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Results 1 - 4 of 4 for dnumerical (0.1 seconds)

  1. docs/pt/docs/tutorial/path-params-numeric-validations.md

    {* ../../docs_src/path_params_numeric_validations/tutorial003_an_py310.py hl[10] *}
    
    ## Validações numéricas: maior que ou igual { #number-validations-greater-than-or-equal }
    
    Com `Query` e `Path` (e outras que você verá depois) você pode declarar restrições numéricas.
    
    Aqui, com `ge=1`, `item_id` precisará ser um número inteiro “`g`reater than or `e`qual” a `1`.
    
    Created: Sun Apr 05 07:19:11 GMT 2026
    - Last Modified: Thu Mar 19 18:20:43 GMT 2026
    - 6.7K bytes
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  2. docs/es/docs/tutorial/path-params-numeric-validations.md

    {* ../../docs_src/path_params_numeric_validations/tutorial003_an_py310.py hl[10] *}
    
    ## Validaciones numéricas: mayor o igual { #number-validations-greater-than-or-equal }
    
    Con `Query` y `Path` (y otros que verás más adelante) puedes declarar restricciones numéricas.
    
    Aquí, con `ge=1`, `item_id` necesitará ser un número entero "`g`reater than or `e`qual" a `1`.
    
    Created: Sun Apr 05 07:19:11 GMT 2026
    - Last Modified: Thu Mar 19 18:15:55 GMT 2026
    - 6.4K bytes
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  3. android/guava/src/com/google/common/io/BaseEncoding.java

     * <td>1.60
     * <td>=
     * <td>Human-readable; no possibility of mixing up 0/O or 1/I. Defaults to upper case.
     * <tr>
     * <td>{@link #base32Hex()}
     * <td>0-9 A-V
     * <td>1.60
     * <td>=
     * <td>"Numerical" base 32; extended from the traditional hex alphabet. Defaults to upper case.
     * <tr>
     * <td>{@link #base64()}
     * <td>A-Z a-z 0-9 + /
     * <td>1.33
     * <td>=
     * <td>
     * <tr>
     * <td>{@link #base64Url()}
    Created: Fri Apr 03 12:43:13 GMT 2026
    - Last Modified: Tue Mar 17 16:45:58 GMT 2026
    - 41.6K bytes
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  4. RELEASE.md

      * Note that NumPy's type promotion rules have been changed(See [NEP 50](https://numpy.org/neps/nep-0050-scalar-promotion.html#nep50)for details). This may change the precision at which computations happen, leading either to type errors or to numerical changes to results.
      * Tensorflow will continue to support NumPy 1.26 until 2025, aligning with community standard deprecation timeline [here](https://scientific-python.org/specs/spec-0000/).
    
    * Hermetic CUDA support is added.
    Created: Tue Apr 07 12:39:13 GMT 2026
    - Last Modified: Mon Mar 30 18:31:38 GMT 2026
    - 746.5K bytes
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