PyArmor Documentation v8.5.10is organized 1.2. Installation 1.2.1. Prerequisite 1.2.2. Installation from PyPI 1.2.3. Using virtual environments 1.2.4. Installation from source 1.2.5. Installation in offline device 1.2.6. Termux from PyPI 1.2.2.1. Installed command 1.2.2.2. Start Pyarmor by Python interpreter 1.2.3. Using virtual environments 1.2.4. Installation from source 1.2.5. Installation in offline device 1.2.6. Termux arguments. C Function Conversion: Converts some Python functions to C functions and compiles them into machine instructions using high optimization options for irreversible obfuscation. Script Binding: Binds0 码力 | 193 页 | 154.05 KB | 1 年前3
PyArmor Documentation v8.1.9How the documentation is organized 1.2. Installation 1.2.1. Installation from PyPI 1.2.2. Using virtual environments 1.2.3. Installation from source 1.2.4. Run Pyarmor from Python script 1.2.5. Clean uninstallation from PyPI 1.2.1.1. Installed command 1.2.1.2. Start Pyarmor by Python interpreter 1.2.2. Using virtual environments 1.2.3. Installation from source 1.2.4. Run Pyarmor from Python script 1.2.5. Clean uninstallation arguments. C Function Conversion: Converts some Python functions to C functions and compiles them into machine instructions using high optimization options for irreversible obfuscation. Script Binding: Binds0 码力 | 131 页 | 111.00 KB | 1 年前3
Conda 24.5.x Documentationidentical conda environment on the same operating system platform, either on the same machine or on a different machine. Use the terminal for the following steps: 1. Run conda list --explicit to produce already in the spec. To use the spec file to create an identical environment on the same machine or another machine: conda create --name myenv --file spec-file.txt To use the spec file to install its listed minor release, use the conda install command instead: conda install python=3.10 Managing virtual packages "Virtual" packages are injected into the conda solver to allow real packages to depend on features0 码力 | 794 页 | 5.01 MB | 8 月前3
Conda 24.7.x Documentationidentical conda environment on the same operating system platform, either on the same machine or on a different machine. Use the terminal for the following steps: 1. Run conda list --explicit to produce already in the spec. To use the spec file to create an identical environment on the same machine or another machine: conda create --name myenv --file spec-file.txt To use the spec file to install its listed minor release, use the conda install command instead: conda install python=3.10 Managing virtual packages "Virtual" packages are injected into the conda solver to allow real packages to depend on features0 码力 | 808 页 | 4.97 MB | 8 月前3
Conda 24.3.x Documentationidentical conda environment on the same operating system platform, either on the same machine or on a different machine. Use the terminal for the following steps: 1. Run conda list --explicit to produce already in the spec. To use the spec file to create an identical environment on the same machine or another machine: conda create --name myenv --file spec-file.txt To use the spec file to install its listed minor release, use the conda install command instead: conda install python=3.10 Managing virtual packages "Virtual" packages are injected into the conda solver to allow real packages to depend on features0 码力 | 786 页 | 4.98 MB | 8 月前3
Conda 24.4.x Documentationidentical conda environment on the same operating system platform, either on the same machine or on a different machine. Use the terminal for the following steps: 1. Run conda list --explicit to produce already in the spec. To use the spec file to create an identical environment on the same machine or another machine: conda create --name myenv --file spec-file.txt To use the spec file to install its listed minor release, use the conda install command instead: conda install python=3.10 Managing virtual packages "Virtual" packages are injected into the conda solver to allow real packages to depend on features0 码力 | 786 页 | 4.99 MB | 8 月前3
Conda 24.1.x Documentationidentical conda environment on the same operating system platform, either on the same machine or on a different machine. Use the terminal for the following steps: 1. Run conda list --explicit to produce already in the spec. To use the spec file to create an identical environment on the same machine or another machine: conda create --name myenv --file spec-file.txt To use the spec file to install its listed minor release, use the conda install command instead: conda install python=3.10 Managing virtual packages "Virtual" packages are injected into the conda solver to allow real packages to depend on features0 码力 | 795 页 | 4.73 MB | 8 月前3
Conda 23.11.x Documentationconda environments usually contain the same subdirectories as the default environment. Virtual environments A virtual environment is a tool that helps to keep dependencies required by different projects contain per-project dependencies for them. Users can create virtual environments using one of several tools such as Pipenv or Poetry, or a conda virtual environ- ment. Pipenv and Poetry are based around Python's Python's built-in venv library, whereas conda has its own notion of virtual environments that is lower-level (Python itself is a dependency provided in conda environments). Scroll to the right in the table0 码力 | 781 页 | 4.79 MB | 8 月前3
Conda 23.9.x Documentationconda environments usually contain the same subdirectories as the default environment. Virtual environments A virtual environment is a tool that helps to keep dependencies required by different projects contain per-project dependencies for them. Users can create virtual environments using one of several tools such as Pipenv or Poetry, or a conda virtual environ- ment. Pipenv and Poetry are based around Python's notion of virtual environments that is lower-level (Python itself is a dependency provided in conda environments). Scroll to the right in the table below. Some other traits are: Python virtual environment0 码力 | 753 页 | 4.86 MB | 8 月前3
Conda 23.10.x Documentationconda environments usually contain the same subdirectories as the default environment. Virtual environments A virtual environment is a tool that helps to keep dependencies required by different projects contain per-project dependencies for them. Users can create virtual environments using one of several tools such as Pipenv or Poetry, or a conda virtual environ- ment. Pipenv and Poetry are based around Python's Python's built-in venv library, whereas conda has its own notion of virtual environments that is lower-level (Python itself is a dependency provided in conda environments). Scroll to the right in the table0 码力 | 773 页 | 5.05 MB | 8 月前3
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