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本次搜索耗时 1.199 秒，为您找到相关结果约 28 个.

  • epub文档 Django 2.2.x Documentation

    RunPython. Here’s an example of a non-atomic data migration that updates a large table in smaller batches: import uuid from django.db import migrations, transaction def gen_uuid(apps, schema_editor): objects with a manually set primary key can be inserted first. If you want to insert objects in batches without evaluating the entire generator at once, you can use this technique as long as the objects the database adapter using the fetchmany() method defined in PEP 249. SQLite can fetch results in batches using fetchmany(), but since SQLite doesn’t provide isolation between queries within a connection
    0 码力 | 2915 页 | 2.83 MB | 1 年前
    3

  • pdf文档 Django 2.2.x Documentation

    RunPython. Here’s an example of a non-atomic data migration that updates a large table in smaller batches: import uuid from django.db import migrations, transaction def gen_uuid(apps, schema_editor): objects with a manually set primary key can be inserted first. If you want to insert objects in batches without evaluating the entire generator at once, you can use this technique as long as the objects the database adapter using the fetchmany() method defined in PEP 249. SQLite can fetch results in batches using fetchmany(), but since SQLite doesn’t provide isolation between queries within a connection
    0 码力 | 2060 页 | 7.23 MB | 1 年前
    3

  • epub文档 Django 3.0.x Documentation

    RunPython. Here’s an example of a non-atomic data migration that updates a large table in smaller batches: import uuid from django.db import migrations, transaction def gen_uuid(apps, schema_editor): objects with a manually set primary key can be inserted first. If you want to insert objects in batches without evaluating the entire generator at once, you can use this technique as long as the objects the database adapter using the fetchmany() method defined in PEP 249. SQLite can fetch results in batches using fetchmany(), but since SQLite doesn’t provide isolation between queries within a connection
    0 码力 | 3085 页 | 2.95 MB | 1 年前
    3

  • pdf文档 Django 4.0.x Documentation

    RunPython. Here’s an example of a non-atomic data migration that updates a large table in smaller batches: import uuid from django.db import migrations, transaction def gen_uuid(apps, schema_editor): objects with a manually set primary key can be inserted first. If you want to insert objects in batches without evaluating the entire generator at once, you can use this technique as long as the objects the database adapter using the fetchmany() method defined in PEP 249. SQLite can fetch results in batches using fetchmany(), but since SQLite doesn’t provide isolation between queries within a connection
    0 码力 | 2248 页 | 7.90 MB | 1 年前
    3

  • pdf文档 Django 3.2.x Documentation

    RunPython. Here’s an example of a non-atomic data migration that updates a large table in smaller batches: import uuid from django.db import migrations, transaction def gen_uuid(apps, schema_editor): objects with a manually set primary key can be inserted first. If you want to insert objects in batches without evaluating the entire generator at once, you can use this technique as long as the objects the database adapter using the fetchmany() method defined in PEP 249. SQLite can fetch results in batches using fetchmany(), but since SQLite doesn’t provide isolation between queries within a connection
    0 码力 | 2199 页 | 7.89 MB | 1 年前
    3

  • pdf文档 Django 3.0.x Documentation

    RunPython. Here’s an example of a non-atomic data migration that updates a large table in smaller batches: import uuid from django.db import migrations, transaction def gen_uuid(apps, schema_editor): objects with a manually set primary key can be inserted first. If you want to insert objects in batches without evaluating the entire generator at once, you can use this technique as long as the objects the database adapter using the fetchmany() method defined in PEP 249. SQLite can fetch results in batches using fetchmany(), but since SQLite doesn’t provide isolation between queries within a connection
    0 码力 | 2002 页 | 6.73 MB | 1 年前
    3

  • pdf文档 Django 3.1.x Documentation

    RunPython. Here’s an example of a non-atomic data migration that updates a large table in smaller batches: import uuid from django.db import migrations, transaction def gen_uuid(apps, schema_editor): objects with a manually set primary key can be inserted first. If you want to insert objects in batches without evaluating the entire generator at once, you can use this technique as long as the objects the database adapter using the fetchmany() method defined in PEP 249. SQLite can fetch results in batches using fetchmany(), but since SQLite doesn’t provide isolation between queries within a connection
    0 码力 | 2053 页 | 6.92 MB | 1 年前
    3

  • epub文档 Django 4.2.x Documentation

    RunPython. Here’s an example of a non-atomic data migration that updates a large table in smaller batches: import uuid from django.db import migrations, transaction def gen_uuid(apps, schema_editor): objects with a manually set primary key can be inserted first. If you want to insert objects in batches without evaluating the entire generator at once, you can use this technique as long as the objects the database adapter using the fetchmany() method defined in PEP 249. SQLite can fetch results in batches using fetchmany(), but since SQLite doesn’t provide isolation between queries within a connection
    0 码力 | 3305 页 | 3.16 MB | 1 年前
    3

  • epub文档 Django 4.1.x Documentation

    RunPython. Here’s an example of a non-atomic data migration that updates a large table in smaller batches: import uuid from django.db import migrations, transaction def gen_uuid(apps, schema_editor): objects with a manually set primary key can be inserted first. If you want to insert objects in batches without evaluating the entire generator at once, you can use this technique as long as the objects the database adapter using the fetchmany() method defined in PEP 249. SQLite can fetch results in batches using fetchmany(), but since SQLite doesn’t provide isolation between queries within a connection
    0 码力 | 3240 页 | 3.13 MB | 1 年前
    3

  • epub文档 Django 4.0.x Documentation

    RunPython. Here’s an example of a non-atomic data migration that updates a large table in smaller batches: import uuid from django.db import migrations, transaction def gen_uuid(apps, schema_editor): objects with a manually set primary key can be inserted first. If you want to insert objects in batches without evaluating the entire generator at once, you can use this technique as long as the objects the database adapter using the fetchmany() method defined in PEP 249. SQLite can fetch results in batches using fetchmany(), but since SQLite doesn’t provide isolation between queries within a connection
    0 码力 | 3184 页 | 3.14 MB | 1 年前
    3
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