Running “docker-compose up” fails to compile successfully (Error on importing STR_NA_VALUES from pandas) in Apache Superset

Explanation of the problem

When running the command “docker-compose up” on version 1.3.2 (and 1.4.0rc3) of the Superset application, the compilation process fails. The error message generated is an “ImportError: cannot import name ‘STR_NA_VALUES’ from ‘pandas.io.parsers’ (/usr/local/lib/python3.8/site-packages/pandas/io/parsers/init.py) in most containers”.

Environment: The environment in which this issue was encountered includes the following components:

• Docker version 20.10.12, build e91ed57
• Python version 3.8.12 (as determined by running the command in the Docker container)
• Node.js version: OCI runtime exec failed: exec failed: container_linux.go:380: starting container process caused: exec: “node”: executable file not found in $PATH: unknown (as determined by running the command in the Docker container)

Reproduction Steps: The issue can be reproduced by following these steps:

1. Go to the release on the GitHub repository, download the 1.3.2 zip (https://github.com/apache/superset/archive/refs/tags/1.3.2.zip)
2. Extract the folder
3. Enter the superset-1.3.2 folder in a terminal
4. Run the command “docker-compose up”

Expected Results:

• The Superset login screen / welcome page is displayed when viewing on a browser.
• The compilation process completes successfully without error.

Actual Results:

• A stack trace of error is displayed when viewing on a browser.
• The Docker logs contain the error message “ImportError: cannot import name ‘STR_NA_VALUES’ from ‘pandas.io.parsers’ (/usr/local/lib/python3.8/site-packages/pandas/io/parsers/init.py) in most containers”.

Additional context:

• The version of pandas installed on the Superset app Docker container is 1.3.4. However, in the requirements base.txt file, the version is specified as 1.2.2. It is unclear how the version of pandas was upgraded.
• This issue may be related to a pull request on the GitHub repository, “https://github.com/apache/superset/pull/16400“
• Another user encountered a similar issue, “https://github.com/apache/superset/issues/17333“, but the resolution is not clear.

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Problem solution for Running “docker-compose up” fails to compile successfully (Error on importing STR_NA_VALUES from pandas) in Apache Superset

ImportError: cannot import name 'STR_NA_VALUES' from 'pandas.io.parsers' (/usr/local/lib/python3.8/site-packages/pandas/io/parsers/__init__.py) in most containers.

Additionally, the environment in which this error was observed includes the following specifications:

• Docker version 20.10.12
• Superset version: 1.3.2 / Superset 0.0.0dev (as per running command in docker container)
• Python version: Python 3.8.12 (as per running command in docker container)
• Node.js version: OCI runtime exec failed: exec failed: container_linux.go:380: starting container process caused: exec: “node”: executable file not found in $PATH: unknown (as per running command in docker container)

It is also worth noting that there is a discrepancy in the version of pandas being used. While the pip freeze on the superset app docker container shows that pandas is on version 1.3.4, the requirements base.txt file lists it as version 1.2.2. This could potentially be a contributing factor to the error.

Other popular problems with Apache Superset

Problem: Error when importing STR_NA_VALUES from pandas when running “docker-compose up”

When attempting to run “docker-compose up” command on version 1.3.2 (and 1.4.0rc3) of Apache Superset, the following error is encountered:

ImportError: cannot import name 'STR_NA_VALUES' from 'pandas.io.parsers' 

This error occurs in most containers, including app, worker, and worker-beat.

Solution:

The issue is related to a version mismatch between the installed pandas library and the version specified in the requirements file. The pip freeze command on the superset app docker container reveals that pandas is on version 1.3.4, while the requirements file, base.txt, specifies version 1.2.2. One solution is to update the version in the requirements file to match the installed version of pandas.

Problem: Error when running “docker-compose up” command

When attempting to run the “docker-compose up” command, the following error is encountered:

OCI runtime exec failed: exec failed: container_linux.go:380: starting container process caused: exec: "node": executable file not found in $PATH: unknown

Solution:

This error occurs because node.js is not installed or is not in the PATH. To resolve this issue, make sure that node.js is installed and that its executable is in the PATH.

Problem: Error when viewing the Superset login screen / welcome page

When attempting to view the Superset login screen / welcome page in the browser, the following error is encountered:

Presented with stack trace of error

Solution:

This error can occur due to various reasons such as misconfigurations in the superset.config.py file or missing dependencies. To troubleshoot this issue, check the superset logs for python stacktraces, ensure that all the dependencies are installed, and check the configuration settings in the superset.config.py file. Additionally, checking the Apache Superset issue tracker for similar issues can be helpful.

Most popular use cases for Apache Superset

1. Apache Superset is an open-source data visualization and business intelligence platform that allows users to create and share interactive dashboards and charts. It can be used to create visual representations of data from various sources such as SQL databases, CSV files, and others.
2. One popular use case of Apache Superset is to create interactive dashboards that allow users to explore and analyze data in real-time. This can be done by creating charts, such as line, bar, and pie charts, and adding filters and aggregate functions to the data.

from superset import db
from superset.models.slice import Slice

#Creating a new slice
slice = Slice(
    slice_name="My Chart",
    viz_type='line',
    datasource_type='table',
    datasource_id=1,
    params={
        "groupby": ["date"],
        "metric": "sum__num",
    },
)

#Saving the slice
db.session.add(slice)
db.session.commit()