%global _empty_manifest_terminate_build 0
Name:		python-aiochclient
Version:	2.3.1
Release:	1
Summary:	Async http clickhouse client for python 3.6+
License:	MIT
URL:		https://github.com/maximdanilchenko/aiochclient
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/5f/7b/269483fdb170c791a369a77a68271911d9aa1eda87726389733ae97337de/aiochclient-2.3.1.tar.gz
BuildArch:	noarch


%description
# aiochclient

[![PyPI version](https://badge.fury.io/py/aiochclient.svg)](https://badge.fury.io/py/aiochclient)
[![Travis CI](https://app.travis-ci.com/maximdanilchenko/aiochclient.svg?branch=master)](https://app.travis-ci.com/maximdanilchenko/aiochclient)
[![Documentation Status](https://readthedocs.org/projects/aiochclient/badge/?version=latest)](https://aiochclient.readthedocs.io/en/latest/?badge=latest)
[![codecov](https://codecov.io/gh/maximdanilchenko/aiochclient/branch/master/graph/badge.svg)](https://codecov.io/gh/maximdanilchenko/aiochclient)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black)

An async http(s) ClickHouse client for python 3.6+ supporting type
conversion in both directions, streaming, lazy decoding on select queries, and a
fully typed interface.

## Table of Contents

- [Installation](#installation)
- [Quick Start](#quick-start)
- [Documentation](#documentation)
- [Type Conversion](#type-conversion)
- [Connection Pool Settings](#connection-pool-settings)
- [Notes on Speed](#notes-on-speed)

## Installation
You can use it with either 
[aiohttp](https://github.com/aio-libs/aiohttp) or 
[httpx](https://github.com/encode/httpx) http connectors.

To use with `aiohttp` install it with command:
```
> pip install aiochclient[aiohttp]
```
Or `aiochclient[aiohttp-speedups]` to install with extra speedups.

To use with `httpx` install it with command:
```
> pip install aiochclient[httpx]
```
Or `aiochclient[httpx-speedups]` to install with extra speedups.

Installing with `[*-speedups]` adds the following:
- [cChardet](https://pypi.python.org/pypi/cchardet) for `aiohttp` speedup
- [aiodns](https://pypi.python.org/pypi/aiodns) for `aiohttp` speedup
- [ciso8601](https://github.com/closeio/ciso8601) for ultra-fast datetime 
  parsing while decoding data from ClickHouse for `aiohttp` and `httpx`.

Additionally the installation process attempts to use Cython for a speed boost
(roughly 30% faster).

## Quick Start

### Connecting to ClickHouse

`aiochclient` needs `aiohttp.ClientSession` or `httpx.AsyncClient` to connect to ClickHouse:

```python
from aiochclient import ChClient
from aiohttp import ClientSession


async def main():
    async with ClientSession() as s:
        client = ChClient(s)
        assert await client.is_alive()  # returns True if connection is Ok

```

### Querying the database

```python
await client.execute(
    "CREATE TABLE t (a UInt8, b Tuple(Date, Nullable(Float32))) ENGINE = Memory"
)
```

For INSERT queries you can pass values as `*args`. Values should be
iterables:
```python
await client.execute(
    "INSERT INTO t VALUES",
    (1, (dt.date(2018, 9, 7), None)),
    (2, (dt.date(2018, 9, 8), 3.14)),
)
```

For fetching all rows at once use the
[`fetch`](https://aiochclient.readthedocs.io/en/latest/api.html#aiochclient.ChClient.fetch)
method:
```python
all_rows = await client.fetch("SELECT * FROM t")
```

For fetching first row from result use the
[`fetchrow`](https://aiochclient.readthedocs.io/en/latest/api.html#aiochclient.ChClient.fetchrow)
method:
```python
row = await client.fetchrow("SELECT * FROM t WHERE a=1")

assert row[0] == 1
assert row["b"] == (dt.date(2018, 9, 7), None)
```

You can also use
[`fetchval`](https://aiochclient.readthedocs.io/en/latest/api.html#aiochclient.ChClient.fetchval)
method, which returns first value of the first row from query result:
```python
val = await client.fetchval("SELECT b FROM t WHERE a=2")

assert val == (dt.date(2018, 9, 8), 3.14)
```

With async iteration on the query results stream you can fetch multiple
rows without loading them all into memory at once:
```python
async for row in client.iterate(
    "SELECT number, number*2 FROM system.numbers LIMIT 10000"
):
    assert row[0] * 2 == row[1]
```

Use `fetch`/`fetchrow`/`fetchval`/`iterate` for SELECT queries and `execute` or
any of last for INSERT and all another queries.

### Working with query results

All fetch queries return rows as lightweight, memory efficient objects. _Before
v`1.0.0` rows were only returned as tuples._ All rows have a full mapping interface, where you can
get fields by names or indexes:
```python
row = await client.fetchrow("SELECT a, b FROM t WHERE a=1")

assert row["a"] == 1
assert row[0] == 1
assert row[:] == (1, (dt.date(2018, 9, 8), 3.14))
assert list(row.keys()) == ["a", "b"]
assert list(row.values()) == [1, (dt.date(2018, 9, 8), 3.14)]
```

## Documentation

To check out the [api docs](https://aiochclient.readthedocs.io/en/latest/api.html), 
visit the [readthedocs site.](https://aiochclient.readthedocs.io/en/latest/).

## Type Conversion

`aiochclient` automatically converts types from ClickHouse to python types and
vice-versa.

| ClickHouse type | Python type |
|:----------------|:------------|
| `UInt8` | `int` |
| `UInt16` | `int` |
| `UInt32` | `int` |
| `UInt64` | `int` |
| `Int8` | `int` |
| `Int16` | `int` |
| `Int32` | `int` |
| `Int64` | `int` |
| `Float32` | `float` |
| `Float64` | `float` |
| `String` | `str` |
| `FixedString` | `str` |
| `Enum8` | `str` |
| `Enum16` | `str` |
| `Date` | `datetime.date` |
| `DateTime` | `datetime.datetime` |
| `DateTime64` | `datetime.datetime` |
| `Decimal` | `decimal.Decimal` |
| `Decimal32` | `decimal.Decimal` |
| `Decimal64` | `decimal.Decimal` |
| `Decimal128` | `decimal.Decimal` |
| `IPv4` | `ipaddress.IPv4Address` |
| `IPv6` | `ipaddress.IPv6Address` |
| `UUID` | `uuid.UUID` |
| `Nothing` | `None` |
| `Tuple(T1, T2, ...)` | `Tuple[T1, T2, ...]` |
| `Array(T)` | `List[T]` |
| `Nullable(T)` | `None` or `T` |
| `LowCardinality(T)` | `T` |
| `Map(T1, T2)` | `Dict[T1, T2]` |

## Connection Pool Settings

`aiochclient` uses the
[aiohttp.TCPConnector](https://docs.aiohttp.org/en/stable/client_advanced.html#limiting-connection-pool-size)
to determine pool size.  By default, the pool limit is 100 open connections.

## Notes on Speed

It's highly recommended using `uvloop` and installing `aiochclient` with
speedups for the sake of speed. Some recent benchmarks on our
machines without parallelization:
- 180k-220k rows/sec on SELECT
- 50k-80k rows/sec on INSERT

_Note: these benchmarks are system dependent_


%package -n python3-aiochclient
Summary:	Async http clickhouse client for python 3.6+
Provides:	python-aiochclient
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-aiochclient
# aiochclient

[![PyPI version](https://badge.fury.io/py/aiochclient.svg)](https://badge.fury.io/py/aiochclient)
[![Travis CI](https://app.travis-ci.com/maximdanilchenko/aiochclient.svg?branch=master)](https://app.travis-ci.com/maximdanilchenko/aiochclient)
[![Documentation Status](https://readthedocs.org/projects/aiochclient/badge/?version=latest)](https://aiochclient.readthedocs.io/en/latest/?badge=latest)
[![codecov](https://codecov.io/gh/maximdanilchenko/aiochclient/branch/master/graph/badge.svg)](https://codecov.io/gh/maximdanilchenko/aiochclient)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black)

An async http(s) ClickHouse client for python 3.6+ supporting type
conversion in both directions, streaming, lazy decoding on select queries, and a
fully typed interface.

## Table of Contents

- [Installation](#installation)
- [Quick Start](#quick-start)
- [Documentation](#documentation)
- [Type Conversion](#type-conversion)
- [Connection Pool Settings](#connection-pool-settings)
- [Notes on Speed](#notes-on-speed)

## Installation
You can use it with either 
[aiohttp](https://github.com/aio-libs/aiohttp) or 
[httpx](https://github.com/encode/httpx) http connectors.

To use with `aiohttp` install it with command:
```
> pip install aiochclient[aiohttp]
```
Or `aiochclient[aiohttp-speedups]` to install with extra speedups.

To use with `httpx` install it with command:
```
> pip install aiochclient[httpx]
```
Or `aiochclient[httpx-speedups]` to install with extra speedups.

Installing with `[*-speedups]` adds the following:
- [cChardet](https://pypi.python.org/pypi/cchardet) for `aiohttp` speedup
- [aiodns](https://pypi.python.org/pypi/aiodns) for `aiohttp` speedup
- [ciso8601](https://github.com/closeio/ciso8601) for ultra-fast datetime 
  parsing while decoding data from ClickHouse for `aiohttp` and `httpx`.

Additionally the installation process attempts to use Cython for a speed boost
(roughly 30% faster).

## Quick Start

### Connecting to ClickHouse

`aiochclient` needs `aiohttp.ClientSession` or `httpx.AsyncClient` to connect to ClickHouse:

```python
from aiochclient import ChClient
from aiohttp import ClientSession


async def main():
    async with ClientSession() as s:
        client = ChClient(s)
        assert await client.is_alive()  # returns True if connection is Ok

```

### Querying the database

```python
await client.execute(
    "CREATE TABLE t (a UInt8, b Tuple(Date, Nullable(Float32))) ENGINE = Memory"
)
```

For INSERT queries you can pass values as `*args`. Values should be
iterables:
```python
await client.execute(
    "INSERT INTO t VALUES",
    (1, (dt.date(2018, 9, 7), None)),
    (2, (dt.date(2018, 9, 8), 3.14)),
)
```

For fetching all rows at once use the
[`fetch`](https://aiochclient.readthedocs.io/en/latest/api.html#aiochclient.ChClient.fetch)
method:
```python
all_rows = await client.fetch("SELECT * FROM t")
```

For fetching first row from result use the
[`fetchrow`](https://aiochclient.readthedocs.io/en/latest/api.html#aiochclient.ChClient.fetchrow)
method:
```python
row = await client.fetchrow("SELECT * FROM t WHERE a=1")

assert row[0] == 1
assert row["b"] == (dt.date(2018, 9, 7), None)
```

You can also use
[`fetchval`](https://aiochclient.readthedocs.io/en/latest/api.html#aiochclient.ChClient.fetchval)
method, which returns first value of the first row from query result:
```python
val = await client.fetchval("SELECT b FROM t WHERE a=2")

assert val == (dt.date(2018, 9, 8), 3.14)
```

With async iteration on the query results stream you can fetch multiple
rows without loading them all into memory at once:
```python
async for row in client.iterate(
    "SELECT number, number*2 FROM system.numbers LIMIT 10000"
):
    assert row[0] * 2 == row[1]
```

Use `fetch`/`fetchrow`/`fetchval`/`iterate` for SELECT queries and `execute` or
any of last for INSERT and all another queries.

### Working with query results

All fetch queries return rows as lightweight, memory efficient objects. _Before
v`1.0.0` rows were only returned as tuples._ All rows have a full mapping interface, where you can
get fields by names or indexes:
```python
row = await client.fetchrow("SELECT a, b FROM t WHERE a=1")

assert row["a"] == 1
assert row[0] == 1
assert row[:] == (1, (dt.date(2018, 9, 8), 3.14))
assert list(row.keys()) == ["a", "b"]
assert list(row.values()) == [1, (dt.date(2018, 9, 8), 3.14)]
```

## Documentation

To check out the [api docs](https://aiochclient.readthedocs.io/en/latest/api.html), 
visit the [readthedocs site.](https://aiochclient.readthedocs.io/en/latest/).

## Type Conversion

`aiochclient` automatically converts types from ClickHouse to python types and
vice-versa.

| ClickHouse type | Python type |
|:----------------|:------------|
| `UInt8` | `int` |
| `UInt16` | `int` |
| `UInt32` | `int` |
| `UInt64` | `int` |
| `Int8` | `int` |
| `Int16` | `int` |
| `Int32` | `int` |
| `Int64` | `int` |
| `Float32` | `float` |
| `Float64` | `float` |
| `String` | `str` |
| `FixedString` | `str` |
| `Enum8` | `str` |
| `Enum16` | `str` |
| `Date` | `datetime.date` |
| `DateTime` | `datetime.datetime` |
| `DateTime64` | `datetime.datetime` |
| `Decimal` | `decimal.Decimal` |
| `Decimal32` | `decimal.Decimal` |
| `Decimal64` | `decimal.Decimal` |
| `Decimal128` | `decimal.Decimal` |
| `IPv4` | `ipaddress.IPv4Address` |
| `IPv6` | `ipaddress.IPv6Address` |
| `UUID` | `uuid.UUID` |
| `Nothing` | `None` |
| `Tuple(T1, T2, ...)` | `Tuple[T1, T2, ...]` |
| `Array(T)` | `List[T]` |
| `Nullable(T)` | `None` or `T` |
| `LowCardinality(T)` | `T` |
| `Map(T1, T2)` | `Dict[T1, T2]` |

## Connection Pool Settings

`aiochclient` uses the
[aiohttp.TCPConnector](https://docs.aiohttp.org/en/stable/client_advanced.html#limiting-connection-pool-size)
to determine pool size.  By default, the pool limit is 100 open connections.

## Notes on Speed

It's highly recommended using `uvloop` and installing `aiochclient` with
speedups for the sake of speed. Some recent benchmarks on our
machines without parallelization:
- 180k-220k rows/sec on SELECT
- 50k-80k rows/sec on INSERT

_Note: these benchmarks are system dependent_


%package help
Summary:	Development documents and examples for aiochclient
Provides:	python3-aiochclient-doc
%description help
# aiochclient

[![PyPI version](https://badge.fury.io/py/aiochclient.svg)](https://badge.fury.io/py/aiochclient)
[![Travis CI](https://app.travis-ci.com/maximdanilchenko/aiochclient.svg?branch=master)](https://app.travis-ci.com/maximdanilchenko/aiochclient)
[![Documentation Status](https://readthedocs.org/projects/aiochclient/badge/?version=latest)](https://aiochclient.readthedocs.io/en/latest/?badge=latest)
[![codecov](https://codecov.io/gh/maximdanilchenko/aiochclient/branch/master/graph/badge.svg)](https://codecov.io/gh/maximdanilchenko/aiochclient)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black)

An async http(s) ClickHouse client for python 3.6+ supporting type
conversion in both directions, streaming, lazy decoding on select queries, and a
fully typed interface.

## Table of Contents

- [Installation](#installation)
- [Quick Start](#quick-start)
- [Documentation](#documentation)
- [Type Conversion](#type-conversion)
- [Connection Pool Settings](#connection-pool-settings)
- [Notes on Speed](#notes-on-speed)

## Installation
You can use it with either 
[aiohttp](https://github.com/aio-libs/aiohttp) or 
[httpx](https://github.com/encode/httpx) http connectors.

To use with `aiohttp` install it with command:
```
> pip install aiochclient[aiohttp]
```
Or `aiochclient[aiohttp-speedups]` to install with extra speedups.

To use with `httpx` install it with command:
```
> pip install aiochclient[httpx]
```
Or `aiochclient[httpx-speedups]` to install with extra speedups.

Installing with `[*-speedups]` adds the following:
- [cChardet](https://pypi.python.org/pypi/cchardet) for `aiohttp` speedup
- [aiodns](https://pypi.python.org/pypi/aiodns) for `aiohttp` speedup
- [ciso8601](https://github.com/closeio/ciso8601) for ultra-fast datetime 
  parsing while decoding data from ClickHouse for `aiohttp` and `httpx`.

Additionally the installation process attempts to use Cython for a speed boost
(roughly 30% faster).

## Quick Start

### Connecting to ClickHouse

`aiochclient` needs `aiohttp.ClientSession` or `httpx.AsyncClient` to connect to ClickHouse:

```python
from aiochclient import ChClient
from aiohttp import ClientSession


async def main():
    async with ClientSession() as s:
        client = ChClient(s)
        assert await client.is_alive()  # returns True if connection is Ok

```

### Querying the database

```python
await client.execute(
    "CREATE TABLE t (a UInt8, b Tuple(Date, Nullable(Float32))) ENGINE = Memory"
)
```

For INSERT queries you can pass values as `*args`. Values should be
iterables:
```python
await client.execute(
    "INSERT INTO t VALUES",
    (1, (dt.date(2018, 9, 7), None)),
    (2, (dt.date(2018, 9, 8), 3.14)),
)
```

For fetching all rows at once use the
[`fetch`](https://aiochclient.readthedocs.io/en/latest/api.html#aiochclient.ChClient.fetch)
method:
```python
all_rows = await client.fetch("SELECT * FROM t")
```

For fetching first row from result use the
[`fetchrow`](https://aiochclient.readthedocs.io/en/latest/api.html#aiochclient.ChClient.fetchrow)
method:
```python
row = await client.fetchrow("SELECT * FROM t WHERE a=1")

assert row[0] == 1
assert row["b"] == (dt.date(2018, 9, 7), None)
```

You can also use
[`fetchval`](https://aiochclient.readthedocs.io/en/latest/api.html#aiochclient.ChClient.fetchval)
method, which returns first value of the first row from query result:
```python
val = await client.fetchval("SELECT b FROM t WHERE a=2")

assert val == (dt.date(2018, 9, 8), 3.14)
```

With async iteration on the query results stream you can fetch multiple
rows without loading them all into memory at once:
```python
async for row in client.iterate(
    "SELECT number, number*2 FROM system.numbers LIMIT 10000"
):
    assert row[0] * 2 == row[1]
```

Use `fetch`/`fetchrow`/`fetchval`/`iterate` for SELECT queries and `execute` or
any of last for INSERT and all another queries.

### Working with query results

All fetch queries return rows as lightweight, memory efficient objects. _Before
v`1.0.0` rows were only returned as tuples._ All rows have a full mapping interface, where you can
get fields by names or indexes:
```python
row = await client.fetchrow("SELECT a, b FROM t WHERE a=1")

assert row["a"] == 1
assert row[0] == 1
assert row[:] == (1, (dt.date(2018, 9, 8), 3.14))
assert list(row.keys()) == ["a", "b"]
assert list(row.values()) == [1, (dt.date(2018, 9, 8), 3.14)]
```

## Documentation

To check out the [api docs](https://aiochclient.readthedocs.io/en/latest/api.html), 
visit the [readthedocs site.](https://aiochclient.readthedocs.io/en/latest/).

## Type Conversion

`aiochclient` automatically converts types from ClickHouse to python types and
vice-versa.

| ClickHouse type | Python type |
|:----------------|:------------|
| `UInt8` | `int` |
| `UInt16` | `int` |
| `UInt32` | `int` |
| `UInt64` | `int` |
| `Int8` | `int` |
| `Int16` | `int` |
| `Int32` | `int` |
| `Int64` | `int` |
| `Float32` | `float` |
| `Float64` | `float` |
| `String` | `str` |
| `FixedString` | `str` |
| `Enum8` | `str` |
| `Enum16` | `str` |
| `Date` | `datetime.date` |
| `DateTime` | `datetime.datetime` |
| `DateTime64` | `datetime.datetime` |
| `Decimal` | `decimal.Decimal` |
| `Decimal32` | `decimal.Decimal` |
| `Decimal64` | `decimal.Decimal` |
| `Decimal128` | `decimal.Decimal` |
| `IPv4` | `ipaddress.IPv4Address` |
| `IPv6` | `ipaddress.IPv6Address` |
| `UUID` | `uuid.UUID` |
| `Nothing` | `None` |
| `Tuple(T1, T2, ...)` | `Tuple[T1, T2, ...]` |
| `Array(T)` | `List[T]` |
| `Nullable(T)` | `None` or `T` |
| `LowCardinality(T)` | `T` |
| `Map(T1, T2)` | `Dict[T1, T2]` |

## Connection Pool Settings

`aiochclient` uses the
[aiohttp.TCPConnector](https://docs.aiohttp.org/en/stable/client_advanced.html#limiting-connection-pool-size)
to determine pool size.  By default, the pool limit is 100 open connections.

## Notes on Speed

It's highly recommended using `uvloop` and installing `aiochclient` with
speedups for the sake of speed. Some recent benchmarks on our
machines without parallelization:
- 180k-220k rows/sec on SELECT
- 50k-80k rows/sec on INSERT

_Note: these benchmarks are system dependent_


%prep
%autosetup -n aiochclient-2.3.1

%build
%py3_build

%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .

%files -n python3-aiochclient -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 2.3.1-1
- Package Spec generated