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%global _empty_manifest_terminate_build 0
Name: python-stream-sqlite
Version: 0.0.41
Release: 1
Summary: Python function to extract all the rows from a SQLite database file concurrently with iterating over its bytes, without needing random access to the file
License: MIT License
URL: https://github.com/uktrade/stream-sqlite
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/61/7c/f41dbc6f6221a6beac3e173ce3895d224807f7dcfe5531c3976b4d98e5de/stream-sqlite-0.0.41.tar.gz
BuildArch: noarch
%description
# stream-sqlite [](https://circleci.com/gh/uktrade/stream-sqlite) [](https://codeclimate.com/github/uktrade/stream-sqlite/test_coverage)
Python function to extract all the rows from a SQLite database file concurrently with iterating over its bytes, without needing random access to the file.
Note that the [SQLite file format](https://www.sqlite.org/fileformat.html) is not designed to be streamed; the data is arranged in _pages_ of a fixed number of bytes, and the information to identify a page often comes _after_ the page in the stream (sometimes a great deal after). Therefore, pages are buffered in memory until they can be identified.
## Installation
```bash
pip install stream-sqlite
```
## Usage
```python
from stream_sqlite import stream_sqlite
import httpx
# Iterable that yields the bytes of a sqlite file
def sqlite_bytes():
with httpx.stream('GET', 'http://www.parlgov.org/static/stable/2020/parlgov-stable.db') as r:
yield from r.iter_bytes(chunk_size=65_536)
# If there is a single table in the file, there will be exactly one iteration of the outer loop.
# If there are multiple tables, each can appear multiple times.
for table_name, pragma_table_info, rows in stream_sqlite(sqlite_bytes(), max_buffer_size=1_048_576):
for row in rows:
print(row)
```
## Recommendations
If you have control over the SQLite file, `VACUUM;` should be run on it before streaming. In addition to minimising the size of the file, `VACUUM;` arranges the pages in a way that often reduces the buffering required when streaming. This is especially true if it was the target of intermingled `INSERT`s and/or `DELETE`s over multiple tables.
Also, indexes are not used for extracting the rows while streaming. If streaming is the only use case of the SQLite file, and you have control over it, indexes should be removed, and `VACUUM;` then run.
Some tests suggest that if the file is written in autovacuum mode, i.e. `PRAGMA auto_vacuum = FULL;`, then the pages are arranged in a way that reduces the buffering required when streaming. Your mileage may vary.
%package -n python3-stream-sqlite
Summary: Python function to extract all the rows from a SQLite database file concurrently with iterating over its bytes, without needing random access to the file
Provides: python-stream-sqlite
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-stream-sqlite
# stream-sqlite [](https://circleci.com/gh/uktrade/stream-sqlite) [](https://codeclimate.com/github/uktrade/stream-sqlite/test_coverage)
Python function to extract all the rows from a SQLite database file concurrently with iterating over its bytes, without needing random access to the file.
Note that the [SQLite file format](https://www.sqlite.org/fileformat.html) is not designed to be streamed; the data is arranged in _pages_ of a fixed number of bytes, and the information to identify a page often comes _after_ the page in the stream (sometimes a great deal after). Therefore, pages are buffered in memory until they can be identified.
## Installation
```bash
pip install stream-sqlite
```
## Usage
```python
from stream_sqlite import stream_sqlite
import httpx
# Iterable that yields the bytes of a sqlite file
def sqlite_bytes():
with httpx.stream('GET', 'http://www.parlgov.org/static/stable/2020/parlgov-stable.db') as r:
yield from r.iter_bytes(chunk_size=65_536)
# If there is a single table in the file, there will be exactly one iteration of the outer loop.
# If there are multiple tables, each can appear multiple times.
for table_name, pragma_table_info, rows in stream_sqlite(sqlite_bytes(), max_buffer_size=1_048_576):
for row in rows:
print(row)
```
## Recommendations
If you have control over the SQLite file, `VACUUM;` should be run on it before streaming. In addition to minimising the size of the file, `VACUUM;` arranges the pages in a way that often reduces the buffering required when streaming. This is especially true if it was the target of intermingled `INSERT`s and/or `DELETE`s over multiple tables.
Also, indexes are not used for extracting the rows while streaming. If streaming is the only use case of the SQLite file, and you have control over it, indexes should be removed, and `VACUUM;` then run.
Some tests suggest that if the file is written in autovacuum mode, i.e. `PRAGMA auto_vacuum = FULL;`, then the pages are arranged in a way that reduces the buffering required when streaming. Your mileage may vary.
%package help
Summary: Development documents and examples for stream-sqlite
Provides: python3-stream-sqlite-doc
%description help
# stream-sqlite [](https://circleci.com/gh/uktrade/stream-sqlite) [](https://codeclimate.com/github/uktrade/stream-sqlite/test_coverage)
Python function to extract all the rows from a SQLite database file concurrently with iterating over its bytes, without needing random access to the file.
Note that the [SQLite file format](https://www.sqlite.org/fileformat.html) is not designed to be streamed; the data is arranged in _pages_ of a fixed number of bytes, and the information to identify a page often comes _after_ the page in the stream (sometimes a great deal after). Therefore, pages are buffered in memory until they can be identified.
## Installation
```bash
pip install stream-sqlite
```
## Usage
```python
from stream_sqlite import stream_sqlite
import httpx
# Iterable that yields the bytes of a sqlite file
def sqlite_bytes():
with httpx.stream('GET', 'http://www.parlgov.org/static/stable/2020/parlgov-stable.db') as r:
yield from r.iter_bytes(chunk_size=65_536)
# If there is a single table in the file, there will be exactly one iteration of the outer loop.
# If there are multiple tables, each can appear multiple times.
for table_name, pragma_table_info, rows in stream_sqlite(sqlite_bytes(), max_buffer_size=1_048_576):
for row in rows:
print(row)
```
## Recommendations
If you have control over the SQLite file, `VACUUM;` should be run on it before streaming. In addition to minimising the size of the file, `VACUUM;` arranges the pages in a way that often reduces the buffering required when streaming. This is especially true if it was the target of intermingled `INSERT`s and/or `DELETE`s over multiple tables.
Also, indexes are not used for extracting the rows while streaming. If streaming is the only use case of the SQLite file, and you have control over it, indexes should be removed, and `VACUUM;` then run.
Some tests suggest that if the file is written in autovacuum mode, i.e. `PRAGMA auto_vacuum = FULL;`, then the pages are arranged in a way that reduces the buffering required when streaming. Your mileage may vary.
%prep
%autosetup -n stream-sqlite-0.0.41
%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-stream-sqlite -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Thu May 18 2023 Python_Bot <Python_Bot@openeuler.org> - 0.0.41-1
- Package Spec generated
|
