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I think the Snakefile is ok, SRR3350597_GSM2112330_RA_hip_3_Homo_sapiens_RNA-Seq_1.fastq.gz is simply missing. See the ls output of yours, that file is not in it.

Figured it out thanks to the comments, thanks guys.

Yes, the file I loaded from script tag was being cached and not being updated. A solution is very easy, I just needed to create a variable counter and add it as a version to the new script every time I create it, so it's considered a new one

Unfortunately, the environment variable LD_LIBRARY_PATH must be set prior to starting the process, so changing it in your Python script won't work.

In addition, due to limitations in how the instant client is currently built, cx_Oracle.init_oracle_client() cannot be used on Linux without also previously setting LD_LIBRARY_PATH outside of the process. Hopefully that limitation will be removed soon, but in the meantime, that's what you have to do. You can also use ld.so.conf configuration to make the installation work for your entire machine, in which case setting LD_LIBRARY_PATH is no longer needed.

Have two paths - one for function one for command. Remember about quoting arguments - always quote variable expansions. Remember about quotes - your use of " quotes is strange, be consistent. Simplified proof of concept:

You have a list of dict in your first example. So first you need to select which dict you want. For instance, if your query is called 'json_list'

I guess you missed a part in the setup for the tutorial (https://snakemake.readthedocs.io/en/stable/tutorial/setup.html). In step 2, you download an environment.yaml and use it to install all needed packages. Or you could try and install all packages yourself, look at the list under "Requirements".

You can install packages using pip inside conda even though it is not the preferred method for packages that exist in conda. This method may avoid whatever is causing your conda install to be unusably slow.

According to the docs:

• There is no need to worry about creating a venv or virtualenv (older and newer styles of python virtual environments) for pip to install the package into because a conda environment is already a virtualenv
• Once you are in the conda environment you want to install the package into, just pip install

This question has some related tips.

Using a fresh conda environment also might help if the slowness is due to having a vast number of packages, or a problematic package, already in the environment. The purpose of virtual environments is to isolate the set of packages installed so other projects can't be impacted, and so you are clear which packages you are potentially using. Whether you create a fresh environment for each experiment, or do all your experiments in a common environment which gradually accumulates packages in it, is up to you.

solved by this, refer to the GitHub link. delete android and ios directories then run "flutter create" https://github.com/flutter/flutter/wiki/Workarounds-for-common-issues#generated-project-files-outdated

I solved the issue by lining up the naming convention for the attributes with the front-end and back-end. And it worked!

Thank you @jvillian for the insight!!