[INFO] fetching crate smartnoise_validator 0.1.2... [INFO] checking smartnoise_validator-0.1.2 against try#8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8 for pr-82565 [INFO] extracting crate smartnoise_validator 0.1.2 into /workspace/builds/worker-5/source [INFO] validating manifest of crates.io crate smartnoise_validator 0.1.2 on toolchain 8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8 [INFO] running `Command { std: "/workspace/cargo-home/bin/cargo" "+8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8" "metadata" "--manifest-path" "Cargo.toml" "--no-deps", kill_on_drop: false }` [INFO] started tweaking crates.io crate smartnoise_validator 0.1.2 [INFO] finished tweaking crates.io crate smartnoise_validator 0.1.2 [INFO] tweaked toml for crates.io crate smartnoise_validator 0.1.2 written to /workspace/builds/worker-5/source/Cargo.toml [INFO] running `Command { std: "/workspace/cargo-home/bin/cargo" "+8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8" "generate-lockfile" "--manifest-path" "Cargo.toml" "-Zno-index-update", kill_on_drop: false }` [INFO] running `Command { std: "/workspace/cargo-home/bin/cargo" "+8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8" "fetch" "--locked" "--manifest-path" "Cargo.toml", kill_on_drop: false }` [INFO] [stderr] Downloading crates ... [INFO] [stderr] Downloaded ndarray-stats v0.3.0 [INFO] [stderr] Downloaded build-deps v0.1.4 [INFO] [stderr] Downloaded statrs v0.12.0 [INFO] [stderr] Downloaded noisy_float v0.1.15 [INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-5/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-5/source:/opt/rustwide/workdir:ro,Z" "-v" "/var/lib/crater-agent-workspace/cargo-home:/opt/rustwide/cargo-home:ro,Z" "-v" "/var/lib/crater-agent-workspace/rustup-home:/opt/rustwide/rustup-home:ro,Z" "-e" "SOURCE_DIR=/opt/rustwide/workdir" "-e" "CARGO_TARGET_DIR=/opt/rustwide/target" "-e" "CARGO_HOME=/opt/rustwide/cargo-home" "-e" "RUSTUP_HOME=/opt/rustwide/rustup-home" "-w" "/opt/rustwide/workdir" "-m" "1610612736" "--user" "0:0" "--network" "none" "rustops/crates-build-env@sha256:f2f6bcd4b43ebee4e173f653a26493129bdb64017c85f916b780ca7fbdbaa79d" "/opt/rustwide/cargo-home/bin/cargo" "+8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8" "metadata" "--no-deps" "--format-version=1", kill_on_drop: false }` [INFO] [stdout] 094e4718e5c05c2607db372724edcc3b62159b9ceec942fe38b06ba886197b08 [INFO] [stderr] WARNING: Your kernel does not support swap limit capabilities or the cgroup is not mounted. Memory limited without swap. [INFO] running `Command { std: "docker" "start" "-a" "094e4718e5c05c2607db372724edcc3b62159b9ceec942fe38b06ba886197b08", kill_on_drop: false }` [INFO] running `Command { std: "docker" "inspect" "094e4718e5c05c2607db372724edcc3b62159b9ceec942fe38b06ba886197b08", kill_on_drop: false }` [INFO] running `Command { std: "docker" "rm" "-f" "094e4718e5c05c2607db372724edcc3b62159b9ceec942fe38b06ba886197b08", kill_on_drop: false }` [INFO] [stdout] 094e4718e5c05c2607db372724edcc3b62159b9ceec942fe38b06ba886197b08 [INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-5/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-5/source:/opt/rustwide/workdir:ro,Z" "-v" "/var/lib/crater-agent-workspace/cargo-home:/opt/rustwide/cargo-home:ro,Z" "-v" "/var/lib/crater-agent-workspace/rustup-home:/opt/rustwide/rustup-home:ro,Z" "-e" "SOURCE_DIR=/opt/rustwide/workdir" "-e" "CARGO_TARGET_DIR=/opt/rustwide/target" "-e" "CARGO_INCREMENTAL=0" "-e" "RUST_BACKTRACE=full" "-e" "RUSTFLAGS=--cap-lints=forbid" "-e" "CARGO_HOME=/opt/rustwide/cargo-home" "-e" "RUSTUP_HOME=/opt/rustwide/rustup-home" "-w" "/opt/rustwide/workdir" "-m" "1610612736" "--user" "0:0" "--network" "none" "rustops/crates-build-env@sha256:f2f6bcd4b43ebee4e173f653a26493129bdb64017c85f916b780ca7fbdbaa79d" "/opt/rustwide/cargo-home/bin/cargo" "+8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8" "check" "--frozen" "--all" "--all-targets" "--message-format=json", kill_on_drop: false }` [INFO] [stdout] d06fc5ce012d1501979b85c26bfec45e6ac396895d45f7858a67645cb0c23887 [INFO] [stderr] WARNING: Your kernel does not support swap limit capabilities or the cgroup is not mounted. Memory limited without swap. [INFO] running `Command { std: "docker" "start" "-a" "d06fc5ce012d1501979b85c26bfec45e6ac396895d45f7858a67645cb0c23887", kill_on_drop: false }` [INFO] [stderr] Compiling autocfg v1.0.1 [INFO] [stderr] Compiling libc v0.2.88 [INFO] [stderr] Compiling proc-macro2 v1.0.24 [INFO] [stderr] Compiling unicode-xid v0.2.1 [INFO] [stderr] Compiling syn v1.0.64 [INFO] [stderr] Compiling either v1.6.1 [INFO] [stderr] Compiling anyhow v1.0.38 [INFO] [stderr] Compiling cfg-if v1.0.0 [INFO] [stderr] Compiling getrandom v0.2.2 [INFO] [stderr] Compiling ryu v1.0.5 [INFO] [stderr] Compiling getrandom v0.1.16 [INFO] [stderr] Compiling ppv-lite86 v0.2.10 [INFO] [stderr] Compiling hashbrown v0.9.1 [INFO] [stderr] Compiling log v0.4.14 [INFO] [stderr] Compiling serde_json v1.0.64 [INFO] [stderr] Compiling remove_dir_all v0.5.3 [INFO] [stderr] Compiling unicode-segmentation v1.7.1 [INFO] [stderr] Compiling glob v0.3.0 [INFO] [stderr] Checking gimli v0.23.0 [INFO] [stderr] Compiling itoa v0.4.7 [INFO] [stderr] Checking adler v1.0.2 [INFO] [stderr] Compiling version_check v0.9.2 [INFO] [stderr] Checking object v0.23.0 [INFO] [stderr] Checking rustc-demangle v0.1.18 [INFO] [stderr] Compiling itertools v0.8.2 [INFO] [stderr] Compiling itertools v0.9.0 [INFO] [stderr] Compiling build-deps v0.1.4 [INFO] [stderr] Compiling num-traits v0.2.14 [INFO] [stderr] Compiling num-integer v0.1.44 [INFO] [stderr] Compiling indexmap v1.6.2 [INFO] [stderr] Compiling miniz_oxide v0.4.4 [INFO] [stderr] Compiling num-complex v0.2.4 [INFO] [stderr] Compiling num-bigint v0.3.2 [INFO] [stderr] Compiling num-iter v0.1.42 [INFO] [stderr] Compiling num-rational v0.3.2 [INFO] [stderr] Compiling heck v0.3.2 [INFO] [stderr] Compiling error-chain v0.12.4 [INFO] [stderr] Compiling which v3.1.1 [INFO] [stderr] Compiling quote v1.0.9 [INFO] [stderr] Compiling rand_core v0.6.2 [INFO] [stderr] Compiling prost-build v0.6.1 [INFO] [stderr] Checking rand_core v0.5.1 [INFO] [stderr] Compiling rand_chacha v0.3.0 [INFO] [stderr] Checking rand_chacha v0.2.2 [INFO] [stderr] Checking noisy_float v0.1.15 [INFO] [stderr] Checking num-complex v0.3.1 [INFO] [stderr] Checking rand v0.7.3 [INFO] [stderr] Compiling rand v0.8.3 [INFO] [stderr] Checking addr2line v0.14.1 [INFO] [stderr] Checking ndarray v0.13.1 [INFO] [stderr] Compiling tempfile v3.2.0 [INFO] [stderr] Checking statrs v0.12.0 [INFO] [stderr] Checking backtrace v0.3.56 [INFO] [stderr] Checking num v0.3.1 [INFO] [stderr] Compiling serde_derive v1.0.124 [INFO] [stderr] Compiling prost-derive v0.6.1 [INFO] [stderr] Compiling prost v0.6.1 [INFO] [stderr] Compiling prost-types v0.6.1 [INFO] [stderr] Compiling serde v1.0.124 [INFO] [stderr] Checking ndarray-stats v0.3.0 [INFO] [stderr] Compiling petgraph v0.5.1 [INFO] [stderr] Compiling smartnoise_validator v0.1.2 (/opt/rustwide/workdir) [INFO] [stderr] error: failed to run custom build command for `smartnoise_validator v0.1.2 (/opt/rustwide/workdir)` [INFO] [stderr] [INFO] [stderr] Caused by: [INFO] [stderr] process didn't exit successfully: `/opt/rustwide/target/debug/build/smartnoise_validator-5ea990bc3d77dcf8/build-script-main` (exit code: 101) [INFO] [stderr] --- stdout [INFO] [stderr] cargo:rerun-if-changed=prototypes [INFO] [stderr] cargo:rerun-if-changed=prototypes/api.proto [INFO] [stderr] cargo:rerun-if-changed=prototypes/base.proto [INFO] [stderr] cargo:rerun-if-changed=prototypes/components [INFO] [stderr] cargo:rerun-if-changed=prototypes/value.proto [INFO] [stderr] cargo:rerun-if-changed=prototypes/components [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Abs.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Add.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/And.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Bin.json_x [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Cast.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Clamp.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/ColumnBind.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Count.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Covariance.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/DPCount.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/DPCovariance.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/DPGumbelMedian.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/DPHistogram.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/DPLinearRegression.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/DPMaximum.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/DPMean.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/DPMedian.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/DPMinimum.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/DPQuantile.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/DPRawMoment.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/DPSum.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/DPVariance.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Digitize.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Divide.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Equal.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/ExponentialMechanism.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Filter.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/GaussianMechanism.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/GreaterThan.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Histogram.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Impute.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Index.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/LaplaceMechanism.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/LessThan.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Literal.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Log.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Map.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Materialize.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Maximum.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Mean.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Median.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Minimum.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Modulo.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Multiply.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Negate.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Negative.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Or.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Partition.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Power.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Quantile.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/RawMoment.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Reshape.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Resize.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/RowMax.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/RowMin.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/SimpleGeometricMechanism.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/SnappingMechanism.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Subtract.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Sum.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/TheilSen.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/ToBool.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/ToDataframe.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/ToFloat.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/ToInt.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/ToString.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Union.json [INFO] [stderr] cargo:rerun-if-changed=prototypes/components/Variance.json [INFO] [stderr] ComponentJSON { id: "Abs", name: "abs", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: None, proto_id: 0 } [INFO] [stderr] ComponentJSON { id: "Add", name: "add", arguments: {"left": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "right": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: None, proto_id: 1 } [INFO] [stderr] ComponentJSON { id: "Cast", name: "cast", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Data to be cast to another type.") }, "true_label": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Positive class (class to be mapped to `true`) for each column. Used only if casting to `bool`.") }, "lower": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Minimum allowable imputation value. Used only if casting to `i64`.") }, "upper": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Maximum allowable imputation value. Used only if casting to `i64`.") }}, options: {"atomic_type": ArgumentJSON { nature: None, type_value: None, type_proto: Some("string"), type_rust: Some("String"), default_rust: None, default_python: None, description: Some("Type to which data should be cast. One of [`string`, `int`, `bool`, `float`]") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: Some("Cast data to an atomic type."), proto_id: 4 } [INFO] [stderr] ComponentJSON { id: "Clamp", name: "clamp", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Data to be clamped.") }, "lower": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Desired lower bound for each column of the data. Used only if `categories` is `None`.") }, "upper": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Desired upper bound for each column of the data. Used only if `categories` is `None`.") }, "categories": ArgumentJSON { nature: None, type_value: Some("Jagged"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("The set of categories you want to be represented for each column of the data.") }, "null_value": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("The value to which elements not included in `categories` will be mapped for each column of the data. Used only if `categories` is not `None`.") }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Clamped data.") }, description: Some("Clamps data to the provided bounds.\n\nIf data are numeric, clamping maps elements outside of an interval `[lower, upper]` to the closer endpoint.\nIf data are categorical, clamping maps elements outside of the `categories` argument to the associated `null`.\nUsing clamp sets the `categories` property for the analysis with value `categories` plus `null_value` in the last position."), proto_id: 5 } [INFO] [stderr] ComponentJSON { id: "ColumnBind", name: "column_bind", arguments: {}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: Some("Bind arguments as columns of an array to produce a larger array"), proto_id: 68 } [INFO] [stderr] ComponentJSON { id: "Count", name: "count", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }}, options: {"distinct": ArgumentJSON { nature: None, type_value: None, type_proto: Some("bool"), type_rust: Some("bool"), default_rust: Some("false"), default_python: Some("False"), description: Some("Set to true for the number of unique members in the data.") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: Some("Returns the number of rows in the data."), proto_id: 6 } [INFO] [stderr] ComponentJSON { id: "Covariance", name: "covariance", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("2D data array used to construct covariance matrix.") }, "left": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Left data array used to calculate cross-covariance matrix. Used only if `data` not provided.") }, "right": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Right data array used to calculate cross-covariance matrix. Used only if `data` not provided.") }}, options: {"finite_sample_correction": ArgumentJSON { nature: None, type_value: None, type_proto: Some("bool"), type_rust: Some("bool"), default_rust: Some("true"), default_python: Some("True"), description: Some("Whether or not to use the finite sample correction (Bessel\'s correction).") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Flattened covariance or cross-covariance matrix.") }, description: Some("Calculate covariance.\n\nIf `data` argument is provided as a 2D array, calculate covariance matrix. Otherwise, `left` and `right` 1D arrays are used to calculate a cross-covariance matrix between elements of the two arrays."), proto_id: 7 } [INFO] [stderr] ComponentJSON { id: "Digitize", name: "digitize", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Data to be binned.") }, "edges": ArgumentJSON { nature: None, type_value: Some("Jagged"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Values representing the edges of bins.") }, "null_value": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Value to which to map if there is no valid bin (e.g. if the element falls outside the bin range). The null value is the final category.") }, "inclusive_left": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: Some("True"), description: Some("Whether or not the left edge of the bin is inclusive, i.e. the bins are of the form [lower, upper).") }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: Some("Maps data to bins.\n\nBins will be of the form [lower, upper) or (lower, upper]. The null value is the final category."), proto_id: 19 } [INFO] [stderr] ComponentJSON { id: "Divide", name: "divide", arguments: {"left": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "right": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: None, proto_id: 20 } [INFO] [stderr] ComponentJSON { id: "DPCount", name: "dp_count", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "lower": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: Some("0"), description: Some("Estimated minimum possible value of the statistic. Useful to help bound elapsed time when sampling for the geometric mechanism. Required for the snapping mechanism.") }, "upper": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated maximum possible value of the statistic. Useful to help bound elapsed time when sampling for the geometric mechanism. Required for the snapping mechanism.") }}, options: {"distinct": ArgumentJSON { nature: None, type_value: None, type_proto: Some("bool"), type_rust: Some("bool"), default_rust: Some("false"), default_python: Some("False"), description: Some("Set to true for the number of unique members in the data.") }, "mechanism": ArgumentJSON { nature: None, type_value: None, type_proto: Some("string"), type_rust: Some("String"), default_rust: Some("String::from(\"SimpleGeometric\")"), default_python: Some("\"SimpleGeometric\""), description: Some("Privatizing mechanism to use. One of [`SimpleGeometric`, `Laplace`, `Snapping`, `Gaussian`, `AnalyticGaussian`]. Only `SimpleGeometric` is accepted if floating-point protections are enabled.") }, "privacy_usage": ArgumentJSON { nature: None, type_value: None, type_proto: Some("repeated PrivacyUsage"), type_rust: Some("Vec"), default_rust: None, default_python: Some("None"), description: Some("Object describing the type and amount of privacy to be used for the mechanism release.") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Differentially private row count.") }, description: Some("Returns a differentially private row count."), proto_id: 8 } [INFO] [stderr] ComponentJSON { id: "DPCovariance", name: "dp_covariance", arguments: {"left": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Left data array used to calculate cross-covariance matrix. Used only if `data` not provided.") }, "right": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Right data array used to calculate cross-covariance matrix. Used only if `data` not provided.") }, "data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("2D data array used to construct covariance matrix.") }, "lower": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated minimum possible value of the statistic. Only useful for the snapping mechanism.") }, "upper": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated maximum possible value of the statistic. Only useful for the snapping mechanism.") }}, options: {"mechanism": ArgumentJSON { nature: None, type_value: None, type_proto: Some("string"), type_rust: Some("String"), default_rust: Some("String::from(\"Automatic\")"), default_python: Some("\"Automatic\""), description: Some("Privatizing mechanism to use. One of [`Laplace`, `Snapping`, `Gaussian`, `AnalyticGaussian`]") }, "privacy_usage": ArgumentJSON { nature: None, type_value: None, type_proto: Some("repeated PrivacyUsage"), type_rust: Some("Vec"), default_rust: None, default_python: Some("None"), description: Some("Object describing the type and amount of privacy to be used for the mechanism release.") }, "finite_sample_correction": ArgumentJSON { nature: None, type_value: None, type_proto: Some("bool"), type_rust: Some("bool"), default_rust: Some("true"), default_python: Some("True"), description: Some("Whether or not to use the finite sample correction (Bessel\'s correction).") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Flattened covariance or cross-covariance matrix.") }, description: Some("Calculate differentially private covariance.\n\nIf `data` argument is provided as a 2D array, calculate covariance matrix. Otherwise, `left` and `right` 1D arrays are used to calculate a cross-covariance matrix between elements of the two arrays."), proto_id: 9 } [INFO] [stderr] ComponentJSON { id: "DPGumbelMedian", name: "dp_gumbel_median", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "r_lower": ArgumentJSON { nature: None, type_value: None, type_proto: Some("double"), type_rust: Some("f64"), default_rust: None, default_python: None, description: Some("Min candidate") }, "r_upper": ArgumentJSON { nature: None, type_value: None, type_proto: Some("double"), type_rust: Some("f64"), default_rust: None, default_python: None, description: Some("Max candidate") }, "enforce_constant_time": ArgumentJSON { nature: None, type_value: None, type_proto: Some("bool"), type_rust: Some("bool"), default_rust: Some("true"), default_python: Some("True"), description: Some("Enforce constant time for median") }}, options: {"privacy_usage": ArgumentJSON { nature: None, type_value: None, type_proto: Some("repeated PrivacyUsage"), type_rust: Some("Vec"), default_rust: None, default_python: Some("None"), description: Some("Object describing the type and amount of privacy to be used for the mechanism release.") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Differentially private estimates of the median of each column of the data.") }, description: Some("Returns differentially private estimates of the median of each column of the data."), proto_id: 66 } [INFO] [stderr] ComponentJSON { id: "DPHistogram", name: "dp_histogram", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "edges": ArgumentJSON { nature: None, type_value: Some("Jagged"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Set of edges to bin continuous-valued data. Used only if data are of `continuous` nature.") }, "categories": ArgumentJSON { nature: None, type_value: Some("Jagged"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Set of categories in data. Used only if data are of `categorical` nature.") }, "null_value": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("The value to which elements not included in `categories` will be mapped for each column of the data. Used only if `categories` is not `None`. The null value is the final category- counts for the null category are at the end of the vector of counts.") }, "lower": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: Some("0"), description: Some("Estimated minimum possible value of bin counts. Useful to help bound elapsed time when sampling for the geometric mechanism. Required for the snapping mechanism.") }, "upper": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated maximum possible value of bin counts. Useful to help bound elapsed time when sampling for the geometric mechanism. Required for the snapping mechanism.") }, "inclusive_left": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: Some("True"), description: Some("Whether or not the left edge of the bin is inclusive. If `true` bins are of the form [lower, upper). Otherwise, bins are of the form (lower, upper]. Used only if data are of `continuous` nature.") }}, options: {"mechanism": ArgumentJSON { nature: None, type_value: None, type_proto: Some("string"), type_rust: Some("String"), default_rust: Some("String::from(\"SimpleGeometric\")"), default_python: Some("\"SimpleGeometric\""), description: Some("Privatizing mechanism to use. One of [`SimpleGeometric`, `Laplace`, `Snapping`, `Gaussian`, `AnalyticGaussian`]. Only `SimpleGeometric` is accepted if floating-point protections are enabled.") }, "privacy_usage": ArgumentJSON { nature: None, type_value: None, type_proto: Some("repeated PrivacyUsage"), type_rust: Some("Vec"), default_rust: None, default_python: Some("None"), description: Some("Object describing the type and amount of privacy to be used for the mechanism release.") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Differentially private histogram.") }, description: Some("Returns a differentially private histogram over user-defined categories. The final cell contains the counts for null values (outside the set of categories)."), proto_id: 10 } [INFO] [stderr] ComponentJSON { id: "DPLinearRegression", name: "dp_linear_regression", arguments: {"data_x": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Predictor variable") }, "data_y": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Target variable") }, "k": ArgumentJSON { nature: None, type_value: Some("Integer"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Number of matchings. Memory usage is quadratic in K.") }, "lower_slope": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated minimum possible value of the slope.") }, "upper_slope": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated maximum possible value of the slope.") }, "lower_intercept": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated minimum possible value of the intercept.") }, "upper_intercept": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated maximum possible value of the intercept.") }}, options: {"implementation": ArgumentJSON { nature: None, type_value: None, type_proto: Some("string"), type_rust: Some("String"), default_rust: Some("String::from(\"theil-sen-k-match\")"), default_python: Some("\"theil-sen-k-match\""), description: Some("Theil-Sen implementation to use. One of [`theil-sen`, `theil-sen-k-match`]") }, "privacy_usage": ArgumentJSON { nature: None, type_value: None, type_proto: Some("repeated PrivacyUsage"), type_rust: Some("Vec"), default_rust: None, default_python: Some("None"), description: Some("Object describing the type and amount of privacy to be used for the mechanism release.") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Differentially private estimate of the slope and intercept of the line fit to the data.") }, description: Some("Returns differentially private estimates of the slope and intercept."), proto_id: 67 } [INFO] [stderr] ComponentJSON { id: "DPMaximum", name: "dp_maximum", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "candidates": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Set from which the Exponential mechanism will return an element.") }, "lower": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated minimum possible value of the statistic. Only useful for the snapping mechanism.") }, "upper": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated maximum possible value of the statistic. Only useful for the snapping mechanism.") }}, options: {"mechanism": ArgumentJSON { nature: None, type_value: None, type_proto: Some("string"), type_rust: Some("String"), default_rust: Some("String::from(\"Automatic\")"), default_python: Some("\"Automatic\""), description: Some("Privatizing mechanism to use. One of [`Laplace`, `Snapping`, `Gaussian`, `AnalyticGaussian`]") }, "privacy_usage": ArgumentJSON { nature: None, type_value: None, type_proto: Some("repeated PrivacyUsage"), type_rust: Some("Vec"), default_rust: None, default_python: Some("None"), description: Some("Object describing the type and amount of privacy to be used for the mechanism release.") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Differentially private estimates of the maximum elements of the data.") }, description: Some("Returns differentially private estimates of the maximum elements of each column of the data."), proto_id: 11 } [INFO] [stderr] ComponentJSON { id: "DPMean", name: "dp_mean", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "lower": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated minimum possible value of the statistic. Only useful for the snapping mechanism.") }, "upper": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated maximum possible value of the statistic. Only useful for the snapping mechanism.") }}, options: {"implementation": ArgumentJSON { nature: None, type_value: None, type_proto: Some("string"), type_rust: Some("String"), default_rust: Some("String::from(\"resize\")"), default_python: Some("\"resize\""), description: Some("Privatizing algorithm to use. One of [`resize`, `plug-in`]") }, "mechanism": ArgumentJSON { nature: None, type_value: None, type_proto: Some("string"), type_rust: Some("String"), default_rust: Some("String::from(\"Automatic\")"), default_python: Some("\"Automatic\""), description: Some("Privatizing mechanism to use. One of [`Laplace`, `Snapping`, `Gaussian`, `AnalyticGaussian`]") }, "privacy_usage": ArgumentJSON { nature: None, type_value: None, type_proto: Some("repeated PrivacyUsage"), type_rust: Some("Vec"), default_rust: None, default_python: Some("None"), description: Some("Object describing the type and amount of privacy to be used for the mechanism release.") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Differentially private estimate of the mean of each column of the data.") }, description: Some("Returns differentially private estimates of the means of each column of the data."), proto_id: 12 } [INFO] [stderr] ComponentJSON { id: "DPMedian", name: "dp_median", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "candidates": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Set from which the Exponential mechanism will return an element.") }, "lower": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated minimum possible value of the statistic. Only useful for the snapping mechanism.") }, "upper": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated maximum possible value of the statistic. Only useful for the snapping mechanism.") }}, options: {"mechanism": ArgumentJSON { nature: None, type_value: None, type_proto: Some("string"), type_rust: Some("String"), default_rust: Some("String::from(\"Automatic\")"), default_python: Some("\'Automatic\'"), description: Some("Privatizing mechanism to use. One of [`Exponential`, `Laplace`, `Snapping`, `Gaussian`, `AnalyticGaussian`]") }, "privacy_usage": ArgumentJSON { nature: None, type_value: None, type_proto: Some("repeated PrivacyUsage"), type_rust: Some("Vec"), default_rust: None, default_python: Some("None"), description: Some("Object describing the type and amount of privacy to be used for the mechanism release.") }, "interpolation": ArgumentJSON { nature: None, type_value: None, type_proto: Some("string"), type_rust: Some("String"), default_rust: Some("String::from(\"midpoint\")"), default_python: Some("\"midpoint\""), description: Some("Interpolation strategy. One of [`lower`, `upper`, `midpoint`, `nearest`, `linear`]") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Differentially private estimates of the median of each column of the data.") }, description: Some("Returns differentially private estimates of the median of each column of the data."), proto_id: 13 } [INFO] [stderr] ComponentJSON { id: "DPMinimum", name: "dp_minimum", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "candidates": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Set from which the Exponential mechanism will return an element.") }, "lower": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated minimum possible value of the statistic. Only useful for the snapping mechanism.") }, "upper": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated maximum possible value of the statistic. Only useful for the snapping mechanism.") }}, options: {"mechanism": ArgumentJSON { nature: None, type_value: None, type_proto: Some("string"), type_rust: Some("String"), default_rust: Some("String::from(\"Automatic\")"), default_python: Some("\"Automatic\""), description: Some("Privatizing mechanism to use. One of [`Exponential`, `Laplace`, `Snapping`, `Gaussian`, `AnalyticGaussian`]") }, "privacy_usage": ArgumentJSON { nature: None, type_value: None, type_proto: Some("repeated PrivacyUsage"), type_rust: Some("Vec"), default_rust: None, default_python: Some("None"), description: Some("Object describing the type and amount of privacy to be used for the mechanism release.") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Differentially private estimates of the minimum elements of the data.") }, description: Some("Returns differentially private estimates of the minimum elements of each column of the data."), proto_id: 14 } [INFO] [stderr] ComponentJSON { id: "DPQuantile", name: "dp_quantile", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "candidates": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Set from which the Exponential mechanism will return an element.") }, "lower": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated minimum possible value of the statistic. Only useful for the snapping mechanism.") }, "upper": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated maximum possible value of the statistic. Only useful for the snapping mechanism.") }}, options: {"alpha": ArgumentJSON { nature: None, type_value: None, type_proto: Some("double"), type_rust: Some("f64"), default_rust: None, default_python: None, description: Some("Desired quantiles, defined on `[0,1]`.") }, "mechanism": ArgumentJSON { nature: None, type_value: None, type_proto: Some("string"), type_rust: Some("String"), default_rust: Some("String::from(\"Automatic\")"), default_python: Some("\"Automatic\""), description: Some("Privatizing mechanism to use. One of [`Exponential`, `Laplace`, `Snapping`, `Gaussian`, `AnalyticGaussian`]") }, "privacy_usage": ArgumentJSON { nature: None, type_value: None, type_proto: Some("repeated PrivacyUsage"), type_rust: Some("Vec"), default_rust: None, default_python: Some("None"), description: Some("Object describing the type and amount of privacy to be used for the mechanism release.") }, "interpolation": ArgumentJSON { nature: None, type_value: None, type_proto: Some("string"), type_rust: Some("String"), default_rust: Some("String::from(\"midpoint\")"), default_python: Some("\"midpoint\""), description: Some("Interpolation strategy. One of [`lower`, `upper`, `midpoint`, `nearest`, `linear`]") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Differentially private estimates of the median of each column of the data.") }, description: Some("Returns differentially private estimates of the median of each column of the data."), proto_id: 16 } [INFO] [stderr] ComponentJSON { id: "DPRawMoment", name: "dp_raw_moment", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "lower": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated minimum possible value of the statistic. Only useful for the snapping mechanism.") }, "upper": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated maximum possible value of the statistic. Only useful for the snapping mechanism.") }}, options: {"order": ArgumentJSON { nature: None, type_value: None, type_proto: Some("uint32"), type_rust: Some("u32"), default_rust: None, default_python: None, description: Some("Integer statistical moment indicator.") }, "mechanism": ArgumentJSON { nature: None, type_value: None, type_proto: Some("string"), type_rust: Some("String"), default_rust: Some("String::from(\"Automatic\")"), default_python: Some("\"Automatic\""), description: Some("Privatizing mechanism to use. One of [`Laplace`, `Snapping`, `Gaussian`, `AnalyticGaussian`]") }, "privacy_usage": ArgumentJSON { nature: None, type_value: None, type_proto: Some("repeated PrivacyUsage"), type_rust: Some("Vec"), default_rust: None, default_python: Some("None"), description: Some("Object describing the type and amount of privacy to be used for the mechanism release.") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Sample estimate of raw moment for each column of the data.") }, description: Some("Returns sample estimate of a raw moment for each column of the data."), proto_id: 15 } [INFO] [stderr] ComponentJSON { id: "DPSum", name: "dp_sum", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "lower": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated minimum possible value of the statistic, on integral data. Useful to help bound elapsed time when sampling for the geometric mechanism. Useful for the snapping mechanism.") }, "upper": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated maximum possible value of the statistic, on integral data. Useful to help bound elapsed time when sampling for the geometric mechanism. Useful for the snapping mechanism.") }}, options: {"mechanism": ArgumentJSON { nature: None, type_value: None, type_proto: Some("string"), type_rust: Some("String"), default_rust: Some("String::from(\"Automatic\")"), default_python: Some("\"Automatic\""), description: Some("Privatizing mechanism to use. One of [`Automatic`, `Laplace`, `Snapping`, `Gaussian`, `AnalyticGaussian`, `SimpleGeometric`]. `Automatic` chooses based on the input data type.") }, "privacy_usage": ArgumentJSON { nature: None, type_value: None, type_proto: Some("repeated PrivacyUsage"), type_rust: Some("Vec"), default_rust: None, default_python: Some("None"), description: Some("Object describing the type and amount of privacy to be used for the mechanism release.") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Differentially private sum over elements for each column of the data.") }, description: Some("Returns differentially private estimates of the sums of each column of the data."), proto_id: 17 } [INFO] [stderr] ComponentJSON { id: "DPVariance", name: "dp_variance", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "lower": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated minimum possible value of the statistic. Only useful for the snapping mechanism.") }, "upper": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated maximum possible value of the statistic. Only useful for the snapping mechanism.") }}, options: {"mechanism": ArgumentJSON { nature: None, type_value: None, type_proto: Some("string"), type_rust: Some("String"), default_rust: Some("String::from(\"Automatic\")"), default_python: Some("\"Automatic\""), description: Some("Privatizing mechanism to use. One of [`Laplace`, `Snapping`, `Gaussian`, `AnalyticGaussian`]") }, "privacy_usage": ArgumentJSON { nature: None, type_value: None, type_proto: Some("repeated PrivacyUsage"), type_rust: Some("Vec"), default_rust: None, default_python: Some("None"), description: Some("Object describing the type and amount of privacy to be used for the mechanism release.") }, "finite_sample_correction": ArgumentJSON { nature: None, type_value: None, type_proto: Some("bool"), type_rust: Some("bool"), default_rust: Some("true"), default_python: Some("True"), description: Some("Whether or not to use the finite sample correction (Bessel\'s correction).") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Differentially private sample variance for each column of the data.") }, description: Some("Returns a differentially private estimate of the variance for each column of the data."), proto_id: 18 } [INFO] [stderr] ComponentJSON { id: "Equal", name: "equal", arguments: {"left": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "right": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: None, proto_id: 21 } [INFO] [stderr] ComponentJSON { id: "ExponentialMechanism", name: "exponential_mechanism", arguments: {"utilities": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Respective scores for each candidate.") }, "candidates": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Set from which the Exponential mechanism will return an element.") }}, options: {"privacy_usage": ArgumentJSON { nature: None, type_value: None, type_proto: Some("repeated PrivacyUsage"), type_rust: Some("Vec"), default_rust: None, default_python: Some("None"), description: Some("Object describing the type and amount of privacy to be used for the mechanism release.") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Element from the candidate set selected via the Exponential mechanism.") }, description: Some("Returns an element from a finite set with probability relative to its utility."), proto_id: 22 } [INFO] [stderr] ComponentJSON { id: "Filter", name: "filter", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "mask": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Boolean mask giving whether or not each row should be kept.") }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Data with only the desired rows.") }, description: Some("Filters data down into only the desired rows."), proto_id: 23 } [INFO] [stderr] ComponentJSON { id: "GaussianMechanism", name: "gaussian_mechanism", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Result to be released privately via the Gaussian mechanism.") }}, options: {"privacy_usage": ArgumentJSON { nature: None, type_value: None, type_proto: Some("repeated PrivacyUsage"), type_rust: Some("Vec"), default_rust: None, default_python: Some("None"), description: Some("Object describing the type and amount of privacy to be used for the mechanism release.") }, "analytic": ArgumentJSON { nature: None, type_value: None, type_proto: Some("bool"), type_rust: Some("bool"), default_rust: Some("true"), default_python: Some("True"), description: Some("Set to enable use of the analytic gaussian mechanism.") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Original data perturbed with Gaussian noise.") }, description: Some("Privatizes a result by returning it perturbed with Gaussian noise."), proto_id: 24 } [INFO] [stderr] ComponentJSON { id: "GreaterThan", name: "greater_than", arguments: {"left": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "right": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: None, proto_id: 25 } [INFO] [stderr] ComponentJSON { id: "Histogram", name: "histogram", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "edges": ArgumentJSON { nature: None, type_value: Some("Jagged"), type_proto: None, type_rust: None, default_rust: None, default_python: Some("None"), description: Some("Set of edges to bin continuous-valued data. Used only if data are of `continuous` nature.") }, "categories": ArgumentJSON { nature: None, type_value: Some("Jagged"), type_proto: None, type_rust: None, default_rust: None, default_python: Some("None"), description: Some("Set of categories in data. Used only if data are of `categorical` nature.") }, "null_value": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: Some("None"), description: Some("The value to which elements not included in `categories` will be mapped for each column of the data. Used only if `categories` is not `None`.") }, "inclusive_left": ArgumentJSON { nature: None, type_value: None, type_proto: Some("bool"), type_rust: None, default_rust: None, default_python: Some("True"), description: Some("Whether or not the left edge of the bin is inclusive. If `true` bins are of the form [lower, upper). Otherwise, bins are of the form (lower, upper]. Used only if data are of `continuous` nature.") }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: None, proto_id: 26 } [INFO] [stderr] ComponentJSON { id: "Impute", name: "impute", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("The data for which null values will be imputed.") }, "lower": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("A lower bound on data elements for each column. Used only if `categories` is `None`.") }, "upper": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("An upper bound on data elements for each column. Used only if `categories` is `None`.") }, "categories": ArgumentJSON { nature: None, type_value: Some("Jagged"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("The set of categories you want to be represented for each column of the data, if the data is categorical.") }, "null_values": ArgumentJSON { nature: None, type_value: Some("Jagged"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("The set of values that are considered null for each column of the data, if the data is categorical.") }, "weights": ArgumentJSON { nature: None, type_value: Some("Jagged"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Optional. The weight of each category when imputing. Uniform weights are used if not specified.") }, "distribution": ArgumentJSON { nature: None, type_value: Some("String"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("The distribution to be used when imputing records. Used only if `categories` is `None`.") }, "shift": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("The expectation of the Gaussian distribution to be used for imputation. Used only if `distribution` is `Gaussian`.") }, "scale": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("The standard deviation of the Gaussian distribution to be used for imputation. Used only if `distribution` is `Gaussian`.") }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Data with null values replaced by imputed values.") }, description: Some("Replaces null values with draws from a specified distribution.\n\nIf the `categories` argument is provided, the data are considered to be categorical regardless of atomic type and the elements provided in `null_value` will be replaced with those in `categories` according to `weights`.\n\nIf the `categories` argument is not provided, the data are considered to be numeric and elements that are `f64::NAN` will be replaced according to the specified distribution."), proto_id: 27 } [INFO] [stderr] ComponentJSON { id: "Index", name: "index", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Indexmap"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "names": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: Some("None"), description: None }, "indices": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: Some("None"), description: None }, "mask": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: Some("None"), description: None }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: Some("Index into data frames, partitions and arrays to retrieve homogeneously typed contiguous arrays"), proto_id: 28 } [INFO] [stderr] ComponentJSON { id: "LaplaceMechanism", name: "laplace_mechanism", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("True value to be released privately via the Laplace mechanism.") }}, options: {"privacy_usage": ArgumentJSON { nature: None, type_value: None, type_proto: Some("repeated PrivacyUsage"), type_rust: Some("Vec"), default_rust: None, default_python: Some("None"), description: Some("Object describing the type and amount of privacy to be used for the mechanism release.") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Original data perturbed with Laplace noise.") }, description: Some("Privatizes a result by returning it perturbed with Laplace noise."), proto_id: 30 } [INFO] [stderr] ComponentJSON { id: "LessThan", name: "less_than", arguments: {"left": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "right": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: None, proto_id: 31 } [INFO] [stderr] ComponentJSON { id: "Literal", name: "literal", arguments: {}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: None, proto_id: 32 } [INFO] [stderr] ComponentJSON { id: "Log", name: "log", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "base": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: Some("2.71828"), description: None }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: None, proto_id: 33 } [INFO] [stderr] ComponentJSON { id: "And", name: "logical_and", arguments: {"left": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "right": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: None, proto_id: 2 } [INFO] [stderr] ComponentJSON { id: "Or", name: "logical_or", arguments: {"left": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "right": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: None, proto_id: 44 } [INFO] [stderr] ComponentJSON { id: "Map", name: "map", arguments: {}, options: {"component": ArgumentJSON { nature: None, type_value: None, type_proto: Some("Component"), type_rust: Some("proto::Component"), default_rust: None, default_python: None, description: None }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Indexmap"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: Some("Apply Component to each data partition."), proto_id: 34 } [INFO] [stderr] ComponentJSON { id: "Materialize", name: "materialize", arguments: {"column_names": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }}, options: {"public": ArgumentJSON { nature: None, type_value: None, type_proto: Some("bool"), type_rust: Some("bool"), default_rust: Some("false"), default_python: Some("False"), description: None }, "skip_row": ArgumentJSON { nature: None, type_value: None, type_proto: Some("bool"), type_rust: Some("bool"), default_rust: Some("true"), default_python: Some("True"), description: Some("when set, skip the first line (header) in a csv") }, "file_path": ArgumentJSON { nature: None, type_value: None, type_proto: Some("string"), type_rust: Some("String"), default_rust: None, default_python: None, description: Some("Path to the file on the system.") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Dataframe"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: Some("Load a tabular frame from a data source"), proto_id: 35 } [INFO] [stderr] ComponentJSON { id: "Maximum", name: "maximum", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Data for which you want the maximum value in each column.") }, "candidates": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Set from which the Exponential mechanism will return an element.") }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Maximum of each column in the data.") }, description: Some("Find the maximum value of each column in the data."), proto_id: 36 } [INFO] [stderr] ComponentJSON { id: "Mean", name: "mean", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Arithmetic mean for each column of the data in question.") }, description: Some("Calculates the arithmetic mean of each column in the provided data."), proto_id: 37 } [INFO] [stderr] ComponentJSON { id: "Median", name: "median", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Data for which you want the median value in each column.") }, "candidates": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Set from which to compute scores for the Exponential mechanism.") }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Median of each column in the data.") }, description: Some("Find the median value of each column in the data."), proto_id: 63 } [INFO] [stderr] ComponentJSON { id: "Minimum", name: "minimum", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Data for which you want the maximum value in each column.") }, "candidates": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Set from which the Exponential mechanism will return an element.") }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Maximum of each column in the data.") }, description: Some("Find the minimum value of each column in the data."), proto_id: 39 } [INFO] [stderr] ComponentJSON { id: "Modulo", name: "modulo", arguments: {"left": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "right": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: None, proto_id: 40 } [INFO] [stderr] ComponentJSON { id: "Multiply", name: "multiply", arguments: {"left": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "right": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: None, proto_id: 41 } [INFO] [stderr] ComponentJSON { id: "Negate", name: "negate", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: None, proto_id: 42 } [INFO] [stderr] ComponentJSON { id: "Negative", name: "negative", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: None, proto_id: 43 } [INFO] [stderr] ComponentJSON { id: "Partition", name: "partition", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "num_partitions": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: None }, "by": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: None }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Indexmap"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: Some("Split the rows of data into either into k equally sized partitions, or by the categories of a vector"), proto_id: 45 } [INFO] [stderr] ComponentJSON { id: "Power", name: "power", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "radical": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: None, proto_id: 46 } [INFO] [stderr] ComponentJSON { id: "Quantile", name: "quantile", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "candidates": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Set from which the Exponential mechanism will return an element.") }}, options: {"alpha": ArgumentJSON { nature: None, type_value: None, type_proto: Some("double"), type_rust: Some("f64"), default_rust: None, default_python: None, description: Some("Desired quantiles, defined on `[0,1]`.") }, "interpolation": ArgumentJSON { nature: None, type_value: None, type_proto: Some("string"), type_rust: Some("String"), default_rust: Some("String::from(\"midpoint\")"), default_python: Some("\"midpoint\""), description: Some("Interpolation strategy. One of [`lower`, `upper`, `midpoint`, `nearest`, `linear`]") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Quantile values for each column.") }, description: Some("Get values corresponding to specified quantiles for each column of the data."), proto_id: 47 } [INFO] [stderr] ComponentJSON { id: "RawMoment", name: "raw_moment", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Data for which you would like the kth raw moments.") }}, options: {"order": ArgumentJSON { nature: None, type_value: None, type_proto: Some("uint32"), type_rust: Some("u32"), default_rust: None, default_python: None, description: Some("Indicate the kth integer statistical moment.") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("kth raw sample moment for each column.") }, description: Some("Returns sample estimate of kth raw moment for each column of the data."), proto_id: 29 } [INFO] [stderr] ComponentJSON { id: "Reshape", name: "reshape", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Vector of data to stack into a matrix. A Indexmap of matrices will be emitted if multiple rows are provided.") }}, options: {"symmetric": ArgumentJSON { nature: None, type_value: None, type_proto: Some("bool"), type_rust: Some("bool"), default_rust: Some("false"), default_python: Some("False"), description: Some("Set if data are elements from the upper triangle of a symmetric matrix.") }, "layout": ArgumentJSON { nature: None, type_value: None, type_proto: Some("string"), type_rust: Some("String"), default_rust: Some("String::from(\"row\")"), default_python: Some("\'row\'"), description: Some("Consecutive elements of either the `row` or `column` reside next to each other.") }, "shape": ArgumentJSON { nature: None, type_value: None, type_proto: Some("repeated uint32"), type_rust: Some("Vec"), default_rust: None, default_python: None, description: Some("The shape of the output matrix.") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Reshape of data.") }, description: Some("Reshapes a row vector into a matrix."), proto_id: 49 } [INFO] [stderr] ComponentJSON { id: "Resize", name: "resize", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("The data to be resized.") }, "number_rows": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("An estimate of the number of rows in the data. This could be the guess of the user, or the result of a DP release.") }, "number_columns": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("An estimate of the number of columns in the data. This must be the guess of the user, if not previously known (optional).") }, "lower": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("A lower bound on data elements for each column.") }, "upper": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("An upper bound on data elements for each column.") }, "categories": ArgumentJSON { nature: None, type_value: Some("Jagged"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("The set of categories you want to be represented for each column of the data, if the data is categorical.") }, "weights": ArgumentJSON { nature: None, type_value: Some("Jagged"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Optional. The weight of each category when imputing. Uniform weights are used if not specified.") }, "distribution": ArgumentJSON { nature: None, type_value: Some("String"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("The distribution to be used when imputing records.") }, "shift": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("The expectation of the Gaussian distribution used for imputation (used only if `distribution = Gaussian`).") }, "scale": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("The standard deviation of the Gaussian distribution used for imputation (used only if `distribution = Gaussian`).") }, "sample_proportion": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("The proportion of underlying data that may be used to construct the new data. May be > 1.") }, "minimum_rows": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Only add synthetic data if the actual row count is less than this number. No sampling is performed. Cannot be set with `number_rows`") }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("A resized version of data consistent with the provided `n`") }, description: Some("Resizes the data in question to be consistent with a provided sample size, `n`.\n\nThe library does not, in general, assume that the sample size of the data being analyzed is known. This introduces a number of problems around how to calculate statistics that are a function of the sample size.\n\nTo address this problem, the library asks the user to provide `n`, an estimate of the true sample size based on their own beliefs about the data or a previous differentially private count of the number of rows in the data. This component then either subsamples or appends to the data in order to make it consistent with the provided `n`."), proto_id: 50 } [INFO] [stderr] ComponentJSON { id: "RowMax", name: "row_max", arguments: {"left": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "right": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: Some("Returns the maximum of the left and right arguments, per row."), proto_id: 51 } [INFO] [stderr] ComponentJSON { id: "RowMin", name: "row_min", arguments: {"left": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "right": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: Some("Returns the minimum of the left and right arguments, per row."), proto_id: 52 } [INFO] [stderr] ComponentJSON { id: "SimpleGeometricMechanism", name: "simple_geometric_mechanism", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Result to be released privately via the Geometric mechanism.") }, "lower": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: Some("None"), description: Some("Lower bound of the statistic to be privatized.") }, "upper": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: Some("None"), description: Some("Upper bound of the statistic to be privatized.") }}, options: {"privacy_usage": ArgumentJSON { nature: None, type_value: None, type_proto: Some("repeated PrivacyUsage"), type_rust: Some("Vec"), default_rust: None, default_python: Some("None"), description: Some("Object describing the type and amount of privacy to be used for the mechanism release.") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Original data perturbed with Geometric noise.") }, description: Some("Privatizes a result by returning it perturbed with Geometric noise."), proto_id: 53 } [INFO] [stderr] ComponentJSON { id: "SnappingMechanism", name: "snapping_mechanism", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Result to be released privately via the Snapping mechanism.") }, "lower": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated minimum possible value of the data. Only useful for the snapping mechanism.") }, "upper": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Estimated maximum possible value of the statistic. Only useful for the snapping mechanism.") }, "binding_probability": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: Some("None"), default_python: Some("None"), description: Some("Upper bound on probability that final clamp binds. Must be within [0, 1).") }}, options: {"privacy_usage": ArgumentJSON { nature: None, type_value: None, type_proto: Some("repeated PrivacyUsage"), type_rust: Some("Vec"), default_rust: None, default_python: Some("None"), description: Some("Object describing the type and amount of privacy to be used for the mechanism release.") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Original data perturbed via the Snapping mechanism.") }, description: Some("Privatizes a result by returning it perturbed via the Snapping mechanism."), proto_id: 64 } [INFO] [stderr] ComponentJSON { id: "Subtract", name: "subtract", arguments: {"left": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "right": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: None, proto_id: 55 } [INFO] [stderr] ComponentJSON { id: "Sum", name: "sum", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Data for which you want the sum of each column.") }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Sum of each column of the data.") }, description: Some("Calculates the sum of each column of the data."), proto_id: 56 } [INFO] [stderr] ComponentJSON { id: "TheilSen", name: "theil_sen", arguments: {"data_x": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "data_y": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }}, options: {"implementation": ArgumentJSON { nature: None, type_value: None, type_proto: Some("string"), type_rust: Some("String"), default_rust: Some("String::from(\"theil-sen-k-match\")"), default_python: Some("\"theil-sen-k-match\""), description: Some("Theil-Sen implementation to use. One of [`theil-sen`, `theil-sen-k-match`]") }, "k": ArgumentJSON { nature: None, type_value: None, type_proto: Some("uint32"), type_rust: Some("u32"), default_rust: Some("0"), default_python: Some("0"), description: Some("Number of trials to run for Theil-Sen K Match.") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("All slope and intercept estimates for point pairs") }, description: Some("Returns slope and intercept estimates for point pairs"), proto_id: 65 } [INFO] [stderr] ComponentJSON { id: "ToBool", name: "to_bool", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Data to be cast to another type.") }, "true_label": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Positive class (class to be mapped to `true`) for each column.") }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: Some("Cast data to a bool atomic type."), proto_id: 57 } [INFO] [stderr] ComponentJSON { id: "ToDataframe", name: "to_dataframe", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, "names": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Dataframe"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: Some("Name columns of an array to produce a Dataframe with the specified names"), proto_id: 48 } [INFO] [stderr] ComponentJSON { id: "ToFloat", name: "to_float", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Data to be cast to another type.") }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: Some("Cast data to a float atomic type."), proto_id: 58 } [INFO] [stderr] ComponentJSON { id: "ToInt", name: "to_int", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Data to be cast to another type.") }, "lower": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Minimum allowable imputation value. Integers cannot represent null, so values that cannot be parsed are imputed.") }, "upper": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Maximum allowable imputation value.") }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: Some("Cast data to a int atomic type."), proto_id: 59 } [INFO] [stderr] ComponentJSON { id: "ToString", name: "to_string", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Data to be cast to another type.") }}, options: {}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: Some("Cast data to a string atomic type."), proto_id: 60 } [INFO] [stderr] ComponentJSON { id: "Union", name: "union", arguments: {}, options: {"flatten": ArgumentJSON { nature: None, type_value: None, type_proto: Some("bool"), type_rust: Some("bool"), default_rust: None, default_python: Some("True"), description: Some("When set, the output is an array. When unset, the output is an indexmap of arrays.") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }, description: Some("Union the arrays in the arguments into one array."), proto_id: 62 } [INFO] [stderr] ComponentJSON { id: "Variance", name: "variance", arguments: {"data": ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: None }}, options: {"finite_sample_correction": ArgumentJSON { nature: None, type_value: None, type_proto: Some("bool"), type_rust: Some("bool"), default_rust: Some("true"), default_python: Some("True"), description: Some("Whether or not to use the finite sample correction (Bessel\'s correction).") }}, arg_return: ArgumentJSON { nature: None, type_value: Some("Array"), type_proto: None, type_rust: None, default_rust: None, default_python: None, description: Some("Sample variance for each column of the data.") }, description: Some("Calculates the sample variance for each column of the data."), proto_id: 61 } [INFO] [stderr] [INFO] [stderr] --- stderr [INFO] [stderr] thread 'main' panicked at 'called `Result::unwrap()` on an `Err` value: Os { code: 30, kind: Other, message: "Read-only file system" }', build/protobuf.rs:98:50 [INFO] [stderr] stack backtrace: [INFO] [stderr] 0: 0x5637c543eb20 - std::backtrace_rs::backtrace::libunwind::trace::h9d49145f95eb5894 [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/std/src/../../backtrace/src/backtrace/libunwind.rs:90:5 [INFO] [stderr] 1: 0x5637c543eb20 - std::backtrace_rs::backtrace::trace_unsynchronized::hab1d020365bb6864 [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/std/src/../../backtrace/src/backtrace/mod.rs:66:5 [INFO] [stderr] 2: 0x5637c543eb20 - std::sys_common::backtrace::_print_fmt::h7659588431e304bd [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/std/src/sys_common/backtrace.rs:67:5 [INFO] [stderr] 3: 0x5637c543eb20 - ::fmt::h09f4a9e3befae3c7 [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/std/src/sys_common/backtrace.rs:46:22 [INFO] [stderr] 4: 0x5637c545fcfc - core::fmt::write::hf3fdfde304b9a088 [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/core/src/fmt/mod.rs:1092:17 [INFO] [stderr] 5: 0x5637c543b412 - std::io::Write::write_fmt::h1cb850689c7116f0 [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/std/src/io/mod.rs:1568:15 [INFO] [stderr] 6: 0x5637c5440d65 - std::sys_common::backtrace::_print::hdbccd5aa093ba544 [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/std/src/sys_common/backtrace.rs:49:5 [INFO] [stderr] 7: 0x5637c5440d65 - std::sys_common::backtrace::print::hc639c4f320222558 [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/std/src/sys_common/backtrace.rs:36:9 [INFO] [stderr] 8: 0x5637c5440d65 - std::panicking::default_hook::{{closure}}::hdb012dd7a485bb5d [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/std/src/panicking.rs:208:50 [INFO] [stderr] 9: 0x5637c5440813 - std::panicking::default_hook::h75facbce77b6ba91 [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/std/src/panicking.rs:225:9 [INFO] [stderr] 10: 0x5637c5441501 - std::panicking::rust_panic_with_hook::hbcaa5de2cb5e22d5 [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/std/src/panicking.rs:591:17 [INFO] [stderr] 11: 0x5637c5441047 - std::panicking::begin_panic_handler::{{closure}}::h4ee6cde415c8f62d [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/std/src/panicking.rs:497:13 [INFO] [stderr] 12: 0x5637c543efdc - std::sys_common::backtrace::__rust_end_short_backtrace::h895319f2d3f611c0 [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/std/src/sys_common/backtrace.rs:141:18 [INFO] [stderr] 13: 0x5637c5440fa9 - rust_begin_unwind [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/std/src/panicking.rs:493:5 [INFO] [stderr] 14: 0x5637c545e221 - core::panicking::panic_fmt::h0123abb763a6e96f [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/core/src/panicking.rs:92:14 [INFO] [stderr] 15: 0x5637c545e043 - core::option::expect_none_failed::h9fff90ea7603aa1d [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/core/src/option.rs:1300:5 [INFO] [stderr] 16: 0x5637c52d9e2b - core::result::Result::unwrap::hca20e377716b1b4b [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/core/src/result.rs:1037:23 [INFO] [stderr] 17: 0x5637c52be519 - build_script_main::protobuf::build_protobuf::h931af295ad0d220b [INFO] [stderr] at /opt/rustwide/workdir/build/protobuf.rs:98:24 [INFO] [stderr] 18: 0x5637c52f7b71 - build_script_main::main::haf9b3129b8e7d1e1 [INFO] [stderr] at /opt/rustwide/workdir/build/main.rs:88:5 [INFO] [stderr] 19: 0x5637c52a670b - core::ops::function::FnOnce::call_once::ha9af10430c5afa54 [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/core/src/ops/function.rs:227:5 [INFO] [stderr] 20: 0x5637c528740e - std::sys_common::backtrace::__rust_begin_short_backtrace::hc16a9e4570afe6f2 [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/std/src/sys_common/backtrace.rs:125:18 [INFO] [stderr] 21: 0x5637c52ae3a1 - std::rt::lang_start::{{closure}}::h9ac5f22441828e97 [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/std/src/rt.rs:66:18 [INFO] [stderr] 22: 0x5637c544191a - core::ops::function::impls:: for &F>::call_once::h31ee16c075ae2d62 [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/core/src/ops/function.rs:259:13 [INFO] [stderr] 23: 0x5637c544191a - std::panicking::try::do_call::h3993344bf97066b6 [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/std/src/panicking.rs:379:40 [INFO] [stderr] 24: 0x5637c544191a - std::panicking::try::h09e523df7c9c2d28 [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/std/src/panicking.rs:343:19 [INFO] [stderr] 25: 0x5637c544191a - std::panic::catch_unwind::h9d4ddb10ebb815ff [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/std/src/panic.rs:431:14 [INFO] [stderr] 26: 0x5637c544191a - std::rt::lang_start_internal::hc92e27a69d75de2a [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/std/src/rt.rs:51:25 [INFO] [stderr] 27: 0x5637c52ae377 - std::rt::lang_start::hf16b5321690686ed [INFO] [stderr] at /rustc/8e3afc79c11f48cb3acd1be5b3b7de98fe3f93a8/library/std/src/rt.rs:65:5 [INFO] [stderr] 28: 0x5637c52fed0a - main [INFO] [stderr] 29: 0x7fa07350e0b3 - __libc_start_main [INFO] [stderr] 30: 0x5637c527d0de - _start [INFO] [stderr] 31: 0x0 - [INFO] running `Command { std: "docker" "inspect" "d06fc5ce012d1501979b85c26bfec45e6ac396895d45f7858a67645cb0c23887", kill_on_drop: false }` [INFO] running `Command { std: "docker" "rm" "-f" "d06fc5ce012d1501979b85c26bfec45e6ac396895d45f7858a67645cb0c23887", kill_on_drop: false }` [INFO] [stdout] d06fc5ce012d1501979b85c26bfec45e6ac396895d45f7858a67645cb0c23887