SKU: 71154767613

Standard Hundeleine S Länge 1,8m Braun Edition

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Description

Standard Hundeleine S Länge 1,8m Braun EditionBreite: 2 cmLnge: 1,8 mFarbe Neopren: Braun Farbe Karabiner: DunkelbraunMaterial: strapazierfhiges, reifestes Nylon Karabiner Lnge: 7,5cm, Karabiner Haken Breite: 2,5cmZugkraft: 100 150kgGewicht: g Diese funktionale Hundeleine wurde fr den tglichen Einsatz entwickelt und vereint geringes Gewicht mit hoher Belastbarkeit. Mit einer Lnge von 1,8 m und einer Breite von 2 cm bietet sie optimale Kontrolle und Bewegungsfreiheit bei Spaziergngen, Training

Breite: 2 cm
Länge: 1,8 m
Farbe Neopren: Braun
Farbe Karabiner: Dunkelbraun
Material: strapazierfähiges, reißfestes Nylon
Karabiner Länge: 7,5cm,
Karabiner Haken Breite: 2,5cm
Zugkraft: 100-150kg
Gewicht:  g

Diese funktionale Hundeleine wurde für den täglichen Einsatz entwickelt und vereint geringes Gewicht mit hoher Belastbarkeit. Mit einer Länge von 1,8 m und einer Breite von 2 cm bietet sie optimale Kontrolle und Bewegungsfreiheit bei Spaziergängen, Training oder Stadtbummeln.

Der stabile, schwarze Karabiner sorgt für eine sichere Verbindung und ist ideal für mittelgroße bis große Hunde geeignet. Trotz ihrer Robustheit wiegt die Leine nur  g und liegt dank des weich gepolsterten Handgriffs besonders angenehm in der Hand.

Das hochwertige, langlebige Material ist pflegeleicht, formstabil und optimal auf den aktiven Alltag abgestimmt – für zuverlässige Funktionalität bei jedem Abenteuer.

Hinweis:
Die schwarze Beschichtung der Metallteile (z. B. Karabiner, D-Ring) kann sich mit der Zeit durch Abrieb, insbesondere bei Kontakt mit harten Oberflächen wie Beton, teilweise abnutzen. Dies ist ein normaler, rein optischer Verschleiß und hat keinen Einfluss auf die Funktionalität oder Sicherheit der Leine.

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SKU: 71154767613

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4.4 ★★★★★
Based on 26 reviews
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Z
Verified Purchase
Zay
Charlottesville, US
★★★★★ 5
Upside down (Great)
Format: Hardcover
Was extremely relatable and a blessing I gifted this book and want it back lol but I will be ordering again
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on October 23, 2024
R
Verified Purchase
Rory Derrick
Battle Creek, US
★★★★★ 5
Good book
Format: Paperback
Still working through it but I have no complaints. I have a shelf of no starch books and have not been disappointed by any. Some, of course, are better than others but this is a good book.
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Reviewed in the United States on December 2, 2021
C
Verified Purchase
Cory P.
New York, US
★★★★★ 5
Dive into Algorithms is more like eating a Parfait than trying understand algorithms!
Format: Paperback
Seriously though great writing and explanation along with great history lessons. Also highly recommend for anyone working in the data science field.
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Reviewed in the United States on August 3, 2021
F
Verified Purchase
Frank Gonzalez
New York, US
★★★★★ 3
Ok content, not great explanations (2.5 our of 5 stars)
Format: Paperback
I found the contents of this book to be simply ok: either too simple, or the more complicated algorithms and concepts would not be as carefully explained as they should have been. It is not a terrible book, but it feels as though the author did not go over many drafts/iterations of this work.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on April 7, 2024
I
Ira Laefsky
Lake Worth, US
★★★★★ 5
An Excellent Self-Discovery Approach to Learning Algorithms
Format: Paperback
I have an Ivy League Master's Degree in Computer Science although it was accomplished 35 years ago. Of course, I had to complete an ACM-type course in Algorithms and Data Structures on the undergraduate and graduate level and managed to by rote accomplish enough to satisfy these courses. But until seeing this great book I never had the feeling of gaining an understanding of the approach to learning and building algorithms and the extent to which it is an important component of all programs. By a journey of guided self-discovery the author shows, not only the necessity of algorithms and their canonical forms, but a path to understanding the construction of algorithms to accomplish common and not so common practical problems. These range from the simple to understand, e.g. implementing Russian Peasant Multiplication, to advanced and up to date topics like Machine Learning. The highest praise I can give this book is that as a journey of guided self-discovery it produces an understanding in the reader of the process of constructing and understanding these algorithms and their place in all programming.
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Reviewed in the United States on February 7, 2021

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