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Prepare for schemars v1.0.0 #27

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316786c
Test schemars v1.0.0-rc.1
juntyr Jun 16, 2025
ab24888
Update schema tests
juntyr Jun 16, 2025
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10 changes: 5 additions & 5 deletions Cargo.toml
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Expand Up @@ -100,7 +100,7 @@ pyo3-error = { version = "0.5", default-features = false }
pyo3-log = { version = "0.12.4", default-features = false }
pythonize = { version = "0.25", default-features = false }
rand = { version = "0.9.1", default-features = false }
schemars = { version = "=1.0.0-alpha.15", default-features = false }
schemars = { version = "=1.0.0-rc.1", default-features = false }
scratch = { version = "1.0", default-features = false }
semver = { version = "1.0.23", default-features = false }
serde = { version = "1.0.218", default-features = false }
Expand All @@ -117,14 +117,14 @@ wac-graph = { version = "0.6", default-features = false }
wasi-sandboxed-component-provider = { version = "=0.2.3", default-features = false }
wasi-logger = { version = "0.1", default-features = false }
wasi-preview1-component-adapter-provider = { version = "33.0", default-features = false }
wasmparser = { version = "0.231", default-features = false }
wasmparser = { version = "0.235", default-features = false }
wasmtime = { version = "33.0", default-features = false }
wasmtime_runtime_layer = { version = "33.0", default-features = false }
wasm-encoder = { version = "0.231", default-features = false }
wasm-encoder = { version = "0.235", default-features = false }
wasm_runtime_layer = { version = "0.5", default-features = false }
wit-bindgen = { version = "0.42", default-features = false }
wit-component = { version = "0.231", default-features = false }
wit-parser = { version = "0.231", default-features = false }
wit-component = { version = "0.235", default-features = false }
wit-parser = { version = "0.235", default-features = false }
wyhash = { version = "0.6", default-features = false }
zfp-sys = { version = "0.4.0", default-features = false }
zstd = { version = "0.13", default-features = false }
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4 changes: 2 additions & 2 deletions codecs/fourier-network/tests/schema.json
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Expand Up @@ -37,7 +37,7 @@
],
"format": "uint",
"minimum": 1,
"description": "The optional mini-batch size used during training\n\n Setting the mini-batch size to `None` disables the use of batching,\n i.e. the network is trained using one large batch that includes the\n full data."
"description": "The optional mini-batch size used during training\n\nSetting the mini-batch size to `None` disables the use of batching,\ni.e. the network is trained using one large batch that includes the\nfull data."
},
"seed": {
"type": "integer",
Expand All @@ -61,7 +61,7 @@
"mini_batch_size",
"seed"
],
"description": "Fourier network codec which trains and overfits a fourier feature neural\n network on encoding and predicts during decoding.\n\n The approach is based on the papers by Tancik et al. 2020\n (<https://dl.acm.org/doi/abs/10.5555/3495724.3496356>)\n and by Huang and Hoefler 2020 (<https://arxiv.org/abs/2210.12538>).",
"description": "Fourier network codec which trains and overfits a fourier feature neural\nnetwork on encoding and predicts during decoding.\n\nThe approach is based on the papers by Tancik et al. 2020\n(<https://dl.acm.org/doi/abs/10.5555/3495724.3496356>)\nand by Huang and Hoefler 2020 (<https://arxiv.org/abs/2210.12538>).",
"title": "FourierNetworkCodec",
"$schema": "https://json-schema.org/draft/2020-12/schema"
}
2 changes: 1 addition & 1 deletion codecs/jpeg2000/tests/schema.json
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Expand Up @@ -54,7 +54,7 @@
"description": "Lossless compression"
}
],
"description": "Codec providing compression using JPEG 2000.\n\n Arrays that are higher-dimensional than 2D are encoded by compressing each\n 2D slice with JPEG 2000 independently. Specifically, the array's shape is\n interpreted as `[.., height, width]`. If you want to compress 2D slices\n along two different axes, you can swizzle the array axes beforehand.",
"description": "Codec providing compression using JPEG 2000.\n\nArrays that are higher-dimensional than 2D are encoded by compressing each\n2D slice with JPEG 2000 independently. Specifically, the array's shape is\ninterpreted as `[.., height, width]`. If you want to compress 2D slices\nalong two different axes, you can swizzle the array axes beforehand.",
"properties": {
"_version": {
"type": "string",
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20 changes: 10 additions & 10 deletions codecs/pco/tests/schema.json
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Expand Up @@ -21,7 +21,7 @@
11,
12
],
"description": "Compression level, ranging from 0 (weak) over 8 (very good) to 12\n (expensive)"
"description": "Compression level, ranging from 0 (weak) over 8 (very good) to 12\n(expensive)"
},
"_version": {
"type": "string",
Expand All @@ -46,7 +46,7 @@
"required": [
"mode"
],
"description": "Automatically detects a good mode.\n\n This works well most of the time, but costs some compression time and\n can select a bad mode in adversarial cases."
"description": "Automatically detects a good mode.\n\nThis works well most of the time, but costs some compression time and\ncan select a bad mode in adversarial cases."
},
{
"type": "object",
Expand All @@ -63,7 +63,7 @@
},
{
"type": "object",
"description": "Tries using the `FloatMult` mode with a given base.\n\n Only applies to floating-point types.",
"description": "Tries using the `FloatMult` mode with a given base.\n\nOnly applies to floating-point types.",
"properties": {
"float_mult_base": {
"type": "number",
Expand All @@ -82,7 +82,7 @@
},
{
"type": "object",
"description": "Tries using the `FloatQuant` mode with the given number of bits of\n quantization.\n\n Only applies to floating-point types.",
"description": "Tries using the `FloatQuant` mode with the given number of bits of\nquantization.\n\nOnly applies to floating-point types.",
"properties": {
"float_quant_bits": {
"type": "integer",
Expand All @@ -102,7 +102,7 @@
},
{
"type": "object",
"description": "Tries using the `IntMult` mode with a given base.\n\n Only applies to integer types.",
"description": "Tries using the `IntMult` mode with a given base.\n\nOnly applies to integer types.",
"properties": {
"int_mult_base": {
"type": "integer",
Expand Down Expand Up @@ -135,7 +135,7 @@
"required": [
"delta"
],
"description": "Automatically detects a detects a good delta encoding.\n\n This works well most of the time, but costs some compression time and\n can select a bad delta encoding in adversarial cases."
"description": "Automatically detects a detects a good delta encoding.\n\nThis works well most of the time, but costs some compression time and\ncan select a bad delta encoding in adversarial cases."
},
{
"type": "object",
Expand All @@ -148,11 +148,11 @@
"required": [
"delta"
],
"description": "Never uses delta encoding.\n\n This is best if your data is in a random order or adjacent numbers have\n no relation to each other."
"description": "Never uses delta encoding.\n\nThis is best if your data is in a random order or adjacent numbers have\nno relation to each other."
},
{
"type": "object",
"description": "Tries taking nth order consecutive deltas.\n\n Supports a delta encoding order up to 7. For instance, 1st order is\n just regular delta encoding, 2nd is deltas-of-deltas, etc. It is legal\n to use 0th order, but it is identical to None.",
"description": "Tries taking nth order consecutive deltas.\n\nSupports a delta encoding order up to 7. For instance, 1st order is\njust regular delta encoding, 2nd is deltas-of-deltas, etc. It is legal\nto use 0th order, but it is identical to None.",
"properties": {
"delta_encoding_order": {
"type": "integer",
Expand Down Expand Up @@ -189,15 +189,15 @@
"required": [
"delta"
],
"description": "Tries delta encoding according to an extra latent variable of\n \"lookback\".\n\n This can improve compression ratio when there are nontrivial patterns\n in the array, but reduces compression speed substantially."
"description": "Tries delta encoding according to an extra latent variable of\n\"lookback\".\n\nThis can improve compression ratio when there are nontrivial patterns\nin the array, but reduces compression speed substantially."
}
]
}
],
"oneOf": [
{
"type": "object",
"description": "Divide the chunk into equal pages of up to this many numbers.\n\n For example, with equal pages up to 100,000, a chunk of 150,000 numbers\n would be divided into 2 pages, each of 75,000 numbers.",
"description": "Divide the chunk into equal pages of up to this many numbers.\n\nFor example, with equal pages up to 100,000, a chunk of 150,000 numbers\nwould be divided into 2 pages, each of 75,000 numbers.",
"properties": {
"equal_pages_up_to": {
"type": "integer",
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12 changes: 6 additions & 6 deletions codecs/random-projection/tests/schema.json
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Expand Up @@ -17,7 +17,7 @@
"required": [
"seed"
],
"description": "Codec that uses random projections to reduce the dimensionality of high-\n dimensional data to compress it.\n\n A two-dimensional array of shape `$N \\times D$` is encoded as n array of\n shape `$N \\times K$`, where `$K$` is either set explicitly or chosen using\n the the Johnson-Lindenstrauss lemma. For `$K$` to be smaller than `$D$`,\n `$D$` must be quite large. Therefore, this codec should only applied on\n large datasets as it otherwise significantly inflates the data size instead\n of reducing it.\n\n Choosing a lower distortion rate `epsilon` will improve the quality of the\n lossy compression, i.e. reduce the compression error, at the cost of\n increasing `$K$`.\n\n This codec only supports finite floating point data.",
"description": "Codec that uses random projections to reduce the dimensionality of high-\ndimensional data to compress it.\n\nA two-dimensional array of shape `$N \\times D$` is encoded as n array of\nshape `$N \\times K$`, where `$K$` is either set explicitly or chosen using\nthe the Johnson-Lindenstrauss lemma. For `$K$` to be smaller than `$D$`,\n`$D$` must be quite large. Therefore, this codec should only applied on\nlarge datasets as it otherwise significantly inflates the data size instead\nof reducing it.\n\nChoosing a lower distortion rate `epsilon` will improve the quality of the\nlossy compression, i.e. reduce the compression error, at the cost of\nincreasing `$K$`.\n\nThis codec only supports finite floating point data.",
"allOf": [
{
"oneOf": [
Expand All @@ -39,7 +39,7 @@
"reduction",
"epsilon"
],
"description": "The reduced dimensionality `$K$` is derived from `epsilon`, as defined\n by the Johnson-Lindenstrauss lemma."
"description": "The reduced dimensionality `$K$` is derived from `epsilon`, as defined\nby the Johnson-Lindenstrauss lemma."
},
{
"type": "object",
Expand All @@ -59,7 +59,7 @@
"reduction",
"k"
],
"description": "The reduced dimensionality `$K$`, to which the data is projected, is\n given explicitly."
"description": "The reduced dimensionality `$K$`, to which the data is projected, is\ngiven explicitly."
}
]
},
Expand All @@ -76,7 +76,7 @@
"required": [
"projection"
],
"description": "The random projection matrix is dense and its components are sampled\n from `$\\text{N}\\left( 0, \\frac{1}{k} \\right)$`"
"description": "The random projection matrix is dense and its components are sampled\nfrom `$\\text{N}\\left( 0, \\frac{1}{k} \\right)$`"
},
{
"type": "object",
Expand All @@ -88,7 +88,7 @@
],
"exclusiveMinimum": 0.0,
"maximum": 1.0,
"description": "The `density` of the sparse projection matrix.\n\n Setting `density` to `$\\frac{1}{3}$` reproduces the settings by\n Achlioptas [^1]. If `density` is `None`, it is set to\n `$\\frac{1}{\\sqrt{d}}$`,\n the minimum density as recommended by Li et al [^2].\n\n\n [^1]: Achlioptas, D. (2003). Database-friendly random projections:\n Johnson-Lindenstrauss with binary coins. *Journal of Computer\n and System Sciences*, 66(4), 671-687. Available from:\n [doi:10.1016/S0022-0000(03)00025-4](https://doi.org/10.1016/S0022-0000(03)00025-4).\n\n [^2]: Li, P., Hastie, T. J., and Church, K. W. (2006). Very sparse\n random projections. In *Proceedings of the 12th ACM SIGKDD\n international conference on Knowledge discovery and data\n mining (KDD '06)*. Association for Computing Machinery, New\n York, NY, USA, 287–296. Available from:\n [doi:10.1145/1150402.1150436](https://doi.org/10.1145/1150402.1150436)."
"description": "The `density` of the sparse projection matrix.\n\nSetting `density` to `$\\frac{1}{3}$` reproduces the settings by\nAchlioptas [^1]. If `density` is `None`, it is set to\n`$\\frac{1}{\\sqrt{d}}$`,\nthe minimum density as recommended by Li et al [^2].\n\n\n[^1]: Achlioptas, D. (2003). Database-friendly random projections:\n Johnson-Lindenstrauss with binary coins. *Journal of Computer\n and System Sciences*, 66(4), 671-687. Available from:\n [doi:10.1016/S0022-0000(03)00025-4](https://doi.org/10.1016/S0022-0000(03)00025-4).\n\n[^2]: Li, P., Hastie, T. J., and Church, K. W. (2006). Very sparse\n random projections. In *Proceedings of the 12th ACM SIGKDD\n international conference on Knowledge discovery and data\n mining (KDD '06)*. Association for Computing Machinery, New\n York, NY, USA, 287–296. Available from:\n [doi:10.1145/1150402.1150436](https://doi.org/10.1145/1150402.1150436)."
},
"projection": {
"type": "string",
Expand All @@ -98,7 +98,7 @@
"required": [
"projection"
],
"description": "The random projection matrix is sparse where only `density`% of entries\n are non-zero.\n\n The matrix's components are sampled from\n\n - `$-\\sqrt{\\frac{1}{k \\cdot density}}$` with probability\n `$0.5 \\cdot density$`\n - `$0$` with probability `$1 - density$`\n - `$+\\sqrt{\\frac{1}{k \\cdot density}}$` with probability\n `$0.5 \\cdot density$`"
"description": "The random projection matrix is sparse where only `density`% of entries\nare non-zero.\n\nThe matrix's components are sampled from\n\n- `$-\\sqrt{\\frac{1}{k \\cdot density}}$` with probability\n `$0.5 \\cdot density$`\n- `$0$` with probability `$1 - density$`\n- `$+\\sqrt{\\frac{1}{k \\cdot density}}$` with probability\n `$0.5 \\cdot density$`"
}
]
}
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2 changes: 1 addition & 1 deletion codecs/sperr/tests/schema.json
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Expand Up @@ -60,7 +60,7 @@
"description": "Fixed point-wise (absolute) error"
}
],
"description": "Codec providing compression using SPERR.\n\n Arrays that are higher-dimensional than 3D are encoded by compressing each\n 3D slice with SPERR independently. Specifically, the array's shape is\n interpreted as `[.., depth, height, width]`. If you want to compress 3D\n slices along three different axes, you can swizzle the array axes\n beforehand.",
"description": "Codec providing compression using SPERR.\n\nArrays that are higher-dimensional than 3D are encoded by compressing each\n3D slice with SPERR independently. Specifically, the array's shape is\ninterpreted as `[.., depth, height, width]`. If you want to compress 3D\nslices along three different axes, you can swizzle the array axes\nbeforehand.",
"properties": {
"_version": {
"type": "string",
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4 changes: 2 additions & 2 deletions codecs/sz3/tests/schema.json
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Expand Up @@ -121,7 +121,7 @@
"oneOf": [
{
"type": "object",
"description": "Errors are bounded by *both* the absolute and relative error, i.e. by\n whichever bound is stricter",
"description": "Errors are bounded by *both* the absolute and relative error, i.e. by\nwhichever bound is stricter",
"properties": {
"eb_abs": {
"type": "number",
Expand All @@ -146,7 +146,7 @@
},
{
"type": "object",
"description": "Errors are bounded by *either* the absolute or relative error, i.e. by\n whichever bound is weaker",
"description": "Errors are bounded by *either* the absolute or relative error, i.e. by\nwhichever bound is weaker",
"properties": {
"eb_abs": {
"type": "number",
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10 changes: 5 additions & 5 deletions codecs/zfp-classic/tests/schema.json
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Expand Up @@ -27,7 +27,7 @@
"min_exp": {
"type": "integer",
"format": "int32",
"description": "Smallest absolute bit plane number encoded.\n\n This parameter applies to floating-point data only and is ignored\n for integer data."
"description": "Smallest absolute bit plane number encoded.\n\nThis parameter applies to floating-point data only and is ignored\nfor integer data."
},
"mode": {
"type": "string",
Expand All @@ -44,7 +44,7 @@
},
{
"type": "object",
"description": "In fixed-rate mode, each d-dimensional compressed block of `$4^d$`\n values is stored using a fixed number of bits. This number of\n compressed bits per block is amortized over the `$4^d$` values to give\n a rate of `$rate = \\frac{maxbits}{4^d}$` in bits per value.",
"description": "In fixed-rate mode, each d-dimensional compressed block of `$4^d$`\nvalues is stored using a fixed number of bits. This number of\ncompressed bits per block is amortized over the `$4^d$` values to give\na rate of `$rate = \\frac{maxbits}{4^d}$` in bits per value.",
"properties": {
"rate": {
"type": "number",
Expand All @@ -63,7 +63,7 @@
},
{
"type": "object",
"description": "In fixed-precision mode, the number of bits used to encode a block may\n vary, but the number of bit planes (the precision) encoded for the\n transform coefficients is fixed.",
"description": "In fixed-precision mode, the number of bits used to encode a block may\nvary, but the number of bit planes (the precision) encoded for the\ntransform coefficients is fixed.",
"properties": {
"precision": {
"type": "integer",
Expand All @@ -83,7 +83,7 @@
},
{
"type": "object",
"description": "In fixed-accuracy mode, all transform coefficient bit planes up to a\n minimum bit plane number are encoded. The smallest absolute bit plane\n number is chosen such that\n `$minexp = \\text{floor}(\\log_{2}(tolerance))$`.",
"description": "In fixed-accuracy mode, all transform coefficient bit planes up to a\nminimum bit plane number are encoded. The smallest absolute bit plane\nnumber is chosen such that\n`$minexp = \\text{floor}(\\log_{2}(tolerance))$`.",
"properties": {
"tolerance": {
"type": "number",
Expand Down Expand Up @@ -111,7 +111,7 @@
"required": [
"mode"
],
"description": "Lossless per-block compression that preserves integer and floating point\n bit patterns."
"description": "Lossless per-block compression that preserves integer and floating point\nbit patterns."
}
],
"description": "Codec providing compression using ZFP (classic)",
Expand Down
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