它不仅可以在给定的 csv 上运行 sql(在后台将其转换为 sqlite),还可以转换并插入到许多受支持的 sql 数据库之一!
这里有示例命令(也在csvsql_CDs_join.sh中):
csvsql --query 'SELECT CDTitle,Location,Artist FROM CDs JOIN Artists ON CDs.ArtistID=Artists.ArtistID JOIN Locations ON CDs.LocID = Locations.LocID' "$@"
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显示如何连接三个表(可在csv_dbs_examples中的csv_inputs中找到)。
(使用csvlook进行格式化也是csvkit的一部分)
$ csvlook csv_inputs/CDs.csv
| CDTitle | ArtistID | LocID |
| -------- | -------- | ----- |
| CDTitle1 | A1 | L1 |
| CDTitle2 | A1 | L2 |
| CDTitle3 | A2 | L1 |
| CDTitle4 | A2 | L2 |
$ csvlook csv_inputs/Artists.csv
| ArtistID | Artist |
| -------- | ------- |
| A1 | Artist1 |
| A2 | Artist2 |
$ csvlook csv_inputs/Locations.csv
| LocID | Location |
| ----- | --------- |
| L1 | Location1 |
| L2 | Location2 |
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$ csvsql --query 'SELECT CDTitle,Location,Artist FROM CDs JOIN Artists ON CDs.ArtistID=Artists.ArtistID JOIN Locations ON CDs.LocID = Locations.LocID' "$@" | csvlook
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生产:
| CDTitle | Location | Artist |
| -------- | --------- | ------- |
| CDTitle1 | Location1 | Artist1 |
| CDTitle2 | Location2 | Artist1 |
| CDTitle3 | Location1 | Artist2 |
| CDTitle4 | Location2 | Artist2 |
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看一下https://github.com/harelba/q,这是一个将文本视为数据库的 Python 工具。默认情况下,它使用空格来分隔字段,但该-d ,参数将允许它处理 CSV 文件。
或者,您可以将 CSV 文件导入 SQLite,然后对其运行 SQL 命令。这是可编写脚本的,需要付出一些努力。