【python】【conda】【Commands 命令3】【conda create】创建新的conda环境

本文详细介绍了conda create命令的使用,包括如何创建新的conda环境、指定环境名称和路径,以及如何自定义渠道、调整求解器模式和设置安装选项。通过这个命令,你可以从指定的包列表中创建或更新环境,并了解如何控制网络选项和输出控制。

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目录

1 conda create

2 Positional Arguments

2 位置参数

3 Named Arguments 命名参数

--clone

--file

--dev

4 Target Environment Specification

4 目标环境规范编号

-n, --name

-p, --prefix

5 Channel Customization

5 渠道定制

-c, --channel

--use-local

--override-channels

--repodata-fn

--experimental

--no-lock

--repodata-use-zst, --no-repodata-use-zst

--subdir, --platform

6 Solver Mode Modifiers

6 求解器模式修改器

--strict-channel-priority

--no-channel-priority

--no-deps

--only-deps

--no-pin

--no-default-packages

--solver

7 Package Linking and Install-time Options

7 软件包链接和安装时选项#

--copy

--no-shortcuts

--shortcuts-only

8 Networking Options

8 网络选项

-C, --use-index-cache

-k, --insecure

--offline

9 Output, Prompt, and Flow Control Options

9 输出、提示和流控制选项

--json

-v, --verbose

-q, --quiet

-d, --dry-run

-y, --yes

--download-only

--show-channel-urls

10 Examples: 示例如下

1 conda create

Create a new conda environment from a list of specified packages.
从指定包的列表中创建新的conda环境。

To use the newly-created environment, use 'conda activate envname'. This command requires either the -n NAME or -p PREFIX option.
要使用新创建的环境,请使用“conda activate envname”。此命令需要-n NAME或-p PREFIX选项。

usage: conda create [-h] [--clone ENV] (-n ENVIRONMENT | -p PATH) [-c CHANNEL]
                    [--use-local] [--override-channels]
                    [--repodata-fn REPODATA_FNS] [--experimental {
        jlap,lock}]
                    [--no-lock] [--repodata-use-zst | --no-repodata-use-zst]
                    [--strict-channel-priority] [--no-channel-priority]
                    [--no-deps | --only-deps] [--no-pin] [--copy]
                    
### Conda Globe Package Installation and Usage Conda is an open-source package management system that simplifies the process of installing software packages and managing environments across various operating systems including Windows, macOS, and Linux[^2]. The `globe` package does not appear to be a standard or widely recognized package within the Anaconda distribution or broader Python ecosystem as indicated by available documentation on conda commands and package repositories[^3]. For any typical package installation using conda, one would use the following command structure: ```bash conda install -c channel_name package_name ``` However, since specific information about a `globe` package cannot be found through conventional sources related to conda, it suggests this might either be a custom-built package shared privately among users or teams, or there could have been confusion with another tool or library name. If intending to work with geographical data visualization which may involve terms like 'globe', libraries such as GeoPandas, Basemap toolkit for Matplotlib, Cartopy are more commonly used in conjunction with conda environment setup[^4]. #### Installing Geographical Data Visualization Libraries via Conda To set up an environment suitable for handling geographic datasets along with visualizations resembling globes, consider these examples: ```bash conda create --name geo_env python=3.9 geopandas basemap cartopy matplotlib pandas jupyterlab conda activate geo_env ``` This creates an isolated environment named `geo_env`, ensuring dependencies do not interfere with other projects while providing powerful tools tailored towards spatial analysis tasks involving map projections similar to what one might expect from interacting with globe representations.
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