetworkscript-backend-1  |   File &quot;/app/vegamain.py&quot;, line 8, in &lt;module&gt;
3veganetworkscript-backend-1  |     from flask import Flask
4veganetworkscript-backend-1  |   File &quot;/usr/local/lib/python3.9/site-packages/flask/__init__.py&quot;, line 19, in &lt;module&gt;
5veganetworkscript-backend-1  |     from . import json
6veganetworkscript-backend-1  |   File &quot;/usr/local/lib/python3.9/site-packages/flask/json/__init__.py&quot;, line 15, in &lt;module&gt;
7veganetworkscript-backend-1  |     from itsdangerous import json as _json
8veganetworkscript-backend-1  | ImportError: cannot import name 'json' from 'itsdangerous' (/usr/local/lib/python3.9/site-packages/itsdangerous/__init__.py)
9veganetworkscript-backend-1 exited with code 1
10

Here are my requirements.txt, vegamain.py, Dockerfile, and docker-compose.yml files:

requirements.txt:

1veganetworkscript-backend-1  | Traceback (most recent call last):
2veganetworkscript-backend-1  |   File &quot;/app/vegamain.py&quot;, line 8, in &lt;module&gt;
3veganetworkscript-backend-1  |     from flask import Flask
4veganetworkscript-backend-1  |   File &quot;/usr/local/lib/python3.9/site-packages/flask/__init__.py&quot;, line 19, in &lt;module&gt;
5veganetworkscript-backend-1  |     from . import json
6veganetworkscript-backend-1  |   File &quot;/usr/local/lib/python3.9/site-packages/flask/json/__init__.py&quot;, line 15, in &lt;module&gt;
7veganetworkscript-backend-1  |     from itsdangerous import json as _json
8veganetworkscript-backend-1  | ImportError: cannot import name 'json' from 'itsdangerous' (/usr/local/lib/python3.9/site-packages/itsdangerous/__init__.py)
9veganetworkscript-backend-1 exited with code 1
10Flask==2.0.0
11Flask-SQLAlchemy==2.4.4
12SQLAlchemy==1.3.20
13Flask-Migrate==2.5.3
14Flask-Script==2.0.6
15Flask-Cors==3.0.9
16requests==2.25.0
17mysqlclient==2.0.1
18pika==1.1.0
19wolframalpha==4.3.0
20

vegamain.py:

1veganetworkscript-backend-1  | Traceback (most recent call last):
2veganetworkscript-backend-1  |   File &quot;/app/vegamain.py&quot;, line 8, in &lt;module&gt;
3veganetworkscript-backend-1  |     from flask import Flask
4veganetworkscript-backend-1  |   File &quot;/usr/local/lib/python3.9/site-packages/flask/__init__.py&quot;, line 19, in &lt;module&gt;
5veganetworkscript-backend-1  |     from . import json
6veganetworkscript-backend-1  |   File &quot;/usr/local/lib/python3.9/site-packages/flask/json/__init__.py&quot;, line 15, in &lt;module&gt;
7veganetworkscript-backend-1  |     from itsdangerous import json as _json
8veganetworkscript-backend-1  | ImportError: cannot import name 'json' from 'itsdangerous' (/usr/local/lib/python3.9/site-packages/itsdangerous/__init__.py)
9veganetworkscript-backend-1 exited with code 1
10Flask==2.0.0
11Flask-SQLAlchemy==2.4.4
12SQLAlchemy==1.3.20
13Flask-Migrate==2.5.3
14Flask-Script==2.0.6
15Flask-Cors==3.0.9
16requests==2.25.0
17mysqlclient==2.0.1
18pika==1.1.0
19wolframalpha==4.3.0
20# Veganetwork (C) TetraSystemSolutions 2022
21# all rights are reserved.  
22# 
23# Author: Trevor R. Blanchard Feb-19-2022-Jul-30-2022
24#
25
26# get our imports in order first
27from flask import Flask # &lt;-- error occurs here!!!
28
29# start the application through flask.
30app = Flask(__name__)
31
32# if set to true will return only a &quot;Hello World&quot; string.
33Debug = True
34
35# start a route to the index part of the app in flask.
36@app.route('/')
37def index():
38    if (Debug == True):
39        return 'Hello World!'
40    else:
41        pass
42
43# start the flask app here ---&gt;
44if __name__ == '__main__':
45    app.run(debug=True, host='0.0.0.0') 
46

Dockerfile:

1veganetworkscript-backend-1  | Traceback (most recent call last):
2veganetworkscript-backend-1  |   File &quot;/app/vegamain.py&quot;, line 8, in &lt;module&gt;
3veganetworkscript-backend-1  |     from flask import Flask
4veganetworkscript-backend-1  |   File &quot;/usr/local/lib/python3.9/site-packages/flask/__init__.py&quot;, line 19, in &lt;module&gt;
5veganetworkscript-backend-1  |     from . import json
6veganetworkscript-backend-1  |   File &quot;/usr/local/lib/python3.9/site-packages/flask/json/__init__.py&quot;, line 15, in &lt;module&gt;
7veganetworkscript-backend-1  |     from itsdangerous import json as _json
8veganetworkscript-backend-1  | ImportError: cannot import name 'json' from 'itsdangerous' (/usr/local/lib/python3.9/site-packages/itsdangerous/__init__.py)
9veganetworkscript-backend-1 exited with code 1
10Flask==2.0.0
11Flask-SQLAlchemy==2.4.4
12SQLAlchemy==1.3.20
13Flask-Migrate==2.5.3
14Flask-Script==2.0.6
15Flask-Cors==3.0.9
16requests==2.25.0
17mysqlclient==2.0.1
18pika==1.1.0
19wolframalpha==4.3.0
20# Veganetwork (C) TetraSystemSolutions 2022
21# all rights are reserved.  
22# 
23# Author: Trevor R. Blanchard Feb-19-2022-Jul-30-2022
24#
25
26# get our imports in order first
27from flask import Flask # &lt;-- error occurs here!!!
28
29# start the application through flask.
30app = Flask(__name__)
31
32# if set to true will return only a &quot;Hello World&quot; string.
33Debug = True
34
35# start a route to the index part of the app in flask.
36@app.route('/')
37def index():
38    if (Debug == True):
39        return 'Hello World!'
40    else:
41        pass
42
43# start the flask app here ---&gt;
44if __name__ == '__main__':
45    app.run(debug=True, host='0.0.0.0') 
46FROM python:3.9
47ENV PYTHONUNBUFFERED 1
48WORKDIR /app
49COPY requirements.txt /app/requirements.txt
50RUN pip install -r requirements.txt
51COPY . /app
52

docker-compose.yml:

1veganetworkscript-backend-1  | Traceback (most recent call last):
2veganetworkscript-backend-1  |   File &quot;/app/vegamain.py&quot;, line 8, in &lt;module&gt;
3veganetworkscript-backend-1  |     from flask import Flask
4veganetworkscript-backend-1  |   File &quot;/usr/local/lib/python3.9/site-packages/flask/__init__.py&quot;, line 19, in &lt;module&gt;
5veganetworkscript-backend-1  |     from . import json
6veganetworkscript-backend-1  |   File &quot;/usr/local/lib/python3.9/site-packages/flask/json/__init__.py&quot;, line 15, in &lt;module&gt;
7veganetworkscript-backend-1  |     from itsdangerous import json as _json
8veganetworkscript-backend-1  | ImportError: cannot import name 'json' from 'itsdangerous' (/usr/local/lib/python3.9/site-packages/itsdangerous/__init__.py)
9veganetworkscript-backend-1 exited with code 1
10Flask==2.0.0
11Flask-SQLAlchemy==2.4.4
12SQLAlchemy==1.3.20
13Flask-Migrate==2.5.3
14Flask-Script==2.0.6
15Flask-Cors==3.0.9
16requests==2.25.0
17mysqlclient==2.0.1
18pika==1.1.0
19wolframalpha==4.3.0
20# Veganetwork (C) TetraSystemSolutions 2022
21# all rights are reserved.  
22# 
23# Author: Trevor R. Blanchard Feb-19-2022-Jul-30-2022
24#
25
26# get our imports in order first
27from flask import Flask # &lt;-- error occurs here!!!
28
29# start the application through flask.
30app = Flask(__name__)
31
32# if set to true will return only a &quot;Hello World&quot; string.
33Debug = True
34
35# start a route to the index part of the app in flask.
36@app.route('/')
37def index():
38    if (Debug == True):
39        return 'Hello World!'
40    else:
41        pass
42
43# start the flask app here ---&gt;
44if __name__ == '__main__':
45    app.run(debug=True, host='0.0.0.0') 
46FROM python:3.9
47ENV PYTHONUNBUFFERED 1
48WORKDIR /app
49COPY requirements.txt /app/requirements.txt
50RUN pip install -r requirements.txt
51COPY . /app
52version: '3.8'
53services:
54  backend:
55    build:
56      context: .
57      dockerfile: Dockerfile
58    command: 'python vegamain.py'
59    ports:
60      - 8004:5000
61    volumes:
62      - .:/app
63    depends_on:
64      - db
65
66#  queue:
67#    build:
68#      context: .
69#      dockerfile: Dockerfile
70#    command: 'python -u consumer.py'
71#    depends_on:
72#      - db
73
74  db:
75    image: mysql:5.7.22
76    restart: always
77    environment:
78      MYSQL_DATABASE: admin
79      MYSQL_USER: root
80      MYSQL_PASSWORD: root
81      MYSQL_ROOT_PASSWORD: root
82    volumes:
83      - .dbdata:/var/lib/mysql
84    ports:
85      - 33069:3306
86

How exactly can I fix this code? thank you!

ANSWER

Answered 2022-Feb-20 at 12:31

I was facing the same issue while running docker containers with flask.

I downgraded Flask to 1.1.4 and markupsafe to 2.0.1 which solved my issue.

Check this for reference.

Source https://stackoverflow.com/questions/71189819