Title: [Bug]: Memory leak in 3.4.3 · Issue #21259 · matplotlib/matplotlib · GitHub
Open Graph Title: [Bug]: Memory leak in 3.4.3 · Issue #21259 · matplotlib/matplotlib
X Title: [Bug]: Memory leak in 3.4.3 · Issue #21259 · matplotlib/matplotlib
Description: Bug summary As reported in jupyterlab/jupyterlab#11182, running below code with a 30M row data frame (pandas) only increases memory. Code for reproduction %matplotlib widget # with this commented out or not, same result import modin.pand...
Open Graph Description: Bug summary As reported in jupyterlab/jupyterlab#11182, running below code with a 30M row data frame (pandas) only increases memory. Code for reproduction %matplotlib widget # with this commented o...
X Description: Bug summary As reported in jupyterlab/jupyterlab#11182, running below code with a 30M row data frame (pandas) only increases memory. Code for reproduction %matplotlib widget # with this commented o...
Opengraph URL: https://github.com/matplotlib/matplotlib/issues/21259
X: @github
Domain: github.com
{"@context":"https://schema.org","@type":"DiscussionForumPosting","headline":"[Bug]: Memory leak in 3.4.3","articleBody":"### Bug summary\n\nAs reported in https://github.com/jupyterlab/jupyterlab/issues/11182, running below code with a 30M row data frame (pandas) only increases memory.\n\n### Code for reproduction\n\n```python\n%matplotlib widget # with this commented out or not, same result\r\nimport modin.pandas as pd\r\nimport matplotlib.pyplot as plt\r\n\r\n# get your df\r\n\r\nplt.rcParams[\"figure.figsize\"] = [40, 15]\r\nplt.rcParams[\"figure.autolayout\"] = True\r\n\r\n# plt.cla() # with this commented out or not, same result\r\n# plt.clf() # with this commented out or not, same result\r\n# plt.close(fig) # with this commented out or not, same result\r\n\r\n# this works but then of course the figure is empty\r\n# import gc\r\n# fig.clear() # also this must be commented out on the second run since on the first one it's not defined\r\n# gc.collect()\r\n\r\nfig, axs = plt.subplots(1, 1, sharex=True)\r\n# fig.clear() # draws only one plot, still leaks\r\naxs.plot(df[df.columns[0]], color=\"black\")\r\n\r\nax1 = axs.twinx()\r\nax1.plot(df[df.columns[1]], color=\"blue\")\r\n\r\n# with this 2 lines commented out or not, same result\r\nfig.tight_layout()\r\nplt.show()\n```\n\n\n### Actual outcome\n\nMemory only increases.\n\n### Expected outcome\n\nNo memory leak prefferably.\n\n### Operating system\n\nUbuntu 21.04\n\n### Matplotlib Version\n\n3.4.3\n\n### Matplotlib Backend\n\nQt5Agg, same with `%matplotlib` and `%matplotlib widget`\n\n### Python version\n\n3.7.10\n\n### Jupyter version\n\n3.1.11\n\n### Other libraries\n\nConda's `env.yaml`:\r\n```shell\r\nname: test\r\nchannels:\r\n - pyviz\r\n - conda-forge\r\n - defaults\r\ndependencies:\r\n - _libgcc_mutex=0.1=conda_forge\r\n - _openmp_mutex=4.5=1_gnu\r\n - abseil-cpp=20210324.2=h9c3ff4c_0\r\n - alembic=1.7.3=pyhd8ed1ab_0\r\n - alsa-lib=1.2.3=h516909a_0\r\n - anyio=3.3.0=py37h89c1867_0\r\n - argcomplete=1.12.3=pyhd8ed1ab_2\r\n - argon2-cffi=20.1.0=py37h5e8e339_2\r\n - arrow-cpp=5.0.0=py37hdf48254_5_cpu\r\n - async_generator=1.10=py_0\r\n - attrs=21.2.0=pyhd8ed1ab_0\r\n - autopage=0.4.0=pyhd8ed1ab_0\r\n - aws-c-cal=0.5.11=h95a6274_0\r\n - aws-c-common=0.6.2=h7f98852_0\r\n - aws-c-event-stream=0.2.7=h3541f99_13\r\n - aws-c-io=0.10.5=hfb6a706_0\r\n - aws-checksums=0.1.11=ha31a3da_7\r\n - aws-sdk-cpp=1.8.186=hb4091e7_3\r\n - babel=2.9.1=pyh44b312d_0\r\n - backcall=0.2.0=pyh9f0ad1d_0\r\n - backports=1.0=py_2\r\n - backports.functools_lru_cache=1.6.4=pyhd8ed1ab_0\r\n - backports.zoneinfo=0.2.1=py37h5e8e339_4\r\n - bleach=4.1.0=pyhd8ed1ab_0\r\n - bokeh=2.3.3=py37h89c1867_0\r\n - brotlipy=0.7.0=py37h5e8e339_1001\r\n - bzip2=1.0.8=h7f98852_4\r\n - c-ares=1.17.2=h7f98852_0\r\n - ca-certificates=2021.5.30=ha878542_0\r\n - certifi=2021.5.30=py37h89c1867_0\r\n - cffi=1.14.6=py37hc58025e_0\r\n - chardet=4.0.0=py37h89c1867_1\r\n - charset-normalizer=2.0.0=pyhd8ed1ab_0\r\n - click=8.0.1=py37h89c1867_0\r\n - clickhouse-cityhash=1.0.2.3=py37h3340039_2\r\n - clickhouse-driver=0.2.1=py37h5e8e339_0\r\n - cliff=3.9.0=pyhd8ed1ab_0\r\n - cloudpickle=2.0.0=pyhd8ed1ab_0\r\n - cmaes=0.8.2=pyh44b312d_0\r\n - cmd2=2.2.0=py37h89c1867_0\r\n - colorama=0.4.4=pyh9f0ad1d_0\r\n - colorcet=2.0.6=pyhd8ed1ab_0\r\n - colorlog=6.4.1=py37h89c1867_0\r\n - conda=4.10.3=py37h89c1867_1\r\n - conda-package-handling=1.7.3=py37h5e8e339_0\r\n - cramjam=2.3.1=py37h5e8e339_1\r\n - cryptography=3.4.7=py37h5d9358c_0\r\n - cycler=0.10.0=py_2\r\n - cytoolz=0.11.0=py37h5e8e339_3\r\n - dask=2021.9.0=pyhd8ed1ab_0\r\n - dask-core=2021.9.0=pyhd8ed1ab_0\r\n - datashader=0.13.0=pyh6c4a22f_0\r\n - datashape=0.5.4=py_1\r\n - dbus=1.13.6=h48d8840_2\r\n - debugpy=1.4.1=py37hcd2ae1e_0\r\n - decorator=5.1.0=pyhd8ed1ab_0\r\n - defusedxml=0.7.1=pyhd8ed1ab_0\r\n - distributed=2021.9.0=py37h89c1867_0\r\n - entrypoints=0.3=py37hc8dfbb8_1002\r\n - expat=2.4.1=h9c3ff4c_0\r\n - fastparquet=0.7.1=py37hb1e94ed_0\r\n - filelock=3.0.12=pyh9f0ad1d_0\r\n - fontconfig=2.13.1=hba837de_1005\r\n - freetype=2.10.4=h0708190_1\r\n - fsspec=2021.8.1=pyhd8ed1ab_0\r\n - gettext=0.19.8.1=h0b5b191_1005\r\n - gflags=2.2.2=he1b5a44_1004\r\n - gitdb=4.0.7=pyhd8ed1ab_0\r\n - gitpython=3.1.23=pyhd8ed1ab_1\r\n - glib=2.68.4=h9c3ff4c_0\r\n - glib-tools=2.68.4=h9c3ff4c_0\r\n - glog=0.5.0=h48cff8f_0\r\n - greenlet=1.1.1=py37hcd2ae1e_0\r\n - grpc-cpp=1.40.0=h850795e_0\r\n - gst-plugins-base=1.18.5=hf529b03_0\r\n - gstreamer=1.18.5=h76c114f_0\r\n - heapdict=1.0.1=py_0\r\n - holoviews=1.14.5=py_0\r\n - hvplot=0.7.3=py_0\r\n - icu=68.1=h58526e2_0\r\n - idna=3.1=pyhd3deb0d_0\r\n - importlib-metadata=4.8.1=py37h89c1867_0\r\n - importlib_metadata=4.8.1=hd8ed1ab_0\r\n - importlib_resources=5.2.2=pyhd8ed1ab_0\r\n - ipykernel=6.4.1=py37h6531663_0\r\n - ipympl=0.7.0=pyhd8ed1ab_0\r\n - ipython=7.27.0=py37h6531663_0\r\n - ipython_genutils=0.2.0=py_1\r\n - ipywidgets=7.6.5=pyhd8ed1ab_0\r\n - jbig=2.1=h7f98852_2003\r\n - jedi=0.18.0=py37h89c1867_2\r\n - jinja2=3.0.1=pyhd8ed1ab_0\r\n - joblib=1.0.1=pyhd8ed1ab_0\r\n - jpeg=9d=h36c2ea0_0\r\n - json5=0.9.5=pyh9f0ad1d_0\r\n - jsonschema=3.2.0=py37hc8dfbb8_1\r\n - jupyter-server-mathjax=0.2.3=pyhd8ed1ab_0\r\n - jupyter_client=7.0.2=pyhd8ed1ab_0\r\n - jupyter_contrib_core=0.3.3=py_2\r\n - jupyter_contrib_nbextensions=0.5.1=py37hc8dfbb8_1\r\n - jupyter_core=4.7.1=py37h89c1867_0\r\n - jupyter_highlight_selected_word=0.2.0=py37h89c1867_1002\r\n - jupyter_latex_envs=1.4.6=py37h89c1867_1001\r\n - jupyter_nbextensions_configurator=0.4.1=py37h89c1867_2\r\n - jupyter_server=1.11.0=pyhd8ed1ab_0\r\n - jupyterlab=3.1.11=pyhd8ed1ab_0\r\n - jupyterlab-git=0.32.2=pyhd8ed1ab_0\r\n - jupyterlab_pygments=0.1.2=pyh9f0ad1d_0\r\n - jupyterlab_server=2.8.1=pyhd8ed1ab_0\r\n - jupyterlab_widgets=1.0.2=pyhd8ed1ab_0\r\n - kiwisolver=1.3.2=py37h2527ec5_0\r\n - krb5=1.19.2=hcc1bbae_0\r\n - lcms2=2.12=hddcbb42_0\r\n - ld_impl_linux-64=2.36.1=hea4e1c9_2\r\n - lerc=2.2.1=h9c3ff4c_0\r\n - libarchive=3.5.2=hccf745f_0\r\n - libblas=3.9.0=11_linux64_openblas\r\n - libbrotlicommon=1.0.9=h7f98852_5\r\n - libbrotlidec=1.0.9=h7f98852_5\r\n - libbrotlienc=1.0.9=h7f98852_5\r\n - libcblas=3.9.0=11_linux64_openblas\r\n - libclang=11.1.0=default_ha53f305_1\r\n - libcurl=7.78.0=h2574ce0_0\r\n - libdeflate=1.7=h7f98852_5\r\n - libedit=3.1.20191231=he28a2e2_2\r\n - libev=4.33=h516909a_1\r\n - libevent=2.1.10=hcdb4288_3\r\n - libffi=3.3=h58526e2_2\r\n - libgcc-ng=11.1.0=hc902ee8_8\r\n - libgfortran-ng=11.1.0=h69a702a_8\r\n - libgfortran5=11.1.0=h6c583b3_8\r\n - libglib=2.68.4=h3e27bee_0\r\n - libgomp=11.1.0=hc902ee8_8\r\n - libiconv=1.16=h516909a_0\r\n - liblapack=3.9.0=11_linux64_openblas\r\n - libllvm11=11.1.0=hf817b99_2\r\n - libnghttp2=1.43.0=h812cca2_0\r\n - libogg=1.3.4=h7f98852_1\r\n - libopenblas=0.3.17=pthreads_h8fe5266_1\r\n - libopus=1.3.1=h7f98852_1\r\n - libpng=1.6.37=h21135ba_2\r\n - libpq=13.3=hd57d9b9_0\r\n - libprotobuf=3.16.0=h780b84a_0\r\n - libsodium=1.0.18=h36c2ea0_1\r\n - libsolv=0.7.19=h780b84a_5\r\n - libssh2=1.10.0=ha56f1ee_0\r\n - libstdcxx-ng=11.1.0=h56837e0_8\r\n - libta-lib=0.4.0=h516909a_0\r\n - libthrift=0.14.2=he6d91bd_1\r\n - libtiff=4.3.0=hf544144_1\r\n - libutf8proc=2.6.1=h7f98852_0\r\n - libuuid=2.32.1=h7f98852_1000\r\n - libuv=1.42.0=h7f98852_0\r\n - libvorbis=1.3.7=h9c3ff4c_0\r\n - libwebp-base=1.2.1=h7f98852_0\r\n - libxcb=1.13=h7f98852_1003\r\n - libxkbcommon=1.0.3=he3ba5ed_0\r\n - libxml2=2.9.12=h72842e0_0\r\n - libxslt=1.1.33=h15afd5d_2\r\n - llvmlite=0.37.0=py37h9d7f4d0_0\r\n - locket=0.2.0=py_2\r\n - lxml=4.6.3=py37h77fd288_0\r\n - lz4-c=1.9.3=h9c3ff4c_1\r\n - lzo=2.10=h516909a_1000\r\n - mako=1.1.5=pyhd8ed1ab_0\r\n - mamba=0.15.3=py37h7f483ca_0\r\n - markdown=3.3.4=pyhd8ed1ab_0\r\n - markupsafe=2.0.1=py37h5e8e339_0\r\n - matplotlib=3.4.3=py37h89c1867_0\r\n - matplotlib-base=3.4.3=py37h1058ff1_0\r\n - matplotlib-inline=0.1.3=pyhd8ed1ab_0\r\n - mistune=0.8.4=py37h5e8e339_1004\r\n - modin-core=0.10.2=py37h89c1867_3\r\n - modin-ray=0.10.2=py37h89c1867_3\r\n - msgpack-python=1.0.2=py37h2527ec5_1\r\n - multipledispatch=0.6.0=py_0\r\n - mysql-common=8.0.25=ha770c72_2\r\n - mysql-libs=8.0.25=hfa10184_2\r\n - nb_conda_kernels=2.3.1=py37h89c1867_0\r\n - nbclassic=0.3.1=pyhd8ed1ab_1\r\n - nbclient=0.5.4=pyhd8ed1ab_0\r\n - nbconvert=6.1.0=py37h89c1867_0\r\n - nbdime=3.1.0=pyhd8ed1ab_0\r\n - nbformat=5.1.3=pyhd8ed1ab_0\r\n - ncurses=6.2=h58526e2_4\r\n - nest-asyncio=1.5.1=pyhd8ed1ab_0\r\n - notebook=6.4.3=pyha770c72_0\r\n - nspr=4.30=h9c3ff4c_0\r\n - nss=3.69=hb5efdd6_0\r\n - numba=0.54.0=py37h2d894fd_0\r\n - numpy=1.20.3=py37h038b26d_1\r\n - olefile=0.46=pyh9f0ad1d_1\r\n - openjpeg=2.4.0=hb52868f_1\r\n - openssl=1.1.1l=h7f98852_0\r\n - optuna=2.9.1=pyhd8ed1ab_0\r\n - orc=1.6.10=h58a87f1_0\r\n - packaging=21.0=pyhd8ed1ab_0\r\n - pandas=1.3.2=py37he8f5f7f_0\r\n - pandoc=2.14.2=h7f98852_0\r\n - pandocfilters=1.4.2=py_1\r\n - panel=0.12.1=py_0\r\n - param=1.11.1=pyh6c4a22f_0\r\n - parquet-cpp=1.5.1=1\r\n - parso=0.8.2=pyhd8ed1ab_0\r\n - partd=1.2.0=pyhd8ed1ab_0\r\n - patsy=0.5.2=pyhd8ed1ab_0\r\n - pbr=5.6.0=pyhd8ed1ab_0\r\n - pcre=8.45=h9c3ff4c_0\r\n - pexpect=4.8.0=py37hc8dfbb8_1\r\n - pickle5=0.0.11=py37h5e8e339_0\r\n - pickleshare=0.7.5=py37hc8dfbb8_1002\r\n - pillow=8.3.2=py37h0f21c89_0\r\n - pip=21.2.4=pyhd8ed1ab_0\r\n - prettytable=2.2.0=pyhd8ed1ab_0\r\n - prometheus_client=0.11.0=pyhd8ed1ab_0\r\n - prompt-toolkit=3.0.20=pyha770c72_0\r\n - psutil=5.8.0=py37h5e8e339_1\r\n - pthread-stubs=0.4=h36c2ea0_1001\r\n - ptyprocess=0.7.0=pyhd3deb0d_0\r\n - pyarrow=5.0.0=py37h58331f5_5_cpu\r\n - pycosat=0.6.3=py37h5e8e339_1006\r\n - pycparser=2.20=pyh9f0ad1d_2\r\n - pyct=0.4.6=py_0\r\n - pyct-core=0.4.6=py_0\r\n - pygments=2.10.0=pyhd8ed1ab_0\r\n - pykalman=0.9.5=py_1\r\n - pyopenssl=20.0.1=pyhd8ed1ab_0\r\n - pyparsing=2.4.7=pyh9f0ad1d_0\r\n - pyperclip=1.8.2=pyhd8ed1ab_2\r\n - pyqt=5.12.3=py37h89c1867_7\r\n - pyqt-impl=5.12.3=py37he336c9b_7\r\n - pyqt5-sip=4.19.18=py37hcd2ae1e_7\r\n - pyqtchart=5.12=py37he336c9b_7\r\n - pyqtwebengine=5.12.1=py37he336c9b_7\r\n - pyrsistent=0.17.3=py37h5e8e339_2\r\n - pysocks=1.7.1=py37h89c1867_3\r\n - python=3.7.10=hffdb5ce_100_cpython\r\n - python-dateutil=2.8.2=pyhd8ed1ab_0\r\n - python_abi=3.7=2_cp37m\r\n - pytz=2021.1=pyhd8ed1ab_0\r\n - pyviz_comms=2.1.0=py_0\r\n - pyyaml=5.4.1=py37h5e8e339_1\r\n - pyzmq=22.2.1=py37h336d617_0\r\n - qt=5.12.9=hda022c4_4\r\n - ray-core=1.6.0=py37hf931bba_0\r\n - re2=2021.09.01=h9c3ff4c_0\r\n - readline=8.1=h46c0cb4_0\r\n - redis-py=3.5.3=pyh9f0ad1d_0\r\n - reproc=14.2.3=h7f98852_0\r\n - reproc-cpp=14.2.3=h9c3ff4c_0\r\n - requests=2.26.0=pyhd8ed1ab_0\r\n - requests-unixsocket=0.2.0=py_0\r\n - ruamel_yaml=0.15.80=py37h5e8e339_1004\r\n - s2n=1.0.10=h9b69904_0\r\n - scikit-learn=0.24.2=py37hf0f1638_1\r\n - send2trash=1.8.0=pyhd8ed1ab_0\r\n - setproctitle=1.1.10=py37h5e8e339_1004\r\n - setuptools=58.0.4=py37h89c1867_0\r\n - six=1.16.0=pyh6c4a22f_0\r\n - smmap=3.0.5=pyh44b312d_0\r\n - snappy=1.1.8=he1b5a44_3\r\n - sniffio=1.2.0=py37h89c1867_1\r\n - sortedcontainers=2.4.0=pyhd8ed1ab_0\r\n - sqlalchemy=1.4.25=py37h5e8e339_0\r\n - sqlite=3.36.0=h9cd32fc_1\r\n - statsmodels=0.12.2=py37hb1e94ed_0\r\n - stevedore=3.4.0=py37h89c1867_0\r\n - ta-lib=0.4.19=py37ha21ca33_2\r\n - tabulate=0.8.9=pyhd8ed1ab_0\r\n - tblib=1.7.0=pyhd8ed1ab_0\r\n - tensorboardx=2.4=pyhd8ed1ab_0\r\n - terminado=0.12.1=py37h89c1867_0\r\n - testpath=0.5.0=pyhd8ed1ab_0\r\n - threadpoolctl=2.2.0=pyh8a188c0_0\r\n - thrift=0.13.0=py37hcd2ae1e_2\r\n - tk=8.6.11=h27826a3_1\r\n - toolz=0.11.1=py_0\r\n - tornado=6.1=py37h5e8e339_1\r\n - tqdm=4.62.2=pyhd8ed1ab_0\r\n - traitlets=5.1.0=pyhd8ed1ab_0\r\n - typing_extensions=3.10.0.0=pyha770c72_0\r\n - tzdata=2021a=he74cb21_1\r\n - tzlocal=3.0=py37h89c1867_2\r\n - urllib3=1.26.6=pyhd8ed1ab_0\r\n - wcwidth=0.2.5=pyh9f0ad1d_2\r\n - webencodings=0.5.1=py_1\r\n - websocket-client=0.57.0=py37h89c1867_4\r\n - wheel=0.37.0=pyhd8ed1ab_1\r\n - widgetsnbextension=3.5.1=py37h89c1867_4\r\n - xarray=0.19.0=pyhd8ed1ab_1\r\n - xeus=2.0.0=h7d0c39e_0\r\n - xeus-python=0.13.0=py37h4b46df4_1\r\n - xeus-python-shell=0.1.5=pyhd8ed1ab_0\r\n - xorg-libxau=1.0.9=h7f98852_0\r\n - xorg-libxdmcp=1.1.3=h7f98852_0\r\n - xz=5.2.5=h516909a_1\r\n - yaml=0.2.5=h516909a_0\r\n - zeromq=4.3.4=h9c3ff4c_1\r\n - zict=2.0.0=py_0\r\n - zipp=3.5.0=pyhd8ed1ab_0\r\n - zlib=1.2.11=h516909a_1010\r\n - zstandard=0.15.2=py37h5e8e339_0\r\n - zstd=1.5.0=ha95c52a_0\r\n - pip:\r\n - absl-py==0.13.0\r\n - aiohttp==3.7.4.post0\r\n - aiohttp-cors==0.7.0\r\n - aioredis==1.3.1\r\n - async-timeout==3.0.1\r\n - autograd==1.3\r\n - bayesian-optimization==1.2.0\r\n - blessings==1.7\r\n - cachetools==4.2.2\r\n - cma==2.7.0\r\n - colorful==0.5.4\r\n - cython==0.29.24\r\n - future==0.18.2\r\n - google-api-core==1.31.2\r\n - google-auth==1.35.0\r\n - google-auth-oauthlib==0.4.6\r\n - googleapis-common-protos==1.53.0\r\n - gpustat==0.6.0\r\n - gpy==1.10.0\r\n - gpytorch==1.5.1\r\n - grpcio==1.40.0\r\n - hebo==0.1.0\r\n - hiredis==2.0.0\r\n - multidict==5.1.0\r\n - nevergrad==0.4.3.post8\r\n - nvidia-ml-py3==7.352.0\r\n - oauthlib==3.1.1\r\n - opencensus==0.7.13\r\n - opencensus-context==0.1.2\r\n - paramz==0.9.5\r\n - protobuf==3.17.3\r\n - py-spy==0.3.9\r\n - pyasn1==0.4.8\r\n - pyasn1-modules==0.2.8\r\n - pymoo==0.4.2.2\r\n - requests-oauthlib==1.3.0\r\n - rsa==4.7.2\r\n - scipy==1.5.4\r\n - sklearn==0.0\r\n - tensorboard==2.6.0\r\n - tensorboard-data-server==0.6.1\r\n - tensorboard-plugin-wit==1.8.0\r\n - torch==1.9.1\r\n - werkzeug==2.0.1\r\n - yarl==1.6.3\r\n```\n\n### Installation\n\nconda\n\n### Conda channel\n\n_No response_","author":{"url":"https://github.com/jmakov","@type":"Person","name":"jmakov"},"datePublished":"2021-10-01T20:35:06.000Z","interactionStatistic":{"@type":"InteractionCounter","interactionType":"https://schema.org/CommentAction","userInteractionCount":18},"url":"https://github.com/21259/matplotlib/issues/21259"}
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| og:image:alt | Bug summary As reported in jupyterlab/jupyterlab#11182, running below code with a 30M row data frame (pandas) only increases memory. Code for reproduction %matplotlib widget # with this commented o... |
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