Skip to main content

Parse and emit YAML, and do it fast. Python wrapper for the C++ library

Project description

Rapid YAML - Python package

MIT Licensed PyPI

Or ryml, for short. ryml is a C++ library to parse and emit YAML, and do it fast, on everything from x64 to bare-metal chips without operating system. This repo contains the rapidyaml python package, which was previously in the original repo (up to release 0.11.0).

This python wrapper exposes only the index-based low-level C++ API, which works with node indices and string views. This API is blazing fast, but you may find it hard to use: it does not build a python structure of dicts/seqs/scalars (that's up to you), and all the scalars are untyped strings. With that said, it is really fast, and once you have the tree you can still walk over the tree to create the native python structure.

Performance

Here are some results for a timeit benchmark comparing ryml against PyYaml and ruamel.yaml (and note you can use this script with your YAML files!). ryml parses quicker by generally 100x and up to 400x:

+----------------------------------------+-------+----------+----------+-----------+
| style_seqs_blck_outer1000_inner100.yml | count | time(ms) | avg(ms)  | avg(MB/s) |
+----------------------------------------+-------+----------+----------+-----------+
| parse:RuamelYamlParse                  |     1 | 4564.812 | 4564.812 |     0.173 |
| parse:PyYamlParse                      |     1 | 2815.426 | 2815.426 |     0.280 |
| parse:RymlParseInArena                 |    38 |  588.024 |   15.474 |    50.988 |
| parse:RymlParseInArenaReuse            |    38 |  466.997 |   12.289 |    64.202 |
| parse:RymlParseInPlace                 |    38 |  579.770 |   15.257 |    51.714 |
| parse:RymlParseInPlaceReuse            |    38 |  462.932 |   12.182 |    64.765 |
+----------------------------------------+-------+----------+----------+-----------+

(Note that the parse timings above are somewhat biased towards ryml, because it does not perform any type conversions in Python-land: return types are merely memoryviews to the source buffer, possibly copied to the tree's arena).

As for emitting, the improvement can be as high as 3000x:

+----------------------------------------+-------+-----------+-----------+-----------+
| style_maps_blck_outer1000_inner100.yml | count |  time(ms) |  avg(ms)  | avg(MB/s) |
+----------------------------------------+-------+-----------+-----------+-----------+
| emit_yaml:RuamelYamlEmit               |     1 | 18149.288 | 18149.288 |     0.054 |
| emit_yaml:PyYamlEmit                   |     1 |  2683.380 |  2683.380 |     0.365 |
| emit_yaml:RymlEmitToNewBuffer          |    88 |   861.726 |     9.792 |    99.976 |
| emit_yaml:RymlEmitReuse                |    88 |   437.931 |     4.976 |   196.725 |
+----------------------------------------+-------+-----------+-----------+-----------+

Examples

Parsing a file

Here's a quick example (this is a unit test at test/test_ex_read.py):

import ryml

def test_read_yaml():
    yaml = b"{HELLO: a, foo: b, bar: c, baz: d, seq: [0, 1, 2, 3]}"

    # ryml holds only views to the parsed yaml source (following the C++ library).
    #
    # parse_in_place() parses directly the input buffer,
    # so this requires the user to keep the input buffer
    # alive while using the tree.
    #
    # parse_in_arena() copies the input buffer to
    # an arena in the tree, then parses the copy.
    # This is safer, so let's use it here:
    tree = ryml.parse_in_arena(yaml)

    # The returned tree has the following structure:
    #
    #   [node 0] root, map
    #     ` [node 1] "HELLO": "a"
    #     ` [node 2] "foo": "b"
    #     ` [node 3] "bar": "c"
    #     ` [node 4] "baz": "d"
    #     ` [node 5] "seq":
    #         ` [node 6] "0"
    #         ` [node 7] "1"
    #         ` [node 8] "2"
    #         ` [node 9] "3"
    #
    # let's now do some assertions (keeping this structure in mind):
    assert tree.size() == 10
    assert tree.root_id() == 0
    assert tree.is_root(0)
    assert tree.is_map(0)
    assert tree.is_keyval(1)
    assert tree.is_seq(5)
    assert tree.is_val(6)
    # use bytes or str objects for queries
    assert tree.find_child(0, b"HELLO") == 1
    assert tree.find_child(0, "HELLO") == 1
    assert tree.find_child(0, b"foo") == 2
    assert tree.find_child(0, "foo") == 2
    assert tree.find_child(0, b"seq") == 5
    assert tree.find_child(0, "seq") == 5
    assert tree.key(1) == b"HELLO"
    assert tree.val(1) == b"a"
    assert tree.key(2) == b"foo"
    assert tree.val(2) == b"b"
    assert tree.find_child(0, b"seq") == 5
    assert tree.find_child(0, "seq") == 5
    # hierarchy:
    assert tree.first_child(0) == 1
    assert tree.last_child(0) == 5
    assert tree.next_sibling(1) == 2
    assert tree.first_sibling(5) == 1
    assert tree.last_sibling(1) == 5
    assert tree.first_child(5) == 6
    assert tree.last_child(5) == 9
    # to loop over children:
    expected = [b"0", b"1", b"2", b"3"]
    for i, ch in enumerate(ryml.children(tree, 5)):
        assert tree.val(ch) == expected[i]
    # to loop over siblings:
    expected = [b"HELLO", b"foo", b"bar", b"baz", b"seq"]
    for i, sib in enumerate(ryml.siblings(tree, 5)):
        assert tree.key(sib) == expected[i]
    # to walk over all elements
    visited = [False] * tree.size()
    for node_id, indentation_level in ryml.walk(tree):
        visited[node_id] = True
    assert False not in visited
    # NOTE about encoding!
    k = tree.key(5)
    assert isinstance(k, memoryview)
    #print(k)  # '<memory at 0x7f80d5b93f48>'
    assert k == b"seq"               # ok, as expected
    assert k != "seq"                # not ok - NOTE THIS!
    assert str(k) != "seq"           # not ok
    assert str(k, "utf8") == "seq"   # ok again

Creating and emitting a tree

Here are some examples on how to create trees programatically (this is a unit test at test/test_ex_write.py):

import ryml


# all the tests below create this tree
expected_yaml = '{HELLO: a,foo: b,bar: c,baz: d,seq: [0,1,2,3]}'
expected_json = '{"HELLO": "a","foo": "b","bar": "c","baz": "d","seq": [0,1,2,3]}'


# helper to create map children nodes
def _append_keyval(tree: ryml.Tree, node_id: int, key, val, flags=0):
    child_id = tree.append_child(node_id)
    tree.to_keyval(child_id, key, val, flags)
    return child_id


# helper to create seq children nodes
def _append_val(tree: ryml.Tree, node_id: int, val, flags=0):
    child_id = tree.append_child(node_id)
    tree.to_val(child_id, val, flags)
    return child_id


def test_create_tree():
    tree = ryml.Tree()
    root_id = tree.root_id()
    tree.to_map(root_id, ryml.FLOW_SL) # set the root node as a map,
                                       # with FLOW_SL style (flow, single line)
    _append_keyval(tree, root_id, "HELLO", "a")
    _append_keyval(tree, root_id, "foo", "b")
    _append_keyval(tree, root_id, "bar", "c")
    _append_keyval(tree, root_id, "baz", "d")
    seq_id = tree.append_child(root_id)
    tree.to_seq(seq_id, "seq", ryml.FLOW_SL)  # append a sequence
    _append_val(tree, seq_id, "0")
    _append_val(tree, seq_id, "1")
    _append_val(tree, seq_id, "2")
    _append_val(tree, seq_id, "3")
    # check that this tree is emitted as expected
    _check_emits(tree)


# BEWARE! The tree is pointing at the memory of the scalars!
#
# If you are using dynamic strings for scalars, you must be sure to
# hold onto them while using the tree!
#
# Because explicitly managing lifetimes is generally hard or
# cumbersome to do in python, ryml provides you a tree.to_arena()
# helper to do this: it copies the scalar to the tree's arena, which
# will fix any lifetime issues.
#
# Here's an example:
def test_create_tree_dynamic():
    # let's now programmatically create the same tree as above:
    tree = ryml.Tree()
    root_id = tree.root_id()
    tree.to_map(root_id, ryml.FLOW_SL) # set the root node as a map,
                                       # with FLOW_SL style (flow, single line)
    # utility function to create a dynamic string and store it in the tree:
    def ds(s: str):
        # make a dynamic copy (using f-string to force creation a
        # different string object)
        dyn = f"_{s}_"[1:-1]
        # ...serialize the copy in the tree's arena
        saved = tree.to_arena(dyn)
        return saved
    # now we use ds() with each scalar, making it safer
    _append_keyval(tree, root_id, ds("HELLO"), ds("a"))
    _append_keyval(tree, root_id, ds("foo"), ds("b"))
    _append_keyval(tree, root_id, ds("bar"), ds("c"))
    _append_keyval(tree, root_id, ds("baz"), ds("d"))
    seq_id = tree.append_child(root_id)
    tree.to_seq(seq_id, ds("seq"), ryml.FLOW_SL)  # append a sequence
    _append_val(tree, seq_id, ds("0"))
    _append_val(tree, seq_id, ds("1"))
    _append_val(tree, seq_id, ds("2"))
    _append_val(tree, seq_id, ds("3"))
    # check that this tree is emitted as expected
    _check_emits(tree)


# But note you don't need to use tree.to_arena(); you can save the
# dynamic scalars for example by keeping them in a tree. But then you
# must take care of the lifetimes!
#
# Here's an example:
def test_create_tree_dynamic_explicit_save():
    # let's now programmatically create the same tree as above:
    tree = ryml.Tree()
    root_id = tree.root_id()
    tree.to_map(root_id, ryml.FLOW_SL) # set the root node as a map,
                                       # with FLOW_SL style (flow, single line)
    # this time we'll use a list to save the scalars. It works because
    # both `tree` and `saved_scalars` are defined and used in the same
    # scope. But it would fail if `saved_scalars` went out of scope
    # before ending the use of `tree`, eg if tree was returned from
    # this function but `saved_scalars` were not.
    saved_scalars = []
    # utility function to create a dynamic string and store it:
    def ds(s: str):
        # make a dynamic copy (using f-string to force creation a
        # different string object)
        dyn = f"_{s}_"[1:-1]
        # save the string in the list
        saved_scalars.append(dyn)
        return dyn
    # now we use ds() with each scalar, making it safer
    _append_keyval(tree, root_id, ds("HELLO"), ds("a"))
    _append_keyval(tree, root_id, ds("foo"), ds("b"))
    _append_keyval(tree, root_id, ds("bar"), ds("c"))
    _append_keyval(tree, root_id, ds("baz"), ds("d"))
    seq_id = tree.append_child(root_id)
    tree.to_seq(seq_id, ds("seq"), ryml.FLOW_SL)  # append a sequence
    _append_val(tree, seq_id, ds("0"))
    _append_val(tree, seq_id, ds("1"))
    _append_val(tree, seq_id, ds("2"))
    _append_val(tree, seq_id, ds("3"))
    # check that this tree is emitted as expected
    _check_emits(tree)


def test_create_tree_bytes():
    # ryml also works with bytes scalars
    tree = ryml.Tree()
    root_id = tree.root_id()
    tree.to_map(root_id, ryml.FLOW_SL) # set the root node as a map,
                                       # with FLOW_SL style (flow, single line)
    _append_keyval(tree, root_id, b"HELLO", b"a")
    _append_keyval(tree, root_id, b"foo", b"b")
    _append_keyval(tree, root_id, b"bar", b"c")
    _append_keyval(tree, root_id, b"baz", b"d")
    seq_id = tree.append_child(root_id)
    tree.to_seq(seq_id, b"seq", ryml.FLOW_SL)  # append a sequence
    _append_val(tree, seq_id, b"0")
    _append_val(tree, seq_id, b"1")
    _append_val(tree, seq_id, b"2")
    _append_val(tree, seq_id, b"3")
    # check that this tree is emitted as expected
    _check_emits(tree)


def test_create_tree_memoryview():
    # ryml also works with memoryview scalars
    tree = ryml.Tree()
    root_id = tree.root_id()
    tree.to_map(root_id, ryml.FLOW_SL) # set the root node as a map,
                                       # with FLOW_SL style (flow, single line)
    def s(scalar: bytes):
        return memoryview(scalar)
    _append_keyval(tree, root_id, s(b"HELLO"), s(b"a"))
    _append_keyval(tree, root_id, s(b"foo"), s(b"b"))
    _append_keyval(tree, root_id, s(b"bar"), s(b"c"))
    _append_keyval(tree, root_id, s(b"baz"), s(b"d"))
    seq_id = tree.append_child(root_id)
    tree.to_seq(seq_id, s(b"seq"), ryml.FLOW_SL)  # append a sequence
    _append_val(tree, seq_id, s(b"0"))
    _append_val(tree, seq_id, s(b"1"))
    _append_val(tree, seq_id, s(b"2"))
    _append_val(tree, seq_id, s(b"3"))
    # check that this tree is emitted as expected
    _check_emits(tree)


# this function shows several different ways of emitting from an
# existing tree (and tests that the results are as expected).
def _check_emits(tree: ryml.Tree):
    # emit_yaml() and emit_json() return a str object
    out_yaml = ryml.emit_yaml(tree)
    out_json = ryml.emit_json(tree)
    assert isinstance(out_yaml, str)
    assert isinstance(out_json, str)
    assert out_yaml == expected_yaml
    assert out_json == expected_json
    # if it is really important, you can emit to existing buffers:
    len_yaml = ryml.compute_yaml_length(tree) #
    len_json = ryml.compute_json_length(tree)
    buf_yaml = bytearray(len_yaml)
    buf_json = bytearray(len_json)
    out_yaml = ryml.emit_yaml_in_place(tree, buf_yaml)
    out_json = ryml.emit_json_in_place(tree, buf_json)
    assert isinstance(out_yaml, memoryview)
    assert isinstance(out_json, memoryview)
    assert out_yaml.tobytes().decode('utf8') == expected_yaml
    assert out_json.tobytes().decode('utf8') == expected_json

License

ryml is permissively licensed under the MIT license.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

rapidyaml-0.14.0.tar.gz (492.4 kB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

rapidyaml-0.14.0-cp314-cp314-win_arm64.whl (378.0 kB view details)

Uploaded CPython 3.14Windows ARM64

rapidyaml-0.14.0-cp314-cp314-win_amd64.whl (385.6 kB view details)

Uploaded CPython 3.14Windows x86-64

rapidyaml-0.14.0-cp314-cp314-win32.whl (318.4 kB view details)

Uploaded CPython 3.14Windows x86

rapidyaml-0.14.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (605.1 kB view details)

Uploaded CPython 3.14manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

rapidyaml-0.14.0-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl (595.4 kB view details)

Uploaded CPython 3.14manylinux: glibc 2.17+ ARM64manylinux: glibc 2.28+ ARM64

rapidyaml-0.14.0-cp314-cp314-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl (293.5 kB view details)

Uploaded CPython 3.14manylinux: glibc 2.28+ i686manylinux: glibc 2.5+ i686

rapidyaml-0.14.0-cp314-cp314-macosx_11_0_arm64.whl (5.4 MB view details)

Uploaded CPython 3.14macOS 11.0+ ARM64

rapidyaml-0.14.0-cp314-cp314-macosx_10_15_x86_64.whl (5.4 MB view details)

Uploaded CPython 3.14macOS 10.15+ x86-64

rapidyaml-0.14.0-cp314-cp314-macosx_10_15_universal2.whl (5.4 MB view details)

Uploaded CPython 3.14macOS 10.15+ universal2 (ARM64, x86-64)

rapidyaml-0.14.0-cp313-cp313-win_arm64.whl (366.0 kB view details)

Uploaded CPython 3.13Windows ARM64

rapidyaml-0.14.0-cp313-cp313-win_amd64.whl (372.0 kB view details)

Uploaded CPython 3.13Windows x86-64

rapidyaml-0.14.0-cp313-cp313-win32.whl (307.4 kB view details)

Uploaded CPython 3.13Windows x86

rapidyaml-0.14.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (605.1 kB view details)

Uploaded CPython 3.13manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

rapidyaml-0.14.0-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl (595.1 kB view details)

Uploaded CPython 3.13manylinux: glibc 2.17+ ARM64manylinux: glibc 2.28+ ARM64

rapidyaml-0.14.0-cp313-cp313-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl (293.6 kB view details)

Uploaded CPython 3.13manylinux: glibc 2.28+ i686manylinux: glibc 2.5+ i686

rapidyaml-0.14.0-cp313-cp313-macosx_11_0_arm64.whl (5.1 MB view details)

Uploaded CPython 3.13macOS 11.0+ ARM64

rapidyaml-0.14.0-cp313-cp313-macosx_10_13_x86_64.whl (5.1 MB view details)

Uploaded CPython 3.13macOS 10.13+ x86-64

rapidyaml-0.14.0-cp313-cp313-macosx_10_13_universal2.whl (5.1 MB view details)

Uploaded CPython 3.13macOS 10.13+ universal2 (ARM64, x86-64)

rapidyaml-0.14.0-cp312-cp312-win_arm64.whl (366.4 kB view details)

Uploaded CPython 3.12Windows ARM64

rapidyaml-0.14.0-cp312-cp312-win_amd64.whl (372.3 kB view details)

Uploaded CPython 3.12Windows x86-64

rapidyaml-0.14.0-cp312-cp312-win32.whl (307.6 kB view details)

Uploaded CPython 3.12Windows x86

rapidyaml-0.14.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (605.3 kB view details)

Uploaded CPython 3.12manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

rapidyaml-0.14.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl (595.0 kB view details)

Uploaded CPython 3.12manylinux: glibc 2.17+ ARM64manylinux: glibc 2.28+ ARM64

rapidyaml-0.14.0-cp312-cp312-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl (293.8 kB view details)

Uploaded CPython 3.12manylinux: glibc 2.28+ i686manylinux: glibc 2.5+ i686

rapidyaml-0.14.0-cp312-cp312-macosx_11_0_arm64.whl (5.1 MB view details)

Uploaded CPython 3.12macOS 11.0+ ARM64

rapidyaml-0.14.0-cp312-cp312-macosx_10_13_x86_64.whl (5.1 MB view details)

Uploaded CPython 3.12macOS 10.13+ x86-64

rapidyaml-0.14.0-cp312-cp312-macosx_10_13_universal2.whl (5.1 MB view details)

Uploaded CPython 3.12macOS 10.13+ universal2 (ARM64, x86-64)

rapidyaml-0.14.0-cp311-cp311-win_arm64.whl (365.4 kB view details)

Uploaded CPython 3.11Windows ARM64

rapidyaml-0.14.0-cp311-cp311-win_amd64.whl (372.1 kB view details)

Uploaded CPython 3.11Windows x86-64

rapidyaml-0.14.0-cp311-cp311-win32.whl (307.4 kB view details)

Uploaded CPython 3.11Windows x86

rapidyaml-0.14.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (605.5 kB view details)

Uploaded CPython 3.11manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

rapidyaml-0.14.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl (594.7 kB view details)

Uploaded CPython 3.11manylinux: glibc 2.17+ ARM64manylinux: glibc 2.28+ ARM64

rapidyaml-0.14.0-cp311-cp311-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl (295.1 kB view details)

Uploaded CPython 3.11manylinux: glibc 2.28+ i686manylinux: glibc 2.5+ i686

rapidyaml-0.14.0-cp311-cp311-macosx_11_0_arm64.whl (4.9 MB view details)

Uploaded CPython 3.11macOS 11.0+ ARM64

rapidyaml-0.14.0-cp311-cp311-macosx_10_9_x86_64.whl (4.9 MB view details)

Uploaded CPython 3.11macOS 10.9+ x86-64

rapidyaml-0.14.0-cp311-cp311-macosx_10_9_universal2.whl (4.9 MB view details)

Uploaded CPython 3.11macOS 10.9+ universal2 (ARM64, x86-64)

rapidyaml-0.14.0-cp310-cp310-win_arm64.whl (365.6 kB view details)

Uploaded CPython 3.10Windows ARM64

rapidyaml-0.14.0-cp310-cp310-win_amd64.whl (372.1 kB view details)

Uploaded CPython 3.10Windows x86-64

rapidyaml-0.14.0-cp310-cp310-win32.whl (307.3 kB view details)

Uploaded CPython 3.10Windows x86

rapidyaml-0.14.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (605.5 kB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

rapidyaml-0.14.0-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl (594.7 kB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ ARM64manylinux: glibc 2.28+ ARM64

rapidyaml-0.14.0-cp310-cp310-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl (295.1 kB view details)

Uploaded CPython 3.10manylinux: glibc 2.28+ i686manylinux: glibc 2.5+ i686

rapidyaml-0.14.0-cp310-cp310-macosx_11_0_arm64.whl (3.9 MB view details)

Uploaded CPython 3.10macOS 11.0+ ARM64

rapidyaml-0.14.0-cp310-cp310-macosx_10_9_x86_64.whl (3.9 MB view details)

Uploaded CPython 3.10macOS 10.9+ x86-64

rapidyaml-0.14.0-cp310-cp310-macosx_10_9_universal2.whl (3.9 MB view details)

Uploaded CPython 3.10macOS 10.9+ universal2 (ARM64, x86-64)

rapidyaml-0.14.0-cp39-cp39-win_arm64.whl (365.6 kB view details)

Uploaded CPython 3.9Windows ARM64

rapidyaml-0.14.0-cp39-cp39-win_amd64.whl (372.2 kB view details)

Uploaded CPython 3.9Windows x86-64

rapidyaml-0.14.0-cp39-cp39-win32.whl (307.3 kB view details)

Uploaded CPython 3.9Windows x86

rapidyaml-0.14.0-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (605.6 kB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

rapidyaml-0.14.0-cp39-cp39-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl (594.7 kB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ ARM64manylinux: glibc 2.28+ ARM64

rapidyaml-0.14.0-cp39-cp39-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl (295.1 kB view details)

Uploaded CPython 3.9manylinux: glibc 2.28+ i686manylinux: glibc 2.5+ i686

rapidyaml-0.14.0-cp39-cp39-macosx_11_0_arm64.whl (3.0 MB view details)

Uploaded CPython 3.9macOS 11.0+ ARM64

rapidyaml-0.14.0-cp39-cp39-macosx_10_9_x86_64.whl (3.0 MB view details)

Uploaded CPython 3.9macOS 10.9+ x86-64

rapidyaml-0.14.0-cp39-cp39-macosx_10_9_universal2.whl (3.0 MB view details)

Uploaded CPython 3.9macOS 10.9+ universal2 (ARM64, x86-64)

rapidyaml-0.14.0-cp38-cp38-win_amd64.whl (372.1 kB view details)

Uploaded CPython 3.8Windows x86-64

rapidyaml-0.14.0-cp38-cp38-win32.whl (307.3 kB view details)

Uploaded CPython 3.8Windows x86

rapidyaml-0.14.0-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (605.4 kB view details)

Uploaded CPython 3.8manylinux: glibc 2.17+ x86-64manylinux: glibc 2.28+ x86-64

rapidyaml-0.14.0-cp38-cp38-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl (594.6 kB view details)

Uploaded CPython 3.8manylinux: glibc 2.17+ ARM64manylinux: glibc 2.28+ ARM64

rapidyaml-0.14.0-cp38-cp38-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl (294.8 kB view details)

Uploaded CPython 3.8manylinux: glibc 2.28+ i686manylinux: glibc 2.5+ i686

rapidyaml-0.14.0-cp38-cp38-macosx_10_9_x86_64.whl (1.5 MB view details)

Uploaded CPython 3.8macOS 10.9+ x86-64

File details

Details for the file rapidyaml-0.14.0.tar.gz.

File metadata

  • Download URL: rapidyaml-0.14.0.tar.gz
  • Upload date:
  • Size: 492.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for rapidyaml-0.14.0.tar.gz
Algorithm Hash digest
SHA256 ba9628aad78baf9eef4f0208951225366bd81b370772d1fe3b065d5d56e6eedf
MD5 b81ac4e634a078852d56948ea83b6f85
BLAKE2b-256 8b7b2b9d03d5646e3949fd73ddafc836fa397a240d391a8ada5a43752da52f5d

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp314-cp314-win_arm64.whl.

File metadata

  • Download URL: rapidyaml-0.14.0-cp314-cp314-win_arm64.whl
  • Upload date:
  • Size: 378.0 kB
  • Tags: CPython 3.14, Windows ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for rapidyaml-0.14.0-cp314-cp314-win_arm64.whl
Algorithm Hash digest
SHA256 8c115e0cabff9b3d11f4514a351c7af99a315ddb82ba7584ec230e24619a5adf
MD5 17cc9bcf3894c4c64c264e176a836da7
BLAKE2b-256 2ffedfac543003bf399b62b309bea007cdfc56afb913cacf76002ad0d2512adc

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp314-cp314-win_amd64.whl.

File metadata

  • Download URL: rapidyaml-0.14.0-cp314-cp314-win_amd64.whl
  • Upload date:
  • Size: 385.6 kB
  • Tags: CPython 3.14, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for rapidyaml-0.14.0-cp314-cp314-win_amd64.whl
Algorithm Hash digest
SHA256 9ed9e0e8f75ff5d9bd5b666732ab1a867fa5bc554747505c50ece7dcda25d418
MD5 f1540868f7513956b839e19a9d70e635
BLAKE2b-256 37dba7e0c0cb173092ebdedb4c64a09ffe6f2ce71a6a714ec56f4d93e1b1e1b9

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp314-cp314-win32.whl.

File metadata

  • Download URL: rapidyaml-0.14.0-cp314-cp314-win32.whl
  • Upload date:
  • Size: 318.4 kB
  • Tags: CPython 3.14, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for rapidyaml-0.14.0-cp314-cp314-win32.whl
Algorithm Hash digest
SHA256 c7c98c4e4f34c242a5f00dd1cb0a8b5e3f53472e8598a36f295eefc11dd457b3
MD5 4e6516e4e4d1f896b1592a4973f2bd76
BLAKE2b-256 19e26a1ff220a775c446b79f38a20cac8ccf91cd8bf09841befd6bd5f732bed8

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 f0c595dd8af2427818171a92b86b78ae6bdfffc77dd026d7d4876da7f00888c1
MD5 b738ea836ee825f623dc20d7dd82f55c
BLAKE2b-256 cc51161b3201edfc4061c39effe380e2e19df76ead7196188817958dbc6c1377

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 58587908ae3fd385b3b2c56fa42139e6a8c47daa7712b8ee88a171f60de11447
MD5 91ff0838060a9705d13afdc196bfdabb
BLAKE2b-256 d8066e74cad3e42d16eb428a8cd20feca8c62e7e4200048812ca35b973130c92

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp314-cp314-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp314-cp314-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl
Algorithm Hash digest
SHA256 6c622f92dff6d9f473f3d84aad5f1bb2ced95eddd44589b84c3b75eaed265a54
MD5 cab59fd563b2c3ba32675bb31d262a08
BLAKE2b-256 f9234f587683ce4a6696332428ee0ef36828cd1e812e05febc17ffa416345252

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp314-cp314-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp314-cp314-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 63fb540b925ac173e47e79b4abd8b91452e20b6f6b6f4b3475cc733ec6a53e9b
MD5 2cd4f2ae525e71ac5f8f6d5b83f3f5c7
BLAKE2b-256 577b77161b5d3be0cc5482e30f0f052752c64d58e9127f06ecf08fddd3d702b7

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp314-cp314-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp314-cp314-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 45e60d9fcd279acd527fbc79de75b625fef22ee953291f8239017ec7bb6a29bc
MD5 39595ea6d0386ba5496a64fe224dfcce
BLAKE2b-256 9c8efa61bb8abac51e74cb17eb1f6a93df7f62bb037e0df87f3c98dbd2e66870

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp314-cp314-macosx_10_15_universal2.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp314-cp314-macosx_10_15_universal2.whl
Algorithm Hash digest
SHA256 6b24d4b5883048aad13847c36cb48aa4c23f81c6d0a97f644dfcaaf2a8e51ed0
MD5 180ec2eb7b156e70d173494d05975d1d
BLAKE2b-256 7f58401eacda518e5229e1b6a89fcdf002d8e69b67531b294978b0d01e9b3ee6

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp313-cp313-win_arm64.whl.

File metadata

  • Download URL: rapidyaml-0.14.0-cp313-cp313-win_arm64.whl
  • Upload date:
  • Size: 366.0 kB
  • Tags: CPython 3.13, Windows ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for rapidyaml-0.14.0-cp313-cp313-win_arm64.whl
Algorithm Hash digest
SHA256 7799ac517ec34d3941e3b969f01ca70f2ad9cef0cc6971eb8a32cc40834ed455
MD5 547e04773ac9dbd864e81ca225c09f72
BLAKE2b-256 60c5761ef3d57960863fd03d538716ed3f6f5cad8f67df0029dbcd51c0c5927b

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp313-cp313-win_amd64.whl.

File metadata

  • Download URL: rapidyaml-0.14.0-cp313-cp313-win_amd64.whl
  • Upload date:
  • Size: 372.0 kB
  • Tags: CPython 3.13, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for rapidyaml-0.14.0-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 1a1473ac595d0ca48624d7618a8ddbdf67345a6895cf934c108a4461f38562b4
MD5 3793d1c03b28424cdafc61fd58d17f51
BLAKE2b-256 36cf85297a9cfa2747de3d7282b01c58a75cb627ba02adc7860df2e58ed9f990

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp313-cp313-win32.whl.

File metadata

  • Download URL: rapidyaml-0.14.0-cp313-cp313-win32.whl
  • Upload date:
  • Size: 307.4 kB
  • Tags: CPython 3.13, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for rapidyaml-0.14.0-cp313-cp313-win32.whl
Algorithm Hash digest
SHA256 57b11d97c30b292021cd0e08f4ab34f2008894f322aabeecfa81420d64f7774e
MD5 67be6ea1c5f13307ec63aac3db29387e
BLAKE2b-256 28e03744a920024b5c13032ced6ba0277bc0155c0d3057ee111b493a7e8eb875

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 73b4653fa7f9a0b349d5c612b26dd1bdb5f968137b35d2188ca13469397cee2a
MD5 a00791afc588158ce266997df0e84e3b
BLAKE2b-256 506b4c73359b7c015d64ff4d006460690d925fd80a06611ae1df72b22f316b5e

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 5f6d29cff16262268d8c13bea8704a57400b1db3de37dd5ff1abe853af371191
MD5 56db5efd80bcdce92af3dfcfbb268eef
BLAKE2b-256 f598b175d05058e23c1159c731560dd43de327249ada77747466b5107e37fbb8

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp313-cp313-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp313-cp313-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl
Algorithm Hash digest
SHA256 3c8249715145656a329fe4a57adf06ff78ca1edf625bdc52b9d8f1e257d11aae
MD5 7844eaded8a04c0c91a62e9993830820
BLAKE2b-256 ee44858df837d227a20f52fc090c168f62e661f0d2e30e22cc49793159d47013

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp313-cp313-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp313-cp313-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 1f27e95684ee97cc6617eea3a71d829195a82326bbdd0c605ba338aaaef6aa2a
MD5 1a5d6ee504418f9d82f74326f044c074
BLAKE2b-256 6082e751c040fddd17c606642e975760bcdc678d83214f16900e4dadf2ebab2a

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp313-cp313-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp313-cp313-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 cd5701e4bf5af7a34ceed11d57b6f316ccee92f53380d5fb2cc0af60e437079e
MD5 f579a3a231e0192fc866876eca6d710d
BLAKE2b-256 d882121b6724a23b0635f64d2b5cb9587232a3358740c6faf9b55f1c2b69edc2

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp313-cp313-macosx_10_13_universal2.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp313-cp313-macosx_10_13_universal2.whl
Algorithm Hash digest
SHA256 9614f8456c1c0868a7667214fae0668e55a3bb966ecf99204df797dd951ba600
MD5 e3f1db099ebd981622b8ccdbf4fc6b0b
BLAKE2b-256 6ba72e92df45f3530d4ccc4903e50848079e8f01f6f9d5f2e39cb133f3e64f87

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp312-cp312-win_arm64.whl.

File metadata

  • Download URL: rapidyaml-0.14.0-cp312-cp312-win_arm64.whl
  • Upload date:
  • Size: 366.4 kB
  • Tags: CPython 3.12, Windows ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for rapidyaml-0.14.0-cp312-cp312-win_arm64.whl
Algorithm Hash digest
SHA256 f9f355e7c9b52d5503637ebaedcf3ce2c2e1fb503bc8995724c0b74172bfced7
MD5 45cc1aa806de27283c925dbcab928ddb
BLAKE2b-256 e8c03556478fd72616f2fc9f17dc08602c23735b03b9101d98f33bd58ae0ccb9

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: rapidyaml-0.14.0-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 372.3 kB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for rapidyaml-0.14.0-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 06fe7edf21037e52e2f0c9bf554bd564eca3981970ea0c0eaceb2a53a58a27e9
MD5 12c95c3849973947731c7056fae4484f
BLAKE2b-256 113539afef9ddfb6c7eeda8f1f5e7180dee575028ffa2af76196de16df82e093

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp312-cp312-win32.whl.

File metadata

  • Download URL: rapidyaml-0.14.0-cp312-cp312-win32.whl
  • Upload date:
  • Size: 307.6 kB
  • Tags: CPython 3.12, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for rapidyaml-0.14.0-cp312-cp312-win32.whl
Algorithm Hash digest
SHA256 67cca0453dd6e2d16c70bb3b18f4a28648b7e7ee94d42907787eae12afcfd9c2
MD5 237fbab642e33848dcfd00f5d5aff697
BLAKE2b-256 49bc5e055e869349d58c3affb134b017f118c75ce879979e0cf8c89c9d6f7cdb

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 674539d976ef861c3385d1bfd50b91689af0798cf388cb09721fbebccf2ea144
MD5 7ca82f04d09a132586ba91a8d7cefdee
BLAKE2b-256 2b9900c5379fe628e67c70f09867561c49a397abf67db5dc4be5cac000bfdc36

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 bda54adb877a97deae8f510d41c63fd49ef2ee8c0b06bfe7ee5992e70cdc5dc3
MD5 732af9f01caac918ff6515b38cbc2e60
BLAKE2b-256 354872a72e198dd9dedb312ffb25485c9e7662c0646e1a20c514405875f585a8

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp312-cp312-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp312-cp312-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl
Algorithm Hash digest
SHA256 3617f80b5f774f7fcd7d2cf91222ae4e2d320db9bec70aee27ce34a154cffc6f
MD5 222d00b5ecc1c5bcf7d896e62b8276f0
BLAKE2b-256 e3e15c3c8bc48852c1de9b7317e6fd2eb119667c9eb46b0745db7d197378fde8

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 95d951531593058a106110b0ccae0c6f76807c9425215428f35a66ae0eeb2ba3
MD5 ac78d074d193f94dd06e8aec4b030d60
BLAKE2b-256 662535bc6cc5c6ee76b7289eb4f4bf863cf7e91e053ebf46b9b12deda05ac2fb

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp312-cp312-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp312-cp312-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 09f678e344ae060d9734985df804b62cd3348693a54dc0cb6c78981102761424
MD5 df2f80b20084f0aff74ee1b6cd36a113
BLAKE2b-256 e9bbfe5786f1a01bc1ab2c65cd4e080bc6f07ad3e53bf054d89d6fca63a24d90

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp312-cp312-macosx_10_13_universal2.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp312-cp312-macosx_10_13_universal2.whl
Algorithm Hash digest
SHA256 85f06cea3d814cc25c31976e9f65b71b1db281defb02b6af4c20381818cf5e13
MD5 e06df438bdbb648bba8d1d4600252176
BLAKE2b-256 b9198054b29a35335709858f5414b23ad73814141fe4b984a52166364368d2b1

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp311-cp311-win_arm64.whl.

File metadata

  • Download URL: rapidyaml-0.14.0-cp311-cp311-win_arm64.whl
  • Upload date:
  • Size: 365.4 kB
  • Tags: CPython 3.11, Windows ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for rapidyaml-0.14.0-cp311-cp311-win_arm64.whl
Algorithm Hash digest
SHA256 13f4e76688066da21ad71ea8db8959d356eaf49bf49c1d7589677d644702f2d6
MD5 03d66ec4a62425d3d716f1920795127e
BLAKE2b-256 60bd793c531797a2cc2b37f0b9afca43b27b0e48f433605b6fb32188af8caf66

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: rapidyaml-0.14.0-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 372.1 kB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for rapidyaml-0.14.0-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 704eb7822a77cc5f9ba81962cebf011d0e664dd3b64c1599de13e21ba2361692
MD5 7bb381eaf5ce416e143e8bc18345f977
BLAKE2b-256 245ea1f7f85f193557e77fcbeb4227a0aea4328c52d3cbfdd626c5a8dc2fc496

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp311-cp311-win32.whl.

File metadata

  • Download URL: rapidyaml-0.14.0-cp311-cp311-win32.whl
  • Upload date:
  • Size: 307.4 kB
  • Tags: CPython 3.11, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for rapidyaml-0.14.0-cp311-cp311-win32.whl
Algorithm Hash digest
SHA256 f7d6f46f5ff38e604ab412f98705b18c7d7e3bfc26281747885167f6dd458a81
MD5 8574fcd4c2a2664215fae0d5ab17cb88
BLAKE2b-256 5548939b405e87e974f8dd3c6d51b7cf99dbcd670952314f42b5fa21810bb92d

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 d7678add4230478272a1cfc8efb5be89a494f307329164a01c19f7cf7d7107d2
MD5 cb682e2138ed18a800b801dad68b08cd
BLAKE2b-256 027ba56a825893197270e138d210568da1141bf473db6ba0d9a3092b3f84c6c0

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 ebe7a808e9abf919b433f440d1c2f1505a34377b8f677fd7595bebdb8a271ac7
MD5 3f08d528062c63da701b022873d801ba
BLAKE2b-256 7689cba6f542d9e3938356ba55e0f4f580af5aa59a8809d06f541b93ff691942

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp311-cp311-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp311-cp311-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl
Algorithm Hash digest
SHA256 a539f26e713d0a4f30b9107260fb67bdec63e6b841b8edcb5510874e82b8fdf6
MD5 47f9b39d522146cb16d35eedb5ea861b
BLAKE2b-256 5d0c8262196fe1ca3715aa149c86fef2e05c87157a77e59d20f966d2d215acfe

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 3c818a9da359123f34a7cef4738e29e6029ca28c7c8c89ff2d7c747c647e0511
MD5 45ebeb4091433cbe9d146b5229ce7e5d
BLAKE2b-256 6431df82230e9a5d66ad8aedba2b54f72e10385fcd547d0d966d993dd79a6f1e

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 9f696c4425d2358574efc3686e9ed01a4af347855211cff045ec50a32b59a33b
MD5 2b5b28bfea8959350dd6cb7b607c0fc1
BLAKE2b-256 8288663b213e487187224777fec9e36706cf1beaa8f28dc9f795f1eb7bc55a14

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp311-cp311-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp311-cp311-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 d50839a2e90878672da965643ee950e0bde6731c9f727e440da7867a111a0c78
MD5 1fc5d229d8d85825b1684087308aa4e1
BLAKE2b-256 0a455b329afd50c30a6bebf58f0ab9bbbbe3370698b92bcde77bbd4b18d2d5a6

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp310-cp310-win_arm64.whl.

File metadata

  • Download URL: rapidyaml-0.14.0-cp310-cp310-win_arm64.whl
  • Upload date:
  • Size: 365.6 kB
  • Tags: CPython 3.10, Windows ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for rapidyaml-0.14.0-cp310-cp310-win_arm64.whl
Algorithm Hash digest
SHA256 aed91a01d4c1718221101b98ed33020c961658a6f6daa7a4d487c7c4b85361b1
MD5 4b0d804e3fd4b1719439f45a8f4dbd33
BLAKE2b-256 657ffc0d2b18582303434bd4f39ac4b7d9ea0e78d7292ea00151521a682f2aad

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: rapidyaml-0.14.0-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 372.1 kB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for rapidyaml-0.14.0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 42ff6fc3a705c394c9a898b4d9eceaa250c1e56fa69434bdccb2f37db3c1d79b
MD5 cd6bf41d8fc06e66e5e3f2e993cc0247
BLAKE2b-256 38d4bf3bace8cd11d64878a72b0ad88a7a67673944adc476b1dafa042a482b4e

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp310-cp310-win32.whl.

File metadata

  • Download URL: rapidyaml-0.14.0-cp310-cp310-win32.whl
  • Upload date:
  • Size: 307.3 kB
  • Tags: CPython 3.10, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for rapidyaml-0.14.0-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 ca46aa40e60d32a05cc46b69586290b0dc694ca74590c47f53b0de419f0f9697
MD5 777508527192024e19f2b7c78818e26c
BLAKE2b-256 2e0b25f21a5a6a6f31f4189ec26334dd0a2047ed74ceb97243d4161338e25975

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 b3f3151305c4e67366b2cc6e474eec5bd1c0670e650b18ffb2520ef69282d269
MD5 ed4a2472fd52b4e4727bdd099f5d1a2a
BLAKE2b-256 0f5b14ac1639b323a4c0e76f99fa8cb67f4ec23fdaa8923b52f7d8aa3996fc26

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 b4ce71402f5e59ad325fb19db2b40c4af1a23441f96e76701dedf60db1d88b0e
MD5 1ae090d6be782ac188dd513fefded3a8
BLAKE2b-256 12b96b64df90afce5eefcf819ffaa8fefc5fa7d43dc60079075f8a3636557a8c

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp310-cp310-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp310-cp310-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl
Algorithm Hash digest
SHA256 5ed79434ccc9d700911989ca0d90648cb4d42d2d11f35c60cd3ae9af9a2e8a92
MD5 6104c8fc2f114ddae2913287934e7cd7
BLAKE2b-256 e8c379f79bd0755eaa0fdc4fcef48eb139118e30ba783cc261f831cf20186d73

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 4c476532d690645f3d8d88630909857d1a74d0509fb6a00728c7f2dd3fe424a9
MD5 7109051e30ac627fccef4ef72bb5cbaa
BLAKE2b-256 b66b788639291b3d56dfa39e00dfd57f83c78f3036ba02e2b9f7bbc7f8d2c97b

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 9b5466c4bd4e4f8cc2e4e0818b68a77b80be2a64e751e67a807005db063e14f8
MD5 675b6419b14bc776ffc8e130ef402d8c
BLAKE2b-256 df3e08b9fd75c1a9aee9121d1d9812bd8fcfbedb47756e3a28f249410420ae1d

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp310-cp310-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp310-cp310-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 3769fe8992ee55f5f177c05b1823bafacc2d24b3c3c37d60e2b3f0093d29dc31
MD5 fe0dc7121d16c8e92d0b0fca01130d00
BLAKE2b-256 92296c9707ab89642cd3ef12b5b4124ae537045ab0cee2a0c0eba6b7d7d7ac7d

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp39-cp39-win_arm64.whl.

File metadata

  • Download URL: rapidyaml-0.14.0-cp39-cp39-win_arm64.whl
  • Upload date:
  • Size: 365.6 kB
  • Tags: CPython 3.9, Windows ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for rapidyaml-0.14.0-cp39-cp39-win_arm64.whl
Algorithm Hash digest
SHA256 5190786fbee7630df4c1846311aaf160c1b6839bd5e3f21df1e77af72753caed
MD5 e73baf8345bfb437d9107c3ef0a00e00
BLAKE2b-256 deb334f1d8b47392cfe53cce1de7aaaccd7b9cb5f20fb874ecc08dbd2e423c25

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: rapidyaml-0.14.0-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 372.2 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for rapidyaml-0.14.0-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 fc55772a0235ef15454a8a499a98990a8bf2967411ea03c8967df80d23539486
MD5 780885ffeb99fb95da296e2fa5309bf3
BLAKE2b-256 a8a8d370aa9bc8b13554c306906bc8281b6c5f53a61686002b42e2672fe3c967

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp39-cp39-win32.whl.

File metadata

  • Download URL: rapidyaml-0.14.0-cp39-cp39-win32.whl
  • Upload date:
  • Size: 307.3 kB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for rapidyaml-0.14.0-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 732171ed4d43b25734c3eeb8a71357f4de92ac0efea03b9282fb4882196bb1f2
MD5 0a2ebf4f42603f20709be0ac41eedf87
BLAKE2b-256 b390535109e78118f9c0357dac0e8e3e9d28f826925d242a08d4181d0e9cead7

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 d582bf00a440979d4745669dc649eefc1352ca93043b131ad2bcea40f86f6d8e
MD5 9807828c6a1e61d67b8becd81a29e569
BLAKE2b-256 0f57741db841837c281b6ae3567675ea5f88f23e83d8c53f28389452d96eb550

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp39-cp39-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp39-cp39-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 3624b14169628e1d1237d95dc6a5eafc6ac6291b161f3153b60fc0ca02d0e40d
MD5 a2033b8e5b54b326983b0813a5892a60
BLAKE2b-256 a29021477549b03f549979db89ef46da7e15444876ad3384a762a2c6f15c8098

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp39-cp39-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp39-cp39-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl
Algorithm Hash digest
SHA256 c62ca109d205dbb4947e0b0f113f31acbc7dc2d79d652d36d61c776403421cbd
MD5 a3d94588a475481d958f20cb593f844f
BLAKE2b-256 c3b4fdb0fdb80991d7a604236cbb5853a87233e33ae28b8407ab4902780e4f86

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 0612fe56a41103f15a8ef0d0345cf2f205fc04983896740ae5cc6e0be7852c4d
MD5 4d131bfec0f500fe08ca283fce6e4789
BLAKE2b-256 5a052fa8d3f8615365ed0ff6727ca8b6514692b55420f5dcff38d9ba884885a4

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 0b05acf75363e3231800c8543e71f4c143981c0cc985a2717477ff0823f026d0
MD5 684740c0c03f204298b5b5b682b20d13
BLAKE2b-256 bf3715251a63e77420d352a52f17aff38dbd3a4d0903007bcc130d0cd686f56d

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp39-cp39-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp39-cp39-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 b4c5aac2eac24797cd6dc3acc066dee3cd9b7faf69995fbc10d4beef471d5f8f
MD5 7108fe5f3d6f0e0dbb1ffac271d61aa4
BLAKE2b-256 aecbb713962c2ecf61e952853b075b2dcbc40bd97f3ce8089bb43dd2eae6d17d

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: rapidyaml-0.14.0-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 372.1 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for rapidyaml-0.14.0-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 04d8c56fb18acf81e73bd102e2cc662b2cb558225c7b7c7dfcab3439a764f56c
MD5 beeeee20bb6aced7fc1c892e98060823
BLAKE2b-256 a7daeb326958af0747dce124a5d2f72d46f17abf20a9417d1e514ec319d8c5fd

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp38-cp38-win32.whl.

File metadata

  • Download URL: rapidyaml-0.14.0-cp38-cp38-win32.whl
  • Upload date:
  • Size: 307.3 kB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for rapidyaml-0.14.0-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 58cac6390e8e81ada870905133a5eece5d1deb1999002e7fffc5bd4ce69586a3
MD5 df1c0c5bedceb6fb3e7e5df45ec109a7
BLAKE2b-256 f58daa64b161b214b1a855c92d2054c85c65bcbc555fa2bf7a5ae7502892ed11

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 d802c5035cd7492296fcdcf36d52484c32574bdce5bfc6f825e73e520a72f5aa
MD5 8b5033d879050a1bf236f637c8c65bef
BLAKE2b-256 4e74416f46cb9cde86f8e87922ad3ae7a9c57bdceeabb79039a66d21b7fdacb5

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp38-cp38-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp38-cp38-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 5970f3d1163118092175155d3246773cd6ec2d7574e0b3a78f8b7e9b007a6c15
MD5 5113d209f96eedc49c8dd49f3d6369df
BLAKE2b-256 1d5b8a98656810dc74526961dd7c49fc9858f29036ed35c98f64ad5a806dcf88

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp38-cp38-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp38-cp38-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl
Algorithm Hash digest
SHA256 f9f2787d74da44bdff187304fea81274521bd7a1ec9b16eca923f3ecce73113a
MD5 503520ae0b0b63c82332a30c6cb1e81d
BLAKE2b-256 24e92cbd181def21f254a9bae859f07620354cd34d4e694f62fbcec0f9bdfc09

See more details on using hashes here.

File details

Details for the file rapidyaml-0.14.0-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for rapidyaml-0.14.0-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 0879ba323eec3a0bc256951a8708769cb8415f62a39ce150ec64fd7102fe925a
MD5 3f1cf60150e3280baeb184857f0a5617
BLAKE2b-256 d5c5600196f7294ac4b20369774e438c2cce9e53c8add8294ef3eee6954efa37

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page