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I am setting a python code step that I have previously used in other workflows with no problem, but the workflow is throwing this error:
Command failed: python3 -m pip install --target=/tmp/__pdg__/dist/python -r requirements.txt --upgrade WARNING: The directory '/home/sbx_user1051/.cache/pip' or its parent directory is not owned or is not writable by the current user. The cache has been disabled. Check the permissions and owner of that directory. If executing pip with sudo, you should use sudo's -H flag. error: subprocess-exited-with-error × Building wheel for cchardet (pyproject.toml) did not run successfully. │ exit code: 1 ╰─> [23 lines of output] running bdist_wheel running build running build_py creating build creating build/lib.linux-x86_64-cpython-312 creating build/lib.linux-x86_64-cpython-312/cchardet copying src/cchardet/version.py -> build/lib.linux-x86_64-cpython-312/cchardet copying src/cchardet/__init__.py -> build/lib.linux-x86_64-cpython-312/cchardet running build_ext building 'cchardet._cchardet' extension creating build/temp.linux-x86_64-cpython-312 creating build/temp.linux-x86_64-cpython-312/src creating build/temp.linux-x86_64-cpython-312/src/cchardet creating build/temp.linux-x86_64-cpython-312/src/ext creating build/temp.linux-x86_64-cpython-312/src/ext/uchardet creating build/temp.linux-x86_64-cpython-312/src/ext/uchardet/src creating build/temp.linux-x86_64-cpython-312/src/ext/uchardet/src/LangModels gcc -fno-strict-overflow -Wsign-compare -DNDEBUG -g -O3 -Wall -fPIC -Isrc/ext/uchardet/src -I/var/lang/include/python3.12 -c src/cchardet/_cchardet.cpp -o build/temp.linux-x86_64-cpython-312/src/cchardet/_cchardet.o src/cchardet/_cchardet.cpp:196:12: fatal error: longintrepr.h: No such file or directory 196 | #include "longintrepr.h" | ^~~~~~~~~~~~~~~ compilation terminated. error: command '/usr/bin/gcc' failed with exit code 1 [end of output] note: This error originates from a subprocess, and is likely not a problem with pip. ERROR: Failed building wheel for cchardet ERROR: Could not build wheels for cchardet, which is required to install pyproject.toml-based projects [notice] A new release of pip is available: 23.2.1 -> 24.0 [notice] To update, run: pip install --upgrade pip
The i import statements self:
import base64
import re
import requests
from talon.quotations import extract_from
from bs4 import BeautifulSoup
from dateutil.parser import parse
Please help me RCA this based on the pipedream docs and the code + error
Based on the error message you’ve provided, it seems like the issue is with installing the cchardet package, which is a dependency required by your Python code. The error specifically mentions that building the wheel for cchardet did not run successfully due to a missing file (longintrepr.h) and a failed command (/usr/bin/gcc). From the Pipedream documentation, we know that some Python packages require binaries present within the environment to function properly, or they include binaries that are not compatible with the Pipedream workflow environment. Unfortunately, Pipedream cannot support these types of packages at this time. This seems to be the case with the cchardet package, as indicated by the error message related to the compilation process and the missing file. To address this issue, you have a few options: 1. Find an Alternative Package: Look for an alternative package that does not require compilation or has fewer dependencies on binaries not available in the Pipedream environment. For parsing and character detection, you might explore other libraries that offer similar functionality but with better compatibility. 2. Modify Your Code: If the functionality provided by cchardet is not critical to your workflow, consider modifying your code to remove the dependency on this package. This might involve using built-in Python libraries or other compatible packages for your needs. 3. Report the Issue: Although Pipedream currently does not support packages requiring specific binaries, it’s still valuable to report this issue. You can open an issue on Pipedream’s GitHub detailing the problem. This helps the Pipedream team track demand for supporting such packages and might lead to a solution in the future. For more information on the limitations of Python packages in Pipedream and to report issues, please visit Pipedream’s Python FAQ. Remember, when working with Python in Pipedream, you have access to a wide range of PyPI packages, but some packages might not be compatible due to the reasons mentioned above. Always consider the environment and the available documentation when integrating third-party packages into your workflows.
Based on the information provided and the relevant Pipedream documentation, it seems you’re inquiring about the use of the cchardet package from PyPI in a Pipedream workflow. While Pipedream supports Python and allows the use of many packages available on PyPI, there are some limitations. Specifically, some Python packages require binaries present within the environment to function properly, or they include binaries that are not compatible with the Pipedream workflow environment. If cchardet is functioning in your Pipedream workflow, it’s likely because it doesn’t fall into the category of packages that are unsupported due to the reasons mentioned above. However, if you encounter any issues or if the package stops working, it could be related to these limitations. For more detailed information on Python support and package limitations within Pipedream, you can refer to the Python documentation on Pipedream’s website (Python in Pipedream) and the FAQs regarding Python package installation issues (Python FAQs). If you have specific issues or errors with cchardet or any other package, I recommend opening an issue on Pipedream’s GitHub for further assistance.
The Pipedream runtime was recently updated to support Python 3.12—when you test or re-deploy a workflow, it uses the new runtime.
If you can find a replacement for the extract_from import, I think the workflow should work in the new runtime.
For example, ChatGPT gave me this:
import re
def extract_from(message_body):
# Regex pattern to match lines that are quoted messages, considering
# lines that start with ">" possibly preceded by whitespace and
# capturing multiline quoted blocks
quoted_message_pattern = re.compile(r"^\s**>.**(?:\n\s**>.**)*", re.MULTILINE)
# Split the message body into lines
lines = message_body.split('\n')
# Filter out lines that match the quoted message pattern
original_lines = [line for line in lines if not re.match(quoted_message_pattern, line)]
# Join the remaining lines back into a single string
original_message = '\n'.join(original_lines).strip()
return original_message
Hey That makes sense, I was just coming that conclusion myself after some digging - I appreciate your message and you taking the time to generate that example. Thanks! (great name btw lol)