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+Metadata-Version: 2.4
+Name: tqdm
+Version: 4.67.3
+Summary: Fast, Extensible Progress Meter
+Maintainer-email: tqdm developers <devs@tqdm.ml>
+License: MPL-2.0 AND MIT
+Project-URL: homepage, https://tqdm.github.io
+Project-URL: repository, https://github.com/tqdm/tqdm
+Project-URL: changelog, https://tqdm.github.io/releases
+Project-URL: wiki, https://github.com/tqdm/tqdm/wiki
+Keywords: progressbar,progressmeter,progress,bar,meter,rate,eta,console,terminal,time
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Environment :: Console
+Classifier: Environment :: MacOS X
+Classifier: Environment :: Other Environment
+Classifier: Environment :: Win32 (MS Windows)
+Classifier: Environment :: X11 Applications
+Classifier: Framework :: IPython
+Classifier: Framework :: Jupyter
+Classifier: Intended Audience :: Developers
+Classifier: Intended Audience :: Education
+Classifier: Intended Audience :: End Users/Desktop
+Classifier: Intended Audience :: Other Audience
+Classifier: Intended Audience :: System Administrators
+Classifier: Operating System :: MacOS
+Classifier: Operating System :: MacOS :: MacOS X
+Classifier: Operating System :: Microsoft
+Classifier: Operating System :: Microsoft :: MS-DOS
+Classifier: Operating System :: Microsoft :: Windows
+Classifier: Operating System :: POSIX
+Classifier: Operating System :: POSIX :: BSD
+Classifier: Operating System :: POSIX :: BSD :: FreeBSD
+Classifier: Operating System :: POSIX :: Linux
+Classifier: Operating System :: POSIX :: SunOS/Solaris
+Classifier: Operating System :: Unix
+Classifier: Programming Language :: Python
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.7
+Classifier: Programming Language :: Python :: 3.8
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3.12
+Classifier: Programming Language :: Python :: 3.13
+Classifier: Programming Language :: Python :: 3 :: Only
+Classifier: Programming Language :: Python :: Implementation
+Classifier: Programming Language :: Python :: Implementation :: IronPython
+Classifier: Programming Language :: Python :: Implementation :: PyPy
+Classifier: Programming Language :: Unix Shell
+Classifier: Topic :: Desktop Environment
+Classifier: Topic :: Education :: Computer Aided Instruction (CAI)
+Classifier: Topic :: Education :: Testing
+Classifier: Topic :: Office/Business
+Classifier: Topic :: Other/Nonlisted Topic
+Classifier: Topic :: Software Development :: Build Tools
+Classifier: Topic :: Software Development :: Libraries
+Classifier: Topic :: Software Development :: Libraries :: Python Modules
+Classifier: Topic :: Software Development :: Pre-processors
+Classifier: Topic :: Software Development :: User Interfaces
+Classifier: Topic :: System :: Installation/Setup
+Classifier: Topic :: System :: Logging
+Classifier: Topic :: System :: Monitoring
+Classifier: Topic :: System :: Shells
+Classifier: Topic :: Terminals
+Classifier: Topic :: Utilities
+Requires-Python: >=3.7
+Description-Content-Type: text/x-rst
+License-File: LICENCE
+Requires-Dist: colorama; platform_system == "Windows"
+Requires-Dist: importlib_metadata; python_version < "3.8"
+Provides-Extra: dev
+Requires-Dist: pytest>=6; extra == "dev"
+Requires-Dist: pytest-cov; extra == "dev"
+Requires-Dist: pytest-timeout; extra == "dev"
+Requires-Dist: pytest-asyncio>=0.24; extra == "dev"
+Requires-Dist: nbval; extra == "dev"
+Provides-Extra: discord
+Requires-Dist: requests; extra == "discord"
+Provides-Extra: slack
+Requires-Dist: slack-sdk; extra == "slack"
+Provides-Extra: telegram
+Requires-Dist: requests; extra == "telegram"
+Provides-Extra: notebook
+Requires-Dist: ipywidgets>=6; extra == "notebook"
+Dynamic: license-file
+
+|Logo|
+
+tqdm
+====
+
+|Py-Versions| |Versions| |Conda-Forge-Status| |Docker| |Snapcraft|
+
+|Build-Status| |Coverage-Status| |Branch-Coverage-Status| |Codacy-Grade| |Libraries-Rank| |PyPI-Downloads|
+
+|LICENCE| |OpenHub-Status| |binder-demo| |awesome-python|
+
+``tqdm`` derives from the Arabic word *taqaddum* (تقدّم) which can mean "progress,"
+and is an abbreviation for "I love you so much" in Spanish (*te quiero demasiado*).
+
+Instantly make your loops show a smart progress meter - just wrap any
+iterable with ``tqdm(iterable)``, and you're done!
+
+.. code:: python
+
+    from tqdm import tqdm
+    for i in tqdm(range(10000)):
+        ...
+
+``76%|████████████████████████        | 7568/10000 [00:33<00:10, 229.00it/s]``
+
+``trange(N)`` can be also used as a convenient shortcut for
+``tqdm(range(N))``.
+
+|Screenshot|
+    |Video| |Slides| |Merch|
+
+It can also be executed as a module with pipes:
+
+.. code:: sh
+
+    $ seq 9999999 | tqdm --bytes | wc -l
+    75.2MB [00:00, 217MB/s]
+    9999999
+
+    $ tar -zcf - docs/ | tqdm --bytes --total `du -sb docs/ | cut -f1` \
+        > backup.tgz
+     32%|██████████▍                      | 8.89G/27.9G [00:42<01:31, 223MB/s]
+
+Overhead is low -- about 60ns per iteration (80ns with ``tqdm.gui``), and is
+unit tested against performance regression.
+By comparison, the well-established
+`ProgressBar <https://github.com/niltonvolpato/python-progressbar>`__ has
+an 800ns/iter overhead.
+
+In addition to its low overhead, ``tqdm`` uses smart algorithms to predict
+the remaining time and to skip unnecessary iteration displays, which allows
+for a negligible overhead in most cases.
+
+``tqdm`` works on any platform
+(Linux, Windows, Mac, FreeBSD, NetBSD, Solaris/SunOS),
+in any console or in a GUI, and is also friendly with IPython/Jupyter notebooks.
+
+``tqdm`` does not require any dependencies (not even ``curses``!), just
+Python and an environment supporting ``carriage return \r`` and
+``line feed \n`` control characters.
+
+------------------------------------------
+
+.. contents:: Table of contents
+   :backlinks: top
+   :local:
+
+
+Installation
+------------
+
+Latest PyPI stable release
+~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+|Versions| |PyPI-Downloads| |Libraries-Dependents|
+
+.. code:: sh
+
+    pip install tqdm
+
+Latest development release on GitHub
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+|GitHub-Status| |GitHub-Stars| |GitHub-Commits| |GitHub-Forks| |GitHub-Updated|
+
+Pull and install pre-release ``devel`` branch:
+
+.. code:: sh
+
+    pip install "git+https://github.com/tqdm/tqdm.git@devel#egg=tqdm"
+
+Latest Conda release
+~~~~~~~~~~~~~~~~~~~~
+
+|Conda-Forge-Status|
+
+.. code:: sh
+
+    conda install -c conda-forge tqdm
+
+Latest Snapcraft release
+~~~~~~~~~~~~~~~~~~~~~~~~
+
+|Snapcraft|
+
+There are 3 channels to choose from:
+
+.. code:: sh
+
+    snap install tqdm  # implies --stable, i.e. latest tagged release
+    snap install tqdm  --candidate  # master branch
+    snap install tqdm  --edge  # devel branch
+
+Note that ``snap`` binaries are purely for CLI use (not ``import``-able), and
+automatically set up ``bash`` tab-completion.
+
+Latest Docker release
+~~~~~~~~~~~~~~~~~~~~~
+
+|Docker|
+
+.. code:: sh
+
+    docker pull tqdm/tqdm
+    docker run -i --rm tqdm/tqdm --help
+
+Other
+~~~~~
+
+There are other (unofficial) places where ``tqdm`` may be downloaded, particularly for CLI use:
+
+|Repology|
+
+.. |Repology| image:: https://repology.org/badge/tiny-repos/python:tqdm.svg
+   :target: https://repology.org/project/python:tqdm/versions
+
+Changelog
+---------
+
+The list of all changes is available either on GitHub's Releases:
+|GitHub-Status|, on the
+`wiki <https://github.com/tqdm/tqdm/wiki/Releases>`__, or on the
+`website <https://tqdm.github.io/releases>`__.
+
+
+Usage
+-----
+
+``tqdm`` is very versatile and can be used in a number of ways.
+The three main ones are given below.
+
+Iterable-based
+~~~~~~~~~~~~~~
+
+Wrap ``tqdm()`` around any iterable:
+
+.. code:: python
+
+    from tqdm import tqdm
+    from time import sleep
+
+    text = ""
+    for char in tqdm(["a", "b", "c", "d"]):
+        sleep(0.25)
+        text = text + char
+
+``trange(i)`` is a special optimised instance of ``tqdm(range(i))``:
+
+.. code:: python
+
+    from tqdm import trange
+
+    for i in trange(100):
+        sleep(0.01)
+
+Instantiation outside of the loop allows for manual control over ``tqdm()``:
+
+.. code:: python
+
+    pbar = tqdm(["a", "b", "c", "d"])
+    for char in pbar:
+        sleep(0.25)
+        pbar.set_description("Processing %s" % char)
+
+Manual
+~~~~~~
+
+Manual control of ``tqdm()`` updates using a ``with`` statement:
+
+.. code:: python
+
+    with tqdm(total=100) as pbar:
+        for i in range(10):
+            sleep(0.1)
+            pbar.update(10)
+
+If the optional variable ``total`` (or an iterable with ``len()``) is
+provided, predictive stats are displayed.
+
+``with`` is also optional (you can just assign ``tqdm()`` to a variable,
+but in this case don't forget to ``del`` or ``close()`` at the end:
+
+.. code:: python
+
+    pbar = tqdm(total=100)
+    for i in range(10):
+        sleep(0.1)
+        pbar.update(10)
+    pbar.close()
+
+Module
+~~~~~~
+
+Perhaps the most wonderful use of ``tqdm`` is in a script or on the command
+line. Simply inserting ``tqdm`` (or ``python -m tqdm``) between pipes will pass
+through all ``stdin`` to ``stdout`` while printing progress to ``stderr``.
+
+The example below demonstrate counting the number of lines in all Python files
+in the current directory, with timing information included.
+
+.. code:: sh
+
+    $ time find . -name '*.py' -type f -exec cat \{} \; | wc -l
+    857365
+
+    real    0m3.458s
+    user    0m0.274s
+    sys     0m3.325s
+
+    $ time find . -name '*.py' -type f -exec cat \{} \; | tqdm | wc -l
+    857366it [00:03, 246471.31it/s]
+    857365
+
+    real    0m3.585s
+    user    0m0.862s
+    sys     0m3.358s
+
+Note that the usual arguments for ``tqdm`` can also be specified.
+
+.. code:: sh
+
+    $ find . -name '*.py' -type f -exec cat \{} \; |
+        tqdm --unit loc --unit_scale --total 857366 >> /dev/null
+    100%|█████████████████████████████████| 857K/857K [00:04<00:00, 246Kloc/s]
+
+Backing up a large directory?
+
+.. code:: sh
+
+    $ tar -zcf - docs/ | tqdm --bytes --total `du -sb docs/ | cut -f1` \
+      > backup.tgz
+     44%|██████████████▊                   | 153M/352M [00:14<00:18, 11.0MB/s]
+
+This can be beautified further:
+
+.. code:: sh
+
+    $ BYTES=$(du -sb docs/ | cut -f1)
+    $ tar -cf - docs/ \
+      | tqdm --bytes --total "$BYTES" --desc Processing | gzip \
+      | tqdm --bytes --total "$BYTES" --desc Compressed --position 1 \
+      > ~/backup.tgz
+    Processing: 100%|██████████████████████| 352M/352M [00:14<00:00, 30.2MB/s]
+    Compressed:  42%|█████████▎            | 148M/352M [00:14<00:19, 10.9MB/s]
+
+Or done on a file level using 7-zip:
+
+.. code:: sh
+
+    $ 7z a -bd -r backup.7z docs/ | grep Compressing \
+      | tqdm --total $(find docs/ -type f | wc -l) --unit files \
+      | grep -v Compressing
+    100%|██████████████████████████▉| 15327/15327 [01:00<00:00, 712.96files/s]
+
+Pre-existing CLI programs already outputting basic progress information will
+benefit from ``tqdm``'s ``--update`` and ``--update_to`` flags:
+
+.. code:: sh
+
+    $ seq 3 0.1 5 | tqdm --total 5 --update_to --null
+    100%|████████████████████████████████████| 5.0/5 [00:00<00:00, 9673.21it/s]
+    $ seq 10 | tqdm --update --null  # 1 + 2 + ... + 10 = 55 iterations
+    55it [00:00, 90006.52it/s]
+
+FAQ and Known Issues
+--------------------
+
+|GitHub-Issues|
+
+The most common issues relate to excessive output on multiple lines, instead
+of a neat one-line progress bar.
+
+- Consoles in general: require support for carriage return (``CR``, ``\r``).
+
+  * Some cloud logging consoles which don't support ``\r`` properly
+    (`cloudwatch <https://github.com/tqdm/tqdm/issues/966>`__,
+    `K8s <https://github.com/tqdm/tqdm/issues/1319>`__) may benefit from
+    ``export TQDM_POSITION=-1``.
+
+- Nested progress bars:
+
+  * Consoles in general: require support for moving cursors up to the
+    previous line. For example,
+    `IDLE <https://github.com/tqdm/tqdm/issues/191#issuecomment-230168030>`__,
+    `ConEmu <https://github.com/tqdm/tqdm/issues/254>`__ and
+    `PyCharm <https://github.com/tqdm/tqdm/issues/203>`__ (also
+    `here <https://github.com/tqdm/tqdm/issues/208>`__,
+    `here <https://github.com/tqdm/tqdm/issues/307>`__, and
+    `here <https://github.com/tqdm/tqdm/issues/454#issuecomment-335416815>`__)
+    lack full support.
+  * Windows: additionally may require the Python module ``colorama``
+    to ensure nested bars stay within their respective lines.
+
+- Unicode:
+
+  * Environments which report that they support unicode will have solid smooth
+    progressbars. The fallback is an ``ascii``-only bar.
+  * Windows consoles often only partially support unicode and thus
+    `often require explicit ascii=True <https://github.com/tqdm/tqdm/issues/454#issuecomment-335416815>`__
+    (also `here <https://github.com/tqdm/tqdm/issues/499>`__). This is due to
+    either normal-width unicode characters being incorrectly displayed as
+    "wide", or some unicode characters not rendering.
+
+- Wrapping generators:
+
+  * Generator wrapper functions tend to hide the length of iterables.
+    ``tqdm`` does not.
+  * Replace ``tqdm(enumerate(...))`` with ``enumerate(tqdm(...))`` or
+    ``tqdm(enumerate(x), total=len(x), ...)``.
+    The same applies to ``numpy.ndenumerate``.
+  * Replace ``tqdm(zip(a, b))`` with ``zip(tqdm(a), b)`` or even
+    ``zip(tqdm(a), tqdm(b))``.
+  * The same applies to ``itertools``.
+  * Some useful convenience functions can be found under ``tqdm.contrib``.
+
+- `No intermediate output in docker-compose <https://github.com/tqdm/tqdm/issues/771>`__:
+  use ``docker-compose run`` instead of ``docker-compose up`` and ``tty: true``.
+
+- Overriding defaults via environment variables:
+  e.g. in CI/cloud jobs, ``export TQDM_MININTERVAL=5`` to avoid log spam.
+  This override logic is handled by the ``tqdm.utils.envwrap`` decorator
+  (useful independent of ``tqdm``).
+
+If you come across any other difficulties, browse and file |GitHub-Issues|.
+
+Documentation
+-------------
+
+|Py-Versions| |README-Hits| (Since 19 May 2016)
+
+.. code:: python
+
+    class tqdm():
+      """
+      Decorate an iterable object, returning an iterator which acts exactly
+      like the original iterable, but prints a dynamically updating
+      progressbar every time a value is requested.
+      """
+
+      @envwrap("TQDM_")  # override defaults via env vars
+      def __init__(self, iterable=None, desc=None, total=None, leave=True,
+                   file=None, ncols=None, mininterval=0.1,
+                   maxinterval=10.0, miniters=None, ascii=None, disable=False,
+                   unit='it', unit_scale=False, dynamic_ncols=False,
+                   smoothing=0.3, bar_format=None, initial=0, position=None,
+                   postfix=None, unit_divisor=1000, write_bytes=False,
+                   lock_args=None, nrows=None, colour=None, delay=0):
+
+Parameters
+~~~~~~~~~~
+
+* iterable  : iterable, optional  
+    Iterable to decorate with a progressbar.
+    Leave blank to manually manage the updates.
+* desc  : str, optional  
+    Prefix for the progressbar.
+* total  : int or float, optional  
+    The number of expected iterations. If unspecified,
+    len(iterable) is used if possible. If float("inf") or as a last
+    resort, only basic progress statistics are displayed
+    (no ETA, no progressbar).
+    If ``gui`` is True and this parameter needs subsequent updating,
+    specify an initial arbitrary large positive number,
+    e.g. 9e9.
+* leave  : bool, optional  
+    If [default: True], keeps all traces of the progressbar
+    upon termination of iteration.
+    If ``None``, will leave only if ``position`` is ``0``.
+* file  : ``io.TextIOWrapper`` or ``io.StringIO``, optional  
+    Specifies where to output the progress messages
+    (default: sys.stderr). Uses ``file.write(str)`` and ``file.flush()``
+    methods.  For encoding, see ``write_bytes``.
+* ncols  : int, optional  
+    The width of the entire output message. If specified,
+    dynamically resizes the progressbar to stay within this bound.
+    If unspecified, attempts to use environment width. The
+    fallback is a meter width of 10 and no limit for the counter and
+    statistics. If 0, will not print any meter (only stats).
+* mininterval  : float, optional  
+    Minimum progress display update interval [default: 0.1] seconds.
+* maxinterval  : float, optional  
+    Maximum progress display update interval [default: 10] seconds.
+    Automatically adjusts ``miniters`` to correspond to ``mininterval``
+    after long display update lag. Only works if ``dynamic_miniters``
+    or monitor thread is enabled.
+* miniters  : int or float, optional  
+    Minimum progress display update interval, in iterations.
+    If 0 and ``dynamic_miniters``, will automatically adjust to equal
+    ``mininterval`` (more CPU efficient, good for tight loops).
+    If > 0, will skip display of specified number of iterations.
+    Tweak this and ``mininterval`` to get very efficient loops.
+    If your progress is erratic with both fast and slow iterations
+    (network, skipping items, etc) you should set miniters=1.
+* ascii  : bool or str, optional  
+    If unspecified or False, use unicode (smooth blocks) to fill
+    the meter. The fallback is to use ASCII characters " 123456789#".
+* disable  : bool, optional  
+    Whether to disable the entire progressbar wrapper
+    [default: False]. If set to None, disable on non-TTY.
+* unit  : str, optional  
+    String that will be used to define the unit of each iteration
+    [default: it].
+* unit_scale  : bool or int or float, optional  
+    If 1 or True, the number of iterations will be reduced/scaled
+    automatically and a metric prefix following the
+    International System of Units standard will be added
+    (kilo, mega, etc.) [default: False]. If any other non-zero
+    number, will scale ``total`` and ``n``.
+* dynamic_ncols  : bool, optional  
+    If set, constantly alters ``ncols`` and ``nrows`` to the
+    environment (allowing for window resizes) [default: False].
+* smoothing  : float, optional  
+    Exponential moving average smoothing factor for speed estimates
+    (ignored in GUI mode). Ranges from 0 (average speed) to 1
+    (current/instantaneous speed) [default: 0.3].
+* bar_format  : str, optional  
+    Specify a custom bar string formatting. May impact performance.
+    [default: '{l_bar}{bar}{r_bar}'], where
+    l_bar='{desc}: {percentage:3.0f}%|' and
+    r_bar='| {n_fmt}/{total_fmt} [{elapsed}<{remaining}, '
+    '{rate_fmt}{postfix}]'
+    Possible vars: l_bar, bar, r_bar, n, n_fmt, total, total_fmt,
+    percentage, elapsed, elapsed_s, ncols, nrows, desc, unit,
+    rate, rate_fmt, rate_noinv, rate_noinv_fmt,
+    rate_inv, rate_inv_fmt, postfix, unit_divisor,
+    remaining, remaining_s, eta.
+    Note that a trailing ": " is automatically removed after {desc}
+    if the latter is empty.
+* initial  : int or float, optional  
+    The initial counter value. Useful when restarting a progress
+    bar [default: 0]. If using float, consider specifying ``{n:.3f}``
+    or similar in ``bar_format``, or specifying ``unit_scale``.
+* position  : int, optional  
+    Specify the line offset to print this bar (starting from 0)
+    Automatic if unspecified.
+    Useful to manage multiple bars at once (eg, from threads).
+* postfix  : dict or ``*``, optional  
+    Specify additional stats to display at the end of the bar.
+    Calls ``set_postfix(**postfix)`` if possible (dict).
+* unit_divisor  : float, optional  
+    [default: 1000], ignored unless ``unit_scale`` is True.
+* write_bytes  : bool, optional  
+    Whether to write bytes. If (default: False) will write unicode.
+* lock_args  : tuple, optional  
+    Passed to ``refresh`` for intermediate output
+    (initialisation, iterating, and updating).
+* nrows  : int, optional  
+    The screen height. If specified, hides nested bars outside this
+    bound. If unspecified, attempts to use environment height.
+    The fallback is 20.
+* colour  : str, optional  
+    Bar colour (e.g. 'green', '#00ff00').
+* delay  : float, optional  
+    Don't display until [default: 0] seconds have elapsed.
+
+Extra CLI Options
+~~~~~~~~~~~~~~~~~
+
+* delim  : chr, optional  
+    Delimiting character [default: '\n']. Use '\0' for null.
+    N.B.: on Windows systems, Python converts '\n' to '\r\n'.
+* buf_size  : int, optional  
+    String buffer size in bytes [default: 256]
+    used when ``delim`` is specified.
+* bytes  : bool, optional  
+    If true, will count bytes, ignore ``delim``, and default
+    ``unit_scale`` to True, ``unit_divisor`` to 1024, and ``unit`` to 'B'.
+* tee  : bool, optional  
+    If true, passes ``stdin`` to both ``stderr`` and ``stdout``.
+* update  : bool, optional  
+    If true, will treat input as newly elapsed iterations,
+    i.e. numbers to pass to ``update()``. Note that this is slow
+    (~2e5 it/s) since every input must be decoded as a number.
+* update_to  : bool, optional  
+    If true, will treat input as total elapsed iterations,
+    i.e. numbers to assign to ``self.n``. Note that this is slow
+    (~2e5 it/s) since every input must be decoded as a number.
+* null  : bool, optional  
+    If true, will discard input (no stdout).
+* manpath  : str, optional  
+    Directory in which to install tqdm man pages.
+* comppath  : str, optional  
+    Directory in which to place tqdm completion.
+* log  : str, optional  
+    CRITICAL|FATAL|ERROR|WARN(ING)|[default: 'INFO']|DEBUG|NOTSET.
+
+Returns
+~~~~~~~
+
+* out  : decorated iterator.  
+
+.. code:: python
+
+    class tqdm():
+      def update(self, n=1):
+          """
+          Manually update the progress bar, useful for streams
+          such as reading files.
+          E.g.:
+          >>> t = tqdm(total=filesize) # Initialise
+          >>> for current_buffer in stream:
+          ...    ...
+          ...    t.update(len(current_buffer))
+          >>> t.close()
+          The last line is highly recommended, but possibly not necessary if
+          ``t.update()`` will be called in such a way that ``filesize`` will be
+          exactly reached and printed.
+
+          Parameters
+          ----------
+          n  : int or float, optional
+              Increment to add to the internal counter of iterations
+              [default: 1]. If using float, consider specifying ``{n:.3f}``
+              or similar in ``bar_format``, or specifying ``unit_scale``.
+
+          Returns
+          -------
+          out  : bool or None
+              True if a ``display()`` was triggered.
+          """
+
+      def close(self):
+          """Cleanup and (if leave=False) close the progressbar."""
+
+      def clear(self, nomove=False):
+          """Clear current bar display."""
+
+      def refresh(self):
+          """
+          Force refresh the display of this bar.
+
+          Parameters
+          ----------
+          nolock  : bool, optional
+              If ``True``, does not lock.
+              If [default: ``False``]: calls ``acquire()`` on internal lock.
+          lock_args  : tuple, optional
+              Passed to internal lock's ``acquire()``.
+              If specified, will only ``display()`` if ``acquire()`` returns ``True``.
+          """
+
+      def unpause(self):
+          """Restart tqdm timer from last print time."""
+
+      def reset(self, total=None):
+          """
+          Resets to 0 iterations for repeated use.
+
+          Consider combining with ``leave=True``.
+
+          Parameters
+          ----------
+          total  : int or float, optional. Total to use for the new bar.
+          """
+
+      def set_description(self, desc=None, refresh=True):
+          """
+          Set/modify description of the progress bar.
+
+          Parameters
+          ----------
+          desc  : str, optional
+          refresh  : bool, optional
+              Forces refresh [default: True].
+          """
+
+      def set_postfix(self, ordered_dict=None, refresh=True, **tqdm_kwargs):
+          """
+          Set/modify postfix (additional stats)
+          with automatic formatting based on datatype.
+
+          Parameters
+          ----------
+          ordered_dict  : dict or OrderedDict, optional
+          refresh  : bool, optional
+              Forces refresh [default: True].
+          kwargs  : dict, optional
+          """
+
+      @classmethod
+      def write(cls, s, file=sys.stdout, end="\n"):
+          """Print a message via tqdm (without overlap with bars)."""
+
+      @property
+      def format_dict(self):
+          """Public API for read-only member access."""
+
+      def display(self, msg=None, pos=None):
+          """
+          Use ``self.sp`` to display ``msg`` in the specified ``pos``.
+
+          Consider overloading this function when inheriting to use e.g.:
+          ``self.some_frontend(**self.format_dict)`` instead of ``self.sp``.
+
+          Parameters
+          ----------
+          msg  : str, optional. What to display (default: ``repr(self)``).
+          pos  : int, optional. Position to ``moveto``
+            (default: ``abs(self.pos)``).
+          """
+
+      @classmethod
+      @contextmanager
+      def wrapattr(cls, stream, method, total=None, bytes=True, **tqdm_kwargs):
+          """
+          stream  : file-like object.
+          method  : str, "read" or "write". The result of ``read()`` and
+              the first argument of ``write()`` should have a ``len()``.
+
+          >>> with tqdm.wrapattr(file_obj, "read", total=file_obj.size) as fobj:
+          ...     while True:
+          ...         chunk = fobj.read(chunk_size)
+          ...         if not chunk:
+          ...             break
+          """
+
+      @classmethod
+      def pandas(cls, *targs, **tqdm_kwargs):
+          """Registers the current `tqdm` class with `pandas`."""
+
+    def trange(*args, **tqdm_kwargs):
+        """Shortcut for `tqdm(range(*args), **tqdm_kwargs)`."""
+
+Convenience Functions
+~~~~~~~~~~~~~~~~~~~~~
+
+.. code:: python
+
+    def tqdm.contrib.tenumerate(iterable, start=0, total=None,
+                                tqdm_class=tqdm.auto.tqdm, **tqdm_kwargs):
+        """Equivalent of `numpy.ndenumerate` or builtin `enumerate`."""
+
+    def tqdm.contrib.tzip(iter1, *iter2plus, **tqdm_kwargs):
+        """Equivalent of builtin `zip`."""
+
+    def tqdm.contrib.tmap(function, *sequences, **tqdm_kwargs):
+        """Equivalent of builtin `map`."""
+
+Submodules
+~~~~~~~~~~
+
+.. code:: python
+
+    class tqdm.notebook.tqdm(tqdm.tqdm):
+        """IPython/Jupyter Notebook widget."""
+
+    class tqdm.auto.tqdm(tqdm.tqdm):
+        """Automatically chooses beween `tqdm.notebook` and `tqdm.tqdm`."""
+
+    class tqdm.asyncio.tqdm(tqdm.tqdm):
+      """Asynchronous version."""
+      @classmethod
+      def as_completed(cls, fs, *, loop=None, timeout=None, total=None,
+                       **tqdm_kwargs):
+          """Wrapper for `asyncio.as_completed`."""
+
+    class tqdm.gui.tqdm(tqdm.tqdm):
+        """Matplotlib GUI version."""
+
+    class tqdm.tk.tqdm(tqdm.tqdm):
+        """Tkinter GUI version."""
+
+    class tqdm.rich.tqdm(tqdm.tqdm):
+        """`rich.progress` version."""
+
+    class tqdm.keras.TqdmCallback(keras.callbacks.Callback):
+        """Keras callback for epoch and batch progress."""
+
+    class tqdm.dask.TqdmCallback(dask.callbacks.Callback):
+        """Dask callback for task progress."""
+
+
+``contrib``
++++++++++++
+
+The ``tqdm.contrib`` package also contains experimental modules:
+
+- ``tqdm.contrib.itertools``: Thin wrappers around ``itertools``
+- ``tqdm.contrib.concurrent``: Thin wrappers around ``concurrent.futures``
+- ``tqdm.contrib.slack``: Posts to `Slack <https://slack.com>`__ bots
+- ``tqdm.contrib.discord``: Posts to `Discord <https://discord.com>`__ bots
+- ``tqdm.contrib.telegram``: Posts to `Telegram <https://telegram.org>`__ bots
+- ``tqdm.contrib.bells``: Automagically enables all optional features
+
+  * ``auto``, ``pandas``, ``slack``, ``discord``, ``telegram``
+
+Examples and Advanced Usage
+---------------------------
+
+- See the `examples <https://github.com/tqdm/tqdm/tree/master/examples>`__
+  folder;
+- import the module and run ``help()``;
+- consult the `wiki <https://github.com/tqdm/tqdm/wiki>`__;
+
+  * this has an
+    `excellent article <https://github.com/tqdm/tqdm/wiki/How-to-make-a-great-Progress-Bar>`__
+    on how to make a **great** progressbar;
+
+- check out the `slides from PyData London <https://tqdm.github.io/PyData2019/slides.html>`__, or
+- run the |binder-demo|.
+
+Description and additional stats
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Custom information can be displayed and updated dynamically on ``tqdm`` bars
+with the ``desc`` and ``postfix`` arguments:
+
+.. code:: python
+
+    from tqdm import tqdm, trange
+    from random import random, randint
+    from time import sleep
+
+    with trange(10) as t:
+        for i in t:
+            # Description will be displayed on the left
+            t.set_description('GEN %i' % i)
+            # Postfix will be displayed on the right,
+            # formatted automatically based on argument's datatype
+            t.set_postfix(loss=random(), gen=randint(1,999), str='h',
+                          lst=[1, 2])
+            sleep(0.1)
+
+    with tqdm(total=10, bar_format="{postfix[0]} {postfix[1][value]:>8.2g}",
+              postfix=["Batch", {"value": 0}]) as t:
+        for i in range(10):
+            sleep(0.1)
+            t.postfix[1]["value"] = i / 2
+            t.update()
+
+Points to remember when using ``{postfix[...]}`` in the ``bar_format`` string:
+
+- ``postfix`` also needs to be passed as an initial argument in a compatible
+  format, and
+- ``postfix`` will be auto-converted to a string if it is a ``dict``-like
+  object. To prevent this behaviour, insert an extra item into the dictionary
+  where the key is not a string.
+
+Additional ``bar_format`` parameters may also be defined by overriding
+``format_dict``, and the bar itself may be modified using ``ascii``:
+
+.. code:: python
+
+    from tqdm import tqdm
+    class TqdmExtraFormat(tqdm):
+        """Provides a `total_time` format parameter"""
+        @property
+        def format_dict(self):
+            d = super().format_dict
+            total_time = d["elapsed"] * (d["total"] or 0) / max(d["n"], 1)
+            d.update(total_time=self.format_interval(total_time) + " in total")
+            return d
+
+    for i in TqdmExtraFormat(
+          range(9), ascii=" .oO0",
+          bar_format="{total_time}: {percentage:.0f}%|{bar}{r_bar}"):
+        if i == 4:
+            break
+
+.. code::
+
+    00:00 in total: 44%|0000.     | 4/9 [00:00<00:00, 962.93it/s]
+
+Note that ``{bar}`` also supports a format specifier ``[width][type]``.
+
+- ``width``
+
+  * unspecified (default): automatic to fill ``ncols``
+  * ``int >= 0``: fixed width overriding ``ncols`` logic
+  * ``int < 0``: subtract from the automatic default
+
+- ``type``
+
+  * ``a``: ascii (``ascii=True`` override)
+  * ``u``: unicode (``ascii=False`` override)
+  * ``b``: blank (``ascii="  "`` override)
+
+This means a fixed bar with right-justified text may be created by using:
+``bar_format="{l_bar}{bar:10}|{bar:-10b}right-justified"``
+
+Nested progress bars
+~~~~~~~~~~~~~~~~~~~~
+
+``tqdm`` supports nested progress bars. Here's an example:
+
+.. code:: python
+
+    from tqdm.auto import trange
+    from time import sleep
+
+    for i in trange(4, desc='1st loop'):
+        for j in trange(5, desc='2nd loop'):
+            for k in trange(50, desc='3rd loop', leave=False):
+                sleep(0.01)
+
+For manual control over positioning (e.g. for multi-processing use),
+you may specify ``position=n`` where ``n=0`` for the outermost bar,
+``n=1`` for the next, and so on.
+However, it's best to check if ``tqdm`` can work without manual ``position``
+first.
+
+.. code:: python
+
+    from time import sleep
+    from tqdm import trange, tqdm
+    from multiprocessing import Pool, RLock, freeze_support
+
+    L = list(range(9))
+
+    def progresser(n):
+        interval = 0.001 / (n + 2)
+        total = 5000
+        text = f"#{n}, est. {interval * total:<04.2}s"
+        for _ in trange(total, desc=text, position=n):
+            sleep(interval)
+
+    if __name__ == '__main__':
+        freeze_support()  # for Windows support
+        tqdm.set_lock(RLock())  # for managing output contention
+        p = Pool(initializer=tqdm.set_lock, initargs=(tqdm.get_lock(),))
+        p.map(progresser, L)
+
+Note that in Python 3, ``tqdm.write`` is thread-safe:
+
+.. code:: python
+
+    from time import sleep
+    from tqdm import tqdm, trange
+    from concurrent.futures import ThreadPoolExecutor
+
+    L = list(range(9))
+
+    def progresser(n):
+        interval = 0.001 / (n + 2)
+        total = 5000
+        text = f"#{n}, est. {interval * total:<04.2}s"
+        for _ in trange(total, desc=text):
+            sleep(interval)
+        if n == 6:
+            tqdm.write("n == 6 completed.")
+            tqdm.write("`tqdm.write()` is thread-safe in py3!")
+
+    if __name__ == '__main__':
+        with ThreadPoolExecutor() as p:
+            p.map(progresser, L)
+
+Hooks and callbacks
+~~~~~~~~~~~~~~~~~~~
+
+``tqdm`` can easily support callbacks/hooks and manual updates.
+Here's an example with ``urllib``:
+
+**``urllib.urlretrieve`` documentation**
+
+    | [...]
+    | If present, the hook function will be called once
+    | on establishment of the network connection and once after each block read
+    | thereafter. The hook will be passed three arguments; a count of blocks
+    | transferred so far, a block size in bytes, and the total size of the file.
+    | [...]
+
+.. code:: python
+
+    import urllib, os
+    from tqdm import tqdm
+    urllib = getattr(urllib, 'request', urllib)
+
+    class TqdmUpTo(tqdm):
+        """Provides `update_to(n)` which uses `tqdm.update(delta_n)`."""
+        def update_to(self, b=1, bsize=1, tsize=None):
+            """
+            b  : int, optional
+                Number of blocks transferred so far [default: 1].
+            bsize  : int, optional
+                Size of each block (in tqdm units) [default: 1].
+            tsize  : int, optional
+                Total size (in tqdm units). If [default: None] remains unchanged.
+            """
+            if tsize is not None:
+                self.total = tsize
+            return self.update(b * bsize - self.n)  # also sets self.n = b * bsize
+
+    eg_link = "https://caspersci.uk.to/matryoshka.zip"
+    with TqdmUpTo(unit='B', unit_scale=True, unit_divisor=1024, miniters=1,
+                  desc=eg_link.split('/')[-1]) as t:  # all optional kwargs
+        urllib.urlretrieve(eg_link, filename=os.devnull,
+                           reporthook=t.update_to, data=None)
+        t.total = t.n
+
+Inspired by `twine#242 <https://github.com/pypa/twine/pull/242>`__.
+Functional alternative in
+`examples/tqdm_wget.py <https://github.com/tqdm/tqdm/blob/master/examples/tqdm_wget.py>`__.
+
+It is recommend to use ``miniters=1`` whenever there is potentially
+large differences in iteration speed (e.g. downloading a file over
+a patchy connection).
+
+**Wrapping read/write methods**
+
+To measure throughput through a file-like object's ``read`` or ``write``
+methods, use ``CallbackIOWrapper``:
+
+.. code:: python
+
+    from tqdm.auto import tqdm
+    from tqdm.utils import CallbackIOWrapper
+
+    with tqdm(total=file_obj.size,
+              unit='B', unit_scale=True, unit_divisor=1024) as t:
+        fobj = CallbackIOWrapper(t.update, file_obj, "read")
+        while True:
+            chunk = fobj.read(chunk_size)
+            if not chunk:
+                break
+        t.reset()
+        # ... continue to use `t` for something else
+
+Alternatively, use the even simpler ``wrapattr`` convenience function,
+which would condense both the ``urllib`` and ``CallbackIOWrapper`` examples
+down to:
+
+.. code:: python
+
+    import urllib, os
+    from tqdm import tqdm
+
+    eg_link = "https://caspersci.uk.to/matryoshka.zip"
+    response = getattr(urllib, 'request', urllib).urlopen(eg_link)
+    with tqdm.wrapattr(open(os.devnull, "wb"), "write",
+                       miniters=1, desc=eg_link.split('/')[-1],
+                       total=getattr(response, 'length', None)) as fout:
+        for chunk in response:
+            fout.write(chunk)
+
+The ``requests`` equivalent is nearly identical:
+
+.. code:: python
+
+    import requests, os
+    from tqdm import tqdm
+
+    eg_link = "https://caspersci.uk.to/matryoshka.zip"
+    response = requests.get(eg_link, stream=True)
+    with tqdm.wrapattr(open(os.devnull, "wb"), "write",
+                       miniters=1, desc=eg_link.split('/')[-1],
+                       total=int(response.headers.get('content-length', 0))) as fout:
+        for chunk in response.iter_content(chunk_size=4096):
+            fout.write(chunk)
+
+**Custom callback**
+
+``tqdm`` is known for intelligently skipping unnecessary displays. To make a
+custom callback take advantage of this, simply use the return value of
+``update()``. This is set to ``True`` if a ``display()`` was triggered.
+
+.. code:: python
+
+    from tqdm.auto import tqdm as std_tqdm
+
+    def external_callback(*args, **kwargs):
+        ...
+
+    class TqdmExt(std_tqdm):
+        def update(self, n=1):
+            displayed = super().update(n)
+            if displayed:
+                external_callback(**self.format_dict)
+            return displayed
+
+``asyncio``
+~~~~~~~~~~~
+
+Note that ``break`` isn't currently caught by asynchronous iterators.
+This means that ``tqdm`` cannot clean up after itself in this case:
+
+.. code:: python
+
+    from tqdm.asyncio import tqdm
+
+    async for i in tqdm(range(9)):
+        if i == 2:
+            break
+
+Instead, either call ``pbar.close()`` manually or use the context manager syntax:
+
+.. code:: python
+
+    from tqdm.asyncio import tqdm
+
+    with tqdm(range(9)) as pbar:
+        async for i in pbar:
+            if i == 2:
+                break
+
+Pandas Integration
+~~~~~~~~~~~~~~~~~~
+
+Due to popular demand we've added support for ``pandas`` -- here's an example
+for ``DataFrame.progress_apply`` and ``DataFrameGroupBy.progress_apply``:
+
+.. code:: python
+
+    import pandas as pd
+    import numpy as np
+    from tqdm import tqdm
+
+    df = pd.DataFrame(np.random.randint(0, 100, (100000, 6)))
+
+    # Register `pandas.progress_apply` and `pandas.Series.map_apply` with `tqdm`
+    # (can use `tqdm.gui.tqdm`, `tqdm.notebook.tqdm`, optional kwargs, etc.)
+    tqdm.pandas(desc="my bar!")
+
+    # Now you can use `progress_apply` instead of `apply`
+    # and `progress_map` instead of `map`
+    df.progress_apply(lambda x: x**2)
+    # can also groupby:
+    # df.groupby(0).progress_apply(lambda x: x**2)
+
+In case you're interested in how this works (and how to modify it for your
+own callbacks), see the
+`examples <https://github.com/tqdm/tqdm/tree/master/examples>`__
+folder or import the module and run ``help()``.
+
+Keras Integration
+~~~~~~~~~~~~~~~~~
+
+A ``keras`` callback is also available:
+
+.. code:: python
+
+    from tqdm.keras import TqdmCallback
+
+    ...
+
+    model.fit(..., verbose=0, callbacks=[TqdmCallback()])
+
+Dask Integration
+~~~~~~~~~~~~~~~~
+
+A ``dask`` callback is also available:
+
+.. code:: python
+
+    from tqdm.dask import TqdmCallback
+
+    with TqdmCallback(desc="compute"):
+        ...
+        arr.compute()
+
+    # or use callback globally
+    cb = TqdmCallback(desc="global")
+    cb.register()
+    arr.compute()
+
+IPython/Jupyter Integration
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+IPython/Jupyter is supported via the ``tqdm.notebook`` submodule:
+
+.. code:: python
+
+    from tqdm.notebook import trange, tqdm
+    from time import sleep
+
+    for i in trange(3, desc='1st loop'):
+        for j in tqdm(range(100), desc='2nd loop'):
+            sleep(0.01)
+
+In addition to ``tqdm`` features, the submodule provides a native Jupyter
+widget (compatible with IPython v1-v4 and Jupyter), fully working nested bars
+and colour hints (blue: normal, green: completed, red: error/interrupt,
+light blue: no ETA); as demonstrated below.
+
+|Screenshot-Jupyter1|
+|Screenshot-Jupyter2|
+|Screenshot-Jupyter3|
+
+The ``notebook`` version supports percentage or pixels for overall width
+(e.g.: ``ncols='100%'`` or ``ncols='480px'``).
+
+It is also possible to let ``tqdm`` automatically choose between
+console or notebook versions by using the ``autonotebook`` submodule:
+
+.. code:: python
+
+    from tqdm.autonotebook import tqdm
+    tqdm.pandas()
+
+Note that this will issue a ``TqdmExperimentalWarning`` if run in a notebook
+since it is not meant to be possible to distinguish between ``jupyter notebook``
+and ``jupyter console``. Use ``auto`` instead of ``autonotebook`` to suppress
+this warning.
+
+Note that notebooks will display the bar in the cell where it was created.
+This may be a different cell from the one where it is used.
+If this is not desired, either
+
+- delay the creation of the bar to the cell where it must be displayed, or
+- create the bar with ``display=False``, and in a later cell call
+  ``display(bar.container)``:
+
+.. code:: python
+
+    from tqdm.notebook import tqdm
+    pbar = tqdm(..., display=False)
+
+.. code:: python
+
+    # different cell
+    display(pbar.container)
+
+The ``keras`` callback has a ``display()`` method which can be used likewise:
+
+.. code:: python
+
+    from tqdm.keras import TqdmCallback
+    cbk = TqdmCallback(display=False)
+
+.. code:: python
+
+    # different cell
+    cbk.display()
+    model.fit(..., verbose=0, callbacks=[cbk])
+
+Another possibility is to have a single bar (near the top of the notebook)
+which is constantly re-used (using ``reset()`` rather than ``close()``).
+For this reason, the notebook version (unlike the CLI version) does not
+automatically call ``close()`` upon ``Exception``.
+
+.. code:: python
+
+    from tqdm.notebook import tqdm
+    pbar = tqdm()
+
+.. code:: python
+
+    # different cell
+    iterable = range(100)
+    pbar.reset(total=len(iterable))  # initialise with new `total`
+    for i in iterable:
+        pbar.update()
+    pbar.refresh()  # force print final status but don't `close()`
+
+Custom Integration
+~~~~~~~~~~~~~~~~~~
+
+To change the default arguments (such as making ``dynamic_ncols=True``),
+simply use built-in Python magic:
+
+.. code:: python
+
+    from functools import partial
+    from tqdm import tqdm as std_tqdm
+    tqdm = partial(std_tqdm, dynamic_ncols=True)
+
+For further customisation,
+``tqdm`` may be inherited from to create custom callbacks (as with the
+``TqdmUpTo`` example `above <#hooks-and-callbacks>`__) or for custom frontends
+(e.g. GUIs such as notebook or plotting packages). In the latter case:
+
+1. ``def __init__()`` to call ``super().__init__(..., gui=True)`` to disable
+   terminal ``status_printer`` creation.
+2. Redefine: ``close()``, ``clear()``, ``display()``.
+
+Consider overloading ``display()`` to use e.g.
+``self.frontend(**self.format_dict)`` instead of ``self.sp(repr(self))``.
+
+Some submodule examples of inheritance:
+
+- `tqdm/notebook.py <https://github.com/tqdm/tqdm/blob/master/tqdm/notebook.py>`__
+- `tqdm/gui.py <https://github.com/tqdm/tqdm/blob/master/tqdm/gui.py>`__
+- `tqdm/tk.py <https://github.com/tqdm/tqdm/blob/master/tqdm/tk.py>`__
+- `tqdm/contrib/slack.py <https://github.com/tqdm/tqdm/blob/master/tqdm/contrib/slack.py>`__
+- `tqdm/contrib/discord.py <https://github.com/tqdm/tqdm/blob/master/tqdm/contrib/discord.py>`__
+- `tqdm/contrib/telegram.py <https://github.com/tqdm/tqdm/blob/master/tqdm/contrib/telegram.py>`__
+
+Dynamic Monitor/Meter
+~~~~~~~~~~~~~~~~~~~~~
+
+You can use a ``tqdm`` as a meter which is not monotonically increasing.
+This could be because ``n`` decreases (e.g. a CPU usage monitor) or ``total``
+changes.
+
+One example would be recursively searching for files. The ``total`` is the
+number of objects found so far, while ``n`` is the number of those objects which
+are files (rather than folders):
+
+.. code:: python
+
+    from tqdm import tqdm
+    import os.path
+
+    def find_files_recursively(path, show_progress=True):
+        files = []
+        # total=1 assumes `path` is a file
+        t = tqdm(total=1, unit="file", disable=not show_progress)
+        if not os.path.exists(path):
+            raise IOError("Cannot find:" + path)
+
+        def append_found_file(f):
+            files.append(f)
+            t.update()
+
+        def list_found_dir(path):
+            """returns os.listdir(path) assuming os.path.isdir(path)"""
+            listing = os.listdir(path)
+            # subtract 1 since a "file" we found was actually this directory
+            t.total += len(listing) - 1
+            # fancy way to give info without forcing a refresh
+            t.set_postfix(dir=path[-10:], refresh=False)
+            t.update(0)  # may trigger a refresh
+            return listing
+
+        def recursively_search(path):
+            if os.path.isdir(path):
+                for f in list_found_dir(path):
+                    recursively_search(os.path.join(path, f))
+            else:
+                append_found_file(path)
+
+        recursively_search(path)
+        t.set_postfix(dir=path)
+        t.close()
+        return files
+
+Using ``update(0)`` is a handy way to let ``tqdm`` decide when to trigger a
+display refresh to avoid console spamming.
+
+Writing messages
+~~~~~~~~~~~~~~~~
+
+This is a work in progress (see
+`#737 <https://github.com/tqdm/tqdm/issues/737>`__).
+
+Since ``tqdm`` uses a simple printing mechanism to display progress bars,
+you should not write any message in the terminal using ``print()`` while
+a progressbar is open.
+
+To write messages in the terminal without any collision with ``tqdm`` bar
+display, a ``.write()`` method is provided:
+
+.. code:: python
+
+    from tqdm.auto import tqdm, trange
+    from time import sleep
+
+    bar = trange(10)
+    for i in bar:
+        # Print using tqdm class method .write()
+        sleep(0.1)
+        if not (i % 3):
+            tqdm.write("Done task %i" % i)
+        # Can also use bar.write()
+
+By default, this will print to standard output ``sys.stdout``. but you can
+specify any file-like object using the ``file`` argument. For example, this
+can be used to redirect the messages writing to a log file or class.
+
+Redirecting writing
+~~~~~~~~~~~~~~~~~~~
+
+If using a library that can print messages to the console, editing the library
+by  replacing ``print()`` with ``tqdm.write()`` may not be desirable.
+In that case, redirecting ``sys.stdout`` to ``tqdm.write()`` is an option.
+
+To redirect ``sys.stdout``, create a file-like class that will write
+any input string to ``tqdm.write()``, and supply the arguments
+``file=sys.stdout, dynamic_ncols=True``.
+
+A reusable canonical example is given below:
+
+.. code:: python
+
+    from time import sleep
+    import contextlib
+    import sys
+    from tqdm import tqdm
+    from tqdm.contrib import DummyTqdmFile
+
+
+    @contextlib.contextmanager
+    def std_out_err_redirect_tqdm():
+        orig_out_err = sys.stdout, sys.stderr
+        try:
+            sys.stdout, sys.stderr = map(DummyTqdmFile, orig_out_err)
+            yield orig_out_err[0]
+        # Relay exceptions
+        except Exception as exc:
+            raise exc
+        # Always restore sys.stdout/err if necessary
+        finally:
+            sys.stdout, sys.stderr = orig_out_err
+
+    def some_fun(i):
+        print("Fee, fi, fo,".split()[i])
+
+    # Redirect stdout to tqdm.write() (don't forget the `as save_stdout`)
+    with std_out_err_redirect_tqdm() as orig_stdout:
+        # tqdm needs the original stdout
+        # and dynamic_ncols=True to autodetect console width
+        for i in tqdm(range(3), file=orig_stdout, dynamic_ncols=True):
+            sleep(.5)
+            some_fun(i)
+
+    # After the `with`, printing is restored
+    print("Done!")
+
+Redirecting ``logging``
+~~~~~~~~~~~~~~~~~~~~~~~
+
+Similar to ``sys.stdout``/``sys.stderr`` as detailed above, console ``logging``
+may also be redirected to ``tqdm.write()``.
+
+Warning: if also redirecting ``sys.stdout``/``sys.stderr``, make sure to
+redirect ``logging`` first if needed.
+
+Helper methods are available in ``tqdm.contrib.logging``. For example:
+
+.. code:: python
+
+    import logging
+    from tqdm import trange
+    from tqdm.contrib.logging import logging_redirect_tqdm
+
+    LOG = logging.getLogger(__name__)
+
+    if __name__ == '__main__':
+        logging.basicConfig(level=logging.INFO)
+        with logging_redirect_tqdm():
+            for i in trange(9):
+                if i == 4:
+                    LOG.info("console logging redirected to `tqdm.write()`")
+        # logging restored
+
+Monitoring thread, intervals and miniters
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+``tqdm`` implements a few tricks to increase efficiency and reduce overhead.
+
+- Avoid unnecessary frequent bar refreshing: ``mininterval`` defines how long
+  to wait between each refresh. ``tqdm`` always gets updated in the background,
+  but it will display only every ``mininterval``.
+- Reduce number of calls to check system clock/time.
+- ``mininterval`` is more intuitive to configure than ``miniters``.
+  A clever adjustment system ``dynamic_miniters`` will automatically adjust
+  ``miniters`` to the amount of iterations that fit into time ``mininterval``.
+  Essentially, ``tqdm`` will check if it's time to print without actually
+  checking time. This behaviour can be still be bypassed by manually setting
+  ``miniters``.
+
+However, consider a case with a combination of fast and slow iterations.
+After a few fast iterations, ``dynamic_miniters`` will set ``miniters`` to a
+large number. When iteration rate subsequently slows, ``miniters`` will
+remain large and thus reduce display update frequency. To address this:
+
+- ``maxinterval`` defines the maximum time between display refreshes.
+  A concurrent monitoring thread checks for overdue updates and forces one
+  where necessary.
+
+The monitoring thread should not have a noticeable overhead, and guarantees
+updates at least every 10 seconds by default.
+This value can be directly changed by setting the ``monitor_interval`` of
+any ``tqdm`` instance (i.e. ``t = tqdm.tqdm(...); t.monitor_interval = 2``).
+The monitor thread may be disabled application-wide by setting
+``tqdm.tqdm.monitor_interval = 0`` before instantiation of any ``tqdm`` bar.
+
+
+Merch
+-----
+
+You can buy `tqdm branded merch <https://tqdm.github.io/merch>`__ now!
+
+Contributions
+-------------
+
+|GitHub-Commits| |GitHub-Issues| |GitHub-PRs| |OpenHub-Status| |GitHub-Contributions| |CII Best Practices|
+
+All source code is hosted on `GitHub <https://github.com/tqdm/tqdm>`__.
+Contributions are welcome.
+
+See the
+`CONTRIBUTING <https://github.com/tqdm/tqdm/blob/master/CONTRIBUTING.md>`__
+file for more information.
+
+Developers who have made significant contributions, ranked by *SLoC*
+(surviving lines of code,
+`git fame <https://github.com/casperdcl/git-fame>`__ ``-wMC --excl '\.(png|gif|jpg)$'``),
+are:
+
+==================== ======================================================== ==== ================================
+Name                 ID                                                       SLoC Notes
+==================== ======================================================== ==== ================================
+Casper da Costa-Luis `casperdcl <https://github.com/casperdcl>`__             ~80% primary maintainer |Gift-Casper|
+Stephen Larroque     `lrq3000 <https://github.com/lrq3000>`__                 ~9%  team member
+Martin Zugnoni       `martinzugnoni <https://github.com/martinzugnoni>`__     ~3%
+Daniel Ecer          `de-code <https://github.com/de-code>`__                 ~2%
+Richard Sheridan     `richardsheridan <https://github.com/richardsheridan>`__ ~1%
+Guangshuo Chen       `chengs <https://github.com/chengs>`__                   ~1%
+Helio Machado        `0x2b3bfa0 <https://github.com/0x2b3bfa0>`__             ~1%
+Kyle Altendorf       `altendky <https://github.com/altendky>`__               <1%
+Noam Yorav-Raphael   `noamraph <https://github.com/noamraph>`__               <1%  original author
+Matthew Stevens      `mjstevens777 <https://github.com/mjstevens777>`__       <1%
+Hadrien Mary         `hadim <https://github.com/hadim>`__                     <1%  team member
+Mikhail Korobov      `kmike <https://github.com/kmike>`__                     <1%  team member
+==================== ======================================================== ==== ================================
+
+Ports to Other Languages
+~~~~~~~~~~~~~~~~~~~~~~~~
+
+A list is available on
+`this wiki page <https://github.com/tqdm/tqdm/wiki/tqdm-ports>`__.
+
+
+LICENCE
+-------
+
+Open Source (OSI approved): |LICENCE|
+
+Citation information: |DOI|
+
+|README-Hits| (Since 19 May 2016)
+
+.. |Logo| image:: https://tqdm.github.io/img/logo.gif
+.. |Screenshot| image:: https://tqdm.github.io/img/tqdm.gif
+.. |Video| image:: https://tqdm.github.io/img/video.jpg
+   :target: https://tqdm.github.io/video
+.. |Slides| image:: https://tqdm.github.io/img/slides.jpg
+   :target: https://tqdm.github.io/PyData2019/slides.html
+.. |Merch| image:: https://tqdm.github.io/img/merch.jpg
+   :target: https://tqdm.github.io/merch
+.. |Build-Status| image:: https://img.shields.io/github/actions/workflow/status/tqdm/tqdm/test.yml?branch=master&label=tqdm&logo=GitHub
+   :target: https://github.com/tqdm/tqdm/actions/workflows/test.yml
+.. |Coverage-Status| image:: https://img.shields.io/coveralls/github/tqdm/tqdm/master?logo=coveralls
+   :target: https://coveralls.io/github/tqdm/tqdm
+.. |Branch-Coverage-Status| image:: https://codecov.io/gh/tqdm/tqdm/branch/master/graph/badge.svg
+   :target: https://codecov.io/gh/tqdm/tqdm
+.. |Codacy-Grade| image:: https://app.codacy.com/project/badge/Grade/3f965571598f44549c7818f29cdcf177
+   :target: https://www.codacy.com/gh/tqdm/tqdm/dashboard
+.. |CII Best Practices| image:: https://bestpractices.coreinfrastructure.org/projects/3264/badge
+   :target: https://bestpractices.coreinfrastructure.org/projects/3264
+.. |GitHub-Status| image:: https://img.shields.io/github/tag/tqdm/tqdm.svg?maxAge=86400&logo=github&logoColor=white
+   :target: https://github.com/tqdm/tqdm/releases
+.. |GitHub-Forks| image:: https://img.shields.io/github/forks/tqdm/tqdm.svg?logo=github&logoColor=white
+   :target: https://github.com/tqdm/tqdm/network
+.. |GitHub-Stars| image:: https://img.shields.io/github/stars/tqdm/tqdm.svg?logo=github&logoColor=white
+   :target: https://github.com/tqdm/tqdm/stargazers
+.. |GitHub-Commits| image:: https://img.shields.io/github/commit-activity/y/tqdm/tqdm.svg?logo=git&logoColor=white
+   :target: https://github.com/tqdm/tqdm/graphs/commit-activity
+.. |GitHub-Issues| image:: https://img.shields.io/github/issues-closed/tqdm/tqdm.svg?logo=github&logoColor=white
+   :target: https://github.com/tqdm/tqdm/issues?q=
+.. |GitHub-PRs| image:: https://img.shields.io/github/issues-pr-closed/tqdm/tqdm.svg?logo=github&logoColor=white
+   :target: https://github.com/tqdm/tqdm/pulls
+.. |GitHub-Contributions| image:: https://img.shields.io/github/contributors/tqdm/tqdm.svg?logo=github&logoColor=white
+   :target: https://github.com/tqdm/tqdm/graphs/contributors
+.. |GitHub-Updated| image:: https://img.shields.io/github/last-commit/tqdm/tqdm/master.svg?logo=github&logoColor=white&label=pushed
+   :target: https://github.com/tqdm/tqdm/pulse
+.. |Gift-Casper| image:: https://img.shields.io/badge/dynamic/json.svg?color=ff69b4&label=gifts%20received&prefix=%C2%A3&query=%24..sum&url=https%3A%2F%2Fcaspersci.uk.to%2Fgifts.json
+   :target: https://cdcl.ml/sponsor
+.. |Versions| image:: https://img.shields.io/pypi/v/tqdm.svg
+   :target: https://tqdm.github.io/releases
+.. |PyPI-Downloads| image:: https://img.shields.io/pypi/dm/tqdm.svg?label=pypi%20downloads&logo=PyPI&logoColor=white
+   :target: https://pepy.tech/project/tqdm
+.. |Py-Versions| image:: https://img.shields.io/pypi/pyversions/tqdm.svg?logo=python&logoColor=white
+   :target: https://pypi.org/project/tqdm
+.. |Conda-Forge-Status| image:: https://img.shields.io/conda/v/conda-forge/tqdm.svg?label=conda-forge&logo=conda-forge
+   :target: https://anaconda.org/conda-forge/tqdm
+.. |Snapcraft| image:: https://img.shields.io/badge/snap-install-82BEA0.svg?logo=snapcraft
+   :target: https://snapcraft.io/tqdm
+.. |Docker| image:: https://img.shields.io/badge/docker-pull-blue.svg?logo=docker&logoColor=white
+   :target: https://hub.docker.com/r/tqdm/tqdm
+.. |Libraries-Rank| image:: https://img.shields.io/librariesio/sourcerank/pypi/tqdm.svg?logo=koding&logoColor=white
+   :target: https://libraries.io/pypi/tqdm
+.. |Libraries-Dependents| image:: https://img.shields.io/librariesio/dependent-repos/pypi/tqdm.svg?logo=koding&logoColor=white
+    :target: https://github.com/tqdm/tqdm/network/dependents
+.. |OpenHub-Status| image:: https://www.openhub.net/p/tqdm/widgets/project_thin_badge?format=gif
+   :target: https://www.openhub.net/p/tqdm?ref=Thin+badge
+.. |awesome-python| image:: https://awesome.re/mentioned-badge.svg
+   :target: https://github.com/vinta/awesome-python
+.. |LICENCE| image:: https://img.shields.io/pypi/l/tqdm.svg
+   :target: https://raw.githubusercontent.com/tqdm/tqdm/master/LICENCE
+.. |DOI| image:: https://img.shields.io/badge/DOI-10.5281/zenodo.595120-blue.svg
+   :target: https://doi.org/10.5281/zenodo.595120
+.. |binder-demo| image:: https://mybinder.org/badge_logo.svg
+   :target: https://mybinder.org/v2/gh/tqdm/tqdm/master?filepath=DEMO.ipynb
+.. |Screenshot-Jupyter1| image:: https://tqdm.github.io/img/jupyter-1.gif
+.. |Screenshot-Jupyter2| image:: https://tqdm.github.io/img/jupyter-2.gif
+.. |Screenshot-Jupyter3| image:: https://tqdm.github.io/img/jupyter-3.gif
+.. |README-Hits| image:: https://cgi.cdcl.ml/hits?q=tqdm&style=social&r=https://github.com/tqdm/tqdm&l=https://tqdm.github.io/img/favicon.png&f=https://tqdm.github.io/img/logo.gif
+   :target: https://cgi.cdcl.ml/hits?q=tqdm&a=plot&r=https://github.com/tqdm/tqdm&l=https://tqdm.github.io/img/favicon.png&f=https://tqdm.github.io/img/logo.gif&style=social

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+Metadata-Version: 2.1
+Name: openpyxl
+Version: 3.1.5
+Summary: A Python library to read/write Excel 2010 xlsx/xlsm files
+Home-page: https://openpyxl.readthedocs.io
+Author: See AUTHORS
+Author-email: charlie.clark@clark-consulting.eu
+License: MIT
+Project-URL: Documentation, https://openpyxl.readthedocs.io/en/stable/
+Project-URL: Source, https://foss.heptapod.net/openpyxl/openpyxl
+Project-URL: Tracker, https://foss.heptapod.net/openpyxl/openpyxl/-/issues
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Operating System :: MacOS :: MacOS X
+Classifier: Operating System :: Microsoft :: Windows
+Classifier: Operating System :: POSIX
+Classifier: License :: OSI Approved :: MIT License
+Classifier: Programming Language :: Python
+Classifier: Programming Language :: Python :: 3.6
+Classifier: Programming Language :: Python :: 3.7
+Classifier: Programming Language :: Python :: 3.8
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Requires-Python: >=3.8
+License-File: LICENCE.rst
+Requires-Dist: et-xmlfile
+
+.. image:: https://coveralls.io/repos/bitbucket/openpyxl/openpyxl/badge.svg?branch=default
+    :target: https://coveralls.io/bitbucket/openpyxl/openpyxl?branch=default
+    :alt: coverage status
+
+Introduction
+------------
+
+openpyxl is a Python library to read/write Excel 2010 xlsx/xlsm/xltx/xltm files.
+
+It was born from lack of existing library to read/write natively from Python
+the Office Open XML format.
+
+All kudos to the PHPExcel team as openpyxl was initially based on PHPExcel.
+
+
+Security
+--------
+
+By default openpyxl does not guard against quadratic blowup or billion laughs
+xml attacks. To guard against these attacks install defusedxml.
+
+Mailing List
+------------
+
+The user list can be found on http://groups.google.com/group/openpyxl-users
+
+
+Sample code::
+
+    from openpyxl import Workbook
+    wb = Workbook()
+
+    # grab the active worksheet
+    ws = wb.active
+
+    # Data can be assigned directly to cells
+    ws['A1'] = 42
+
+    # Rows can also be appended
+    ws.append([1, 2, 3])
+
+    # Python types will automatically be converted
+    import datetime
+    ws['A2'] = datetime.datetime.now()
+
+    # Save the file
+    wb.save("sample.xlsx")
+
+
+Documentation
+-------------
+
+The documentation is at: https://openpyxl.readthedocs.io
+
+* installation methods
+* code examples
+* instructions for contributing
+
+Release notes: https://openpyxl.readthedocs.io/en/stable/changes.html

.cache/pip/http-v2/5/b/4/0/d/5b40d68cf8d927e2221e1237399fe71c3f05e873a098ccc481be149a.body

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+Metadata-Version: 2.4
+Name: huggingface_hub
+Version: 1.10.1
+Summary: Client library to download and publish models, datasets and other repos on the huggingface.co hub
+Home-page: https://github.com/huggingface/huggingface_hub
+Author: Hugging Face, Inc.
+Author-email: julien@huggingface.co
+License: Apache-2.0
+Keywords: model-hub machine-learning models natural-language-processing deep-learning pytorch pretrained-models
+Classifier: Intended Audience :: Developers
+Classifier: Intended Audience :: Education
+Classifier: Intended Audience :: Science/Research
+Classifier: License :: OSI Approved :: Apache Software License
+Classifier: Operating System :: OS Independent
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3 :: Only
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3.12
+Classifier: Programming Language :: Python :: 3.13
+Classifier: Programming Language :: Python :: 3.14
+Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
+Requires-Python: >=3.10.0
+Description-Content-Type: text/markdown
+License-File: LICENSE
+Requires-Dist: filelock>=3.10.0
+Requires-Dist: fsspec>=2023.5.0
+Requires-Dist: hf-xet<2.0.0,>=1.4.3; platform_machine == "x86_64" or platform_machine == "amd64" or platform_machine == "AMD64" or platform_machine == "arm64" or platform_machine == "aarch64"
+Requires-Dist: httpx<1,>=0.23.0
+Requires-Dist: packaging>=20.9
+Requires-Dist: pyyaml>=5.1
+Requires-Dist: tqdm>=4.42.1
+Requires-Dist: typer
+Requires-Dist: typing-extensions>=4.1.0
+Provides-Extra: oauth
+Requires-Dist: authlib>=1.3.2; extra == "oauth"
+Requires-Dist: fastapi; extra == "oauth"
+Requires-Dist: httpx; extra == "oauth"
+Requires-Dist: itsdangerous; extra == "oauth"
+Provides-Extra: torch
+Requires-Dist: torch; extra == "torch"
+Requires-Dist: safetensors[torch]; extra == "torch"
+Provides-Extra: fastai
+Requires-Dist: toml; extra == "fastai"
+Requires-Dist: fastai>=2.4; extra == "fastai"
+Requires-Dist: fastcore>=1.3.27; extra == "fastai"
+Provides-Extra: hf-xet
+Requires-Dist: hf-xet<2.0.0,>=1.4.3; extra == "hf-xet"
+Provides-Extra: mcp
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+Provides-Extra: testing
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+Requires-Dist: Jinja2; extra == "testing"
+Requires-Dist: pytest>=8.4.2; extra == "testing"
+Requires-Dist: pytest-cov; extra == "testing"
+Requires-Dist: pytest-env; extra == "testing"
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+Provides-Extra: gradio
+Requires-Dist: gradio>=5.0.0; extra == "gradio"
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+Provides-Extra: typing
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+Requires-Dist: types-simplejson; extra == "typing"
+Requires-Dist: types-toml; extra == "typing"
+Requires-Dist: types-tqdm; extra == "typing"
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+Provides-Extra: quality
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+Requires-Dist: duckdb; extra == "all"
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+Requires-Dist: types-urllib3; extra == "all"
+Provides-Extra: dev
+Requires-Dist: authlib>=1.3.2; extra == "dev"
+Requires-Dist: fastapi; extra == "dev"
+Requires-Dist: httpx; extra == "dev"
+Requires-Dist: itsdangerous; extra == "dev"
+Requires-Dist: jedi; extra == "dev"
+Requires-Dist: Jinja2; extra == "dev"
+Requires-Dist: pytest>=8.4.2; extra == "dev"
+Requires-Dist: pytest-cov; extra == "dev"
+Requires-Dist: pytest-env; extra == "dev"
+Requires-Dist: pytest-xdist; extra == "dev"
+Requires-Dist: pytest-vcr; extra == "dev"
+Requires-Dist: pytest-asyncio; extra == "dev"
+Requires-Dist: pytest-rerunfailures<16.0; extra == "dev"
+Requires-Dist: pytest-mock; extra == "dev"
+Requires-Dist: urllib3<2.0; extra == "dev"
+Requires-Dist: soundfile; extra == "dev"
+Requires-Dist: Pillow; extra == "dev"
+Requires-Dist: numpy; extra == "dev"
+Requires-Dist: duckdb; extra == "dev"
+Requires-Dist: fastapi; extra == "dev"
+Requires-Dist: ruff>=0.9.0; extra == "dev"
+Requires-Dist: mypy==1.15.0; extra == "dev"
+Requires-Dist: libcst>=1.4.0; extra == "dev"
+Requires-Dist: ty; extra == "dev"
+Requires-Dist: typing-extensions>=4.8.0; extra == "dev"
+Requires-Dist: types-PyYAML; extra == "dev"
+Requires-Dist: types-simplejson; extra == "dev"
+Requires-Dist: types-toml; extra == "dev"
+Requires-Dist: types-tqdm; extra == "dev"
+Requires-Dist: types-urllib3; extra == "dev"
+Dynamic: author
+Dynamic: author-email
+Dynamic: classifier
+Dynamic: description
+Dynamic: description-content-type
+Dynamic: home-page
+Dynamic: keywords
+Dynamic: license
+Dynamic: license-file
+Dynamic: provides-extra
+Dynamic: requires-dist
+Dynamic: requires-python
+Dynamic: summary
+
+<p align="center">
+  <picture>
+    <source media="(prefers-color-scheme: dark)" srcset="https://huggingface.co/datasets/huggingface/documentation-images/raw/main/huggingface_hub-dark.svg">
+    <source media="(prefers-color-scheme: light)" srcset="https://huggingface.co/datasets/huggingface/documentation-images/raw/main/huggingface_hub.svg">
+    <img alt="huggingface_hub library logo" src="https://huggingface.co/datasets/huggingface/documentation-images/raw/main/huggingface_hub.svg" width="352" height="59" style="max-width: 100%">
+  </picture>
+  <br/>
+  <br/>
+</p> 
+
+<p align="center">
+    <i>The official Python client for the Huggingface Hub.</i>
+</p>
+
+<p align="center">
+    <a href="https://huggingface.co/docs/huggingface_hub/en/index"><img alt="Documentation" src="https://img.shields.io/website/http/huggingface.co/docs/huggingface_hub/index.svg?down_color=red&down_message=offline&up_message=online&label=doc"></a>
+    <a href="https://github.com/huggingface/huggingface_hub/releases"><img alt="GitHub release" src="https://img.shields.io/github/release/huggingface/huggingface_hub.svg"></a>
+    <a href="https://github.com/huggingface/huggingface_hub"><img alt="PyPi version" src="https://img.shields.io/pypi/pyversions/huggingface_hub.svg"></a>
+    <a href="https://pypi.org/project/huggingface-hub"><img alt="PyPI - Downloads" src="https://img.shields.io/pypi/dm/huggingface_hub"></a>
+    <a href="https://codecov.io/gh/huggingface/huggingface_hub"><img alt="Code coverage" src="https://codecov.io/gh/huggingface/huggingface_hub/branch/main/graph/badge.svg?token=RXP95LE2XL"></a>
+</p>
+
+<h4 align="center">
+    <p>
+        <b>English</b> |
+        <a href="https://github.com/huggingface/huggingface_hub/blob/main/i18n/README_de.md">Deutsch</a> |
+        <a href="https://github.com/huggingface/huggingface_hub/blob/main/i18n/README_fr.md">Français</a> |
+        <a href="https://github.com/huggingface/huggingface_hub/blob/main/i18n/README_hi.md">हिंदी</a> |
+        <a href="https://github.com/huggingface/huggingface_hub/blob/main/i18n/README_ko.md">한국어</a> |
+        <a href="https://github.com/huggingface/huggingface_hub/blob/main/i18n/README_cn.md">中文 (简体)</a>
+    <p>
+</h4>
+
+---
+
+**Documentation**: <a href="https://hf.co/docs/huggingface_hub" target="_blank">https://hf.co/docs/huggingface_hub</a>
+
+**Source Code**: <a href="https://github.com/huggingface/huggingface_hub" target="_blank">https://github.com/huggingface/huggingface_hub</a>
+
+---
+
+## Welcome to the huggingface_hub library
+
+The `huggingface_hub` library allows you to interact with the [Hugging Face Hub](https://huggingface.co/), a platform democratizing open-source Machine Learning for creators and collaborators. Discover pre-trained models and datasets for your projects or play with the thousands of machine learning apps hosted on the Hub. You can also create and share your own models, datasets and demos with the community. The `huggingface_hub` library provides a simple way to do all these things with Python.
+
+## Key features
+
+- [Download files](https://huggingface.co/docs/huggingface_hub/en/guides/download) from the Hub.
+- [Upload files](https://huggingface.co/docs/huggingface_hub/en/guides/upload) to the Hub.
+- [Manage your repositories](https://huggingface.co/docs/huggingface_hub/en/guides/repository).
+- [Run Inference](https://huggingface.co/docs/huggingface_hub/en/guides/inference) on deployed models.
+- [Search](https://huggingface.co/docs/huggingface_hub/en/guides/search) for models, datasets and Spaces.
+- [Share Model Cards](https://huggingface.co/docs/huggingface_hub/en/guides/model-cards) to document your models.
+- [Engage with the community](https://huggingface.co/docs/huggingface_hub/en/guides/community) through PRs and comments.
+
+## Installation
+
+Install the `huggingface_hub` package with [pip](https://pypi.org/project/huggingface-hub/):
+
+```bash
+pip install huggingface_hub
+```
+
+If you prefer, you can also install it with [conda](https://huggingface.co/docs/huggingface_hub/en/installation#install-with-conda).
+
+In order to keep the package minimal by default, `huggingface_hub` comes with optional dependencies useful for some use cases. For example, if you want to use the MCP module, run:
+
+```bash
+pip install "huggingface_hub[mcp]"
+```
+
+To learn more installation and optional dependencies, check out the [installation guide](https://huggingface.co/docs/huggingface_hub/en/installation).
+
+## Quick start
+
+### Download files
+
+Download a single file
+
+```py
+from huggingface_hub import hf_hub_download
+
+hf_hub_download(repo_id="tiiuae/falcon-7b-instruct", filename="config.json")
+```
+
+Or an entire repository
+
+```py
+from huggingface_hub import snapshot_download
+
+snapshot_download("stabilityai/stable-diffusion-2-1")
+```
+
+Files will be downloaded in a local cache folder. More details in [this guide](https://huggingface.co/docs/huggingface_hub/en/guides/manage-cache).
+
+### Login
+
+The Hugging Face Hub uses tokens to authenticate applications (see [docs](https://huggingface.co/docs/hub/security-tokens)). To log in your machine, run the following CLI:
+
+```bash
+hf auth login
+# or using an environment variable
+hf auth login --token $HUGGINGFACE_TOKEN
+```
+
+### Create a repository
+
+```py
+from huggingface_hub import create_repo
+
+create_repo(repo_id="super-cool-model")
+```
+
+### Upload files
+
+Upload a single file
+
+```py
+from huggingface_hub import upload_file
+
+upload_file(
+    path_or_fileobj="/home/lysandre/dummy-test/README.md",
+    path_in_repo="README.md",
+    repo_id="lysandre/test-model",
+)
+```
+
+Or an entire folder
+
+```py
+from huggingface_hub import upload_folder
+
+upload_folder(
+    folder_path="/path/to/local/space",
+    repo_id="username/my-cool-space",
+    repo_type="space",
+)
+```
+
+For details in the [upload guide](https://huggingface.co/docs/huggingface_hub/en/guides/upload).
+
+## Integrating to the Hub.
+
+We're partnering with cool open source ML libraries to provide free model hosting and versioning. You can find the existing integrations [here](https://huggingface.co/docs/hub/libraries).
+
+The advantages are:
+
+- Free model or dataset hosting for libraries and their users.
+- Built-in file versioning, even with very large files, thanks to a git-based approach.
+- In-browser widgets to play with the uploaded models.
+- Anyone can upload a new model for your library, they just need to add the corresponding tag for the model to be discoverable.
+- Fast downloads! We use Cloudfront (a CDN) to geo-replicate downloads so they're blazing fast from anywhere on the globe.
+- Usage stats and more features to come.
+
+If you would like to integrate your library, feel free to open an issue to begin the discussion. We wrote a [step-by-step guide](https://huggingface.co/docs/hub/adding-a-library) with ❤️ showing how to do this integration.
+
+## Contributions (feature requests, bugs, etc.) are super welcome 💙💚💛💜🧡❤️
+
+Everyone is welcome to contribute, and we value everybody's contribution. Code is not the only way to help the community.
+Answering questions, helping others, reaching out and improving the documentations are immensely valuable to the community.
+We wrote a [contribution guide](https://github.com/huggingface/huggingface_hub/blob/main/CONTRIBUTING.md) to summarize
+how to get started to contribute to this repository.

.cache/pip/http-v2/6/5/1/e/5/651e58859e8db8c99b9e7068d03984cfd4577518ff0e021c717afbf4.body

@@ -0,0 +1,78 @@
+Metadata-Version: 2.1
+Name: cycler
+Version: 0.12.1
+Summary: Composable style cycles
+Author-email: Thomas A Caswell <matplotlib-users@python.org>
+License: Copyright (c) 2015, matplotlib project
+        All rights reserved.
+        
+        Redistribution and use in source and binary forms, with or without
+        modification, are permitted provided that the following conditions are met:
+        
+        * Redistributions of source code must retain the above copyright notice, this
+          list of conditions and the following disclaimer.
+        
+        * Redistributions in binary form must reproduce the above copyright notice,
+          this list of conditions and the following disclaimer in the documentation
+          and/or other materials provided with the distribution.
+        
+        * Neither the name of the matplotlib project nor the names of its
+          contributors may be used to endorse or promote products derived from
+          this software without specific prior written permission.
+        
+        THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+        AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+        IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+        DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+        FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+        DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+        SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+        CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+        OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+        OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+Project-URL: homepage, https://matplotlib.org/cycler/
+Project-URL: repository, https://github.com/matplotlib/cycler
+Keywords: cycle kwargs
+Classifier: License :: OSI Approved :: BSD License
+Classifier: Development Status :: 4 - Beta
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.8
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3.12
+Classifier: Programming Language :: Python :: 3 :: Only
+Requires-Python: >=3.8
+Description-Content-Type: text/x-rst
+License-File: LICENSE
+Provides-Extra: docs
+Requires-Dist: ipython ; extra == 'docs'
+Requires-Dist: matplotlib ; extra == 'docs'
+Requires-Dist: numpydoc ; extra == 'docs'
+Requires-Dist: sphinx ; extra == 'docs'
+Provides-Extra: tests
+Requires-Dist: pytest ; extra == 'tests'
+Requires-Dist: pytest-cov ; extra == 'tests'
+Requires-Dist: pytest-xdist ; extra == 'tests'
+
+|PyPi|_ |Conda|_ |Supported Python versions|_ |GitHub Actions|_ |Codecov|_
+
+.. |PyPi| image:: https://img.shields.io/pypi/v/cycler.svg?style=flat
+.. _PyPi: https://pypi.python.org/pypi/cycler
+
+.. |Conda| image:: https://img.shields.io/conda/v/conda-forge/cycler
+.. _Conda:  https://anaconda.org/conda-forge/cycler
+
+.. |Supported Python versions| image:: https://img.shields.io/pypi/pyversions/cycler.svg
+.. _Supported Python versions: https://pypi.python.org/pypi/cycler
+
+.. |GitHub Actions| image:: https://github.com/matplotlib/cycler/actions/workflows/tests.yml/badge.svg
+.. _GitHub Actions: https://github.com/matplotlib/cycler/actions
+
+.. |Codecov| image:: https://codecov.io/github/matplotlib/cycler/badge.svg?branch=main&service=github
+.. _Codecov: https://codecov.io/github/matplotlib/cycler?branch=main
+
+cycler: composable cycles
+=========================
+
+Docs: https://matplotlib.org/cycler/

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+Metadata-Version: 2.4
+Name: optuna
+Version: 4.8.0
+Summary: A hyperparameter optimization framework
+Author: Takuya Akiba
+Project-URL: homepage, https://optuna.org/
+Project-URL: repository, https://github.com/optuna/optuna
+Project-URL: documentation, https://optuna.readthedocs.io
+Project-URL: bugtracker, https://github.com/optuna/optuna/issues
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Intended Audience :: Science/Research
+Classifier: Intended Audience :: Developers
+Classifier: License :: OSI Approved :: MIT License
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3.12
+Classifier: Programming Language :: Python :: 3.13
+Classifier: Programming Language :: Python :: 3.14
+Classifier: Programming Language :: Python :: 3 :: Only
+Classifier: Topic :: Scientific/Engineering
+Classifier: Topic :: Scientific/Engineering :: Mathematics
+Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
+Classifier: Topic :: Software Development
+Classifier: Topic :: Software Development :: Libraries
+Classifier: Topic :: Software Development :: Libraries :: Python Modules
+Requires-Python: >=3.9
+Description-Content-Type: text/markdown
+License-File: LICENSE
+License-File: LICENSE_THIRD_PARTY
+Requires-Dist: alembic>=1.5.0
+Requires-Dist: colorlog
+Requires-Dist: numpy
+Requires-Dist: packaging>=20.0
+Requires-Dist: sqlalchemy>=1.4.2
+Requires-Dist: tqdm
+Requires-Dist: PyYAML
+Provides-Extra: checking
+Requires-Dist: mypy; extra == "checking"
+Requires-Dist: mypy_boto3_s3; extra == "checking"
+Requires-Dist: ruff; extra == "checking"
+Requires-Dist: scipy-stubs; python_version >= "3.10" and extra == "checking"
+Requires-Dist: types-PyYAML; extra == "checking"
+Requires-Dist: types-redis; extra == "checking"
+Requires-Dist: types-setuptools; extra == "checking"
+Requires-Dist: types-tqdm; extra == "checking"
+Requires-Dist: typing_extensions>=3.10.0.0; extra == "checking"
+Provides-Extra: document
+Requires-Dist: ase; extra == "document"
+Requires-Dist: cmaes>=0.12.0; extra == "document"
+Requires-Dist: fvcore; extra == "document"
+Requires-Dist: kaleido<0.4; extra == "document"
+Requires-Dist: lightgbm; extra == "document"
+Requires-Dist: matplotlib!=3.6.0; extra == "document"
+Requires-Dist: pandas; extra == "document"
+Requires-Dist: pillow; extra == "document"
+Requires-Dist: plotly>=4.9.0; extra == "document"
+Requires-Dist: scikit-learn; extra == "document"
+Requires-Dist: sphinx; extra == "document"
+Requires-Dist: sphinx-copybutton; extra == "document"
+Requires-Dist: sphinx-gallery; extra == "document"
+Requires-Dist: sphinx-notfound-page; extra == "document"
+Requires-Dist: sphinx_rtd_theme>=1.2.0; extra == "document"
+Requires-Dist: torch; extra == "document"
+Requires-Dist: torchvision; extra == "document"
+Provides-Extra: optional
+Requires-Dist: boto3; extra == "optional"
+Requires-Dist: cmaes>=0.12.0; extra == "optional"
+Requires-Dist: google-cloud-storage; extra == "optional"
+Requires-Dist: matplotlib!=3.6.0; extra == "optional"
+Requires-Dist: pandas; extra == "optional"
+Requires-Dist: plotly>=4.9.0; extra == "optional"
+Requires-Dist: redis; extra == "optional"
+Requires-Dist: scikit-learn>=0.24.2; extra == "optional"
+Requires-Dist: scipy; extra == "optional"
+Requires-Dist: torch; extra == "optional"
+Requires-Dist: greenlet; extra == "optional"
+Requires-Dist: grpcio; extra == "optional"
+Requires-Dist: protobuf>=5.28.1; extra == "optional"
+Provides-Extra: test
+Requires-Dist: fakeredis[lua]; extra == "test"
+Requires-Dist: kaleido<0.4; extra == "test"
+Requires-Dist: moto; extra == "test"
+Requires-Dist: pytest; extra == "test"
+Requires-Dist: pytest-xdist; extra == "test"
+Requires-Dist: scipy>=1.9.2; extra == "test"
+Requires-Dist: torch; extra == "test"
+Requires-Dist: greenlet; extra == "test"
+Requires-Dist: grpcio; extra == "test"
+Requires-Dist: protobuf>=5.28.1; extra == "test"
+Dynamic: license-file
+
+<div align="center"><img src="https://raw.githubusercontent.com/optuna/optuna/master/docs/image/optuna-logo.png" width="800"/></div>
+
+# Optuna: A hyperparameter optimization framework
+
+[![Python](https://img.shields.io/badge/python-3.9%20%7C%203.10%20%7C%203.11%20%7C%203.12%20%7C%203.13%20%7C%203.14-blue)](https://www.python.org)
+[![pypi](https://img.shields.io/pypi/v/optuna.svg)](https://pypi.python.org/pypi/optuna)
+[![conda](https://img.shields.io/conda/vn/conda-forge/optuna.svg)](https://anaconda.org/conda-forge/optuna)
+[![GitHub license](https://img.shields.io/badge/license-MIT-blue.svg)](https://github.com/optuna/optuna)
+[![Read the Docs](https://readthedocs.org/projects/optuna/badge/?version=stable)](https://optuna.readthedocs.io/en/stable/)
+
+:link: [**Website**](https://optuna.org/)
+| :page_with_curl: [**Docs**](https://optuna.readthedocs.io/en/stable/)
+| :gear: [**Install Guide**](https://optuna.readthedocs.io/en/stable/installation.html)
+| :pencil: [**Tutorial**](https://optuna.readthedocs.io/en/stable/tutorial/index.html)
+| :bulb: [**Examples**](https://github.com/optuna/optuna-examples)
+| [**Twitter**](https://twitter.com/OptunaAutoML)
+| [**LinkedIn**](https://www.linkedin.com/showcase/optuna/)
+| [**Medium**](https://medium.com/optuna)
+
+*Optuna* is an automatic hyperparameter optimization software framework, particularly designed
+for machine learning. It features an imperative, *define-by-run* style user API. Thanks to our
+*define-by-run* API, the code written with Optuna enjoys high modularity, and the user of
+Optuna can dynamically construct the search spaces for the hyperparameters.
+
+## :loudspeaker: News
+Help us create the next version of Optuna!
+
+Optuna 5.0 Roadmap published for review. Please take a look at [the planned improvements to Optuna](https://medium.com/optuna/optuna-v5-roadmap-ac7d6935a878), and share your feedback in [the github issues](https://github.com/optuna/optuna/labels/v5). PR contributions also welcome!
+
+Please take a few minutes to fill in [this survey](https://forms.gle/wVwLCQ9g6st6AXuq9), and let us know how you use Optuna now and what improvements you'd like.🤔
+All questions are optional. 🙇‍♂️
+
+<!-- TODO: when you add a new line, please delete the oldest line -->
+* **Jan 19, 2026**: Optuna 4.7.0 is out! Check out [the release note](https://github.com/optuna/optuna/releases/tag/v4.7.0) for details.
+* **Nov 10, 2025**: A new article [Announcing Optuna 4.6](https://medium.com/optuna/announcing-optuna-4-6-a9e82183ab07) has been published.
+* **Oct 28, 2025**: A new article [AutoSampler: Full Support for Multi-Objective & Constrained Optimization](https://medium.com/optuna/autosampler-full-support-for-multi-objective-constrained-optimization-c1c4fc957ba2) has been published.
+* **Sep 22, 2025**: A new article [[Optuna v4.5] Gaussian Process-Based Sampler (GPSampler) Can Now Perform Constrained Multi-Objective Optimization](https://medium.com/optuna/optuna-v4-5-81e78d8e077a) has been published.
+* **Jun 16, 2025**: Optuna 4.4.0 has been released! Check out [the release blog](https://medium.com/optuna/announcing-optuna-4-4-ece661493126).
+* **May 26, 2025**: Optuna 5.0 roadmap has been published! See [the blog](https://medium.com/optuna/optuna-v5-roadmap-ac7d6935a878) for more details.
+
+## :fire: Key Features
+
+Optuna has modern functionalities as follows:
+
+- [Lightweight, versatile, and platform agnostic architecture](https://optuna.readthedocs.io/en/stable/tutorial/10_key_features/001_first.html)
+  - Handle a wide variety of tasks with a simple installation that has few requirements.
+- [Pythonic search spaces](https://optuna.readthedocs.io/en/stable/tutorial/10_key_features/002_configurations.html)
+  - Define search spaces using familiar Python syntax including conditionals and loops.
+- [Efficient optimization algorithms](https://optuna.readthedocs.io/en/stable/tutorial/10_key_features/003_efficient_optimization_algorithms.html)
+  - Adopt state-of-the-art algorithms for sampling hyperparameters and efficiently pruning unpromising trials.
+- [Easy parallelization](https://optuna.readthedocs.io/en/stable/tutorial/10_key_features/004_distributed.html)
+  - Scale studies to tens or hundreds of workers with little or no changes to the code.
+- [Quick visualization](https://optuna.readthedocs.io/en/stable/tutorial/10_key_features/005_visualization.html)
+  - Inspect optimization histories from a variety of plotting functions.
+
+
+## Basic Concepts
+
+We use the terms *study* and *trial* as follows:
+
+- Study: optimization based on an objective function
+- Trial: a single execution of the objective function
+
+Please refer to the sample code below. The goal of a *study* is to find out the optimal set of
+hyperparameter values (e.g., `regressor` and `svr_c`) through multiple *trials* (e.g.,
+`n_trials=100`). Optuna is a framework designed for automation and acceleration of
+optimization *studies*.
+
+<details open>
+<summary>Sample code with scikit-learn</summary>
+
+[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](http://colab.research.google.com/github/optuna/optuna-examples/blob/main/quickstart.ipynb)
+
+```python
+import optuna
+import sklearn
+
+
+# Define an objective function to be minimized.
+def objective(trial):
+
+    # Invoke suggest methods of a Trial object to generate hyperparameters.
+    regressor_name = trial.suggest_categorical("regressor", ["SVR", "RandomForest"])
+    if regressor_name == "SVR":
+        svr_c = trial.suggest_float("svr_c", 1e-10, 1e10, log=True)
+        regressor_obj = sklearn.svm.SVR(C=svr_c)
+    else:
+        rf_max_depth = trial.suggest_int("rf_max_depth", 2, 32)
+        regressor_obj = sklearn.ensemble.RandomForestRegressor(max_depth=rf_max_depth)
+
+    X, y = sklearn.datasets.fetch_california_housing(return_X_y=True)
+    X_train, X_val, y_train, y_val = sklearn.model_selection.train_test_split(X, y, random_state=0)
+
+    regressor_obj.fit(X_train, y_train)
+    y_pred = regressor_obj.predict(X_val)
+
+    error = sklearn.metrics.mean_squared_error(y_val, y_pred)
+
+    return error  # An objective value linked with the Trial object.
+
+
+study = optuna.create_study()  # Create a new study.
+study.optimize(objective, n_trials=100)  # Invoke optimization of the objective function.
+```
+</details>
+
+> [!NOTE]
+> More examples can be found in [optuna/optuna-examples](https://github.com/optuna/optuna-examples).
+>
+> The examples cover diverse problem setups such as multi-objective optimization, constrained optimization, pruning, and distributed optimization.
+
+## Installation
+
+Optuna is available at [the Python Package Index](https://pypi.org/project/optuna/) and on [Anaconda Cloud](https://anaconda.org/conda-forge/optuna).
+
+```bash
+# PyPI
+$ pip install optuna
+```
+
+```bash
+# Anaconda Cloud
+$ conda install -c conda-forge optuna
+```
+
+> [!IMPORTANT]
+> Optuna supports Python 3.9 or newer.
+>
+> Also, we provide Optuna docker images on [DockerHub](https://hub.docker.com/r/optuna/optuna).
+
+## Integrations
+
+Optuna has integration features with various third-party libraries. Integrations can be found in [optuna/optuna-integration](https://github.com/optuna/optuna-integration) and the document is available [here](https://optuna-integration.readthedocs.io/en/stable/index.html).
+
+<details>
+<summary>Supported integration libraries</summary>
+
+* [Catboost](https://github.com/optuna/optuna-examples/tree/main/catboost/catboost_pruning.py)
+* [Dask](https://github.com/optuna/optuna-examples/tree/main/dask/dask_simple.py)
+* [fastai](https://github.com/optuna/optuna-examples/tree/main/fastai/fastai_simple.py)
+* [Keras](https://github.com/optuna/optuna-examples/tree/main/keras/keras_integration.py)
+* [LightGBM](https://github.com/optuna/optuna-examples/tree/main/lightgbm/lightgbm_integration.py)
+* [MLflow](https://github.com/optuna/optuna-examples/tree/main/mlflow/keras_mlflow.py)
+* [PyTorch](https://github.com/optuna/optuna-examples/tree/main/pytorch/pytorch_simple.py)
+* [PyTorch Ignite](https://github.com/optuna/optuna-examples/tree/main/pytorch/pytorch_ignite_simple.py)
+* [PyTorch Lightning](https://github.com/optuna/optuna-examples/tree/main/pytorch/pytorch_lightning_simple.py)
+* [TensorBoard](https://github.com/optuna/optuna-examples/tree/main/tensorboard/tensorboard_simple.py)
+* [TensorFlow](https://github.com/optuna/optuna-examples/tree/main/tensorflow/tensorflow_estimator_integration.py)
+* [tf.keras](https://github.com/optuna/optuna-examples/tree/main/tfkeras/tfkeras_integration.py)
+* [Weights & Biases](https://github.com/optuna/optuna-examples/tree/main/wandb/wandb_integration.py)
+* [XGBoost](https://github.com/optuna/optuna-examples/tree/main/xgboost/xgboost_integration.py)
+</details>
+
+## Web Dashboard
+
+[Optuna Dashboard](https://github.com/optuna/optuna-dashboard) is a real-time web dashboard for Optuna.
+You can check the optimization history, hyperparameter importance, etc. in graphs and tables.
+You don't need to create a Python script to call [Optuna's visualization](https://optuna.readthedocs.io/en/stable/reference/visualization/index.html) functions.
+Feature requests and bug reports are welcome!
+
+![optuna-dashboard](https://user-images.githubusercontent.com/5564044/204975098-95c2cb8c-0fb5-4388-abc4-da32f56cb4e5.gif)
+
+`optuna-dashboard` can be installed via pip:
+
+```shell
+$ pip install optuna-dashboard
+```
+
+> [!TIP]
+> Please check out the convenience of Optuna Dashboard using the sample code below.
+
+<details>
+<summary>Sample code to launch Optuna Dashboard</summary>
+
+Save the following code as `optimize_toy.py`.
+
+```python
+import optuna
+
+
+def objective(trial):
+    x1 = trial.suggest_float("x1", -100, 100)
+    x2 = trial.suggest_float("x2", -100, 100)
+    return x1**2 + 0.01 * x2**2
+
+
+study = optuna.create_study(storage="sqlite:///db.sqlite3")  # Create a new study with database.
+study.optimize(objective, n_trials=100)
+```
+
+Then try the commands below:
+
+```shell
+# Run the study specified above
+$ python optimize_toy.py
+
+# Launch the dashboard based on the storage `sqlite:///db.sqlite3`
+$ optuna-dashboard sqlite:///db.sqlite3
+...
+Listening on http://localhost:8080/
+Hit Ctrl-C to quit.
+```
+
+</details>
+
+
+## OptunaHub
+
+[OptunaHub](https://hub.optuna.org/) is a feature-sharing platform for Optuna.
+You can use the registered features and publish your packages.
+
+### Use registered features
+
+`optunahub` can be installed via pip:
+
+```shell
+$ pip install optunahub
+# Install AutoSampler dependencies (CPU only is sufficient for PyTorch)
+$ pip install cmaes scipy torch --extra-index-url https://download.pytorch.org/whl/cpu
+```
+
+You can load registered module with `optunahub.load_module`.
+
+```python
+import optuna
+import optunahub
+
+
+def objective(trial: optuna.Trial) -> float:
+    x = trial.suggest_float("x", -5, 5)
+    y = trial.suggest_float("y", -5, 5)
+    return x**2 + y**2
+
+
+module = optunahub.load_module(package="samplers/auto_sampler")
+study = optuna.create_study(sampler=module.AutoSampler())
+study.optimize(objective, n_trials=10)
+
+print(study.best_trial.value, study.best_trial.params)
+```
+
+For more details, please refer to [the optunahub documentation](https://optuna.github.io/optunahub/).
+
+### Publish your packages
+
+You can publish your package via [optunahub-registry](https://github.com/optuna/optunahub-registry).
+See the [Tutorials for Contributors](https://optuna.github.io/optunahub/tutorials_for_contributors.html) in OptunaHub.
+
+
+## Communication
+
+- [GitHub Discussions] for questions.
+- [GitHub Issues] for bug reports and feature requests.
+
+[GitHub Discussions]: https://github.com/optuna/optuna/discussions
+[GitHub issues]: https://github.com/optuna/optuna/issues
+
+
+## Contribution
+
+Any contributions to Optuna are more than welcome!
+
+If you are new to Optuna, please check the [good first issues](https://github.com/optuna/optuna/labels/good%20first%20issue). They are relatively simple, well-defined, and often good starting points for you to get familiar with the contribution workflow and other developers.
+
+If you already have contributed to Optuna, we recommend the other [contribution-welcome issues](https://github.com/optuna/optuna/labels/contribution-welcome).
+
+For general guidelines on how to contribute to the project, take a look at [CONTRIBUTING.md](./CONTRIBUTING.md).
+
+
+## Reference
+
+If you use Optuna in one of your research projects, please cite [our KDD paper](https://doi.org/10.1145/3292500.3330701) "Optuna: A Next-generation Hyperparameter Optimization Framework":
+
+<details open>
+<summary>BibTeX</summary>
+
+```bibtex
+@inproceedings{akiba2019optuna,
+  title={{O}ptuna: A Next-Generation Hyperparameter Optimization Framework},
+  author={Akiba, Takuya and Sano, Shotaro and Yanase, Toshihiko and Ohta, Takeru and Koyama, Masanori},
+  booktitle={The 25th ACM SIGKDD International Conference on Knowledge Discovery \& Data Mining},
+  pages={2623--2631},
+  year={2019}
+}
+```
+</details>
+
+
+## License
+
+MIT License (see [LICENSE](./LICENSE)).
+
+Optuna uses the codes from SciPy and fdlibm projects (see [LICENSE_THIRD_PARTY](./LICENSE_THIRD_PARTY)).

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@@ -0,0 +1,139 @@
+Metadata-Version: 2.4
+Name: alembic
+Version: 1.18.4
+Summary: A database migration tool for SQLAlchemy.
+Author-email: Mike Bayer <mike_mp@zzzcomputing.com>
+License-Expression: MIT
+Project-URL: Homepage, https://alembic.sqlalchemy.org
+Project-URL: Documentation, https://alembic.sqlalchemy.org/en/latest/
+Project-URL: Changelog, https://alembic.sqlalchemy.org/en/latest/changelog.html
+Project-URL: Source, https://github.com/sqlalchemy/alembic/
+Project-URL: Issue Tracker, https://github.com/sqlalchemy/alembic/issues/
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Intended Audience :: Developers
+Classifier: Environment :: Console
+Classifier: Operating System :: OS Independent
+Classifier: Programming Language :: Python
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3.12
+Classifier: Programming Language :: Python :: 3.13
+Classifier: Programming Language :: Python :: Implementation :: CPython
+Classifier: Programming Language :: Python :: Implementation :: PyPy
+Classifier: Topic :: Database :: Front-Ends
+Requires-Python: >=3.10
+Description-Content-Type: text/x-rst
+License-File: LICENSE
+Requires-Dist: SQLAlchemy>=1.4.23
+Requires-Dist: Mako
+Requires-Dist: typing-extensions>=4.12
+Requires-Dist: tomli; python_version < "3.11"
+Provides-Extra: tz
+Requires-Dist: tzdata; extra == "tz"
+Dynamic: license-file
+
+Alembic is a database migrations tool written by the author
+of `SQLAlchemy <http://www.sqlalchemy.org>`_.  A migrations tool
+offers the following functionality:
+
+* Can emit ALTER statements to a database in order to change
+  the structure of tables and other constructs
+* Provides a system whereby "migration scripts" may be constructed;
+  each script indicates a particular series of steps that can "upgrade" a
+  target database to a new version, and optionally a series of steps that can
+  "downgrade" similarly, doing the same steps in reverse.
+* Allows the scripts to execute in some sequential manner.
+
+The goals of Alembic are:
+
+* Very open ended and transparent configuration and operation.   A new
+  Alembic environment is generated from a set of templates which is selected
+  among a set of options when setup first occurs. The templates then deposit a
+  series of scripts that define fully how database connectivity is established
+  and how migration scripts are invoked; the migration scripts themselves are
+  generated from a template within that series of scripts. The scripts can
+  then be further customized to define exactly how databases will be
+  interacted with and what structure new migration files should take.
+* Full support for transactional DDL.   The default scripts ensure that all
+  migrations occur within a transaction - for those databases which support
+  this (Postgresql, Microsoft SQL Server), migrations can be tested with no
+  need to manually undo changes upon failure.
+* Minimalist script construction.  Basic operations like renaming
+  tables/columns, adding/removing columns, changing column attributes can be
+  performed through one line commands like alter_column(), rename_table(),
+  add_constraint(). There is no need to recreate full SQLAlchemy Table
+  structures for simple operations like these - the functions themselves
+  generate minimalist schema structures behind the scenes to achieve the given
+  DDL sequence.
+* "auto generation" of migrations. While real world migrations are far more
+  complex than what can be automatically determined, Alembic can still
+  eliminate the initial grunt work in generating new migration directives
+  from an altered schema.  The ``--autogenerate`` feature will inspect the
+  current status of a database using SQLAlchemy's schema inspection
+  capabilities, compare it to the current state of the database model as
+  specified in Python, and generate a series of "candidate" migrations,
+  rendering them into a new migration script as Python directives. The
+  developer then edits the new file, adding additional directives and data
+  migrations as needed, to produce a finished migration. Table and column
+  level changes can be detected, with constraints and indexes to follow as
+  well.
+* Full support for migrations generated as SQL scripts.   Those of us who
+  work in corporate environments know that direct access to DDL commands on a
+  production database is a rare privilege, and DBAs want textual SQL scripts.
+  Alembic's usage model and commands are oriented towards being able to run a
+  series of migrations into a textual output file as easily as it runs them
+  directly to a database. Care must be taken in this mode to not invoke other
+  operations that rely upon in-memory SELECTs of rows - Alembic tries to
+  provide helper constructs like bulk_insert() to help with data-oriented
+  operations that are compatible with script-based DDL.
+* Non-linear, dependency-graph versioning.   Scripts are given UUID
+  identifiers similarly to a DVCS, and the linkage of one script to the next
+  is achieved via human-editable markers within the scripts themselves.
+  The structure of a set of migration files is considered as a
+  directed-acyclic graph, meaning any migration file can be dependent
+  on any other arbitrary set of migration files, or none at
+  all.  Through this open-ended system, migration files can be organized
+  into branches, multiple roots, and mergepoints, without restriction.
+  Commands are provided to produce new branches, roots, and merges of
+  branches automatically.
+* Provide a library of ALTER constructs that can be used by any SQLAlchemy
+  application. The DDL constructs build upon SQLAlchemy's own DDLElement base
+  and can be used standalone by any application or script.
+* At long last, bring SQLite and its inability to ALTER things into the fold,
+  but in such a way that SQLite's very special workflow needs are accommodated
+  in an explicit way that makes the most of a bad situation, through the
+  concept of a "batch" migration, where multiple changes to a table can
+  be batched together to form a series of instructions for a single, subsequent
+  "move-and-copy" workflow.   You can even use "move-and-copy" workflow for
+  other databases, if you want to recreate a table in the background
+  on a busy system.
+
+Documentation and status of Alembic is at https://alembic.sqlalchemy.org/
+
+The SQLAlchemy Project
+======================
+
+Alembic is part of the `SQLAlchemy Project <https://www.sqlalchemy.org>`_ and
+adheres to the same standards and conventions as the core project.
+
+Development / Bug reporting / Pull requests
+___________________________________________
+
+Please refer to the
+`SQLAlchemy Community Guide <https://www.sqlalchemy.org/develop.html>`_ for
+guidelines on coding and participating in this project.
+
+Code of Conduct
+_______________
+
+Above all, SQLAlchemy places great emphasis on polite, thoughtful, and
+constructive communication between users and developers.
+Please see our current Code of Conduct at
+`Code of Conduct <https://www.sqlalchemy.org/codeofconduct.html>`_.
+
+License
+=======
+
+Alembic is distributed under the `MIT license
+<https://opensource.org/licenses/MIT>`_.

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@@ -0,0 +1,32 @@
+Metadata-Version: 2.1
+Name: mdurl
+Version: 0.1.2
+Summary: Markdown URL utilities
+Keywords: markdown,commonmark
+Author-email: Taneli Hukkinen <hukkin@users.noreply.github.com>
+Requires-Python: >=3.7
+Description-Content-Type: text/markdown
+Classifier: License :: OSI Approved :: MIT License
+Classifier: Operating System :: MacOS
+Classifier: Operating System :: Microsoft :: Windows
+Classifier: Operating System :: POSIX :: Linux
+Classifier: Programming Language :: Python :: 3 :: Only
+Classifier: Programming Language :: Python :: 3.7
+Classifier: Programming Language :: Python :: 3.8
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: Implementation :: CPython
+Classifier: Programming Language :: Python :: Implementation :: PyPy
+Classifier: Topic :: Software Development :: Libraries :: Python Modules
+Classifier: Typing :: Typed
+Project-URL: Homepage, https://github.com/executablebooks/mdurl
+
+# mdurl
+
+[![Build Status](https://github.com/executablebooks/mdurl/workflows/Tests/badge.svg?branch=master)](https://github.com/executablebooks/mdurl/actions?query=workflow%3ATests+branch%3Amaster+event%3Apush)
+[![codecov.io](https://codecov.io/gh/executablebooks/mdurl/branch/master/graph/badge.svg)](https://codecov.io/gh/executablebooks/mdurl)
+[![PyPI version](https://img.shields.io/pypi/v/mdurl)](https://pypi.org/project/mdurl)
+
+This is a Python port of the JavaScript [mdurl](https://www.npmjs.com/package/mdurl) package.
+See the [upstream README.md file](https://github.com/markdown-it/mdurl/blob/master/README.md) for API documentation.
+

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@@ -0,0 +1,479 @@
+Metadata-Version: 2.4
+Name: rich
+Version: 15.0.0
+Summary: Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal
+License: MIT
+License-File: LICENSE
+Author: Will McGugan
+Author-email: willmcgugan@gmail.com
+Requires-Python: >=3.9.0
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Environment :: Console
+Classifier: Framework :: IPython
+Classifier: Intended Audience :: Developers
+Classifier: License :: OSI Approved :: MIT License
+Classifier: Operating System :: MacOS
+Classifier: Operating System :: Microsoft :: Windows
+Classifier: Operating System :: POSIX :: Linux
+Classifier: Programming Language :: Python :: 3
+Classifier: Programming Language :: Python :: 3.9
+Classifier: Programming Language :: Python :: 3.10
+Classifier: Programming Language :: Python :: 3.11
+Classifier: Programming Language :: Python :: 3.12
+Classifier: Programming Language :: Python :: 3.13
+Classifier: Programming Language :: Python :: 3.14
+Classifier: Typing :: Typed
+Provides-Extra: jupyter
+Requires-Dist: ipywidgets (>=7.5.1,<9) ; extra == "jupyter"
+Requires-Dist: markdown-it-py (>=2.2.0)
+Requires-Dist: pygments (>=2.13.0,<3.0.0)
+Project-URL: Documentation, https://rich.readthedocs.io/en/latest/
+Project-URL: Homepage, https://github.com/Textualize/rich
+Description-Content-Type: text/markdown
+
+[![Supported Python Versions](https://img.shields.io/pypi/pyversions/rich)](https://pypi.org/project/rich/) [![PyPI version](https://badge.fury.io/py/rich.svg)](https://badge.fury.io/py/rich)
+
+[![Downloads](https://pepy.tech/badge/rich/month)](https://pepy.tech/project/rich)
+[![codecov](https://img.shields.io/codecov/c/github/Textualize/rich?label=codecov&logo=codecov)](https://codecov.io/gh/Textualize/rich)
+[![Rich blog](https://img.shields.io/badge/blog-rich%20news-yellowgreen)](https://www.willmcgugan.com/tag/rich/)
+[![Twitter Follow](https://img.shields.io/twitter/follow/willmcgugan.svg?style=social)](https://twitter.com/willmcgugan)
+
+![Logo](https://github.com/textualize/rich/raw/master/imgs/logo.svg)
+
+[English readme](https://github.com/textualize/rich/blob/master/README.md)
+ • [简体中文 readme](https://github.com/textualize/rich/blob/master/README.cn.md)
+ • [正體中文 readme](https://github.com/textualize/rich/blob/master/README.zh-tw.md)
+ • [Lengua española readme](https://github.com/textualize/rich/blob/master/README.es.md)
+ • [Deutsche readme](https://github.com/textualize/rich/blob/master/README.de.md)
+ • [Läs på svenska](https://github.com/textualize/rich/blob/master/README.sv.md)
+ • [日本語 readme](https://github.com/textualize/rich/blob/master/README.ja.md)
+ • [한국어 readme](https://github.com/textualize/rich/blob/master/README.kr.md)
+ • [Français readme](https://github.com/textualize/rich/blob/master/README.fr.md)
+ • [Schwizerdütsch readme](https://github.com/textualize/rich/blob/master/README.de-ch.md)
+ • [हिन्दी readme](https://github.com/textualize/rich/blob/master/README.hi.md)
+ • [Português brasileiro readme](https://github.com/textualize/rich/blob/master/README.pt-br.md)
+ • [Italian readme](https://github.com/textualize/rich/blob/master/README.it.md)
+ • [Русский readme](https://github.com/textualize/rich/blob/master/README.ru.md)
+ • [Indonesian readme](https://github.com/textualize/rich/blob/master/README.id.md)
+ • [فارسی readme](https://github.com/textualize/rich/blob/master/README.fa.md)
+ • [Türkçe readme](https://github.com/textualize/rich/blob/master/README.tr.md)
+ • [Polskie readme](https://github.com/textualize/rich/blob/master/README.pl.md)
+
+
+Rich is a Python library for _rich_ text and beautiful formatting in the terminal.
+
+The [Rich API](https://rich.readthedocs.io/en/latest/) makes it easy to add color and style to terminal output. Rich can also render pretty tables, progress bars, markdown, syntax highlighted source code, tracebacks, and more — out of the box.
+
+![Features](https://github.com/textualize/rich/raw/master/imgs/features.png)
+
+For a video introduction to Rich see [calmcode.io](https://calmcode.io/rich/introduction.html) by [@fishnets88](https://twitter.com/fishnets88).
+
+See what [people are saying about Rich](https://www.willmcgugan.com/blog/pages/post/rich-tweets/).
+
+## Compatibility
+
+Rich works with Linux, macOS and Windows. True color / emoji works with new Windows Terminal, classic terminal is limited to 16 colors. Rich requires Python 3.8 or later.
+
+Rich works with [Jupyter notebooks](https://jupyter.org/) with no additional configuration required.
+
+## Installing
+
+Install with `pip` or your favorite PyPI package manager.
+
+```sh
+python -m pip install rich
+```
+
+Run the following to test Rich output on your terminal:
+
+```sh
+python -m rich
+```
+
+## Rich Print
+
+To effortlessly add rich output to your application, you can import the [rich print](https://rich.readthedocs.io/en/latest/introduction.html#quick-start) method, which has the same signature as the builtin Python function. Try this:
+
+```python
+from rich import print
+
+print("Hello, [bold magenta]World[/bold magenta]!", ":vampire:", locals())
+```
+
+![Hello World](https://github.com/textualize/rich/raw/master/imgs/print.png)
+
+## Rich REPL
+
+Rich can be installed in the Python REPL, so that any data structures will be pretty printed and highlighted.
+
+```python
+>>> from rich import pretty
+>>> pretty.install()
+```
+
+![REPL](https://github.com/textualize/rich/raw/master/imgs/repl.png)
+
+## Using the Console
+
+For more control over rich terminal content, import and construct a [Console](https://rich.readthedocs.io/en/latest/reference/console.html#rich.console.Console) object.
+
+```python
+from rich.console import Console
+
+console = Console()
+```
+
+The Console object has a `print` method which has an intentionally similar interface to the builtin `print` function. Here's an example of use:
+
+```python
+console.print("Hello", "World!")
+```
+
+As you might expect, this will print `"Hello World!"` to the terminal. Note that unlike the builtin `print` function, Rich will word-wrap your text to fit within the terminal width.
+
+There are a few ways of adding color and style to your output. You can set a style for the entire output by adding a `style` keyword argument. Here's an example:
+
+```python
+console.print("Hello", "World!", style="bold red")
+```
+
+The output will be something like the following:
+
+![Hello World](https://github.com/textualize/rich/raw/master/imgs/hello_world.png)
+
+That's fine for styling a line of text at a time. For more finely grained styling, Rich renders a special markup which is similar in syntax to [bbcode](https://en.wikipedia.org/wiki/BBCode). Here's an example:
+
+```python
+console.print("Where there is a [bold cyan]Will[/bold cyan] there [u]is[/u] a [i]way[/i].")
+```
+
+![Console Markup](https://github.com/textualize/rich/raw/master/imgs/where_there_is_a_will.png)
+
+You can use a Console object to generate sophisticated output with minimal effort. See the [Console API](https://rich.readthedocs.io/en/latest/console.html) docs for details.
+
+## Rich Inspect
+
+Rich has an [inspect](https://rich.readthedocs.io/en/latest/reference/init.html?highlight=inspect#rich.inspect) function which can produce a report on any Python object, such as class, instance, or builtin.
+
+```python
+>>> my_list = ["foo", "bar"]
+>>> from rich import inspect
+>>> inspect(my_list, methods=True)
+```
+
+![Log](https://github.com/textualize/rich/raw/master/imgs/inspect.png)
+
+See the [inspect docs](https://rich.readthedocs.io/en/latest/reference/init.html#rich.inspect) for details.
+
+# Rich Library
+
+Rich contains a number of builtin _renderables_ you can use to create elegant output in your CLI and help you debug your code.
+
+Click the following headings for details:
+
+<details>
+<summary>Log</summary>
+
+The Console object has a `log()` method which has a similar interface to `print()`, but also renders a column for the current time and the file and line which made the call. By default Rich will do syntax highlighting for Python structures and for repr strings. If you log a collection (i.e. a dict or a list) Rich will pretty print it so that it fits in the available space. Here's an example of some of these features.
+
+```python
+from rich.console import Console
+console = Console()
+
+test_data = [
+    {"jsonrpc": "2.0", "method": "sum", "params": [None, 1, 2, 4, False, True], "id": "1",},
+    {"jsonrpc": "2.0", "method": "notify_hello", "params": [7]},
+    {"jsonrpc": "2.0", "method": "subtract", "params": [42, 23], "id": "2"},
+]
+
+def test_log():
+    enabled = False
+    context = {
+        "foo": "bar",
+    }
+    movies = ["Deadpool", "Rise of the Skywalker"]
+    console.log("Hello from", console, "!")
+    console.log(test_data, log_locals=True)
+
+
+test_log()
+```
+
+The above produces the following output:
+
+![Log](https://github.com/textualize/rich/raw/master/imgs/log.png)
+
+Note the `log_locals` argument, which outputs a table containing the local variables where the log method was called.
+
+The log method could be used for logging to the terminal for long running applications such as servers, but is also a very nice debugging aid.
+
+</details>
+<details>
+<summary>Logging Handler</summary>
+
+You can also use the builtin [Handler class](https://rich.readthedocs.io/en/latest/logging.html) to format and colorize output from Python's logging module. Here's an example of the output:
+
+![Logging](https://github.com/textualize/rich/raw/master/imgs/logging.png)
+
+</details>
+
+<details>
+<summary>Emoji</summary>
+
+To insert an emoji in to console output place the name between two colons. Here's an example:
+
+```python
+>>> console.print(":smiley: :vampire: :pile_of_poo: :thumbs_up: :raccoon:")
+😃 🧛 💩 👍 🦝
+```
+
+Please use this feature wisely.
+
+</details>
+
+<details>
+<summary>Tables</summary>
+
+Rich can render flexible [tables](https://rich.readthedocs.io/en/latest/tables.html) with unicode box characters. There is a large variety of formatting options for borders, styles, cell alignment etc.
+
+![table movie](https://github.com/textualize/rich/raw/master/imgs/table_movie.gif)
+
+The animation above was generated with [table_movie.py](https://github.com/textualize/rich/blob/master/examples/table_movie.py) in the examples directory.
+
+Here's a simpler table example:
+
+```python
+from rich.console import Console
+from rich.table import Table
+
+console = Console()
+
+table = Table(show_header=True, header_style="bold magenta")
+table.add_column("Date", style="dim", width=12)
+table.add_column("Title")
+table.add_column("Production Budget", justify="right")
+table.add_column("Box Office", justify="right")
+table.add_row(
+    "Dec 20, 2019", "Star Wars: The Rise of Skywalker", "$275,000,000", "$375,126,118"
+)
+table.add_row(
+    "May 25, 2018",
+    "[red]Solo[/red]: A Star Wars Story",
+    "$275,000,000",
+    "$393,151,347",
+)
+table.add_row(
+    "Dec 15, 2017",
+    "Star Wars Ep. VIII: The Last Jedi",
+    "$262,000,000",
+    "[bold]$1,332,539,889[/bold]",
+)
+
+console.print(table)
+```
+
+This produces the following output:
+
+![table](https://github.com/textualize/rich/raw/master/imgs/table.png)
+
+Note that console markup is rendered in the same way as `print()` and `log()`. In fact, anything that is renderable by Rich may be included in the headers / rows (even other tables).
+
+The `Table` class is smart enough to resize columns to fit the available width of the terminal, wrapping text as required. Here's the same example, with the terminal made smaller than the table above:
+
+![table2](https://github.com/textualize/rich/raw/master/imgs/table2.png)
+
+</details>
+
+<details>
+<summary>Progress Bars</summary>
+
+Rich can render multiple flicker-free [progress](https://rich.readthedocs.io/en/latest/progress.html) bars to track long-running tasks.
+
+For basic usage, wrap any sequence in the `track` function and iterate over the result. Here's an example:
+
+```python
+from rich.progress import track
+
+for step in track(range(100)):
+    do_step(step)
+```
+
+It's not much harder to add multiple progress bars. Here's an example taken from the docs:
+
+![progress](https://github.com/textualize/rich/raw/master/imgs/progress.gif)
+
+The columns may be configured to show any details you want. Built-in columns include percentage complete, file size, file speed, and time remaining. Here's another example showing a download in progress:
+
+![progress](https://github.com/textualize/rich/raw/master/imgs/downloader.gif)
+
+To try this out yourself, see [examples/downloader.py](https://github.com/textualize/rich/blob/master/examples/downloader.py) which can download multiple URLs simultaneously while displaying progress.
+
+</details>
+
+<details>
+<summary>Status</summary>
+
+For situations where it is hard to calculate progress, you can use the [status](https://rich.readthedocs.io/en/latest/reference/console.html#rich.console.Console.status) method which will display a 'spinner' animation and message. The animation won't prevent you from using the console as normal. Here's an example:
+
+```python
+from time import sleep
+from rich.console import Console
+
+console = Console()
+tasks = [f"task {n}" for n in range(1, 11)]
+
+with console.status("[bold green]Working on tasks...") as status:
+    while tasks:
+        task = tasks.pop(0)
+        sleep(1)
+        console.log(f"{task} complete")
+```
+
+This generates the following output in the terminal.
+
+![status](https://github.com/textualize/rich/raw/master/imgs/status.gif)
+
+The spinner animations were borrowed from [cli-spinners](https://www.npmjs.com/package/cli-spinners). You can select a spinner by specifying the `spinner` parameter. Run the following command to see the available values:
+
+```
+python -m rich.spinner
+```
+
+The above command generates the following output in the terminal:
+
+![spinners](https://github.com/textualize/rich/raw/master/imgs/spinners.gif)
+
+</details>
+
+<details>
+<summary>Tree</summary>
+
+Rich can render a [tree](https://rich.readthedocs.io/en/latest/tree.html) with guide lines. A tree is ideal for displaying a file structure, or any other hierarchical data.
+
+The labels of the tree can be simple text or anything else Rich can render. Run the following for a demonstration:
+
+```
+python -m rich.tree
+```
+
+This generates the following output:
+
+![markdown](https://github.com/textualize/rich/raw/master/imgs/tree.png)
+
+See the [tree.py](https://github.com/textualize/rich/blob/master/examples/tree.py) example for a script that displays a tree view of any directory, similar to the linux `tree` command.
+
+</details>
+
+<details>
+<summary>Columns</summary>
+
+Rich can render content in neat [columns](https://rich.readthedocs.io/en/latest/columns.html) with equal or optimal width. Here's a very basic clone of the (MacOS / Linux) `ls` command which displays a directory listing in columns:
+
+```python
+import os
+import sys
+
+from rich import print
+from rich.columns import Columns
+
+directory = os.listdir(sys.argv[1])
+print(Columns(directory))
+```
+
+The following screenshot is the output from the [columns example](https://github.com/textualize/rich/blob/master/examples/columns.py) which displays data pulled from an API in columns:
+
+![columns](https://github.com/textualize/rich/raw/master/imgs/columns.png)
+
+</details>
+
+<details>
+<summary>Markdown</summary>
+
+Rich can render [markdown](https://rich.readthedocs.io/en/latest/markdown.html) and does a reasonable job of translating the formatting to the terminal.
+
+To render markdown import the `Markdown` class and construct it with a string containing markdown code. Then print it to the console. Here's an example:
+
+```python
+from rich.console import Console
+from rich.markdown import Markdown
+
+console = Console()
+with open("README.md") as readme:
+    markdown = Markdown(readme.read())
+console.print(markdown)
+```
+
+This will produce output something like the following:
+
+![markdown](https://github.com/textualize/rich/raw/master/imgs/markdown.png)
+
+</details>
+
+<details>
+<summary>Syntax Highlighting</summary>
+
+Rich uses the [pygments](https://pygments.org/) library to implement [syntax highlighting](https://rich.readthedocs.io/en/latest/syntax.html). Usage is similar to rendering markdown; construct a `Syntax` object and print it to the console. Here's an example:
+
+```python
+from rich.console import Console
+from rich.syntax import Syntax
+
+my_code = '''
+def iter_first_last(values: Iterable[T]) -> Iterable[Tuple[bool, bool, T]]:
+    """Iterate and generate a tuple with a flag for first and last value."""
+    iter_values = iter(values)
+    try:
+        previous_value = next(iter_values)
+    except StopIteration:
+        return
+    first = True
+    for value in iter_values:
+        yield first, False, previous_value
+        first = False
+        previous_value = value
+    yield first, True, previous_value
+'''
+syntax = Syntax(my_code, "python", theme="monokai", line_numbers=True)
+console = Console()
+console.print(syntax)
+```
+
+This will produce the following output:
+
+![syntax](https://github.com/textualize/rich/raw/master/imgs/syntax.png)
+
+</details>
+
+<details>
+<summary>Tracebacks</summary>
+
+Rich can render [beautiful tracebacks](https://rich.readthedocs.io/en/latest/traceback.html) which are easier to read and show more code than standard Python tracebacks. You can set Rich as the default traceback handler so all uncaught exceptions will be rendered by Rich.
+
+Here's what it looks like on OSX (similar on Linux):
+
+![traceback](https://github.com/textualize/rich/raw/master/imgs/traceback.png)
+
+</details>
+
+All Rich renderables make use of the [Console Protocol](https://rich.readthedocs.io/en/latest/protocol.html), which you can also use to implement your own Rich content.
+
+# Rich CLI
+
+
+See also [Rich CLI](https://github.com/textualize/rich-cli) for a command line application powered by Rich. Syntax highlight code, render markdown, display CSVs in tables, and more, directly from the command prompt.
+
+
+![Rich CLI](https://raw.githubusercontent.com/Textualize/rich-cli/main/imgs/rich-cli-splash.jpg)
+
+# Textual
+
+See also Rich's sister project, [Textual](https://github.com/Textualize/textual), which you can use to build sophisticated User Interfaces in the terminal.
+
+![textual-splash](https://github.com/user-attachments/assets/4caeb77e-48c0-4cf7-b14d-c53ded855ffd)
+
+# Toad
+
+[Toad](https://github.com/batrachianai/toad) is a unified interface for agentic coding. Built with Rich and Textual.
+
+![toad](https://github.com/user-attachments/assets/6678b707-1aeb-420f-99ad-abfcd4356771)
+