Как узнать название таблицы sqlite3 python

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Python получает имя таблицы и имя поля таблицы базы данных sqlite3

При работе с базой данных sqlite3 в Python часто требуется использовать имя поля, однако использование оператора select для sqlite не возвращает набор данных словаря с именами полей, такими как базы данных, такие как MySql. Специально для незнакомой базы данных SQLite, если вам нужно использовать инструменты для просмотра при написании кода, на самом деле немного жаль Python.

Следующие два фрагмента кода могут легко получить список всех имен таблиц данных и имен полей в базе данных sqlite:

Получить имя таблицы из второй базы данных в sqlite, используя python

Я пытаюсь получить имена таблиц двух баз данных, используя python. Я получаю таблицы от первого db, но не от второго db. В каждой базе данных есть только одна таблица.

Он печатает таблицу из db1, но не из db2.

Любая помощь высоко ценится.

1 ответ

Вы должны повторить запрос для второй базы данных:

или объединить два:

(Обратите внимание, что если имя таблицы отличается в двух tblname данных, вашему следующему коду потребуется исправление, поскольку в этом tblname определено имя tblname и оно запоминает только последнее значение)

Как узнать название таблицы sqlite3 python

In this article, we will discuss how to list all the tables in the SQLite database using Python. Here, we will use the already created database table from SQLite. We will also learn exception handling during connecting to our database.

Database Used:

Steps to Fetch all tables using SQLite3 in Python

1. Creating a connection object using connect() method,

2. Created one SQLite query with which we will search a list of all tables which are present inside the sqlite3 database.

3. Using Connection Object, we are creating a cursor object.

4. Using execute() methods, we will execute the above SQL query.

5. Finally, We will print a list of all tables which are present inside the sqlite3 database.

sqlite3 — DB-API 2.0 interface for SQLite databases¶

SQLite is a C library that provides a lightweight disk-based database that doesn’t require a separate server process and allows accessing the database using a nonstandard variant of the SQL query language. Some applications can use SQLite for internal data storage. It’s also possible to prototype an application using SQLite and then port the code to a larger database such as PostgreSQL or Oracle.

The sqlite3 module was written by Gerhard Häring. It provides an SQL interface compliant with the DB-API 2.0 specification described by PEP 249, and requires SQLite 3.7.15 or newer.

This document includes four main sections:

Tutorial teaches how to use the sqlite3 module.

Reference describes the classes and functions this module defines.

How-to guides details how to handle specific tasks.

Explanation provides in-depth background on transaction control.

The SQLite web page; the documentation describes the syntax and the available data types for the supported SQL dialect.

Tutorial, reference and examples for learning SQL syntax.

PEP 249 — Database API Specification 2.0

PEP written by Marc-André Lemburg.

Tutorial¶

In this tutorial, you will create a database of Monty Python movies using basic sqlite3 functionality. It assumes a fundamental understanding of database concepts, including cursors and transactions.

First, we need to create a new database and open a database connection to allow sqlite3 to work with it. Call sqlite3.connect() to create a connection to the database tutorial.db in the current working directory, implicitly creating it if it does not exist:

The returned Connection object con represents the connection to the on-disk database.

In order to execute SQL statements and fetch results from SQL queries, we will need to use a database cursor. Call con.cursor() to create the Cursor :

Now that we’ve got a database connection and a cursor, we can create a database table movie with columns for title, release year, and review score. For simplicity, we can just use column names in the table declaration – thanks to the flexible typing feature of SQLite, specifying the data types is optional. Execute the CREATE TABLE statement by calling cur.execute(. ) :

We can verify that the new table has been created by querying the sqlite_master table built-in to SQLite, which should now contain an entry for the movie table definition (see The Schema Table for details). Execute that query by calling cur.execute(. ) , assign the result to res , and call res.fetchone() to fetch the resulting row:

We can see that the table has been created, as the query returns a tuple containing the table’s name. If we query sqlite_master for a non-existent table spam , res.fetchone() will return None :

Now, add two rows of data supplied as SQL literals by executing an INSERT statement, once again by calling cur.execute(. ) :

The INSERT statement implicitly opens a transaction, which needs to be committed before changes are saved in the database (see Transaction control for details). Call con.commit() on the connection object to commit the transaction:

We can verify that the data was inserted correctly by executing a SELECT query. Use the now-familiar cur.execute(. ) to assign the result to res , and call res.fetchall() to return all resulting rows:

The result is a list of two tuple s, one per row, each containing that row’s score value.

Now, insert three more rows by calling cur.executemany(. ) :

Notice that ? placeholders are used to bind data to the query. Always use placeholders instead of string formatting to bind Python values to SQL statements, to avoid SQL injection attacks (see How to use placeholders to bind values in SQL queries for more details).

We can verify that the new rows were inserted by executing a SELECT query, this time iterating over the results of the query:

Each row is a two-item tuple of (year, title) , matching the columns selected in the query.

Finally, verify that the database has been written to disk by calling con.close() to close the existing connection, opening a new one, creating a new cursor, then querying the database:

You’ve now created an SQLite database using the sqlite3 module, inserted data and retrieved values from it in multiple ways.

How-to guides for further reading:

• How to use placeholders to bind values in SQL queries

• How to adapt custom Python types to SQLite values

• How to convert SQLite values to custom Python types

• How to use the connection context manager

• How to create and use row factories

Explanation for in-depth background on transaction control.

Reference¶

Module functions¶

Open a connection to an SQLite database.

database ( path-like object ) – The path to the database file to be opened. Pass ":memory:" to open a connection to a database that is in RAM instead of on disk.

timeout (float) – How many seconds the connection should wait before raising an OperationalError when a table is locked. If another connection opens a transaction to modify a table, that table will be locked until the transaction is committed. Default five seconds.

detect_types (int) – Control whether and how data types not natively supported by SQLite are looked up to be converted to Python types, using the converters registered with register_converter() . Set it to any combination (using | , bitwise or) of PARSE_DECLTYPES and PARSE_COLNAMES to enable this. Column names takes precedence over declared types if both flags are set. Types cannot be detected for generated fields (for example max(data) ), even when the detect_types parameter is set; str will be returned instead. By default ( 0 ), type detection is disabled.

isolation_level (str | None) – The isolation_level of the connection, controlling whether and how transactions are implicitly opened. Can be "DEFERRED" (default), "EXCLUSIVE" or "IMMEDIATE" ; or None to disable opening transactions implicitly. See Transaction control for more.

check_same_thread (bool) – If True (default), ProgrammingError will be raised if the database connection is used by a thread other than the one that created it. If False , the connection may be accessed in multiple threads; write operations may need to be serialized by the user to avoid data corruption. See threadsafety for more information.

factory (Connection) – A custom subclass of Connection to create the connection with, if not the default Connection class.

cached_statements (int) – The number of statements that sqlite3 should internally cache for this connection, to avoid parsing overhead. By default, 128 statements.

Raises an auditing event sqlite3.connect with argument database .

Raises an auditing event sqlite3.connect/handle with argument connection_handle .

New in version 3.4: The uri parameter.

Changed in version 3.7: database can now also be a path-like object , not only a string.

New in version 3.10: The sqlite3.connect/handle auditing event.

Return True if the string statement appears to contain one or more complete SQL statements. No syntactic verification or parsing of any kind is performed, other than checking that there are no unclosed string literals and the statement is terminated by a semicolon.

This function may be useful during command-line input to determine if the entered text seems to form a complete SQL statement, or if additional input is needed before calling execute() .

sqlite3. enable_callback_tracebacks ( flag , / ) ¶

Enable or disable callback tracebacks. By default you will not get any tracebacks in user-defined functions, aggregates, converters, authorizer callbacks etc. If you want to debug them, you can call this function with flag set to True . Afterwards, you will get tracebacks from callbacks on sys.stderr . Use False to disable the feature again.

Register an unraisable hook handler for an improved debug experience:

Register an adapter callable to adapt the Python type type into an SQLite type. The adapter is called with a Python object of type type as its sole argument, and must return a value of a type that SQLite natively understands .

sqlite3. register_converter ( typename , converter , / ) ¶

Register the converter callable to convert SQLite objects of type typename into a Python object of a specific type. The converter is invoked for all SQLite values of type typename; it is passed a bytes object and should return an object of the desired Python type. Consult the parameter detect_types of connect() for information regarding how type detection works.

Note: typename and the name of the type in your query are matched case-insensitively.

Module constants¶

Pass this flag value to the detect_types parameter of connect() to look up a converter function by using the type name, parsed from the query column name, as the converter dictionary key. The type name must be wrapped in square brackets ( [] ).

This flag may be combined with PARSE_DECLTYPES using the | (bitwise or) operator.

Pass this flag value to the detect_types parameter of connect() to look up a converter function using the declared types for each column. The types are declared when the database table is created. sqlite3 will look up a converter function using the first word of the declared type as the converter dictionary key. For example:

This flag may be combined with PARSE_COLNAMES using the | (bitwise or) operator.

sqlite3. SQLITE_OK ¶ sqlite3. SQLITE_DENY ¶ sqlite3. SQLITE_IGNORE ¶

Flags that should be returned by the authorizer_callback callable passed to Connection.set_authorizer() , to indicate whether:

Access is allowed ( SQLITE_OK ),

The SQL statement should be aborted with an error ( SQLITE_DENY )

The column should be treated as a NULL value ( SQLITE_IGNORE )

String constant stating the supported DB-API level. Required by the DB-API. Hard-coded to "2.0" .

String constant stating the type of parameter marker formatting expected by the sqlite3 module. Required by the DB-API. Hard-coded to "qmark" .

The named DB-API parameter style is also supported.

Version number of the runtime SQLite library as a string .

Version number of the runtime SQLite library as a tuple of integers .

Integer constant required by the DB-API 2.0, stating the level of thread safety the sqlite3 module supports. This attribute is set based on the default threading mode the underlying SQLite library is compiled with. The SQLite threading modes are:

1. Single-thread: In this mode, all mutexes are disabled and SQLite is unsafe to use in more than a single thread at once.

2. Multi-thread: In this mode, SQLite can be safely used by multiple threads provided that no single database connection is used simultaneously in two or more threads.

3. Serialized: In serialized mode, SQLite can be safely used by multiple threads with no restriction.

The mappings from SQLite threading modes to DB-API 2.0 threadsafety levels are as follows: