[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: Make interactive visualizations default for Jupyter <!-- ⚠ If you do not respect this template, your issue will be closed --> <!-- ⚠ Make sure to browse the opened and closed issues to confirm this idea does not exist. --> ### What is the expected enhancement? The interactive visualizations contributed in PR #765 are much better than the static ones, and should be default when the environment is a Jupyter notebook. This is related to Epic #707 for providing better jupyter tools. Several issues must be solved first: - These visualizations need internet connection. Can we eliminate that? - The interface of the static and interactive visualizations are all the same, except for `plot_histogram` vs `iplot_histogram`. These should be made similar for consistency. But the interactive visualization is able to plot multiple histograms in one plot. - How "heavy" is it to run these interactive visualizations? I hear my laptop fan. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the docker/compose codebase. Here's the problem: expose no longer accepts port range in yaml config file docker-compose files stopped working after updating to docker-compose version 1.5.2 (from MacOS Docker Toolbox 1.9.1g). ``` Service 'xxx' configuration key 'expose' '0' is invalid: should be of the format 'PORT[/PROTOCOL]' ``` While the file contains: ``` expose: - "8200-8219" ``` Replacing the range by a single port "resolves" the issue, or reverting to docker-compose version: 1.5.1. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: MatplotlibDeprecationWarning: The M attribute was deprecated in Matplotlib 3.4 <!-- ⚠ If you do not respect this template, your issue will be closed --> <!-- ⚠ Make sure to browse the opened and closed issues --> ### Information - **Qiskit Terra version**: 0.16.4 - **Python version**: 3.8.8 - **Operating system**: Ubuntu Linux ### What is the current behavior? When running the Bloch sphere visualization function, the following warning message appears: ``` /opt/conda/lib/python3.8/site-packages/qiskit/visualization/bloch.py:69: MatplotlibDeprecationWarning: The M attribute was deprecated in Matplotlib 3.4 and will be removed two minor releases later. Use self.axes.M instead. x_s, y_s, _ = proj3d.proj_transform(xs3d, ys3d, zs3d, renderer.M) ``` ### Steps to reproduce the problem ```py from qiskit import QuantumCircuit from qiskit.quantum_info import Statevector from qiskit.visualization import plot_bloch_multivector qc = QuantumCircuit(1) state = Statevector.from_instruction(qc) plot_bloch_multivector(state) ``` ### What is the expected behavior? No warning message ### Suggested solutions Refactor mathplotlib related codes not to use deprecated feature. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the jupyterlab/jupyterlab codebase. Here's the problem: Auto Build is in Production Mode This should be configurable and default to development mode. jupyter lab build fails in webpack install I'm trying to install jupyter lab extensions in a clean linux box. I'm getting install errors which appear to occur because jupyter lab build is calling webpack and not webpack --dev so that the devdependencies are not getting installed warning ipysheet > css-loader > cssnano > postcss-merge-rules > caniuse-api > browserslist@1.7.7: Browserslist 2 could fail on reading Browserslist >3.0 config used in other tools. [2/4] Fetching packages... [###########################----------------------------------------] 419/1051[LabBuildApp] > node /usr/lib/python3.6/site-packages/jupyterlab/staging/yarn.js run build yarn run v1.9.4 $ webpack ✖ ｢config｣: An error occurred while trying to find a config file Did you forget to specify a --require? /usr/lib/node_modules/webpack-command/node_modules/@webpack-contrib/config-loader/lib/load.js:85 throw new LoadConfigError(e, configPath); ^ LoadConfigError: Cannot find module 'fs-extra' at Function.Module._resolveFilename (module.js:547:15) at Function.Module._load (module.js:474:25) at Module.require (module.js:596:17) at require (/usr/lib/node_modules/webpack-command/node_modules/v8-compile-cache/v8-compile-cache.js:159:20) at Object.<anonymous> (/usr/share/jupyter/lab/staging/webpack.config.js:7:10) at Module._compile (/usr/lib/node_modules/webpack-command/node_modules/v8-compile-cache/v8-compile-cache.js:178:30) at Object.Module._extensions..js (module.js:663:10) at Module.load (module.js:565:32) at tryModuleLoad (module.js:505:12) at Function.Module._load (module.js:497:3) error Command failed with exit code 1. info Visit https://yarnpkg.com/en/docs/cli/run for documentation about this command. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the huggingface/transformers codebase. Here's the problem: Examples: label mapping for text classication tasks are not written into configuration Hi, I've shortly discussed this with @patrickvonplaten , and we came to the conclusion that the following scenario is a bug: When using the text classification for a GLUE task, no label mapping will be written into the configuration of the final fine-tuned model. This leads to an unesthetic "label_0" on the model hub, as it can be seen here: ![Bildschirmfoto_2021-08-27_12-17-09](https://user-images.githubusercontent.com/20651387/131112292-ab2fc8f8-2fad-42cf-b436-0a0a5e0a4475.png) One has to manually extend the `config.json`: ```json "id2label": { "0": "NEGATIVE", "1": "POSITIVE" }, "label2id": { "NEGATIVE": 0, "POSITIVE": 1 } ``` to get the following output: ![Bildschirmfoto_2021-08-27_12-17-29](https://user-images.githubusercontent.com/20651387/131112468-bff93d0f-4f3f-428d-ac3b-696ae6e08543.png) The text classification examples should be extended, so that those label mappings are automatically added to the configuration file. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the googleapis/google-cloud-python codebase. Here's the problem: Pub/Sub: return type`future` is not `concurrent.futures.Future` https://github.com/googleapis/google-cloud-python/blob/8f63393a151a22018a3d03c7a35576da25ee17b3/pubsub/google/cloud/pubsub_v1/publisher/client.py#L170 Contrary to what's in the [reference](https://gcloud-python.readthedocs.io/en/latest/pubsub/publisher/api/client.html#google.cloud.pubsub_v1.publisher.client.Client.publish), the correct return type for `publish()` should be `google.cloud.pubsub_v1.publisher.futures.Future`. I didn't find a reference for it but only some reference for [`google.cloud.pubsub_v1.subscriber.futures.StreamingPullFuture`](https://google-cloud.readthedocs.io/en/latest/pubsub/subscriber/api/futures.html). People won't be able to use of Python's concurrent library's `wait()` method on `google.cloud.pubsub_v1.publisher.futures.Future`. But our doc implies they can because we say the return type is `concurrent.futures.Future`. ```Python from concurrent.futures import wait from google.cloud import pubsub_v1 publisher = pubsub_v1.PublisherClient() # future has type `google.cloud.pubsub_v1.publisher.futures.Future` future = publisher.publish('projects/{PROJECT_ID}/topics/{TOPIC_NAME}', data=b'rain') # wait(fs, timeout=None, return_when='ALL_COMPLETED') expects a sequence of `concurrent.futures.Future`. wait([future]) ``` Here is the error: ```Python Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/usr/lib/python3.5/concurrent/futures/_base.py", line 257, in wait with _AcquireFutures(fs): File "/usr/lib/python3.5/concurrent/futures/_base.py", line 146, in __enter__ future._condition.acquire() AttributeError: 'Future' object has no attribute '_condition' ``` I tried in both Python 2 and 3. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conan-io/conan codebase. Here's the problem: [feature] Allow different cpp_info.name depending on the generator Something similar to `self.cpp_info.name['my_generator']` should work. Make it compatible with `cpp_info.name = 'name'` syntax Related to #5984 Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the huggingface/transformers codebase. Here's the problem: GPTNeo: importing model with padded vocab size should truncate wte ## Environment info <!-- You can run the command `transformers-cli env` and copy-and-paste its output below. Don't forget to fill out the missing fields in that output! --> - `transformers` version: latest from `master` ### Who can help @LysandreJik ## Information Model I am using (Bert, XLNet ...): GPTNeo Script: https://github.com/huggingface/transformers/blob/master/src/transformers/models/gpt_neo/convert_gpt_neo_mesh_tf_to_pytorch.py Some GPTNeo models are trained with a vocab size greater than the actual used vocab size (i.e 50304 in config when the actual vocab size is 50257) where all tokens after the first i.e 50257 are unused. These models cannot currently be converted using the script because there is no way to cut the extra embeddings out of wte. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: Transpiling 3+ qubit `UnitaryGate` circuits should work automatically <!-- ⚠ If you do not respect this template, your issue will be closed --> <!-- ⚠ Make sure to browse the opened and closed issues to confirm this idea does not exist. --> ### What is the expected enhancement? 3+ qubit unitary matrices can be transpiled to basis gates using the `isometry` instruction, however this is not used automatically if a circuit contains unitary gate instructions --- circuits with unitary gate instructions can currently only be transpiled if they are 1 or 2 qubits. The definition of the `UnitaryGate` class should be updated to unroll using an `isometry` instruction for 3+ qubits. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the docker/compose codebase. Here's the problem: docker-compose: --quiet for builds ```sh $ docker -v Docker version 18.05.0-ce, build f150324 $ docker-compose -v docker-compose version 1.21.2, build a133471 ``` I want to silence the output of `docker-compose build` just like there is a `--quiet` command in `docker` if so, please display the full command required to get quiet builds. I guess one could just redirect standard out, but I'd rather not do this. Many thanks, Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conan-io/conan codebase. Here's the problem: tools.vcvars() should be a no-op when not using windows and visual studio This way you can wrap all your code in: ``` with tools.vcvars(self.settings): CMake.build() ``` without having to care about what platform you are working with. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the PrefectHQ/prefect codebase. Here's the problem: Add Timeout State Suggestion: subclass `Failed` to create a `Timeout` state (or `TimedOut` state?). The nature of the failure is specific enough that this could be interesting to trap specifically. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the dagster-io/dagster codebase. Here's the problem: accept string values for non_argument_deps argument to asset decorator Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: A check_map analysis pass is needed <!-- ⚠ If you do not respect this template, your issue will be closed --> <!-- ⚠ Make sure to browse the opened and closed issues to confirm this idea does not exist. --> ### What is the expected enhancement? In https://github.com/Qiskit/qiskit-terra/pull/1270#issuecomment-439951585 @ajavadia raised the need to have a pass to check if a circuit is compatible with a coupling map. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the ipython/ipython codebase. Here's the problem: Cannot escape IPython.embed() when called repeatedly within function inside a for-loop I am running `foo.py` from the command line, and it includes a function has a for loop, inside of which is a function that has an IPython.embed() statement. This is to initialize an interpreter at that point within the function to have access to those local variables. However, when trying to escape from the embedded interpreter, it only opens a new interpreter (presumably up to k times for the for loop), effectively locking that terminal. It would be nice to have a command analogous to `ipdb`'s `q`, which immediately throws an exception and exits to the CLI in which `foo.py` was executed. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the google/jax codebase. Here's the problem: jax.random.randint range must be valid `random.randint` doesn't check that `minval` < `maxval`. If it's not, you get surprising results. For example, `print(random.randint(random.PRNGKey(10003), (), 0, 0))` yields -1234647498. The best thing would be to throw an error message, but if that's not practical then it'd at least be nice to have the behavior be defined. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the mesonbuild/meson codebase. Here's the problem: Cannot use private Qt headers without hacks https://github.com/SirCmpwn/qtlayershell/blob/6315d292a72690391d207894f066a10becd1c8e6/qtlayershell/meson.build#L1-L10 Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conan-io/conan codebase. Here's the problem: package rev broke --build missing Environment: conan version 1.18.4 Cent OS 7 conan client + artifactory We recently turned on package revisions and set the package ID to `full_package_id`. Since we did that `conan install . --build missing` is not always able to build all missing packages ```bash $ conan install . --build missing Configuration: [settings] arch=x86_64 arch_build=x86_64 build_type=Release compiler=gcc compiler.libcxx=libstdc++11 compiler.version=7 os=Linux os_build=Linux qt_version=5 [options] [build_requires] [env] [... some packages are beeing built ...] GenericSU/0.3.5@deployment/stable: WARN: Can't find a 'GenericSU/0.3.5@deployment/stable' package for the specified settings, options and dependencies: - Settings: arch=x86_64, build_type=Release, compiler=gcc, compiler.libcxx=libstdc++11, compiler.version=7, os=Linux, qt_version=5 - Options: MccApi:coverage=False, MccApi:shared=True - Dependencies: Log4Qt/0.3.0@deployment/stable, MccApi/3.0.9@deployment/testing, Util/0.3.4@deployment/stable, AppFramework/0.3.5@deployment/stable, AppLauncher/0.3.4@deployment/stable - Package ID: Package_ID_unknown ERROR: Missing prebuilt package for 'GenericSU/0.3.5@deployment/stable' Try to build it from sources with "--build GenericSU" Or read "http://docs.conan.io/en/latest/faq/troubleshooting.html#error-missing-prebuilt-package" ``` However there is a package `GenericSU/0.3.5@deployment/stable` ![grafik](https://user-images.githubusercontent.com/8710880/65147466-79de5a00-da1e-11e9-8f7a-413d27fd8207.png) Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the ipython/ipython codebase. Here's the problem: Fails to install under Jython 2.7 beta This is the error I get: ``` % pip install ipython-0.13.tar.gz Unpacking ./ipython-0.13.tar.gz Running setup.py egg_info for package from file:///home/aaditya/work/epsilon/installer/packages/ipython-0.13.tar.gz Unsupported operating system: java Complete output from command python setup.py egg_info: Unsupported operating system: java ``` Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conda/conda codebase. Here's the problem: activate on master is broken in OSX @msarahan I'm on master, and I get: ``` $ source activate koo path:usage: conda [-h] [-V] [--debug] command ... conda: error: argument command: invalid choice: '..changeps1' (choose from 'info', 'help', 'list', 'search', 'create', 'install', 'update', 'upgrade', 'remove', 'uninstall', 'run', 'config', 'init', 'clean', 'package', 'bundle') prepending /Users/ilan/python/envs/koo and /Users/ilan/python/envs/koo/cmd and /Users/ilan/python/envs/koo/bin to PATH -bash: awk: command not found -bash: dirname: command not found Traceback (most recent call last): File "/Users/ilan/python/bin/conda", line 4, in <module> from conda.cli.main import main File "/Users/ilan/conda/conda/__init__.py", line 19, in <module> __version__ = get_version(__file__, __name__) File "/Users/ilan/python/lib/python2.7/site-packages/auxlib/packaging.py", line 93, in get_version if is_git_repo(here): File "/Users/ilan/python/lib/python2.7/site-packages/auxlib/packaging.py", line 70, in is_git_repo return call(('git', 'rev-parse'), cwd=path) == 0 File "/Users/ilan/python/lib/python2.7/subprocess.py", line 522, in call return Popen(*popenargs, **kwargs).wait() File "/Users/ilan/python/lib/python2.7/subprocess.py", line 710, in __init__ errread, errwrite) File "/Users/ilan/python/lib/python2.7/subprocess.py", line 1335, in _execute_child raise child_exception ``` It is true that the new activate scripts depend on `awk` and `dirname`? Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: Auto scale pulse drawings for given channels   ### What is the expected enhancement? There's a lot of unused space with default Schedule drawing.  Changing the `scaling` option helps, but this still isn't great. We should try to automatically adjust the plotting range, or the scale, or at least not show negative values by default (it looks like the space for neg values leaves a large gap between channels, and I haven't seen it used)  Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the numpy/numpy codebase. Here's the problem: Numpy 1.16.1 fails to run tests Newly released NumPy 1.16.1 built and installed from source fails to run tests: > python3 setup.py build > sudo python3 setup.py install ``` import numpy numpy.test('full') NumPy version 1.16.1 NumPy relaxed strides checking option: True ================================================================================================================== ERRORS =================================================================================================================== _____________________________________________________________________________________________ ERROR collecting core/_multiarray_module_test.py ______________________________________________________________________________________________ import file mismatch: imported module 'numpy.core._multiarray_module_test' has this __file__ attribute: /usr/local/lib/python3.6/dist-packages/numpy-1.16.1-py3.6-linux-x86_64.egg/numpy/core/_multiarray_module_test.cpython-36m-x86_64-linux-gnu.so which is not the same as the test file we want to collect: /usr/local/lib/python3.6/dist-packages/numpy-1.16.1-py3.6-linux-x86_64.egg/numpy/core/_multiarray_module_test.py HINT: remove __pycache__ / .pyc files and/or use a unique basename for your test file modules !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! Interrupted: 1 errors during collection !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! 1 error in 4.18 seconds False ``` Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: Scheduler needs to respect MemSlots in QuantumCircuit Measures <!-- ⚠ If you do not respect this template, your issue will be closed --> <!-- ⚠ Make sure to browse the opened and closed issues --> ### Information Known bug from my PR https://github.com/Qiskit/qiskit-terra/pull/2650 ### What is the current behavior? When passing a circuit through the basic scheduler (`qiskit.scheduler.schedule`), the resulting `Schedule` will always measure qubit results into the `MemorySlot` which matches the qubit index. For example: ``` qc.measure(q[0], c[3]) ``` will measure qubit 0 into `MemorySlot(0)` rather than `MemorySlot(3)` -- it will use the default Acquire from the cmd_def which is probably something like `Acquire([0, 1], [MemSlot(0), MemSlot(1)])`. The correct behaviour is to use the classical reg from the instruction and then modify the `AcquireInstruction` from the `Schedule` returned by the `cmd_def`. It's unclear what we should do with the other qubits that are measured within the same `meas_map` group, if the user doesn't specify those other qubits to be measured. We need a follow up PR to handle this more carefully. The solution likely needs to update the helper function: `qiskit.scheduler.methods.basic.translate_gates_to_pulse_defs.get_measure_schedule` ### Steps to reproduce the problem ### What is the expected behavior? ### Suggested solutions see above Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the PrefectHQ/prefect codebase. Here's the problem: Use literal_eval for parsing configuration values ## Current behavior *Please describe how the feature works today* Currently, Prefect takes a [hardcoded stab](https://github.com/PrefectHQ/prefect/blob/master/src/prefect/configuration.py#L37) at converting strings to Python objects. We could replace this function with `ast.literal_eval()` and instantly gain a more flexible cast, including the ability to natively handle lists and dicts. ## Proposed behavior *Please describe your proposed change to the current behavior* Currently, setting `PREFECT__X__Y="['a', 'b', 3]"` results in `prefect.config.x.y == "['a', 'b', 3]"`. This means some Prefect objects (thinking of environments, but also including the config itself) must re-parse config options. This is after we already make an attempt to coerce some values to known types. Replacing this with `ast.literal_eval()` would result in `prefect.config.x.y == ['a', 'b', 3]`. ## Example *Please give an example of how the enhancement would be useful* Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: circuit.library.graph_state needs testing The object `GraphState` (in `qiskit/circuit/library/graph_state.py`) needs testing. [No line is currently coveraged](https://coveralls.io/builds/30439931/source?filename=qiskit/circuit/library/graph_state.py). Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the numpy/numpy codebase. Here's the problem: mypy --strict error when importing numpy.typing `mypy --strict` disables `implicit_reexport`. Consequently mypy throws an error when trying to import `ArrayLike` and `DTypeLike` from `numpy.typing`. ### Reproducing code example: ```python from numpy.typing import ArrayLike ``` ### Error message: ``` $ mypy --strict foo.py foo.py:1: error: Module 'numpy.typing' has no attribute 'ArrayLike' Found 1 error in 1 file (checked 1 source file) ``` ### NumPy/Python version information: ``` $ python -c 'import sys, numpy; print(numpy.__version__, sys.version)' 1.20.0rc2 3.8.6 (default, Dec 18 2020, 13:50:46) [GCC 10.2.0] $ mypy --version mypy 0.790 ``` ### Possible workarounds I guess that the reason why this happens is than `__all__` is not set when on `TYPE_CHECKING` mode: https://github.com/numpy/numpy/blob/af8e67c4fd368bae710b01f32611b10dfab02b61/numpy/typing/__init__.py#L156-L165 If setting `__all__` is not possible, a workaround might be to "explicitly reexport" the objects using something this: ``` python from ._array_like import ArrayLike as ArrayLike from ._dtype_like import DTypeLike as DTypeLike ``` It might also be possible to enable implicit reexports for this specific module using the numpy mypy plugin. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the dagster-io/dagster codebase. Here's the problem: PartitionMappings in public API and when non-partitioned assets depend on partitioned assets Fixes https://github.com/dagster-io/dagster/issues/8867 Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the apache/airflow codebase. Here's the problem: Remove or limit table of content at the main Airflow doc page Table of content here : http://apache-airflow-docs.s3-website.eu-central-1.amazonaws.com/docs/apache-airflow/latest/index.html at the main page of "apache-airflow" documentation is huge and useless (especially that we have it in directory on the left). We should remove it or limit heavily (to 1st level only) ![Screenshot from 2020-11-22 20-34-28](https://user-images.githubusercontent.com/595491/99915147-27738a00-2d02-11eb-8e6b-1e2717180f26.png) Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the numpy/numpy codebase. Here's the problem: numpy scalars: should np.set_printoptions(legacy=True) in 0.14.dev reverts to 0.13 printing? This is another thing we bumped into our scikit-learn doctests using numpy dev. If this is easy for `np.set_printoptions(legacy=True)` to use pre-dragon4 printing it would make our life (and the life of other downstream projects bumping into the same problems with doctests) a bit easier when numpy 1.14 is released. I think the expected behaviour is that `np.set_printoptions(legacy=True)` does revert to pre-dragon4 format even with all its flaws. If this is not too costly in terms of maintenance, maybe it could be considered? Note we can work-around this issue with doctests ellipsis in scikit-learn. A snippet to illustrate what I mean in more details: ```py import numpy as np try: np.set_printoptions(legacy=True) except TypeError: pass i = 6 numpy_number = np.float64(1.) - i * 1e-17 print('str : ', numpy_number) print('repr : ', repr(numpy_number)) ``` Output on numpy master: ``` str : 0.9999999999999999 repr : 0.9999999999999999 ``` Output on numpy 1.13: ``` str : 1.0 repr : 0.99999999999999989 ``` When using `np.set_printoptions(legacy=True)` I would expect both output to match. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the mesonbuild/meson codebase. Here's the problem: Meson-init can't detect vala-files Hello, I use meson init to create my mesonbuild files quickly, it works fine with "Cs, c, cpp, java" files, but does not work with Vala, I think the option has just been forgotten nothing of very serious ! it's still a bug ```No recognizable source files found. Run meson init in an empty directory to create a sample project.``` Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: latex drawer cannot draw custom gates <!-- ⚠ If you do not respect this template, your issue will be closed --> <!-- ⚠ Make sure to browse the opened and closed issues to confirm this idea does not exist. --> ### What is the expected enhancement? Currently only the text drawer is able to do this. This capability is useful when defining hiearchical circuits. Also refer to #1939 for a discussion of how to draw these. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the mesonbuild/meson codebase. Here's the problem: Boost not detected on Fedora 27 I installed `boost-devel` as well as `boost-static` using `dnf` on Fedora 27. I am including boost in a Meson project with ``` dep_boost = dependency('boost', modules : ['filesystem', 'system', 'asio']) ``` Which results in the following error messages: ``` WARNING: Invalid Boost modules: asio Dependency Boost (filesystem, system, asio) found: NO Meson encountered an error in file meson.build, line 69, column 0: Dependency "boost" not found ``` I also installed `boost-*`, which didn't help. Meson version is `0.44.0`. Works fine with `0.42.1`. To me this does not seem to be related to #2547 and #2564, my locale is English. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the google/jax codebase. Here's the problem: Implement i0e and i1e bessel functions These are useful for the von-Mises distribution on the unit circle. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conan-io/conan codebase. Here's the problem: tools.which also returns dirs Hi, `tools.which` can returns a folder path if his basename match. For example, on Windows, it returns `C:\Program Files (x86)\Microsoft Visual Studio\2017\Community\Common7\IDE\CommonExtensions\Microsoft\TeamFoundation\Team Explorer\Git` which is a directory. You can reproduce with: ```python import os from conans import tools tools.mkdir("C:\Dev") tools.mkdir("C:\Dev\Git") with tools.environment_append({"PATH": "C:\Dev\;"+tools.get_env("PATH")}): git = tools.which("git") # returns "C:\Dev\git" print(os.path.isfile(git)) # Is False ``` I work with: * Conan 1.3.3 * Windows 10 1709 Thanks ! Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the googleapis/google-cloud-python codebase. Here's the problem: blob.acl.save_predefined() only works for private [From the documentation.](https://googlecloudplatform.github.io/gcloud-python/stable/storage-acl.html#gcloud.storage.acl.ACL.save_predefined) > Must be one of the keys in [_PREDEFINED_ACLS](https://github.com/tseaver/gcloud-python/blob/1a210341811aff3b4185f830b07e87b22c1ef73d/gcloud/storage/acl.py#L171) ``` Python _PREDEFINED_ACLS = frozenset([ "private", "project-private", "public-read", "public-read-write", "authenticated-read", "bucket-owner-read", "bucket-owner-full-control", ]) ``` Let's try. ``` Python >>> blob.acl.save_predefined('public-read') ... gcloud.exceptions.BadRequest: 400 Invalid string value: 'public-read'. Allowed values: [authenticatedread, bucketownerfullcontrol, bucketownerread, private, projectprivate, publicread] >>> blob.acl.save_predefined('publicread') ... ValueError: Invalid predefined ACL: publicread ``` Coincidentally, the [tests](https://github.com/tseaver/gcloud-python/blob/1a210341811aff3b4185f830b07e87b22c1ef73d/gcloud/storage/test_acl.py#L633) only try _private_. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the googleapis/google-cloud-python codebase. Here's the problem: Document format for Cloud Storage URIs used in BigQuery BigQuery APIs which load table data from (or extract it to) Cloud Storage blobs take URIs of the format, `gs://<bucket-name>/<object-name-or-glob>`. Ensure that the docstrings for those methods document the expected URI format. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the huggingface/transformers codebase. Here's the problem: [examples] replicate the new `--log_level` feature to all trainer-based pytorch examples https://github.com/huggingface/transformers/pull/12276 introduced a new `--log_level` feature, which now allows users to set their desired log level via CLI or TrainingArguments. `run_translation.py` was used as a "model" for other examples. Now we need to replicate this to all other Trainer-based examples under examples/pytorch/, the 3 changes are 1. importing datasets 2. using `training_args.get_node_log_level()` and setting log_level in 3 modules 3. replacing `datasets` object name with `raw_datasets`, since otherwise we have a conflict with `datasets` the module. and the relevant diff is [here](https://github.com/huggingface/transformers/pull/12276/files?file-filters%5B%5D=.py#diff-09777f56cee1060a535a72ce99a6c96cdb7f330c8cc3f9dcca442b3f7768237a) and of course since we don't quite have extensive tests for examples, you can just test with a staple cmd from the corresponding README.md with `--log_level=error` and check that almost all logs are gone. This is open to all. And thank you. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Lightning-AI/lightning codebase. Here's the problem: Checkpoint naming broken ## 🐛 Bug I would like to be able to save checkpoints with custom names that include the value of my `val_loss`, ie. `path/epoch_2-val_loss_0.2.hdf5 `. The [documentation](https://pytorch-lightning.readthedocs.io/en/latest/pytorch_lightning.callbacks.html#pytorch_lightning.callbacks.ModelCheckpoint) for `ModelCheckpoint` suggests that this is possible using the `filepath` argument. This does not appear to be the case, since the [source code](https://github.com/PyTorchLightning/PyTorch-Lightning/blob/master/pytorch_lightning/callbacks/pt_callbacks.py#L247) calls `os.mkdirs(filepath)`. I have also tried using the `prefix` argument, but it doesn't seem to be possible to pass it a format string containing a variable. ## Expected behavior The documentation claims that `filepath='{epoch:02d}-{val_loss:.2f}.hdf5'` will save a checkpoint at `/path/epoch_2-val_loss_0.2.hdf5`. Instead, it saves a checkpoint at `{epoch:02d}-{val_loss:.2f}.hdf5/_ckpt_epoch_1.ckpt`. The issues in the documentation are two-fold: -- It suggests that `filepath` can contain the directory + name of the checkpoint, when it seems like it should only contain the directory specifying where to save. -- It suggests that it can 'contain named formatting options to be auto-filled', which also doesn't seem to be the case. Is it possible to achieve this functionality with the `prefix` argument instead? If so, how? Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the ipython/ipython codebase. Here's the problem: client doesn't use connection file's 'location' in disambiguating 'interface' be9601be0603cd5de781c4f91b8fc6a3120c9839 seems to have changed client.py to stop using `location` in the call to `util.disambiguate_ip_address` (previously `util.disambiguate_url`). This means that if `interface`'s address is '*', the client tries to connect to localhost, which doesn't seem to me to be the correct behaviour. The fix appears to be as simple as ``` - addr = util.disambiguate_ip_address(addr) + addr = util.disambiguate_ip_address(addr, location) ``` Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the DataDog/integrations-core codebase. Here's the problem: [Supervisor] Can't use user & pass options when using socket On my Supervisor installation, I have no `[inet_http_server]` section, and yet I can do `supervisorctl -c supervisord.conf -u <user> -p <password>` **/etc/supervisor/supervisord.conf** ```ini [unix_http_server] file=/var/run/supervisor.sock [supervisord] ... [rpcinterface:supervisor] supervisor.rpcinterface_factory = supervisor.rpcinterface:make_main_rpcinterface [supervisorctl] serverurl=unix:///var/run/supervisor.sock ``` The code of the integration ignores the `user` & `pass` options when there is a `socket` option. https://github.com/DataDog/integrations-core/blob/5693dc717d4e41533aa693e2a87ad90f08a5985a/supervisord/datadog_checks/supervisord/supervisord.py#L164-L177 Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the apache/airflow codebase. Here's the problem: Manual versioninig with semver for the first release of providers The first release can be manually versioned with 0.1.0 version for all packages. No automation is yet needed. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the numpy/numpy codebase. Here's the problem: Improve documentation of numpy.rint() ## Documentation The difference between `numpy.around()` and `numpy.rint()` is not clear. The doc says: https://numpy.org/doc/stable/reference/generated/numpy.around.html#numpy.around Evenly round to the given number of decimals. https://numpy.org/doc/stable/reference/generated/numpy.rint.html#numpy.rint Round elements of the array to the nearest integer. - `numpy.rint()` seems to also round to even, so the docstring would better be "*Evenly* round elements of the array to the nearest integer." - It seems that `around()` is a more general function but for the default `decimals=0`, `numpy.around(a)` is equal to `numpy.rint(a)`. It would be good to mention that (or if it's different, what the difference is). Can somebody with more insight into this please comment? I'm happy to provide a PR with improved docs, once I understand this. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the docker/compose codebase. Here's the problem: docker-compose network ipam additional properties are not allowed Encounter this issue in the v1.12 & v1.11: ERROR: The Compose file './docker-compose.yml' is invalid because: networks.test.ipam value Additional properties are not allowed ('driver_opts' was unexpected) It has been resolved at docker-py: docker/docker-py#1165 networks part in docker-compose.yml: ```yml networks: internal: driver: bridge internal: true ipam: driver: default onlyoffice: driver: qnet ipam: driver: qnet driver_opts: iface: DEFAULT_NIC ``` Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the googleapis/google-cloud-python codebase. Here's the problem: Logging: payload should be parsed as optional google-cloud-python requires a valid value for the `payload` field in a log entry. However, the proto shows its optional - [https://github.com/googleapis/googleapis/blob/master/google/logging/v2/log_entry.proto#L68](https://github.com/googleapis/googleapis/blob/master/google/logging/v2/log_entry.proto#L68) and i've verified i can emit a log entry w/ `payload=None` and simply the http_request value (this is used in logs groups) Looks like its checked for a value here * https://github.com/GoogleCloudPlatform/google-cloud-python/blob/master/logging/google/cloud/logging/entries.py#L128 ```python if logger is None: logger_name = logger_name_from_path(logger_fullname) logger = loggers[logger_fullname] = client.logger(logger_name) payload = resource[cls._PAYLOAD_KEY] insert_id = resource.get('insertId') timestamp = resource.get('timestamp') ``` * https://github.com/GoogleCloudPlatform/google-cloud-python/blob/master/logging/google/cloud/logging/_helpers.py#L47 ```python if 'textPayload' in resource: return TextEntry.from_api_repr(resource, client, loggers) elif 'jsonPayload' in resource: return StructEntry.from_api_repr(resource, client, loggers) elif 'protoPayload' in resource: return ProtobufEntry.from_api_repr(resource, client, loggers) raise ValueError('Cannot parse log entry resource.') ``` Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conan-io/conan codebase. Here's the problem: [workspace] Adding "conan-project" feature, to allow simultaneous edition of connected packages Everything in user space, linking in user space. How? Redirecting packages "rootfolder" to local folder, not to conan cache. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the huggingface/transformers codebase. Here's the problem: Add in `model.generate` support to encoder outputs for flax models # 🚀 Feature request <!-- A clear and concise description of the feature proposal. Please provide a link to the paper and code in case they exist. --> Add support to encoder outputs in `model.generate` for flax models (similar to Pytorch models). ## Motivation <!-- Please outline the motivation for the proposal. Is your feature request related to a problem? e.g., I'm always frustrated when [...]. If this is related to another GitHub issue, please link here too. --> With JAX, we need to pass a seed for each generation iteration. So when we want different samples, we may need to run the same function multiple times. For Encoder/Decoder models such as Bart, we could calculate the encoder outputs once and then directly pass them to the decoder, which could potentially save half of the computations (when encoder/decoder have same size). ## Your contribution <!-- Is there any way that you could help, e.g. by submitting a PR? Make sure to read the CONTRIBUTING.MD readme: https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md --> Not sure the best way to implement it but it seems that they typically come from `model._prepare_encoder_decoder_kwargs_for_generation` @patil-suraj @patrickvonplaten Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the ipython/ipython codebase. Here's the problem: use XDG_CACHE_HOME for cython objects cython magics fill a lot of object files into the ipython configuration directory usually located in XDG_CONFIG_HOME A better place for these would be the the XDG_CACHE_HOME as they in can be deleted and recreated easily. This is relevant for users with the HOME folder on a shared filesystem with a low quota, who set XDG_CACHE_HOME to a local folder to save space and better performance. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the ipython/ipython codebase. Here's the problem: ipython console ignoring some stream messages? In JuliaLang/IJulia.jl#153, @cbecker commented that `ipython console` does not seem to get standard output (which is sent to the console via `stream` messages according to the message spec). I confirmed this: ``` $ ipython console --profile julia Python 2.7.1 (r271:86832, Jul 31 2011, 19:30:53) Type "copyright", "credits" or "license" for more information. IPython 1.1.0 -- An enhanced Interactive Python. ? -> Introduction and overview of IPython's features. %quickref -> Quick reference. help -> Python's own help system. object? -> Details about 'object', use 'object??' for extra details. IPython profile: julia Starting kernel event loops. In [1]: In [1]: ccall(:printf, Cint, (Ptr{Uint8},), "Hello world!\n") Out[1]: 13 ``` It works (prints `"Hello world!"`) in both the `qtconsole` and `notebook` front-ends, so it seems like it may be a bug in the `console` front-end. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the apache/airflow codebase. Here's the problem: Use appropriate TaskInstance object related to TaskFail to get execution_date `TaskFail` instance has no execution_date attribute. Fetch execution_date from the relevant `TaskInstance` object to form the dictionary key tuple. closes: #22933 related: #22933 Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the numpy/numpy codebase. Here's the problem: legacy 1.13 printing edge case: missing superfluous comma after ellipsis I think this is the last quirk that we found when running the scikit-learn doctests. After this one you will hopefully not hear from me for a while ;-). We have only one doctest affected by this and we can work around this easily by using `repr` instead of `print` or using doctest ellipsis. This edge case does break the `legacy='1.13'` promise so I thought I would let you know and then you can decide whether you want to fix it (i.e. match the buggy behaviour with `legacy='1.13'`) or not. I would completely understand if you just decided to close this issue ```py import numpy as np try: np.set_printoptions(legacy='1.13') except TypeError: pass print(np.arange(10000)) ``` Output numpy dev: ``` [ 0 1 2 ... 9997 9998 9999] ``` Ouput on 1.13.3 (note the additional comma after the ellipsis): ``` [ 0 1 2 ..., 9997 9998 9999] ``` Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the apache/airflow codebase. Here's the problem: Add support for snowflake on the sql_sensor **Description** Enable the support for Snowflake on the SqlSensor. **Use case** Currently, the `SqlSensor` supports only the following connection types, - google_cloud_platform - jdbc - mssql - mysql - oracle - postgres - presto - sqlite - vertica At the moment, it doesn't have support for Snowflake. This ticket is to add support for Snowflake on the `SqlSensor`. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the googleapis/google-cloud-python codebase. Here's the problem: Add system tests for spanner datatypes Show inserting / reading all the datatypes supported by spanner, particularly: - Special-case floats (`nan`, `+inf`, `-inf`). - Arrays of all scalar types. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the mesonbuild/meson codebase. Here's the problem: Link against custom targets For integration with custom toolchains and other such stuff. Basically if you put the output of custom_target to the `link_with` line of a build target it will: - add a dependency in the usual way - add the output file to the link line - assumes that this is enough to make it work, if not, then that is the build definition writer's developer's problem This can probably only be done reasonably for static libraries. Dependencies of dependencies also don't really work, because to do so would mean having to replicate Meson's entire dependency resolution chain for custom targets. I was going to do this today but am mostly been in bed suffering from the seasonal flu. Feel free to implement this if you wish. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the mesonbuild/meson codebase. Here's the problem: configure_file fails for files encoded with not utf-8 or ascii I'm working on wrapping a project (freeglut), and one of the files in the project that need to be configured (using configure_file) is encoded in ISO-8859, and contains an character that isn't compatible with utf-8. meson dies trying to configure said file. Here's the output: ``` Could not read input file /home/user/source/mesa-demos/subprojects/freeglut-3.0.0/freeglut.rc.in: 'utf-8' codec can't decode byte 0xa9 in position 740: invalid start byte ``` I don't know if this is a case really worth solving (how many projects use encodings other than ascii or utf-8?). Since it's just changing the encoding I've just copied the file into my wrap patch. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: remove plot_state and iplot_state <!-- ⚠ If you do not respect this template, your issue will be closed --> <!-- ⚠ Make sure to browse the opened and closed issues to confirm this idea does not exist. --> ### What is the expected enhancement? These functions are not used anymore. We should remove them. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the numpy/numpy codebase. Here's the problem: savez fails on large array of objects I'm getting a RuntimeError "File size unexpectedly exceeded ZIP64 limit" when using `savez` to save a few arrays to a file, the largest of which is an array of matrices each with a different number of rows (so that the top level array's dtype is object). As best I can tell, the condition used by numpy internally to decide whether or not to pass `force_zip64=True` to the zipfile open is checking if any of the arrays to be put into the archive has nbytes greater than 2^30. My array of matrices reports nbytes less than 2^30 but in reality the total number of bytes exceeds this (it's about 1.7GB). I'm using python 3.6 and numpy 1.14.2 on Ubuntu 16.04. The following code produces the error: ```python test_data = np.asarray([np.random.rand(np.random.randint(50,100),4) for i in range(800000)]) np.savez('test', test_data=test_data) ``` whereas changing `np.random.randint(50,100)`->`75` produces no error. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the ipython/ipython codebase. Here's the problem: Floating widgets should be created at the point of code execution, not atop the page I tried running the example notebook `examples/Interactive Widgets/Variable Inspector.ipynb`, and the variable inspector is created atop the page, invisible to the user. You need to scroll back up to find it. This makes for pretty poor usabilit/discoverability. I think we should try to fix it before 3.0, if possible at all. But I don't know how much it would require a big overhaul of the scrolling model, which I know has been already the source of lots of grief. Perhaps @jdfreder has some thoughts here? Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the mesonbuild/meson codebase. Here's the problem: cpp_eh=none should set -fno-exceptions on non-MSVC compilers see title :) Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the docker/compose codebase. Here's the problem: Feature Request: `docker-compose config` Command It would be pretty nice to have a `docker-compose validate` command that would validate the structure of the YAML file. The specific use case I have in mind is for CI pipelines. - Return true if valid YAML of Docker-Compose format - Return false otherwise Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the google/jax codebase. Here's the problem: Implement stratified resampling np.digitize in XLA Hi JAX team, I'm interested in implementing efficient stratified resampling in JAX. This is a technique for variance reduction in sequential monte carlo algorithms (see section 2.2.1 in Naesseth, Lindsten, and Schön "Elements of Sequential Monte Carlo"). The algorithm provided looks like this ```python # w.shape = (N, ) # x.shape = (N, ) # assert np.sum(w) = 1 def stratified_resampling(key, w, x) : N = w.shape[0] u = (np.arange(N) + jax.random.uniform(key, (N, )) / N bins = np.cumsum(w) return x[np.digitize(u, bins)] ``` although I'm also considering a version that doesn't actually do the shuffling in the last step (saving it for a "decoding" process later on which doesn't particularly need to be fast. The immediate issue is that `np.digitize` is not implemented in JAX. As it were, I don't actually need the gradient for it, but as it's in the hot path and defeats the tracer it's causing some real pain. Even more ideally, I'd like to have something like the interface to `jax.random.categorical` where I can just use unnormalized logits. How can I help implement at least tracing through `np.digitize`? Alternatively, is there a clever way of doing stratified resampling without using `np.digitize`? Thanks Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the googleapis/google-cloud-python codebase. Here's the problem: Restore testing of grpc under py27 Once grpc 0.13.1 releases with a fix for https://github.com/grpc/grpc/issues/5280. See: https://github.com/grpc/grpc/pull/5319#issuecomment-192412023 Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the huggingface/transformers codebase. Here's the problem: Doc styling utils adds parasites new lines ## Environment info - `transformers` version: 4.2.0dev0 - Platform: Windows-10-10.0.18362-SP0 - Python version: 3.7.9 - PyTorch version (GPU?): 1.7.1 (False) - Tensorflow version (GPU?): 2.3.1 (False) - Using GPU in script?: Nope - Using distributed or parallel set-up in script?: Nope ### Who can help @sgugger ## Information Running the python util to style docs adds parasite new lines in every single docstring. See: ```bash $ python utils/style_doc.py src/transformers docs/source --max_len 119 --check_only Traceback (most recent call last): File "utils/style_doc.py", line 491, in <module> main(*args.files, max_len=args.max_len, check_only=args.check_only) File "utils/style_doc.py", line 479, in main raise ValueError(f"{len(changed)} files should be restyled!") ValueError: 345 files should be restyled! ``` See this commit for an example of what it does: https://github.com/huggingface/transformers/pull/9150/commits/b4dedd5ca25f043c66d12c774fa00a34c74dffb2 ## To reproduce Steps to reproduce the behavior: 1. Checkout and update master branch 2. run `python utils/style_doc.py src/transformers docs/source --max_len 119 --check-only` from transformers root Output: ```python Traceback (most recent call last): File "utils/style_doc.py", line 491, in <module> main(*args.files, max_len=args.max_len, check_only=args.check_only) File "utils/style_doc.py", line 479, in main raise ValueError(f"{len(changed)} files should be restyled!") ValueError: 345 files should be restyled! ``` It might have something to do with Windows or a particular setup of my machine because behavior cannot be reproduced by @patrickvonplaten. ## Expected behavior On master branch, documentation should not need to be restyled Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conan-io/conan codebase. Here's the problem: [feature] Consider using CMake's `include_guard()` in `conan_toolchain.cmake` Right now at the beginning of `conan_toolchain.cmake` `CMakeToolchain` generates: ```cmake # Avoid including toolchain file several times (bad if appending to variables like # CMAKE_CXX_FLAGS. See https://github.com/android/ndk/issues/323 if(CONAN_TOOLCHAIN_INCLUDED) return() endif() set(CONAN_TOOLCHAIN_INCLUDED TRUE) ``` When minimum version of CMake (3.10) will not be an issue anymore please consider using: https://cmake.org/cmake/help/latest/command/include_guard.html - [x] I've read the [CONTRIBUTING guide](https://github.com/conan-io/conan/blob/develop/.github/CONTRIBUTING.md). Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: Add `items()` method to `Options` ### What should we add? It would be nice if the `Options` class had a method to iterate over the entire set of options and return an iterator of all the fields and current values in the object. Right now the only way to do this is something like `options.__dict__.items()` which isn't a great user interface. So adding a dedicate method that returns an iterator of everything would be useful so we can replace all the places where users are using the `__dict__.items()` pattern (this will still be supported, but having a dedicated method will look cleaner if nothing else). Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the ipython/ipython codebase. Here's the problem: StoreMagic.autorestore not working in 1.0.0 Since upgrading Ipython to version 1.0.0, the variables I have in `%store` don't seem to be loaded on startup, and have to be refreshed manually using `%store -r`. My `ipython_config.py` file contains the line: ``` c.StoreMagic.autorestore = True ``` but this doesn't seem to have any effect. My version info is: ``` {'codename': 'An Afternoon Hack', 'commit_hash': '02da31c', 'commit_source': 'installation', 'default_encoding': 'cp1252', 'ipython_path': 'C:\\Anaconda\\lib\\site-packages\\IPython', 'ipython_version': '1.0.0', 'os_name': 'nt', 'platform': 'Windows-7-6.1.7601-SP1', 'sys_executable': 'C:\\Anaconda\\pythonw.exe', 'sys_platform': 'win32', 'sys_version': '2.7.5 |Anaconda 1.6.2 (32-bit)| (default, Jul 1 2013, 12:41:55) [MSC v.1500 32 bit (Intel)]'} ``` Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the mesonbuild/meson codebase. Here's the problem: regression in 0.53. meson cannot handle CheckCXXSourceRuns.cmake Hi there, **Describe the bug** I'm trying to link with project that uses CMake and it checks supported CPU instructions via [CHECK_CXX_SOURCE_RUNS](https://cmake.org/cmake/help/v3.0/module/CheckCXXSourceRuns.html). Meson 0.52 were handling it without any problems, but 0.53 cannot. Here is cmake file that causes issue [CPUID.cmake](https://github.com/opencv/dldt/blob/2019/inference-engine/src/extension/cmake/CPUID.cmake) **To Reproduce** You should install that project and use this meson.build: ```meson project('mytestproject', ['c', 'cpp']) inference_engine_dep = dependency('InferenceEngine', version: '>=2.0.0', required: true, method : 'cmake', modules: ['IE::inference_engine']) ``` **Expected behavior** After running `meson build/` you must see following output: ```sh Run-time dependency inferenceengine (modules: IE::inference_engine) found: YES 2.1.0 ``` **system parameters** * This is just a plain native build * Operating system is Ubuntu 18.04 * Python version is 3.6.9 * meson version is 0.53.0 Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: Can't set measurements with len=1 NumPy array ### Environment - **Qiskit Terra version**: lastest - **Python version**: - **Operating system**: ### What is happening? This fails for len=1 arrays: ```python qc = QuantumCircuit(2, 1) qc.measure([0], np.array([0])) ``` ``` ~/mambaforge/envs/qiskit/lib/python3.8/site-packages/qiskit/circuit/quantumcircuit.py in _bit_argument_conversion(bit_representation, in_array) 1106 raise CircuitError("Index out of range.") from ex 1107 except TypeError as ex: -> 1108 raise CircuitError( 1109 f"Type error handling {bit_representation} ({type(bit_representation)})" 1110 ) from ex CircuitError: "Type error handling [0] (<class 'numpy.ndarray'>)" ``` For length 2 or higher it works. Also works if cast to list. ### How can we reproduce the issue? See above ### What should happen? It should work for any length array ### Any suggestions? _No response_ Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the mesonbuild/meson codebase. Here's the problem: TypeError when setting up a build directory with LLVM linker **Describe the bug** https://gist.github.com/Akaricchi/23cde7c6782a150af568db920f17a5af **To Reproduce** Try to set up a build directory with the [llvm-mingw](https://github.com/mstorsjo/llvm-mingw) cross toolchain. Not sure if native compilation is affected. **Expected behavior** Successful generation of the build directory. **system parameters** * Cross build (windows i686 via llvm-mingw) * openSUSE Tumbleweed * Python 3.8.2 * meson 0.53.999 (b54e557a40497a0f9080e32cd0da91b2b59762cc) * ninja 1.10.0 Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the numpy/numpy codebase. Here's the problem: DOC: expand_dims returns a view Hi, if we apply expand_dims to a numpy array 'a' : b = numpy.expand_dims(a, axis=0) the 'b' is not a new array, it will be a link to the objects 'a' is it correct behavior? if so, it should be noted in the manual thanks! Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the mesonbuild/meson codebase. Here's the problem: ldconfig on install corrupts freebsd cache **Describe the bug** 2c3a68bc30cf and 6b7d43ebe0d7 make it so `ldconfig` is invoked after install. But it seems like thos corrupts the cache on FreeBSD (maybe other BSDs as well), and results in errors similar to: ld-elf.so.1: Shared object "libreadline.so.8" not found, required by "bash" when running executables after `ninja install`. Example full log: https://builds.sr.ht/~emersion/job/630186#task-tinywl Downstream discussion: https://gitlab.freedesktop.org/wlroots/wlroots/-/merge_requests/3349#note_1162574 cc @jbeich **To Reproduce** Run `ninja install` on freebsd. **Expected behavior** `ldconfig` cache isn't corrupted. **system parameters** * Is this a [cross build](https://mesonbuild.com/Cross-compilation.html) or just a plain native build (for the same computer)? no * what operating system: FreeBSD * what Python version are you using: N/A * what `meson --version`: 0.60.1 * what `ninja --version`: 1.10.2 Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conda/conda codebase. Here's the problem: should_bypass_proxies still an issue in 4.5.7 https://github.com/conda/conda/issues/7506#issuecomment-403811279 Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Lightning-AI/lightning codebase. Here's the problem: support graceful training cleanup after Keyboard Interrupt ## 🚀 Feature In the training loop, we should catch `KeyboardInterrupt` exceptions and enter a graceful termination (ie. run `on_training_end`, print profiler report, etc). ### Motivation Sometimes I'll train a model and just let it run until something interesting happens or my loss has converged. Exiting via "Ctrl + C" can be easier than waiting for "EarlyStopping" to trigger in some cases. However, I may still want certain things to occur (eg. printing out the profiler summary) after stopping training. Salesforce's AWD-LSTM has an example of this feature implemented [here](https://github.com/salesforce/awd-lstm-lm/blob/master/main.py#L287). ### Pitch Figure out what actions we want to run after a KeyboardInterrupt. Then adjust the training loop to catch this exception and ensure the aforementioned actions still run afterwards. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Lightning-AI/lightning codebase. Here's the problem: Add synced batchnorm support https://pytorch.org/docs/stable/nn.html#torch.nn.SyncBatchNorm ![image](https://user-images.githubusercontent.com/3640001/87235279-6be03800-c3a8-11ea-8fd9-efdcebed372b.png) @justusschock or @awaelchli interested? Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the PrefectHQ/prefect codebase. Here's the problem: How can I skip healthchecks with Docker storage? ## Archived from the [Prefect Public Slack Community](https://join.slack.com/t/prefect-public/shared_invite/enQtNzE5OTU3OTQwNzc1LTQ5M2FkZmQzZjI0ODg1ZTBmOTc0ZjVjYWFjMWExZDAyYzBmYjVmMTE1NTQ1Y2IxZTllOTc4MmI3NzYxMDlhYWU) **jeffbrainerd**: Hi Prefecters, I’m struggling with a peculiarity of Django, but I’m wondering if the problem is somewhat more general. The basic issue is that I need to initialize django before importing any ORM objects that many of my prefect tasks use. When Dask is running a task, I’m able to use an initialization hook to call that django function before the flow is deserialized with cloudpickle. The problem comes when building the prefect docker image -- the healthcheck fails during cloudpickle load. I’ve done some code spelunking and I can’t see an obvious way to override or provide a hook to the healthcheck script short of just hacking it (which I’m doing just to get it to pass). So I’m interested if there’s an existing workaround, or if this problem has come up before and if anyone else would benefit from some kind of mechanism for overriding, disabling or providing some kind of pre-run hook for the healthcheck script. Thanks all :pray: **chris**: Hey <@USBCBEJDV> - this is super interesting. First off, if you’d like to open an issue for a `ignore_healthchecks: bool` flag on `Docker` storage we’d be happy to get that in before the next release. Out of curiosity, is it too clunky to import the ORM objects _within_ the task definition (as opposed to the top of the file)? **jeremiah**: <@ULVA73B9P> archive “How can I skip healthchecks with Docker storage?” Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the jupyterlab/jupyterlab codebase. Here's the problem: Releasedocs <!-- Thanks for contributing to JupyterLab! Please fill out the following items to submit a pull request. See the contributing guidelines for more information: https://github.com/jupyterlab/jupyterlab/blob/master/CONTRIBUTING.md --> ## Code changes Adds documentation for releases to reflect what actually happens during a release. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conda/conda codebase. Here's the problem: `conda activate` broken in fish shell (in `native_path_to_unix`) ### Checklist - [X] I added a descriptive title - [X] I searched open reports and couldn't find a duplicate ### What happened? `conda activate` fails. MSYS2, fish shell. It used to work just fine on that same system up until a month ago. Cause of error: `native_path_to_unix(paths)` is being called with an empty string in argument `paths` and can't handle it. As a workaround, I changed this code inside [`native_path_to_unix(paths)`](https://github.com/conda/conda/blob/26c74a12042bf035b76ed8186c3dddabd1f10606/conda/activate.py#L826): ``` if paths is None: return None ``` to that: ``` if not paths: # this will be true for both None and '' return '' ``` Additional info: the code fails on another place if `native_path_to_unix` returns `None`, that's why my workaround returns `''`. Does it make sense at all to return `None`? [ERROR_REPORT_native_path_to_unix.txt](https://github.com/conda/conda/files/11898703/ERROR_REPORT_native_path_to_unix.txt) ### Conda Info _No response_ ### Conda Config ```shell ==> C:\Users\theuser\.condarc <== auto_activate_base: False channel_priority: strict channels: - conda-forge - defaults - intel ``` ### Conda list _No response_ ### Additional Context _No response_ Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the googleapis/google-cloud-python codebase. Here's the problem: Subscribe experimental doesn't appear to be retrying on retryable exceptions, also doesn't surface the error. Full context at https://github.com/GoogleCloudPlatform/google-cloud-python/issues/4841#issuecomment-386988007 downwards. gist with logs: https://gist.github.com/psalaberria002/e91956d94e82d706d65da7111a40ca24 Possible culprits: 1. `send()` and `recv()` expectedly error on `next(self.call)`, but if that was a *retryable* error that somehow re-bubbled, it would not trigger any callbacks. 2. `bidi` uses `rpc._wrapped` because `api_core` doesn't appropriately expose `add_done_callback`. This means that bidi unwraps all of the retry logic. This doesn't explain *why* retrying a perfectly normal looking error somehow still leads us to a broken stream, unless the newly opened stream also has an error. But it's unclear why that wouldn't happen when calling the initial RPC. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the googleapis/google-cloud-python codebase. Here's the problem: PubSub: declaratively drop Python 3.4 support The README and the language classifiers in `setup.py` both only claim support for Python 3.5+ (and 2.7), but not Python 3.4. However, the `python_requires` in `setup.py` does not reflect that, and does not prevent installing the library in Python 3.4. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the googleapis/google-cloud-python codebase. Here's the problem: Datastore transactions do not work without context manager [The docs](https://googlecloudplatform.github.io/gcloud-python/stable/datastore-transactions.html#gcloud.datastore.transaction.Transaction) state that you can use transactions without a context manager, but this is not exactly true because you need to resort to some private methods on `Client`: - [this file](https://gist.github.com/Bogdanp/a86192d1a2a37dd48df5ebdbb39a49d1#file-context-py-L20) uses the context manager and produces correct output - [this file](https://gist.github.com/Bogdanp/a86192d1a2a37dd48df5ebdbb39a49d1#file-failing-py-L20) uses transactions as described by the aforementioned docs and fails the assertion - [this file](https://gist.github.com/Bogdanp/a86192d1a2a37dd48df5ebdbb39a49d1#file-passing-py-L20) uses transactions along with calls to `client._push_batch` and `client._pop_batch` and produces correct output The issue is evident in [`Client.get_multi`](https://github.com/GoogleCloudPlatform/gcloud-python/blob/master/gcloud/datastore/client.py#L284) and [`Client.put_multi`](https://github.com/GoogleCloudPlatform/gcloud-python/blob/master/gcloud/datastore/client.py#L336) where `transaction` and `current` are `None` unless a `Batch` or `Transaction` has been pushed to the `_batch_stack` and the only time that happens is when you [`__enter__`](https://github.com/GoogleCloudPlatform/gcloud-python/blob/master/gcloud/datastore/batch.py#L273) a `Batch`. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conan-io/conan codebase. Here's the problem: Change `conan new` to use dict in default options From: ``` options = {"shared": [True, False]} default_options = "shared=False" ``` To: ``` options = {"shared": [True, False]} default_options = {"shared": False} ``` Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the PrefectHQ/prefect codebase. Here's the problem: Trigger for Mapped Task that resolves to "failed" only if more than x tasks fail For a particular mapped task, I may not expect 100% of the generated tasks to succeed. Further, I may not care if they don't. It would be great to have a trigger that allowed me to specify this. For example: ```python from prefect import task, Flow from prefect.triggers import some_failed @task(trigger=some_failed('>', 3)) def a_mapped_task(some_input): pass ``` Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the dagster-io/dagster codebase. Here's the problem: run status sensors monitoring jobs in other repos allow run status sensors to monitor jobs in other repos https://dagster.slack.com/archives/C01U5LFUZJS/p1660586409688809 Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the ipython/ipython codebase. Here's the problem: Input parsing with %prun clobbers escapes Running this command, where `foo.csv` is a tab-separated file ``` In [3]: %prun -s cumulative table = read_table('foo.csv', sep="\t") ``` it blows up and I stepped up to the top level to see that `sep` has been passed as `t` and not `\t` Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: Utility function to measure only a subset of qubits using OpenPulse ### What is the expected enhancement? Currently, measurement in OpenPulse is often done by getting the default measurement schedule from the `CmdDef`: ``` meas = cmd_def.get('measure', qubits=tuple(range(total_number_of_qubits))) ``` This isn't ideal because it will stimulate measurement on all qubits. More convenient would be to be able to do ``` schedule += measure_qubits(qubits_to_measure: List) ``` where `measure_qubits` is a utility function exposed within `pulse` and `qubits_to_measure` is a subset of all qubits. Only the qubits in `qubits_to_measure` will have a measurement pulse. All qubits will still have to be acquired according to the `meas_map`. The implementation may be similar to changes in the scheduler which have been started here: https://github.com/Qiskit/qiskit-terra/pull/3415 Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conan-io/conan codebase. Here's the problem: [bug] `conan_build_info --v2 publish` returns "ERROR: 400: Bad Request" Still having issues with the new `conan_build_info --v2` command. Publishing fails with "ERROR: 400: Bad Request". It seems that no trace messages are generated for this command so please let me know if you need any more info. ### Environment Details * Operating System+version: Windows 10 * Compiler+version: n/a * Conan version: 1.20.4 * Python version: 3.7.3 * Artifactory version: 6.12.1 * Python Packages: * requests 2.21.0 * six 1.12.0 ### Steps to reproduce run `conan_build_info --v2 publish buildinfo.json --url https://my_server.artifactory.cm.my_company.biz/artifactory --user <user> --password <password>` as per the [how-to](https://docs.conan.io/en/latest/howtos/generic_ci_artifactory.html#generating-build-info-from-lockfiles-information). ### Logs (Executed commands with output) - Conan command output: `ERROR: 400: Bad Request` Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the mesonbuild/meson codebase. Here's the problem: i18n module doesn't help when merging back translations At the moment we have to do: custom_target('desktop-file', input: 'org.gnome.PowerStats.desktop.in', output: 'org.gnome.PowerStats.desktop', install: true, install_dir: join_paths(get_option('datadir'), 'applications'), command: [ msgfmt, '--desktop', '--template', '@INPUT@', '-d', podir, '-o', '@OUTPUT@' ]) Which is pretty horrific for something that's going to be super common for desktop applications. It's also the same issue for AppData files, GSettings schema and lots of other file types. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the numpy/numpy codebase. Here's the problem: genfromtxt won't unpack if dtype=None Not sure if this is a bug or a feature but if I use: ``` f_data = np.genfromtxt('file.dat', dtype=None, unpack=True) ``` where `file.dat` is a standard data file with several columns (ie: http://pastebin.com/ihEW2dxS) the result is not transposed as one would expect having set `unpack=True`. For example, the line `f_data = np.loadtxt('file.dat', unpack=True)` works as expected. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the googleapis/google-cloud-python codebase. Here's the problem: BigQuery: Add missing configuration properties to LoadJob There are several properties in the load job configuration that would be useful to expose in the LoadJob object. For example, `configuration.load.destinationTable` should be exposed as a TableReference property. Perhaps we should just expose a generic "configuration" property so that we get all of the properties and reflect the API resource? Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the docker/compose codebase. Here's the problem: Add an option to the YAML file to specify an alternative signal to stop containers It would be great if we could specify a signal number in the `fig.yml` file. Fig would then use it with `docker kill -s SIGNAL` instead of `docker stop` when stopping a container. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conan-io/conan codebase. Here's the problem: [feature] Add a generator like class wrapping write_conanvcvars Create a public generator `VCVars()` class to wrap the `write_conanvcvars` command. After https://github.com/conan-io/conan/pull/9194 Change the conans/test/functional/toolchains/gnu/autotools/test_win_bash.py test Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the apache/airflow codebase. Here's the problem: Several statsd timers record seconds rather than milliseconds **Apache Airflow version**: 1.10.11 **What happened**: Statsd timers for 3 categories are reporting values 1000x off as the code passes seconds, rather rather than milliseconds (or a `timedelta()` instance) to [`StatsClient.timing()`](https://statsd.readthedocs.io/en/v3.3/reference.html#StatsClient.timing). **What you expected to happen**: The timings should be reported in milliseconds. **How to reproduce it**: Enable the `statsd` client and track reporting timings for: * `dag.loading-duration.*` (emitted from `models/dagbag.py`) * `dag.<dag_id>.<task_id>.duration` (emitted from `models/taskinstance.py`) * `dag_processing.last_duration.<filename>` (emitted from `utils/dag_processing.py`) and it's deprecated alias `dag_processing.last_runtime.*` **Anything else we need to know**: This was reported before, for the `dag_processing.last_*` stats, at https://issues.apache.org/jira/browse/AIRFLOW-6088. The accompanying pull request #6682, fixed 2 out of 3 of these, but only for Airflow 2.0. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the ipython/ipython codebase. Here's the problem: __file__ is not defined when file end with .ipy I named my IPython file.ipy I propose .ipy ? objections ? I feel ipython should not be confused with plain python! ``` echo "#!/usr/bin/env ipython" > test.ipy echo "print __file__" >> test.ipy cat test.ipy #!/usr/bin/env ipython print __file__ ``` ``` chmod +x test.ipy ./test.ipy > NameError: name '__file__' is not defined ipython test.ipy > NameError: name '__file__' is not defined ## run with plain python python test.ipy > ./test.ipy SUCCESS: ## rename file to be .py seems to solve the issue mv ./test.ipy ./test.py ipython test.ipy > ./test.py SUCCESS: ./test.py > ./test.py SUCCESS: ``` Should we not trust files with different endings... I have a feeling files not ending with .py are blacklisted to prevent issues with cgi or something... not to sure.. Perhaps it has something to do with the she-bang notation..? debian kubuntu 12.10 ``` ipython -v 0.12.1 ``` Thanks Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: set tolerance on isometry conversion <!-- ⚠ If you do not respect this template, your issue will be closed --> <!-- ⚠ Make sure to browse the opened and closed issues to confirm this idea does not exist. --> ### What is the expected enhancement? Can the tolerance made to be user definable for setting the tolerance in the isometry to circuit conversion in https://github.com/Qiskit/qiskit-terra/blob/master/qiskit/extensions/quantum_initializer/isometry.py Right now the tolerance is hard-coded to be 1e-10, but it would be useful for the user to be able to adjust this tolerance. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conda/conda codebase. Here's the problem: confusing error message when boto is missing If one tries to install from an s3 channel (e.g., `conda install foo -c s3://bar/baz/conda`) while in an environment, this message shows up: `Error: boto is required for S3 channels. Please install it with: conda install boto`. Installing `boto` in the environment doesn't actually solve the problem, however, because `boto` has to be installed into the main set of packages (e.g., `source deactivate; conda install boto`). Perhaps a simple edit to the error message would address this. (e.g., `Error: boto is required for S3 channels. Please install it with: conda install boto. Make sure to run "source deactivate" if you are in an environment.`) Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the mesonbuild/meson codebase. Here's the problem: run_command() with compiler object behind ccache fails. So say you have a compiler object `cc`: ``` cc = meson.get_compiler('c') ``` This compiler is a GCC behind ccache. `cc.get_id()` returns `gcc`, `cc.version()` returns the GCC version and other features seem to work well (`cc.compiles()` and whatnot). But `run_command()` seems to be run on ccache directly! For instance, try to run: `run_command(cc, '-v')` You won't get the output of `gcc -v` but the one of `ccache -v` (which is an invalid option, so `run_command(cc, '-v').returncode()` is 0, `stdout()` is empty and `stderr()` is ccache usage). P.S.: `run_command()` [docs](https://mesonbuild.com/Reference-manual.html#run_command) says explicitly it should work on a compiler object: > Runs the command specified in positional arguments. command can be a string, or the output of find_program(), files() or configure_file(), or a compiler object. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the docker/compose codebase. Here's the problem: Running one-off containers does not work in 1.3, "is already in use" I used to run tests in docker by running one-off containers, but that is not possible in 1.3. When i try i says ``` $ docker-compose run backend npm test Conflict. The name "app_backend_run_1" is already in use by container e46cb8f520ad. You have to delete (or rename) that container to be able to reuse that name. ``` Same commando that I used before. I have tried running `docker-compose up` and also `docker-compose migrate-to-labels` How do you run one-off containers, like the docs propose https://github.com/docker/compose/blob/master/docs/cli.md#run Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the PrefectHQ/prefect codebase. Here's the problem: Redis Tasks Using https://github.com/andymccurdy/redis-py let's add some tasks for communicating with Redis. These tasks should first connect to a Redis instance and then execute their respective commands. As a first pass (and to keep this minimal) let's add tasks for both `set` and `get` then branch out from there if there are more obvious basic commands we want to support. Other than those two we should also add a task for `execute_command` in which a task would take in a custom Redis command to execute against a db. - [ ] set - [ ] get - [ ] execute_command Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the googleapis/google-cloud-python codebase. Here's the problem: extract_table does not check that the job config is an ExtractJobConfig See: https://github.com/GoogleCloudPlatform/python-docs-samples/issues/1281 bigquery_client = bigquery.Client() dataset_ref = bigquery_client.dataset(dataset_id) table_ref = dataset_ref.table(table_id) job_config = bigquery.LoadJobConfig() job_config.source_format = 'NEWLINE_DELIMITED_JSON' job = bigquery_client.extract_table(table_ref, destination, job_config=job_config) job.result() # Waits for job to complete print('Exported {}:{} to {}'.format( dataset_id, table_id, destination)) Fails with an error ``` google.api_core.exceptions.BadRequest: 400 Operation cannot be performed on a nested schema ``` Whereas it should fail because the `job_config` argument is a `LoadJobConfig`, not a `ExtractJobConfig`. Can you help me debug this systematically and explain your reasoning?